Part I - Loading the ESDC¶
In this tutorial, we will walk through how one can access the ESDC. Fortunately, we have 2 ways: locally and through the internet. I have already personally downloading the cubes to our in-house server. But for reproducibility purposes, the cubes can be accessed externally as well. So we will walk-through the two ways that this is possible.
import sys, os
from pyprojroot import here
root = here(project_files=[".here"])
sys.path.append(str(here()))
import pathlib
from xcube.core.dsio import open_cube
import pathlib
import xarray as xr
DATA_PATH = pathlib.Path("/media/disk/databases/ESDC/")
FIG_PATH = pathlib.Path(str(here()), 'reports/figures/spa_temp')
!ls /media/disk/databases/
ASTER LSASAF BACI-CABLAB MODIS BBDD_video_image MODIS_IGBP_LandCover BELMANIP MULTILAI Belmanip2_VGT_MOD_CYC_2003_2007_v2 NEUROEXPLORA_2016 BigEarth NEUROEXPLORA_2018 BLACKCARBON NEUROEXPLORA_2019 C2X NWPU-RESISC45 CARTOGRAFICO OCEANCLORO CASIAHS ODE_data CAUSALITY PatternNet CHRISLAI PHENOCAM CMIX PhiLab_UNOSAT_challenge DROUGHT PROBAV_CLOUDS EMULATEDS2 PROSAIL_EMULATOR_CAUSAL ESACCI-LandCover PROSPECT ESDC S1S2Luca EuroSAT S1S2Transfer FLUXCOM SEN12MS GF_Landsat_2013_Irrigated_project SENTINEL2_CLOUDS GFZSIF SHAPEFILES Global_TRY_maps_V1 SIx HL_20151110_C2A_noFlu_spec_Rrs_norm_10.txt SMADI HYPERLABELME SMOS-IC HYPERLABELME_OLD_DATA SMOS_SSSMed IASI_data SMOS_VOD IASI Tim SPARC iclradiant StreamFlow IGARSS2019 SYKE indian_wheat_yield TCEP_CAUSAL Inputs_GLOBAL_Trait_spatialization3km temp IRRADIANCE TRAITS KAUSAL UCMERCED LANDSAT7_CLOUDS USGS LANDSAT8_CLOUDS WORLDFLOODS LANDSAT8_SPARCS xview2_challenge Land-Use
Method I - Online¶
For this first example, we will load the cubes from the server. Then we can view the cubes.
ONLINE_CUBE = "https://obs.eu-de.otc.t-systems.com"
CUBE = "obs-esdc-v2.1"
LOW_RES = "obs-esdc-v2.1/esdc-8d-0.25deg-1x720x1440-2.1.0.zarr"
CUBE_VERSION = "2.1.0"
EXT = ".zarr"
ESDC_PATH = "obs-esdc-v2.1/esdc-8d-1x720x1440-2.1.0.zarr"
INFO_EARTH = [
"gross_primary_productivity",
"root_moisture",
"precipitation",
"leaf_area_index",
"land_surface_temperature",
]
path = (
f"{ONLINE_CUBE}/{LOW_RES}"
)
https://obs.eu-de.otc.t-systems.com/obs-esdc-v2.0.0/esdc-8d-0.25deg-1x720x1440-2.0.0.zarr
path
'https://obs.eu-de.otc.t-systems.com/obs-esdc-v2.1/esdc-8d-0.25deg-1x720x1440-2.1.0.zarr'
raw_path = "/media/disk/erc/papers/2020_rbig_eo"
!mkdir $raw_path/raw
t = open_cube(str(path))
# load cube from bit bucket
cube_from_s3_bucket = open_cube("https://obs.eu-de.otc.t-systems.com/obs-esdc-v2.0.0/esdc-8d-0.25deg-1x720x1440-2.0.0.zarr")
cube_from_s3_bucket
xarray.Dataset
- bnds: 2
- lat: 720
- lon: 1440
- time: 1702
- lat(lat)float3289.875 89.625 ... -89.625 -89.875
array([ 89.875, 89.625, 89.375, ..., -89.375, -89.625, -89.875], dtype=float32) - lat_bnds(lat, bnds)float32dask.array<chunksize=(720, 2), meta=np.ndarray>
Array Chunk Bytes 5.76 kB 5.76 kB Shape (720, 2) (720, 2) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - lon(lon)float32-179.875 -179.625 ... 179.875
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875], dtype=float32) - lon_bnds(lon, bnds)float32dask.array<chunksize=(1440, 2), meta=np.ndarray>
Array Chunk Bytes 11.52 kB 11.52 kB Shape (1440, 2) (1440, 2) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - time(time)datetime64[ns]1980-01-05 ... 2016-12-30
- bounds :
- time_bnds
- long_name :
- time
- standard_name :
- time
array(['1980-01-05T00:00:00.000000000', '1980-01-13T00:00:00.000000000', '1980-01-21T00:00:00.000000000', ..., '2016-12-14T00:00:00.000000000', '2016-12-22T00:00:00.000000000', '2016-12-30T00:00:00.000000000'], dtype='datetime64[ns]') - time_bnds(time, bnds)datetime64[ns]dask.array<chunksize=(1702, 2), meta=np.ndarray>
Array Chunk Bytes 27.23 kB 27.23 kB Shape (1702, 2) (1702, 2) Count 2 Tasks 1 Chunks Type datetime64[ns] numpy.ndarray
- Rg(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 2
- esa_cci_path :
- nan
- long_name :
- Downwelling shortwave radiation
- orig_attrs :
- {'long_name': 'Downwelling shortwave radiation', 'project_name': 'BESS', 'references': 'Ryu, Y.*, Jiang, C., Kobayashi, H., & Detto, M. (2018). MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000. Remote Sensing of Environment, 204, 812-825', 'source_name': 'surface_downwelling_shortwave_flux_in_air', 'standard_name': 'surface_downwelling_shortwave_flux_in_air', 'units': 'W m-2', 'url': 'http://environment.snu.ac.kr/bess_rad/'}
- orig_version :
- 15.10.2017
- project_name :
- BESS
- time_coverage_end :
- 2010-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-03-01
- units :
- W m-2
- url :
- http://environment.snu.ac.kr/bess_rad/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - aerosol_optical_thickness_1600(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 25
- esa_cci_path :
- /neodc/esacci/aerosol/data/AATSR_SU/L3/v4.21/DAILY/
- long_name :
- Aerosol optical thickness at 1600 nm
- orig_attrs :
- {'Conventions': 'CF-1.6', 'cdm_data_type': 'grid', 'coordinates': 'latitude longitude', 'creator_email': 'p.r.j.north@swansea.ac.uk, a.heckel@swansea.ac.uk', 'creator_name': 'Swansea University', 'creator_url': 'http:\\/\\/www.swan.ac.uk\\/staff\\/academic\\/environmentsociety\\/geography\\/northpeter\\/', 'date_created': '20151022T231808Z', 'geospatial_lat_max': '90.0', 'geospatial_lat_min': '-90.0', 'geospatial_lat_resolution': '1.0', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': '180.0', 'geospatial_lon_min': '-180.0', 'geospatial_lon_resolution': '1.0', 'geospatial_lon_units': 'degrees_east', 'history': 'Level 3 product from Swansea algorithm', 'id': '20020724141127-ESACCI-L3C_AEROSOL-AER_PRODUCTS-AATSR_ENVISAT-SU_DAILY-v4.21.nc', 'inputfilelist': 'ATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1', 'keywords': 'satellite,observation,atmosphere', 'keywords_vocabulary': 'NASA Global Change Master Directory (GCMD) Science Keywords', 'lat': 180, 'license': 'ESA CCI Data Policy: free and open access', 'lon': 360, 'long_name': 'aerosol optical thickness at 1600 nm', 'naming_authority': 'uk.ac.su.aatsraerosol', 'orig_attrs': {}, 'platform': 'ENVISAT', 'product_version': '4.21', 'project': 'Climate Change Initiative - European Space Agency', 'projection': 'equirectangular', 'references': 'http:\\/\\/www.esa-aerosol-cci.org', 'resolution': '1x1 degrees', 'sensor': 'AATSR', 'source': 'ATS_TOA_1P, V6.05', 'source_name': 'AAOD550_mean', 'standard_name': 'atmosphere_optical_thickness_due_to_ambient_aerosol', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains the level-3 daily mean aerosol properties products from AATSR satellite observations. Data are processed by Swansea algorithm', 'time': '1', 'time_coverage_end': '20020724T233825Z', 'time_coverage_start': '20020724T143513Z', 'title': 'AARDVARC CCI aerosol product level 3', 'tracking_id': 'a63f9cd2-1fed-4f9a-82fd-91f1c1b966b2', 'units': '1'}
- orig_version :
- v4.21
- project_name :
- ESA Aerosol CCI
- time_coverage_end :
- 2012-04-10
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2002-07-24
- units :
- 1
- url :
- http://www.esa-aerosol-cci.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - aerosol_optical_thickness_550(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 26
- esa_cci_path :
- /neodc/esacci/aerosol/data/AATSR_SU/L3/v4.21/DAILY/
- long_name :
- Aerosol optical thickness at 550 nm
- orig_attrs :
- {'Conventions': 'CF-1.6', 'cdm_data_type': 'grid', 'coordinates': 'latitude longitude', 'creator_email': 'p.r.j.north@swansea.ac.uk, a.heckel@swansea.ac.uk', 'creator_name': 'Swansea University', 'creator_url': 'http:\\/\\/www.swan.ac.uk\\/staff\\/academic\\/environmentsociety\\/geography\\/northpeter\\/', 'date_created': '20151022T231808Z', 'geospatial_lat_max': '90.0', 'geospatial_lat_min': '-90.0', 'geospatial_lat_resolution': '1.0', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': '180.0', 'geospatial_lon_min': '-180.0', 'geospatial_lon_resolution': '1.0', 'geospatial_lon_units': 'degrees_east', 'history': 'Level 3 product from Swansea algorithm', 'id': '20020724141127-ESACCI-L3C_AEROSOL-AER_PRODUCTS-AATSR_ENVISAT-SU_DAILY-v4.21.nc', 'inputfilelist': 'ATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1', 'keywords': 'satellite,observation,atmosphere', 'keywords_vocabulary': 'NASA Global Change Master Directory (GCMD) Science Keywords', 'lat': 180, 'license': 'ESA CCI Data Policy: free and open access', 'lon': 360, 'long_name': 'aerosol optical thickness at 550 nm', 'naming_authority': 'uk.ac.su.aatsraerosol', 'orig_attrs': {}, 'platform': 'ENVISAT', 'product_version': '4.21', 'project': 'Climate Change Initiative - European Space Agency', 'projection': 'equirectangular', 'references': 'http:\\/\\/www.esa-aerosol-cci.org', 'resolution': '1x1 degrees', 'sensor': 'AATSR', 'source': 'ATS_TOA_1P, V6.05', 'source_name': 'AAOD550_mean', 'standard_name': 'atmosphere_optical_thickness_due_to_ambient_aerosol', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains the level-3 daily mean aerosol properties products from AATSR satellite observations. Data are processed by Swansea algorithm', 'time': '1', 'time_coverage_end': '20020724T233825Z', 'time_coverage_start': '20020724T143513Z', 'title': 'AARDVARC CCI aerosol product level 3', 'tracking_id': 'a63f9cd2-1fed-4f9a-82fd-91f1c1b966b2', 'units': '1'}
- orig_version :
- v4.21
- project_name :
- ESA Aerosol CCI
- time_coverage_end :
- 2012-04-10
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2002-07-24
- units :
- 1
- url :
- http://www.esa-aerosol-cci.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - aerosol_optical_thickness_670(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 27
- esa_cci_path :
- /neodc/esacci/aerosol/data/AATSR_SU/L3/v4.21/DAILY/
- long_name :
- Aerosol optical thickness at 670 nm
- orig_attrs :
- {'Conventions': 'CF-1.6', 'cdm_data_type': 'grid', 'coordinates': 'latitude longitude', 'creator_email': 'p.r.j.north@swansea.ac.uk, a.heckel@swansea.ac.uk', 'creator_name': 'Swansea University', 'creator_url': 'http:\\/\\/www.swan.ac.uk\\/staff\\/academic\\/environmentsociety\\/geography\\/northpeter\\/', 'date_created': '20151022T231808Z', 'geospatial_lat_max': '90.0', 'geospatial_lat_min': '-90.0', 'geospatial_lat_resolution': '1.0', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': '180.0', 'geospatial_lon_min': '-180.0', 'geospatial_lon_resolution': '1.0', 'geospatial_lon_units': 'degrees_east', 'history': 'Level 3 product from Swansea algorithm', 'id': '20020724141127-ESACCI-L3C_AEROSOL-AER_PRODUCTS-AATSR_ENVISAT-SU_DAILY-v4.21.nc', 'inputfilelist': 'ATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1', 'keywords': 'satellite,observation,atmosphere', 'keywords_vocabulary': 'NASA Global Change Master Directory (GCMD) Science Keywords', 'lat': 180, 'license': 'ESA CCI Data Policy: free and open access', 'lon': 360, 'long_name': 'aerosol optical thickness at 670 nm', 'naming_authority': 'uk.ac.su.aatsraerosol', 'orig_attrs': {}, 'platform': 'ENVISAT', 'product_version': '4.21', 'project': 'Climate Change Initiative - European Space Agency', 'projection': 'equirectangular', 'references': 'http:\\/\\/www.esa-aerosol-cci.org', 'resolution': '1x1 degrees', 'sensor': 'AATSR', 'source': 'ATS_TOA_1P, V6.05', 'source_name': 'AAOD550_mean', 'standard_name': 'atmosphere_optical_thickness_due_to_ambient_aerosol', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains the level-3 daily mean aerosol properties products from AATSR satellite observations. Data are processed by Swansea algorithm', 'time': '1', 'time_coverage_end': '20020724T233825Z', 'time_coverage_start': '20020724T143513Z', 'title': 'AARDVARC CCI aerosol product level 3', 'tracking_id': 'a63f9cd2-1fed-4f9a-82fd-91f1c1b966b2', 'units': '1'}
- orig_version :
- v4.21
- project_name :
- ESA Aerosol CCI
- time_coverage_end :
- 2012-04-10
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2002-07-24
- units :
- 1
- url :
- http://www.esa-aerosol-cci.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - aerosol_optical_thickness_870(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 28
- esa_cci_path :
- /neodc/esacci/aerosol/data/AATSR_SU/L3/v4.21/DAILY/
- long_name :
- Aerosol optical thickness at 870 nm
- orig_attrs :
- {'Conventions': 'CF-1.6', 'cdm_data_type': 'grid', 'coordinates': 'latitude longitude', 'creator_email': 'p.r.j.north@swansea.ac.uk, a.heckel@swansea.ac.uk', 'creator_name': 'Swansea University', 'creator_url': 'http:\\/\\/www.swan.ac.uk\\/staff\\/academic\\/environmentsociety\\/geography\\/northpeter\\/', 'date_created': '20151022T231808Z', 'geospatial_lat_max': '90.0', 'geospatial_lat_min': '-90.0', 'geospatial_lat_resolution': '1.0', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': '180.0', 'geospatial_lon_min': '-180.0', 'geospatial_lon_resolution': '1.0', 'geospatial_lon_units': 'degrees_east', 'history': 'Level 3 product from Swansea algorithm', 'id': '20020724141127-ESACCI-L3C_AEROSOL-AER_PRODUCTS-AATSR_ENVISAT-SU_DAILY-v4.21.nc', 'inputfilelist': 'ATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1 \nATS_TOA_1PUUPA20020724_141127_000065272008_00024_02082_5805.N1', 'keywords': 'satellite,observation,atmosphere', 'keywords_vocabulary': 'NASA Global Change Master Directory (GCMD) Science Keywords', 'lat': 180, 'license': 'ESA CCI Data Policy: free and open access', 'lon': 360, 'long_name': 'aerosol optical thickness at 870 nm', 'naming_authority': 'uk.ac.su.aatsraerosol', 'orig_attrs': {}, 'platform': 'ENVISAT', 'product_version': '4.21', 'project': 'Climate Change Initiative - European Space Agency', 'projection': 'equirectangular', 'references': 'http:\\/\\/www.esa-aerosol-cci.org', 'resolution': '1x1 degrees', 'sensor': 'AATSR', 'source': 'ATS_TOA_1P, V6.05', 'source_name': 'AAOD550_mean', 'standard_name': 'atmosphere_optical_thickness_due_to_ambient_aerosol', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains the level-3 daily mean aerosol properties products from AATSR satellite observations. Data are processed by Swansea algorithm', 'time': '1', 'time_coverage_end': '20020724T233825Z', 'time_coverage_start': '20020724T143513Z', 'title': 'AARDVARC CCI aerosol product level 3', 'tracking_id': 'a63f9cd2-1fed-4f9a-82fd-91f1c1b966b2', 'units': '1'}
- orig_version :
- v4.21
- project_name :
- ESA Aerosol CCI
- time_coverage_end :
- 2012-04-10
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2002-07-24
- units :
- 1
- url :
- http://www.esa-aerosol-cci.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - air_temperature_2m(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 4
- esa_cci_path :
- nan
- long_name :
- 2 Metre Air Temperature
- orig_attrs :
- {'comment': 'Air temperature at 2m from the ERA5 reanalysis product.', 'long_name': '2 metre air temperature', 'orig_attrs': {}, 'project_name': 'ERA5', 'references': '', 'source_name': 'air_temperature_2m', 'units': 'K', 'url': 'https://confluence.ecmwf.int//display/CKB/ERA5+data+documentation'}
- orig_version :
- ERA5
- project_name :
- ERA5
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-05
- units :
- K
- url :
- https://confluence.ecmwf.int//display/CKB/ERA5+data+documentation
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - analysed_sst(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 44
- esa_cci_path :
- /neodc/esacci/sst/data/lt/Analysis/L4/v01.1/
- long_name :
- Analysed Sea Surface Temperature
- orig_attrs :
- {'Conventions': 'CF-1.5, Unidata Observation Dataset v1.0', 'Metadata_Conventions': 'Unidata Dataset Discovery v1.0', 'acknowledgment': 'Funded by ESA', 'cdm_data_type': 'grid', 'comment': 'WARNING Some applications are unable to properly handle signed byte values. If values are encountered > 127, please subtract 256 from this reported value', 'creator_email': 'science.leader@esa-sst-cci.org', 'creator_name': 'ESA SST CCI', 'creator_processing_institution': 'These data were produced at the Met Office as part of the ESA SST CCI project.', 'creator_url': 'http://www.esa-sst-cci.org', 'date_created': '20130309T132046Z', 'easternmost_longitude': 180.00001525878906, 'file_quality_level': 3, 'gds_version_id': '2.0', 'geospatial_lat_max': 90.0, 'geospatial_lat_min': -90.0, 'geospatial_lat_resolution': 0.05000000074505806, 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 180.0, 'geospatial_lon_min': -180.0, 'geospatial_lon_resolution': 0.05000000074505806, 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': -0.20000000298023224, 'geospatial_vertical_min': -0.20000000298023224, 'history': 'Created using OSTIA reanalysis system v2.0', 'id': 'OSTIA-ESACCI-L4-v01.1', 'institution': 'ESACCI', 'keywords': 'Oceans > Ocean Temperature > Sea Surface Temperature', 'keywords_vocabulary': 'NASA Global Change Master Directory (GCMD) Science Keywords', 'license': 'GHRSST protocol describes data use as free and open', 'long_name': 'analysed sea surface temperature', 'metadata_link': 'http://www.esa-cci.org', 'naming_authority': 'org.ghrsst', 'netcdf_version_id': '4.1.3', 'northernmost_latitude': 90.0, 'orig_attrs': {}, 'platform': 'ERS-<1,2>, Envisat, NOAA-<12,14,15,16,17,18>, MetOpA', 'processing_level': 'L4', 'product_version': '1.1', 'project': 'Climate Change Initiative - European Space Agency', 'publisher_email': 'science.leader@esa-sst-cci.org', 'publisher_name': 'ESACCI', 'publisher_url': 'http://www.esa-sst-cci.org', 'references': 'http://www.esa-sst-cci.org', 'sensor': 'ATSR, AATSR, AVHRR_GAC', 'source': 'ATSR<1,2>-ESACCI-L3U-v1.0, AATSR-ESACCI-L3U-v1.0, AVHRR<12,14,15,16,17,18>_G-ESACCI-L2P-v1.0, AVHRRMTA-ESACCI-L2P-v1.0, EUMETSAT_OSI-SAF-ICE-v1.1, EUMETSAT_OSI-SAF-ICE-v2.2', 'source_dir': '/neodc/esacci/sst/data/lt/Analysis/L4/v01.1', 'source_name': 'analysed_sst', 'source_version': 'v01.1', 'southernmost_latitude': -90.0, 'spatial_resolution': '0.05 degree', 'standard_name': 'sea_water_temperature', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Convention', 'start_time': '20100101T000000Z', 'stop_time': '20100101T235959Z', 'summary': 'OSTIA L4 product from the ESA SST CCI project, produced using OSTIA reanalysis system v2.0. Ice field corrected in v1.1 (v1.0 had ice from day-1). Static ice field between 20080101-20080229 and 20080501-20080521 also fixed in v1.1', 'time_coverage_duration': 'P1D', 'time_coverage_end': '20100101T235959Z', 'time_coverage_resolution': 'P1D', 'time_coverage_start': '20100101T000000Z', 'title': 'ESA SST CCI OSTIA L4 product', 'tracking_id': '19b1f7a4-d8d1-44eb-9cfa-37cc33c4c2c1', 'units': 'kelvin', 'url': 'http://www.esa-sst-cci.org', 'uuid': '19b1f7a4-d8d1-44eb-9cfa-37cc33c4c2c1', 'valid_max': 4500.0, 'valid_min': -300.0, 'westernmost_longitude': -180.0}
- orig_version :
- v01.1
- project_name :
- ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI)
- time_coverage_end :
- 2010-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1991-09-02
- units :
- kelvin
- url :
- http://www.esa-sst-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - bare_soil_evaporation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 55
- esa_cci_path :
- nan
- long_name :
- Bare Soil Evaporation
- orig_attrs :
- {'long_name': 'Bare Soil Evaporation', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Eb', 'standard_name': 'bare_soil_water_evaporation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- mm/day
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - black_sky_albedo(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 65
- esa_cci_path :
- nan
- long_name :
- Black Sky Albedo for Visible Wavebands
- orig_attrs :
- {'comment': 'Black sky albedo derived from the GlobAlbedo CCI project dataset', 'long_name': 'Black Sky Albedo for Visible Wavebands', 'orig_attrs': {}, 'project_name': 'GlobAlbedo', 'references': 'Muller, Jan-Peter, et al. "The ESA GLOBALBEDO project for mapping the Earth’s land surface albedo for 15 years from European sensors." Geophysical Research Abstracts. Vol. 13. 2012.', 'source_name': 'DHR_VIS', 'standard_name': 'surface_albedo_black_sky', 'units': '-', 'url': 'http://www.globalbedo.org/'}
- orig_version :
- nan
- project_name :
- GlobAlbedo
- time_coverage_end :
- 2012-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1998-01-05
- units :
- -
- url :
- http://www.globalbedo.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - black_sky_albedo_avhrr(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 76
- esa_cci_path :
- nan
- long_name :
- Directional Hemisphere Reflectance albedo - VIS band
- orig_attrs :
- {'comment': 'Black sky albedo derived from the QA4ECV Albedo Product', 'long_name': 'Directional Hemisphere Reflectance albedo - VIS band', 'orig_attrs': {}, 'project_name': 'QA4ECV - European Union Framework Program 7', 'source_name': 'DHR_VIS', 'standard_name': 'surface_albedo_black_sky', 'units': '1', 'url': 'http://www.qa4ecv.eu/'}
- orig_version :
- nan
- project_name :
- QA4ECV - European Union Framework Program 7
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1982-01-05
- units :
- 1
- url :
- http://www.qa4ecv.eu/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - burnt_area(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 54
- esa_cci_path :
- nan
- long_name :
- Monthly Burnt Area
- orig_attrs :
- {'comment': 'Burnt Area based on the GFED4 fire product.', 'long_name': 'Monthly Burnt Area', 'orig_attrs': {}, 'project_name': 'GFED4', 'references': 'Giglio, Louis, James T. Randerson, and Guido R. Werf. "Analysis of daily, monthly, and annual burned area using the fourth‐generation global fire emissions database (GFED4)." Journal of Geophysical Research: Biogeosciences 118.1 (2013): 317-328.', 'source_name': 'BurntArea', 'standard_name': 'burnt_area', 'units': 'hectares', 'url': 'http://www.globalfiredata.org/'}
- orig_version :
- gfed4
- project_name :
- GFED4
- time_coverage_end :
- 2014-03-02
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1995-01-05
- units :
- hectares
- url :
- http://www.globalfiredata.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - c_emissions(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 53
- esa_cci_path :
- nan
- long_name :
- Carbon Dioxide Emissions Due to Natural Fires
- orig_attrs :
- {'comment': 'Carbon emissions by fires based on the GFED4 fire product.', 'long_name': 'Carbon dioxide emissions due to natural fires expressed as carbon flux.', 'orig_attrs': {}, 'project_name': 'GFED4', 'references': 'Giglio, Louis, James T. Randerson, and Guido R. Werf. "Analysis of daily, monthly, and annual burned area using the fourth‐generation global fire emissions database (GFED4)." Journal of Geophysical Research: Biogeosciences 118.1 (2013): 317-328.', 'source_name': 'Emission', 'standard_name': 'surface_upward_mass_flux_of_carbon_dioxide_expressed_as_carbon_due_to_emission_from_fires', 'units': 'g C m-2 month-1', 'url': 'http://www.globalfiredata.org/'}
- orig_version :
- gfed4
- project_name :
- GFED4
- time_coverage_end :
- 2010-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- units :
- g C m-2 month-1
- url :
- http://www.globalfiredata.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cee(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 30
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Effective Emissivity at 10.8 um
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud effective emissivity at 10.8 um', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cee', 'spatial_resolution': '0.50 degree', 'standard_name': 'cee', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 1.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- 1
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cer(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 31
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Effective Radius
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud effective radius', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cer', 'spatial_resolution': '0.50 degree', 'standard_name': 'cer', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'um', 'url': 'http://www.dwd.de', 'valid_max': 200.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- um
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cfc(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 32
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud fraction
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud fraction', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cfc', 'spatial_resolution': '0.50 degree', 'standard_name': 'cfc', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 1.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- 1
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - chlor_a(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 29
- esa_cci_path :
- /neodc/esacci/ocean_colour/data/v3.1-release/geographic/netcdf/chlor_a/daily/v3.1
- long_name :
- Chlorophyll-a Concentration in Seawater
- orig_attrs :
- {'Conventions': 'CF-1.6', 'Metadata_Conventions': 'Unidata Dataset Discovery v1.0', 'ancillary_variables': 'chlor_a_log10_rmsd chlor_a_log10_bias', 'cdm_data_type': 'Grid', 'comment': 'See summary attribute', 'creation_date': '20160822T065128Z', 'creator_email': 'help@esa-oceancolour-cci.org', 'creator_name': 'Plymouth Marine Laboratory', 'creator_url': 'http://esa-oceancolour-cci.org', 'date_created': '20160822T065128Z', 'geospatial_lat_max': 90.0, 'geospatial_lat_min': -90.0, 'geospatial_lat_resolution': '.04166666666666666666', 'geospatial_lat_units': 'decimal degrees north', 'geospatial_lon_max': 180.0, 'geospatial_lon_min': -180.0, 'geospatial_lon_resolution': '.04166666666666666666', 'geospatial_lon_units': 'decimal degrees east', 'geospatial_vertical_max': 0.0, 'geospatial_vertical_min': 0.0, 'grid_mapping': 'crs', 'history': 'Source data were: NASA OBPG SeaWiFS level2 R2014.0 LAC and GAC [A/C via l2gen], NASA OBPG VIIRS L2 R2014.0.1 (identical to R2014.0.2) [A/C via l2gen], NASA OBPG MODIS Aqua level 1A [A/C: l2gen equivalent to R2014.0.1 + Polymer 3.5] and ESA MERIS L1B (3rd reprocessing inc OCL correction) [Polymer v3.5]; Derived products were mainly produced with functions validated from the current NASA SeaDAS release and some custom implementations. Uncertainty generation determined by the fuzzy classifier scheme of Tim Moore (2009) and Thomas Jackson et al (2017)', 'id': 'ESACCI-OC-L3S-CHLOR_A-MERGED-1D_DAILY_4km_GEO_PML_OCx-20120101-fv3.1.nc', 'institution': 'Plymouth Marine Laboratory', 'keywords': 'satellite,observation,ocean,ocean colour', 'keywords_vocabulary': 'none', 'license': 'ESA CCI Data Policy: free and open access. When referencing, please use: Ocean Colour Climate Change Initiative dataset, Version <Version Number>, European Space Agency, available online at http://www.esa-oceancolour-cci.org. We would also appreciate being notified of publications so that we can list them on the project website at http://www.esa-oceancolour-cci.org/?q=publications', 'long_name': "Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships", 'naming_authority': 'uk.ac.pml', 'netcdf_file_type': 'NETCDF4_CLASSIC', 'number_of_optical_water_types': '14', 'orig_attrs': {}, 'parameter_vocab_uri': 'http://vocab.nerc.ac.uk/collection/P04/current/', 'platform': 'Orbview-2,Aqua,Envisat,Suomi-NPP', 'processing_level': 'Level-3', 'product_version': '3.1', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-oceancolour-cci.org/', 'sensor': 'SeaWiFS,MODIS,MERIS,VIIRS', 'source': 'NASA SeaWiFS L2 R2014.0 LAC and GAC, MODIS-Aqua L1A, MERIS L1B 3rd reprocessing inc OCL corrections, NASA VIIRS L2 R2014.0.1 (data identical to R2014.0.2)', 'source_dir': '/neodc/esacci/ocean_colour/data/v3.1-release/geographic/netcdf/chlor_a/daily/v3.1/', 'source_name': 'chlor_a', 'source_version': 'v3.1', 'spatial_resolution': '4km nominal at equator', 'standard_name': 'mass_concentration_of_chlorophyll_a_in_sea_water', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Conventions Version 1.6', 'start_date': '01-JAN-2012 00:00:00.000000', 'stop_date': '01-JAN-2012 23:59:00.000000', 'summary': "Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are daily composites of merged sensor (MERIS, MODIS Aqua, SeaWiFS LAC & GAC, VIIRS) products. MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007. VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to SeaWiFS levels, for the overlap period 2012-2013. VIIRS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS and MODIS from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v3.5 (for atmospheric correction). The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM. Derived products were generally computed with the standard SeaDAS algorithms. QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting. The final chlorophyll is a combination of OC4, Hu's CI and OC5, depending on the water class memberships. Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017).", 'time_coverage_duration': 'P1D', 'time_coverage_end': '201201012359Z', 'time_coverage_resolution': 'P1D', 'time_coverage_start': '201201010000Z', 'title': 'ESA CCI Ocean Colour Product', 'tracking_id': '4e0985e0-f157-40f6-b0f1-0a2bb0261f12', 'units': 'milligram m-3', 'units_nonstandard': 'mg m^-3', 'url': 'http://esa-oceancolour-cci.org'}
- orig_version :
- v3.1
- project_name :
- ESA CCI Ocean Colour Product
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1997-09-02
- units :
- milligram m-3
- url :
- http://esa-oceancolour-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cot(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 35
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Optical Thickness
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud optical thickness', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cot', 'spatial_resolution': '0.50 degree', 'standard_name': 'cot', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 320.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- 1
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - country_mask(time, lat, lon)float64dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- orig_attrs :
- {'ds_method': 'MODE', 'orig_attrs': {}, 'source_name': 'country_mask', 'standard_name': 'country_mask', 'units': '-'}
- units :
- -
Array Chunk Bytes 14.12 GB 8.29 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float64 numpy.ndarray - cph(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 39
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Fraction of Liquid Water Clouds
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'fraction of liquid water clouds', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cph', 'spatial_resolution': '0.50 degree', 'standard_name': 'cph', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 1.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- 1
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cth(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 36
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Top Height
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud top height', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cth', 'spatial_resolution': '0.50 degree', 'standard_name': 'cth', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'km', 'url': 'http://www.dwd.de', 'valid_max': 20.0, 'valid_min': -1.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- km
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - ctp(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 37
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Top Pressure
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud top pressure', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'ctp', 'spatial_resolution': '0.50 degree', 'standard_name': 'ctp', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'hPa', 'url': 'http://www.dwd.de', 'valid_max': 1200.0, 'valid_min': 50.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- hPa
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - ctt(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 38
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Top Temperature
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud top temperature', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'ctt', 'spatial_resolution': '0.50 degree', 'standard_name': 'ctt', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'K', 'url': 'http://www.dwd.de', 'valid_max': 320.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- K
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - evaporation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 56
- esa_cci_path :
- nan
- long_name :
- Evaporation
- orig_attrs :
- {'long_name': 'Evaporation', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'E', 'standard_name': 'water_evaporation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- mm/day
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - evaporative_stress(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 57
- esa_cci_path :
- nan
- long_name :
- Evaporative Stress Factor
- orig_attrs :
- {'long_name': 'Evaporative Stress Factor', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'S', 'standard_name': 'evaporative_stress_factor', 'units': '', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - fapar_tip(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 74
- esa_cci_path :
- nan
- long_name :
- Fraction of Absorbed PAR
- orig_attrs :
- {'long_name': 'Fraction of Absorbed Photosynthetically Active Radiation', 'orig_attrs': {}, 'project_name': 'QA4ECV', 'source_name': 'fapar', 'standard_name': 'fapar', 'units': '1', 'url': 'http://www.qa4ecv.eu/'}
- orig_version :
- nan
- project_name :
- QA4ECV
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1982-01-05
- units :
- 1
- url :
- http://www.qa4ecv.eu/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - fat_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 21
- esa_cci_path :
- nan
- long_name :
- Tropospheric Ozone Column (Fixed Altitude)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on Fixed Altitude definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'fat_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - fat_p(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 17
- esa_cci_path :
- nan
- long_name :
- Tropopause Air Pressure for the Fixed Altitude Tropopause
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropopause_air_pressure for the Fixed Altitude Tropopause', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'fat_p', 'standard_name': 'tropopause_air_pressure', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'hPa', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- hPa
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - flt_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 19
- esa_cci_path :
- nan
- long_name :
- Tropospheric Ozone Column
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on Fixed Layers definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'flt_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - flt_p(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 18
- esa_cci_path :
- nan
- long_name :
- Tropopause Air Pressure for the Fixed Layer Tropopause
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropopause_air_pressure for the fixed layer tropopause', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'flt_p', 'standard_name': 'tropopause_air_pressure', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'hPa', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- hPa
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - fractional_snow_cover(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 68
- esa_cci_path :
- nan
- long_name :
- Surface Fraction Covered by Snow
- orig_attrs :
- {'comment': 'Grid cell fractional snow cover based on the Globsnow CCI product.', 'long_name': 'Surface fraction covered by snow.', 'orig_attrs': {}, 'project_name': 'GlobSnow', 'references': 'Luojus, Kari, et al. "ESA DUE Globsnow-Global Snow Database for Climate Research." ESA Special Publication. Vol. 686. 2010.', 'source_name': 'MFSC', 'standard_name': 'surface_snow_area_fraction', 'units': 'percent', 'url': 'http://www.globsnow.info/'}
- orig_version :
- v2.0
- project_name :
- GlobSnow
- time_coverage_end :
- 2013-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- percent
- url :
- http://www.globsnow.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_fat_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 22
- esa_cci_path :
- nan
- long_name :
- Tropospheric Ozone Column (Fixed Altitude)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on Fixed Altitude definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_fat_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_flt_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 23
- esa_cci_path :
- nan
- long_name :
- Tropospheric Ozone Column (Fixed Layers)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on Fixed Layers definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_flt_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_lrt_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 20
- esa_cci_path :
- nan
- long_name :
- Tropospheric Ozone Column ( Lapse Rate)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on lapse rate definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_lrt_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_msr_flt(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 8
- esa_cci_path :
- nan
- long_name :
- Residual MSR-FLT (Stratospheric Part Partial)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'residual MSR-FLT_stratospheric_part partial ozone column in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_msr_flt', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_msr_lrt(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 10
- esa_cci_path :
- nan
- long_name :
- Residual MSR-LRT (Stratospheric Part Partial)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'residual MSR-LRT_stratospheric_part partial ozone column in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_msr_lrt', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - gross_primary_productivity(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 47
- esa_cci_path :
- nan
- long_name :
- Gross Primary Productivity
- orig_attrs :
- {'comment': 'Gross Carbon uptake of of the ecosystem through photosynthesis', 'long_name': 'Gross Primary Productivity', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'GPPall', 'standard_name': 'gross_primary_productivity_of_carbon', 'units': 'gC m-2 day-1', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
- project_name :
- FLUXCOM
- time_coverage_end :
- 2015-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- units :
- gC m-2 day-1
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - interception_loss(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 58
- esa_cci_path :
- nan
- long_name :
- Interception Loss
- orig_attrs :
- {'long_name': 'Interception Loss', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Ei', 'standard_name': 'interception_loss', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- mm/day
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - iwp(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 33
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Ice Water Path
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud ice water path', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'iwp', 'spatial_resolution': '0.50 degree', 'standard_name': 'iwp', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'g/m2', 'url': 'http://www.dwd.de', 'valid_max': 32000.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- g/m2
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - land_surface_temperature(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 69
- esa_cci_path :
- nan
- long_name :
- Land Surface Temperature
- orig_attrs :
- {'comment': 'Advanced Along Track Scanning Radiometer pixel land surface temperature product', 'long_name': 'Land Surface Temperature', 'orig_attrs': {}, 'project_name': 'GlobTemperature', 'references': 'Jiménez, C., et al. "Inversion of AMSR‐E observations for land surface temperature estimation: 1. Methodology and evaluation with station temperature." Journal of Geophysical Research: Atmospheres 122.6 (2017): 3330-3347.', 'source_name': 'LST', 'standard_name': 'surface_temperature', 'units': 'K', 'url': 'http://data.globtemperature.info/'}
- orig_version :
- nan
- project_name :
- GlobTemperature
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2002-05-21
- units :
- K
- url :
- http://data.globtemperature.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - latent_energy(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 48
- esa_cci_path :
- nan
- long_name :
- Latent Energy
- orig_attrs :
- {'comment': 'Latent heat flux from the surface.', 'long_name': 'Latent Energy', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'LE', 'standard_name': 'surface_upward_latent_heat_flux', 'units': 'W m-2', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
- project_name :
- FLUXCOM
- time_coverage_end :
- 2015-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- units :
- W m-2
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - leaf_area_index(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 73
- esa_cci_path :
- nan
- long_name :
- Effective Leaf Area Index
- orig_attrs :
- {'long_name': 'Effective Leaf Area Index', 'orig_attrs': {}, 'project_name': 'QA4ECV', 'source_name': 'Lai', 'standard_name': 'leaf_area_index', 'units': '1', 'url': 'http://www.qa4ecv.eu/'}
- orig_version :
- nan
- project_name :
- QA4ECV
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1982-01-05
- units :
- 1
- url :
- http://www.qa4ecv.eu/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - lrt_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 24
- esa_cci_path :
- nan
- long_name :
- Tropospheric Ozone Column (Lapse Rate)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on lapse rate definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'lrt_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
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- project_name :
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- time_coverage_end :
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- time_coverage_resolution :
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- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
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- ID :
- 16
- esa_cci_path :
- nan
- long_name :
- Tropopause Air Pressure (Lapse Rate)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropopause_air_pressure for the lapse rate tropopause', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'lrt_p', 'standard_name': 'tropopause_air_pressure', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'hPa', 'url': 'http://www.temis.nl/protocols/tropo.html'}
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- units :
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- ID :
- 34
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- long_name :
- Cloud Liquid Water Path
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- orig_version :
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- project_name :
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- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
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- time_coverage_start :
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- units :
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- url :
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- ID :
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- long_name :
- Sea/Land/Lake/Ice Field Composite Mask
- orig_attrs :
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- ID :
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- esa_cci_path :
- nan
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- ID :
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- esa_cci_path :
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- long_name :
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- ID :
- 9
- esa_cci_path :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - msr_lrt(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
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- esa_cci_path :
- nan
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- units :
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- ID :
- 49
- esa_cci_path :
- nan
- long_name :
- Net Ecosystem Exchange
- orig_attrs :
- {'comment': 'Net carbon exchange between the ecosystem and the atmopshere.', 'long_name': 'Net Ecosystem Exchange', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'NEE', 'standard_name': 'net_primary_productivity_of_carbon', 'units': 'gC m-2 day-1', 'url': 'http://www.fluxcom.org/'}
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- units :
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- ID :
- 50
- esa_cci_path :
- nan
- long_name :
- Net Radiation
- orig_attrs :
- {'comment': 'Net radiation to the surface', 'long_name': 'Net Radiation', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'Rn', 'standard_name': 'surface_net_radiation_flux', 'units': 'W m-2', 'url': 'http://www.fluxcom.org/'}
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- ID :
- 59
- esa_cci_path :
- nan
- long_name :
- Open-Water Evaporation
- orig_attrs :
- {'long_name': 'Open-water Evaporation', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Ew', 'standard_name': 'water_evaporation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
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- time_coverage_end :
- 2016-12-30
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - ozone(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 72
- esa_cci_path :
- /neodc/esacci/ozone/data/total_columns/l3/merged/v0100/
- long_name :
- Mean Total Ozone Column in dobson units
- orig_attrs :
- {'comment': 'Atmospheric ozone based on the Ozone CCI data.', 'long_name': 'Mean total ozone column in dobson units', 'orig_attrs': {}, 'project_name': 'Ozone CCI', 'references': 'Laeng, A., et al. "The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)." Remote Sensing of Environment 162 (2015): 316-343.', 'source_name': 'atmosphere_mole_content_of_ozone', 'standard_name': 'atmosphere_mole_content_of_ozone', 'units': 'DU', 'url': 'http://www.esa-ozone-cci.org/'}
- orig_version :
- v0100
- project_name :
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- time_coverage_end :
- 2011-06-30
- time_coverage_resolution :
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- time_coverage_start :
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- units :
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- url :
- http://www.esa-ozone-cci.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - par(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 3
- esa_cci_path :
- nan
- long_name :
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- orig_attrs :
- {'long_name': 'Photosynthetically active radiation', 'orig_attrs': {}, 'project_name': 'BESS', 'references': 'Ryu, Y.*, Jiang, C., Kobayashi, H., & Detto, M. (2018). MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000. Remote Sensing of Environment, 204, 812-825', 'source_name': 'surface_downwelling_photosynthetic_radiative_flux_in_air', 'standard_name': 'surface_downwelling_photosynthetic_radiative_flux_in_air', 'units': 'W m-2', 'url': 'http://environment.snu.ac.kr/bess_rad/'}
- orig_version :
- 15.10.2017
- project_name :
- BESS
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
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- units :
- W m-2
- url :
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- ID :
- 1
- esa_cci_path :
- nan
- long_name :
- Diffuse Photosynthetically Active Radiation
- orig_attrs :
- {'long_name': 'Diffuse Photosynthetically active radiation', 'orig_attrs': {}, 'project_name': 'BESS', 'references': 'Ryu, Y.*, Jiang, C., Kobayashi, H., & Detto, M. (2018). MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000. Remote Sensing of Environment, 204, 812-825', 'source_name': 'surface_diffuse_downwelling_photosynthetic_radiative_flux_in_air', 'standard_name': 'surface_diffuse_downwelling_photosynthetic_radiative_flux_in_air', 'units': 'W m-2', 'url': 'http://environment.snu.ac.kr/bess_rad/'}
- orig_version :
- 15.10.2017
- project_name :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - potential_evaporation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 60
- esa_cci_path :
- nan
- long_name :
- Potential Evaporation
- orig_attrs :
- {'long_name': 'Potential Evaporation', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Ep', 'standard_name': 'potential_water_evaporation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- mm/day
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - precipitation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 71
- esa_cci_path :
- nan
- long_name :
- Precipitation
- orig_attrs :
- {'comment': 'Precipitation based on the GPCP dataset.', 'long_name': 'Precip - RealTime [RT] (see documentation for more information)', 'orig_attrs': {}, 'project_name': 'GPCP', 'references': 'Adler, Robert F., et al. "The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present)." Journal of hydrometeorology 4.6 (2003): 1147-1167.', 'source_name': 'Precip', 'standard_name': 'precipitation_flux', 'units': 'mm/day', 'url': 'http://precip.gsfc.nasa.gov/'}
- orig_version :
- nan
- project_name :
- GPCP
- time_coverage_end :
- 2015-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- units :
- mm/day
- url :
- http://precip.gsfc.nasa.gov/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - precipitation_era5(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 5
- esa_cci_path :
- nan
- long_name :
- ERA5 Precipitation
- orig_attrs :
- {'comment': 'Total precipitation from the ERA5 reanalysis product.', 'long_name': 'ERA 5 Precipitation', 'orig_attrs': {}, 'project_name': 'ERA5', 'references': '', 'source_name': 'precipitation', 'units': 'K', 'url': 'https://confluence.ecmwf.int//display/CKB/ERA5+data+documentation'}
- orig_version :
- ERA5
- project_name :
- ERA5
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-05
- units :
- K
- url :
- https://confluence.ecmwf.int//display/CKB/ERA5+data+documentation
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - psurf(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 12
- esa_cci_path :
- nan
- long_name :
- Surface Air Pressure
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'surface_air_pressure', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'psurf', 'standard_name': 'surface_air_pressure', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'hPa', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- hPa
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - root_moisture(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 61
- esa_cci_path :
- nan
- long_name :
- Root-Zone Soil Moisture
- orig_attrs :
- {'long_name': 'Root-Zone Soil Moisture', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'SMroot', 'standard_name': 'soil_moisture_content', 'units': 'm3/m3', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- m3/m3
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - sea_ice_fraction(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 45
- esa_cci_path :
- /neodc/esacci/sst/data/lt/Analysis/L4/v01.1/
- long_name :
- Sea Ice Area Fraction
- orig_attrs :
- {'Conventions': 'CF-1.5, Unidata Observation Dataset v1.0', 'Metadata_Conventions': 'Unidata Dataset Discovery v1.0', 'acknowledgment': 'Funded by ESA', 'cdm_data_type': 'grid', 'comment': 'WARNING Some applications are unable to properly handle signed byte values. If values are encountered > 127, please subtract 256 from this reported value', 'creator_email': 'science.leader@esa-sst-cci.org', 'creator_name': 'ESA SST CCI', 'creator_processing_institution': 'These data were produced at the Met Office as part of the ESA SST CCI project.', 'creator_url': 'http://www.esa-sst-cci.org', 'date_created': '20130309T132046Z', 'easternmost_longitude': 180.00001525878906, 'file_quality_level': 3, 'gds_version_id': '2.0', 'geospatial_lat_max': 90.0, 'geospatial_lat_min': -90.0, 'geospatial_lat_resolution': 0.05000000074505806, 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 180.0, 'geospatial_lon_min': -180.0, 'geospatial_lon_resolution': 0.05000000074505806, 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': -0.20000000298023224, 'geospatial_vertical_min': -0.20000000298023224, 'history': 'Created using OSTIA reanalysis system v2.0', 'id': 'OSTIA-ESACCI-L4-v01.1', 'institution': 'ESACCI', 'keywords': 'Oceans > Ocean Temperature > Sea Surface Temperature', 'keywords_vocabulary': 'NASA Global Change Master Directory (GCMD) Science Keywords', 'license': 'GHRSST protocol describes data use as free and open', 'long_name': 'sea ice area fraction', 'metadata_link': 'http://www.esa-cci.org', 'naming_authority': 'org.ghrsst', 'netcdf_version_id': '4.1.3', 'northernmost_latitude': 90.0, 'platform': 'ERS-<1,2>, Envisat, NOAA-<12,14,15,16,17,18>, MetOpA', 'processing_level': 'L4', 'product_version': '1.1', 'project': 'Climate Change Initiative - European Space Agency', 'publisher_email': 'science.leader@esa-sst-cci.org', 'publisher_name': 'ESACCI', 'publisher_url': 'http://www.esa-sst-cci.org', 'references': 'http://www.esa-sst-cci.org', 'sensor': 'ATSR, AATSR, AVHRR_GAC', 'source': 'ATSR<1,2>-ESACCI-L3U-v1.0, AATSR-ESACCI-L3U-v1.0, AVHRR<12,14,15,16,17,18>_G-ESACCI-L2P-v1.0, AVHRRMTA-ESACCI-L2P-v1.0, EUMETSAT_OSI-SAF-ICE-v1.1, EUMETSAT_OSI-SAF-ICE-v2.2', 'source_dir': '/neodc/esacci/sst/data/lt/Analysis/L4/v01.1', 'source_name': 'sea_ice_fraction', 'source_version': 'v01.1', 'southernmost_latitude': -90.0, 'spatial_resolution': '0.05 degree', 'standard_name': 'sea_ice_area_fraction', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Convention', 'summary': 'OSTIA L4 product from the ESA SST CCI project, produced using OSTIA reanalysis system v2.0. Ice field corrected in v1.1 (v1.0 had ice from day-1). Static ice field between 20080101-20080229 and 20080501-20080521 also fixed in v1.1', 'time_coverage_duration': 'P1D', 'time_coverage_end': '20100101T235959Z', 'time_coverage_resolution': 'P1D', 'time_coverage_start': '20100101T000000Z', 'title': 'ESA SST CCI OSTIA L4 product', 'tracking_id': '19b1f7a4-d8d1-44eb-9cfa-37cc33c4c2c1', 'units': '1', 'url': 'http://www.esa-sst-cci.org', 'uuid': '19b1f7a4-d8d1-44eb-9cfa-37cc33c4c2c1', 'valid_max': 100.0, 'valid_min': 0.0, 'westernmost_longitude': -180.0}
- orig_version :
- v01.1
- project_name :
- ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI)
- time_coverage_end :
- 2010-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1991-09-02
- units :
- 1
- url :
- http://www.esa-sst-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - sensible_heat(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 51
- esa_cci_path :
- nan
- long_name :
- Sensible Heat
- orig_attrs :
- {'comment': 'Sensible heat flux from the surface', 'long_name': 'Sensible Heat', 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'H', 'standard_name': 'surface_upward_sensible_heat_flux', 'units': 'W m-2', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
- project_name :
- FLUXCOM
- time_coverage_end :
- 2015-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- units :
- W m-2
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - snow_sublimation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 62
- esa_cci_path :
- nan
- long_name :
- Snow Sublimation
- orig_attrs :
- {'long_name': 'Snow Sublimation', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Es', 'standard_name': 'snow_sublimation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- mm/day
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - snow_water_equivalent(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 67
- esa_cci_path :
- nan
- long_name :
- Daily Snow Water Equivalent
- orig_attrs :
- {'certain_values': '-2 == mountains, -1 == water bodies, 0 == either SWE, or missing data in the southern hemisphere', 'comment': 'Grid cell fractional snow cover based on the Globsnow CCI product.', 'long_name': 'Daily Snow Water Equivalent', 'project_name': 'GlobSnow', 'references': 'Luojus, Kari, et al. "ESA DUE Globsnow-Global Snow Database for Climate Research." ESA Special Publication. Vol. 686. 2010.', 'source_name': 'SWE', 'units': 'mm', 'url': 'http://www.globsnow.info/'}
- orig_version :
- v2.0
- project_name :
- GlobSnow
- time_coverage_end :
- 2012-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- units :
- mm
- url :
- http://www.globsnow.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - soil_moisture(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 78
- esa_cci_path :
- /neodc/esacci/soil_moisture/data/daily_files/COMBINED/v04.2/
- long_name :
- Soil Moisture
- orig_attrs :
- {'comment': 'Soil moisture based on the SOilmoisture CCI project', 'long_name': 'Soil Moisture', 'project_name': 'SoilMoisture CCI', 'references': 'Liu, Y.Y., Parinussa, R.M., Dorigo, W.A., De Jeu, R.A.M., Wagner, W., McCabe, M.F., Evans, J.P., and van Dijk, A.I.J.M. (2012): Trend-preserving blending of passive and active microwave soil moisture retrievals; Liu, Y.Y., Parinussa, R.M., Dorigo, W.A., De Jeu, R.A.M., Wagner, W., van Dijk, A.I.J.M., McCabe, M.F., & Evans, J.P. (2011): Developing an improved soil moisture dataset by blending passive and active microwave satellite based retrievals. Hydrology and Earth System Sciences, 15, 425-436.', 'source_name': 'SoilMoisture', 'standard_name': 'soil_moisture_content', 'units': 'm3', 'url': 'http://www.esa-soilmoisture-cci.org'}
- orig_version :
- v04.2
- project_name :
- SoilMoisture CCI
- time_coverage_end :
- 2014-01-29
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- units :
- m3
- url :
- http://www.esa-soilmoisture-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - srex_mask(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 77
- esa_cci_path :
- nan
- long_name :
- Mask for SREX Regions
- orig_attrs :
- {'ds_method': 'MODE', 'long_name': 'Mask for SREX regions', 'source_name': 'layer', 'standard_name': 'srex_mask', 'units': '-'}
- orig_version :
- nan
- project_name :
- regionmask - SREX Regions
- time_coverage_end :
- 1980-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- units :
- -
- url :
- https://regionmask.readthedocs.io/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - stemp(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 40
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Surface Temperature
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'surface temperature', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'stemp', 'spatial_resolution': '0.50 degree', 'standard_name': 'stemp', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'K', 'url': 'http://www.dwd.de', 'valid_max': 320.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- units :
- K
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - surface_moisture(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 63
- esa_cci_path :
- nan
- long_name :
- Surface Soil Moisture
- orig_attrs :
- {'long_name': 'Surface Soil Moisture', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'SMsurf', 'standard_name': 'soil_moisture_content', 'units': 'mm3/mm3', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- mm3/mm3
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - terrestrial_ecosystem_respiration(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 52
- esa_cci_path :
- nan
- long_name :
- Terrestrial Ecosystem Respiration
- orig_attrs :
- {'comment': 'Total carbon release of the ecosystem through respiration.', 'long_name': 'Terrestrial Ecosystem Respiration', 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'TERall', 'standard_name': 'ecosystem_respiration_carbon_flux', 'units': 'gC m-2 day-1', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
- project_name :
- FLUXCOM
- time_coverage_end :
- 2012-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- units :
- gC m-2 day-1
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - totcol_assim(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 13
- esa_cci_path :
- nan
- long_name :
- Total Ozone Column (Assimilated TM5 data)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'total ozone column derived from assimilated TM5 data', 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'totcol_assim', 'standard_name': 'atmosphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - totcol_free(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 14
- esa_cci_path :
- nan
- long_name :
- Total Ozone Column (Assimilated TM5 data)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'total ozone column derived from assimilated TM5 data', 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'totcol_free', 'standard_name': 'atmosphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - totcol_msr(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 15
- esa_cci_path :
- nan
- long_name :
- Total Ozone Column (MSR data)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'total ozone column derived from MSR data', 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'totcol_msr', 'standard_name': 'atmosphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- units :
- mol m-2
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - transpiration(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 64
- esa_cci_path :
- nan
- long_name :
- Transpiration
- orig_attrs :
- {'long_name': 'Transpiration', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Et', 'standard_name': 'transpiration_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- units :
- mm/day
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - water_mask(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 43
- esa_cci_path :
- /neodc/esacci/land_cover/data/water_bodies/v4.0/
- long_name :
- Terrestrial or Water Pixel Classification
- orig_attrs :
- {'long_name': 'Terrestrial or water pixel classification', 'project_name': 'Climate Change Initiative - European Space Agency', 'source_name': 'wb_class', 'standard_name': 'land_cover_lccs', 'units': '-', 'url': 'http://www.esa-landcover-cci.org'}
- orig_version :
- v4.0
- project_name :
- ESA Land Cover Climate Change Initiative (Land_Cover_cci)
- time_coverage_end :
- 1980-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- units :
- -
- url :
- http://www.esa-landcover-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - water_vapour(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 70
- esa_cci_path :
- nan
- long_name :
- Total Column Water Vapour
- orig_attrs :
- {'comment': 'Total column water vapour based on the GlobVapour CCI product.', 'long_name': 'Total Column Water Vapour', 'project_name': 'GlobVapour', 'references': 'Schneider, Nadine, et al. "ESA DUE GlobVapour water vapor products: Validation." AIP Conference Proceedings. Vol. 1531. No. 1. 2013.', 'source_name': 'tcwv_res', 'standard_name': 'atmosphere_mass_content_of_water_vapor', 'units': 'kg m-2', 'url': 'http://www.globvapour.info/'}
- orig_version :
- nan
- project_name :
- GlobVapour
- time_coverage_end :
- 2008-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1996-01-05
- units :
- kg m-2
- url :
- http://www.globvapour.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - white_sky_albedo(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 66
- esa_cci_path :
- nan
- long_name :
- White Sky Albedo for Visible Wavebands
- orig_attrs :
- {'comment': 'White sky albedo derived from the GlobAlbedo CCI project dataset', 'long_name': 'White Sky Albedo for Visible Wavebands', 'project_name': 'GlobAlbedo', 'references': 'Muller, Jan-Peter, et al. "The ESA GLOBALBEDO project for mapping the Earth’s land surface albedo for 15 years from European sensors." Geophysical Research Abstracts. Vol. 13. 2012.', 'source_name': 'BHR_VIS', 'standard_name': 'surface_albedo_white_sky', 'units': '-', 'url': 'http://www.globalbedo.org/'}
- orig_version :
- nan
- project_name :
- GlobAlbedo
- time_coverage_end :
- 2012-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1998-01-05
- units :
- -
- url :
- http://www.globalbedo.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - white_sky_albedo_avhrr(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 75
- esa_cci_path :
- nan
- long_name :
- Bi-Hemisphere Reflectance Albedo - VIS band
- orig_attrs :
- {'comment': 'White sky albedo derived from the QA4ECV Albedo Product', 'long_name': 'Bi-Hemisphere Reflectance albedo - VIS band', 'project_name': 'QA4ECV - European Union Framework Program 7', 'source_name': 'BHR_VIS', 'standard_name': 'surface_albedo_white_sky', 'units': '1', 'url': 'http://www.qa4ecv.eu/'}
- orig_version :
- nan
- project_name :
- QA4ECV - European Union Framework Program 7
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1982-01-05
- units :
- 1
- url :
- http://www.qa4ecv.eu/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - xch4(time, lat, lon)float64dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 42
- esa_cci_path :
- /neodc/esacci/ghg/data/obs4mips/crdp_3/CO2/v100/
- long_name :
- Column Average Dry-air Mole Fraction Methane
- orig_attrs :
- {'Conventions': 'CF-1.6', 'associated_files': 'obs4mips_co2_crdp3_v100.sav', 'cell_methods': 'time: mean', 'comment': 'Satellite retrieved column-average dry-air mole fraction of atmospheric carbon dioxide (XCO2)', 'contact': 'maximilian.reuter@iup.physik.uni-bremen.de', 'creation_date': '20160303T111125Z', 'data_structure': 'grid', 'frequency': 'mon', 'institute_id': 'IUP', 'institution': 'Institute of Environmental Physics, University of Bremen', 'long_name': 'column-average dry-air mole fraction of atmospheric carbon dioxide', 'mip_specs': 'CMIP5', 'product': 'observations', 'project_id': 'obs4MIPs', 'project_name': 'Ozone CCI', 'realm': 'atmos', 'references': 'Laeng, A., et al. "The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)." Remote Sensing of Environment 162 (2015): 316-343.', 'source': 'ESA GHG CCI XCO2 CRDP3', 'source_id': 'XCO2_CRDP3', 'source_name': 'xch4', 'source_type': 'satellite_retrieval', 'standard_name': 'dry_atmosphere_mole_fraction_of_carbon_dioxide', 'tracking_id': '60972082-05c2-4a04-947a-99042c642c68', 'units': '1', 'url': 'http://www.esa-ghg-cci.org/'}
- orig_version :
- v100
- project_name :
- ESA Greenhouse Gases Climate Change Initiative (GHG_cci)
- time_coverage_end :
- 2014-12-15
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-13
- units :
- 1
- url :
- http://www.esa-ghg-cci.org/
Array Chunk Bytes 14.12 GB 8.29 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float64 numpy.ndarray - xco2(time, lat, lon)float64dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 41
- esa_cci_path :
- /neodc/esacci/ghg/data/obs4mips/crdp_3/CO2/v100/
- long_name :
- Column Average Dry-air Mole Fraction Carbon Dioxide
- orig_attrs :
- {'Conventions': 'CF-1.6', 'associated_files': 'obs4mips_co2_crdp3_v100.sav', 'cell_methods': 'time: mean', 'comment': 'Satellite retrieved column-average dry-air mole fraction of atmospheric carbon dioxide (XCO2)', 'contact': 'maximilian.reuter@iup.physik.uni-bremen.de', 'creation_date': '20160303T111125Z', 'data_structure': 'grid', 'frequency': 'mon', 'institute_id': 'IUP', 'institution': 'Institute of Environmental Physics, University of Bremen', 'long_name': 'column-average dry-air mole fraction of atmospheric carbon dioxide', 'mip_specs': 'CMIP5', 'product': 'observations', 'project_id': 'obs4MIPs', 'project_name': 'Ozone CCI', 'realm': 'atmos', 'references': 'Laeng, A., et al. "The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)." Remote Sensing of Environment 162 (2015): 316-343.', 'source': 'ESA GHG CCI XCO2 CRDP3', 'source_id': 'XCO2_CRDP3', 'source_name': 'xco2', 'source_type': 'satellite_retrieval', 'standard_name': 'dry_atmosphere_mole_fraction_of_carbon_dioxide', 'tracking_id': '60972082-05c2-4a04-947a-99042c642c68', 'units': '1', 'url': 'http://www.esa-ghg-cci.org/'}
- orig_version :
- v100
- project_name :
- ESA Greenhouse Gases Climate Change Initiative (GHG_cci)
- time_coverage_end :
- 2014-12-15
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-13
- units :
- 1
- url :
- http://www.esa-ghg-cci.org/
Array Chunk Bytes 14.12 GB 8.29 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float64 numpy.ndarray
- Metadata_conventions :
- Unidata Dataset Discovery v1.0
- acknowledgment :
- The ESDL team acknowledges all data providers!
- chunking :
- 1x720x1440
- comment :
- none.
- contributor_name :
- Max Planck Institute for Biogeochemistry
- contributor_role :
- ESDL Science Lead
- creator_email :
- info@earthsystemdatalab.net
- creator_name :
- Brockmann Consult GmbH
- creator_url :
- www.earthsystemdatalab.net
- date_created :
- 17.12.2018
- date_issued :
- 19.12.2018
- date_modified :
- 17.12.2018
- geospatial_lat_max :
- 89.75
- geospatial_lat_min :
- -89.75
- geospatial_lon_max :
- 179.75
- geospatial_lon_min :
- -179.75
- geospatial_resolution :
- 1/4deg
- history :
- - processing with esdl cube v0.1 (https://github.com/esa-esdl/esdl-core/)
- id :
- v2.0.0
- institution :
- Brockmann Consult GmbH
- keywords :
- Earth Science, Geophysical Variables
- license :
- Please refer to individual variables
- naming_authority :
- Earth System Data Lab team
- processing_level :
- Level 4
- project :
- ESA Earth System Data Lab
- publisher_email :
- info@earthsystemdatalab.net
- publisher_name :
- Brockmann Consult GmbH & Max Planck Institute for Biogechemistry
- publisher_url :
- www.brockmann-consult.de
- standard_name_vocabulary :
- CF-1.7
- summary :
- This data set contains a data cube of Earth System variables created by the ESA project Earth System Data Lab.
- time_coverage_duration :
- P37Y
- time_coverage_end :
- 30.12.2016
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 05.01.1980
- title :
- Earth System Data Cube
And now we can access the variables that we require only, e.g.
gross_primary_productivity and soil_moisture.
variables = [
'land_surface_temperature',
'soil_moisture'
]
cubes = cube_from_s3_bucket[variables]
cubes
xarray.Dataset
- lat: 720
- lon: 1440
- time: 1702
- lon(lon)float32-179.875 -179.625 ... 179.875
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875], dtype=float32) - lat(lat)float3289.875 89.625 ... -89.625 -89.875
array([ 89.875, 89.625, 89.375, ..., -89.375, -89.625, -89.875], dtype=float32) - time(time)datetime64[ns]1980-01-05 ... 2016-12-30
- bounds :
- time_bnds
- long_name :
- time
- standard_name :
- time
array(['1980-01-05T00:00:00.000000000', '1980-01-13T00:00:00.000000000', '1980-01-21T00:00:00.000000000', ..., '2016-12-14T00:00:00.000000000', '2016-12-22T00:00:00.000000000', '2016-12-30T00:00:00.000000000'], dtype='datetime64[ns]')
- land_surface_temperature(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 69
- esa_cci_path :
- nan
- long_name :
- Land Surface Temperature
- orig_attrs :
- {'comment': 'Advanced Along Track Scanning Radiometer pixel land surface temperature product', 'long_name': 'Land Surface Temperature', 'orig_attrs': {}, 'project_name': 'GlobTemperature', 'references': 'Jiménez, C., et al. "Inversion of AMSR‐E observations for land surface temperature estimation: 1. Methodology and evaluation with station temperature." Journal of Geophysical Research: Atmospheres 122.6 (2017): 3330-3347.', 'source_name': 'LST', 'standard_name': 'surface_temperature', 'units': 'K', 'url': 'http://data.globtemperature.info/'}
- orig_version :
- nan
- project_name :
- GlobTemperature
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2002-05-21
- units :
- K
- url :
- http://data.globtemperature.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - soil_moisture(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 78
- esa_cci_path :
- /neodc/esacci/soil_moisture/data/daily_files/COMBINED/v04.2/
- long_name :
- Soil Moisture
- orig_attrs :
- {'comment': 'Soil moisture based on the SOilmoisture CCI project', 'long_name': 'Soil Moisture', 'project_name': 'SoilMoisture CCI', 'references': 'Liu, Y.Y., Parinussa, R.M., Dorigo, W.A., De Jeu, R.A.M., Wagner, W., McCabe, M.F., Evans, J.P., and van Dijk, A.I.J.M. (2012): Trend-preserving blending of passive and active microwave soil moisture retrievals; Liu, Y.Y., Parinussa, R.M., Dorigo, W.A., De Jeu, R.A.M., Wagner, W., van Dijk, A.I.J.M., McCabe, M.F., & Evans, J.P. (2011): Developing an improved soil moisture dataset by blending passive and active microwave satellite based retrievals. Hydrology and Earth System Sciences, 15, 425-436.', 'source_name': 'SoilMoisture', 'standard_name': 'soil_moisture_content', 'units': 'm3', 'url': 'http://www.esa-soilmoisture-cci.org'}
- orig_version :
- v04.2
- project_name :
- SoilMoisture CCI
- time_coverage_end :
- 2014-01-29
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- units :
- m3
- url :
- http://www.esa-soilmoisture-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray
- Metadata_conventions :
- Unidata Dataset Discovery v1.0
- acknowledgment :
- The ESDL team acknowledges all data providers!
- chunking :
- 1x720x1440
- comment :
- none.
- contributor_name :
- Max Planck Institute for Biogeochemistry
- contributor_role :
- ESDL Science Lead
- creator_email :
- info@earthsystemdatalab.net
- creator_name :
- Brockmann Consult GmbH
- creator_url :
- www.earthsystemdatalab.net
- date_created :
- 17.12.2018
- date_issued :
- 19.12.2018
- date_modified :
- 17.12.2018
- geospatial_lat_max :
- 89.75
- geospatial_lat_min :
- -89.75
- geospatial_lon_max :
- 179.75
- geospatial_lon_min :
- -179.75
- geospatial_resolution :
- 1/4deg
- history :
- - processing with esdl cube v0.1 (https://github.com/esa-esdl/esdl-core/)
- id :
- v2.0.0
- institution :
- Brockmann Consult GmbH
- keywords :
- Earth Science, Geophysical Variables
- license :
- Please refer to individual variables
- naming_authority :
- Earth System Data Lab team
- processing_level :
- Level 4
- project :
- ESA Earth System Data Lab
- publisher_email :
- info@earthsystemdatalab.net
- publisher_name :
- Brockmann Consult GmbH & Max Planck Institute for Biogechemistry
- publisher_url :
- www.brockmann-consult.de
- standard_name_vocabulary :
- CF-1.7
- summary :
- This data set contains a data cube of Earth System variables created by the ESA project Earth System Data Lab.
- time_coverage_duration :
- P37Y
- time_coverage_end :
- 30.12.2016
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 05.01.1980
- title :
- Earth System Data Cube
cube_from_s3_bucket.precipitation.mean(dim='time').plot()
/home/emmanuel/.conda/envs/rbig_eo/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
<matplotlib.collections.QuadMesh at 0x7f1f505a96d0>
cube_from_s3_bucket.root_moisture.mean(dim='time').plot()
Method II - Personal Server¶
Like I said before, I have personally downloaded the cubes on our server so I can access them in house. First let's look at the available cubes.
!ls $DATA_PATH
Cube_2019highColombiaCube_184x120x120.zarr Cube_2019highColombiaCube_1x3360x2760.zarr esdc-8d-0.083deg-184x270x270-2.0.0.zarr esdc-8d-0.083deg-1x2160x4320-2.0.0.zarr esdc-8d-0.25deg-184x90x90-2.0.0.zarr esdc-8d-0.25deg-1x720x1440-2.0.0.zarr
We're going to open the datacube with
0.25 degree resolution that is optimized for spatial computations.
# get filename
filename = DATA_PATH.joinpath("esdc-8d-0.25deg-1x720x1440-2.0.0.zarr")
# open datacube
datacube = xr.open_zarr(str(filename))
datacube
xarray.Dataset
- bnds: 2
- lat: 720
- lon: 1440
- time: 1702
- lat(lat)float3289.875 89.625 ... -89.625 -89.875
array([ 89.875, 89.625, 89.375, ..., -89.375, -89.625, -89.875], dtype=float32) - lat_bnds(lat, bnds)float32dask.array<chunksize=(720, 2), meta=np.ndarray>
Array Chunk Bytes 5.76 kB 5.76 kB Shape (720, 2) (720, 2) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - lon(lon)float32-179.875 -179.625 ... 179.875
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875], dtype=float32) - lon_bnds(lon, bnds)float32dask.array<chunksize=(1440, 2), meta=np.ndarray>
Array Chunk Bytes 11.52 kB 11.52 kB Shape (1440, 2) (1440, 2) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - time(time)datetime64[ns]1980-01-05 ... 2016-12-30
- bounds :
- time_bnds
- long_name :
- time
- standard_name :
- time
array(['1980-01-05T00:00:00.000000000', '1980-01-13T00:00:00.000000000', '1980-01-21T00:00:00.000000000', ..., '2016-12-14T00:00:00.000000000', '2016-12-22T00:00:00.000000000', '2016-12-30T00:00:00.000000000'], dtype='datetime64[ns]') - time_bnds(time, bnds)datetime64[ns]dask.array<chunksize=(1702, 2), meta=np.ndarray>
Array Chunk Bytes 27.23 kB 27.23 kB Shape (1702, 2) (1702, 2) Count 2 Tasks 1 Chunks Type datetime64[ns] numpy.ndarray
- Rg(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 2
- esa_cci_path :
- nan
- long_name :
- Downwelling shortwave radiation
- orig_attrs :
- {'long_name': 'Downwelling shortwave radiation', 'project_name': 'BESS', 'references': 'Ryu, Y.*, Jiang, C., Kobayashi, H., & Detto, M. (2018). MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000. Remote Sensing of Environment, 204, 812-825', 'source_name': 'surface_downwelling_shortwave_flux_in_air', 'standard_name': 'surface_downwelling_shortwave_flux_in_air', 'units': 'W m-2', 'url': 'http://environment.snu.ac.kr/bess_rad/'}
- orig_version :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - aerosol_optical_thickness_1600(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
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- esa_cci_path :
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- long_name :
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- orig_attrs :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - aerosol_optical_thickness_550(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
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- esa_cci_path :
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- long_name :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - aerosol_optical_thickness_670(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
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- esa_cci_path :
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- long_name :
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- ID :
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- esa_cci_path :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - bare_soil_evaporation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
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- esa_cci_path :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - black_sky_albedo(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
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- esa_cci_path :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - black_sky_albedo_avhrr(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
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- esa_cci_path :
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- url :
- http://www.qa4ecv.eu/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - burnt_area(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 54
- esa_cci_path :
- nan
- long_name :
- Monthly Burnt Area
- orig_attrs :
- {'comment': 'Burnt Area based on the GFED4 fire product.', 'long_name': 'Monthly Burnt Area', 'orig_attrs': {}, 'project_name': 'GFED4', 'references': 'Giglio, Louis, James T. Randerson, and Guido R. Werf. "Analysis of daily, monthly, and annual burned area using the fourth‐generation global fire emissions database (GFED4)." Journal of Geophysical Research: Biogeosciences 118.1 (2013): 317-328.', 'source_name': 'BurntArea', 'standard_name': 'burnt_area', 'units': 'hectares', 'url': 'http://www.globalfiredata.org/'}
- orig_version :
- gfed4
- project_name :
- GFED4
- time_coverage_end :
- 2014-03-02
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1995-01-05
- url :
- http://www.globalfiredata.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - c_emissions(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 53
- esa_cci_path :
- nan
- long_name :
- Carbon Dioxide Emissions Due to Natural Fires
- orig_attrs :
- {'comment': 'Carbon emissions by fires based on the GFED4 fire product.', 'long_name': 'Carbon dioxide emissions due to natural fires expressed as carbon flux.', 'orig_attrs': {}, 'project_name': 'GFED4', 'references': 'Giglio, Louis, James T. Randerson, and Guido R. Werf. "Analysis of daily, monthly, and annual burned area using the fourth‐generation global fire emissions database (GFED4)." Journal of Geophysical Research: Biogeosciences 118.1 (2013): 317-328.', 'source_name': 'Emission', 'standard_name': 'surface_upward_mass_flux_of_carbon_dioxide_expressed_as_carbon_due_to_emission_from_fires', 'units': 'g C m-2 month-1', 'url': 'http://www.globalfiredata.org/'}
- orig_version :
- gfed4
- project_name :
- GFED4
- time_coverage_end :
- 2010-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- url :
- http://www.globalfiredata.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cee(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 30
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Effective Emissivity at 10.8 um
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud effective emissivity at 10.8 um', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cee', 'spatial_resolution': '0.50 degree', 'standard_name': 'cee', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 1.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cer(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 31
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Effective Radius
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud effective radius', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cer', 'spatial_resolution': '0.50 degree', 'standard_name': 'cer', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'um', 'url': 'http://www.dwd.de', 'valid_max': 200.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cfc(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 32
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud fraction
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud fraction', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cfc', 'spatial_resolution': '0.50 degree', 'standard_name': 'cfc', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 1.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - chlor_a(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 29
- esa_cci_path :
- /neodc/esacci/ocean_colour/data/v3.1-release/geographic/netcdf/chlor_a/daily/v3.1
- long_name :
- Chlorophyll-a Concentration in Seawater
- orig_attrs :
- {'Conventions': 'CF-1.6', 'Metadata_Conventions': 'Unidata Dataset Discovery v1.0', 'ancillary_variables': 'chlor_a_log10_rmsd chlor_a_log10_bias', 'cdm_data_type': 'Grid', 'comment': 'See summary attribute', 'creation_date': '20160822T065128Z', 'creator_email': 'help@esa-oceancolour-cci.org', 'creator_name': 'Plymouth Marine Laboratory', 'creator_url': 'http://esa-oceancolour-cci.org', 'date_created': '20160822T065128Z', 'geospatial_lat_max': 90.0, 'geospatial_lat_min': -90.0, 'geospatial_lat_resolution': '.04166666666666666666', 'geospatial_lat_units': 'decimal degrees north', 'geospatial_lon_max': 180.0, 'geospatial_lon_min': -180.0, 'geospatial_lon_resolution': '.04166666666666666666', 'geospatial_lon_units': 'decimal degrees east', 'geospatial_vertical_max': 0.0, 'geospatial_vertical_min': 0.0, 'grid_mapping': 'crs', 'history': 'Source data were: NASA OBPG SeaWiFS level2 R2014.0 LAC and GAC [A/C via l2gen], NASA OBPG VIIRS L2 R2014.0.1 (identical to R2014.0.2) [A/C via l2gen], NASA OBPG MODIS Aqua level 1A [A/C: l2gen equivalent to R2014.0.1 + Polymer 3.5] and ESA MERIS L1B (3rd reprocessing inc OCL correction) [Polymer v3.5]; Derived products were mainly produced with functions validated from the current NASA SeaDAS release and some custom implementations. Uncertainty generation determined by the fuzzy classifier scheme of Tim Moore (2009) and Thomas Jackson et al (2017)', 'id': 'ESACCI-OC-L3S-CHLOR_A-MERGED-1D_DAILY_4km_GEO_PML_OCx-20120101-fv3.1.nc', 'institution': 'Plymouth Marine Laboratory', 'keywords': 'satellite,observation,ocean,ocean colour', 'keywords_vocabulary': 'none', 'license': 'ESA CCI Data Policy: free and open access. When referencing, please use: Ocean Colour Climate Change Initiative dataset, Version <Version Number>, European Space Agency, available online at http://www.esa-oceancolour-cci.org. We would also appreciate being notified of publications so that we can list them on the project website at http://www.esa-oceancolour-cci.org/?q=publications', 'long_name': "Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships", 'naming_authority': 'uk.ac.pml', 'netcdf_file_type': 'NETCDF4_CLASSIC', 'number_of_optical_water_types': '14', 'orig_attrs': {}, 'parameter_vocab_uri': 'http://vocab.nerc.ac.uk/collection/P04/current/', 'platform': 'Orbview-2,Aqua,Envisat,Suomi-NPP', 'processing_level': 'Level-3', 'product_version': '3.1', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-oceancolour-cci.org/', 'sensor': 'SeaWiFS,MODIS,MERIS,VIIRS', 'source': 'NASA SeaWiFS L2 R2014.0 LAC and GAC, MODIS-Aqua L1A, MERIS L1B 3rd reprocessing inc OCL corrections, NASA VIIRS L2 R2014.0.1 (data identical to R2014.0.2)', 'source_dir': '/neodc/esacci/ocean_colour/data/v3.1-release/geographic/netcdf/chlor_a/daily/v3.1/', 'source_name': 'chlor_a', 'source_version': 'v3.1', 'spatial_resolution': '4km nominal at equator', 'standard_name': 'mass_concentration_of_chlorophyll_a_in_sea_water', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Conventions Version 1.6', 'start_date': '01-JAN-2012 00:00:00.000000', 'stop_date': '01-JAN-2012 23:59:00.000000', 'summary': "Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are daily composites of merged sensor (MERIS, MODIS Aqua, SeaWiFS LAC & GAC, VIIRS) products. MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007. VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to SeaWiFS levels, for the overlap period 2012-2013. VIIRS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS and MODIS from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v3.5 (for atmospheric correction). The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM. Derived products were generally computed with the standard SeaDAS algorithms. QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting. The final chlorophyll is a combination of OC4, Hu's CI and OC5, depending on the water class memberships. Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017).", 'time_coverage_duration': 'P1D', 'time_coverage_end': '201201012359Z', 'time_coverage_resolution': 'P1D', 'time_coverage_start': '201201010000Z', 'title': 'ESA CCI Ocean Colour Product', 'tracking_id': '4e0985e0-f157-40f6-b0f1-0a2bb0261f12', 'units': 'milligram m-3', 'units_nonstandard': 'mg m^-3', 'url': 'http://esa-oceancolour-cci.org'}
- orig_version :
- v3.1
- project_name :
- ESA CCI Ocean Colour Product
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1997-09-02
- url :
- http://esa-oceancolour-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cot(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 35
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Optical Thickness
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud optical thickness', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cot', 'spatial_resolution': '0.50 degree', 'standard_name': 'cot', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 320.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - country_mask(time, lat, lon)float64dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- orig_attrs :
- {'ds_method': 'MODE', 'orig_attrs': {}, 'source_name': 'country_mask', 'standard_name': 'country_mask', 'units': '-'}
Array Chunk Bytes 14.12 GB 8.29 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float64 numpy.ndarray - cph(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 39
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Fraction of Liquid Water Clouds
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'fraction of liquid water clouds', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'cph', 'spatial_resolution': '0.50 degree', 'standard_name': 'cph', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': '1', 'url': 'http://www.dwd.de', 'valid_max': 1.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - cth(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 36
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Top Height
- orig_attrs :
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- ID :
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- esa_cci_path :
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- long_name :
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- ID :
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- esa_cci_path :
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- long_name :
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- ID :
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- esa_cci_path :
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- ID :
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- esa_cci_path :
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- ID :
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- esa_cci_path :
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- ID :
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- ID :
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- esa_cci_path :
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- ID :
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- esa_cci_path :
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- long_name :
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- ID :
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- esa_cci_path :
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- long_name :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - fractional_snow_cover(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 68
- esa_cci_path :
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- long_name :
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- ID :
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- esa_cci_path :
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- long_name :
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- ID :
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- esa_cci_path :
- nan
- long_name :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_lrt_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
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- esa_cci_path :
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- long_name :
- Tropospheric Ozone Column ( Lapse Rate)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on lapse rate definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_lrt_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_msr_flt(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 8
- esa_cci_path :
- nan
- long_name :
- Residual MSR-FLT (Stratospheric Part Partial)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'residual MSR-FLT_stratospheric_part partial ozone column in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_msr_flt', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - free_msr_lrt(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 10
- esa_cci_path :
- nan
- long_name :
- Residual MSR-LRT (Stratospheric Part Partial)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'residual MSR-LRT_stratospheric_part partial ozone column in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'free_msr_lrt', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - gross_primary_productivity(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 47
- esa_cci_path :
- nan
- long_name :
- Gross Primary Productivity
- orig_attrs :
- {'comment': 'Gross Carbon uptake of of the ecosystem through photosynthesis', 'long_name': 'Gross Primary Productivity', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'GPPall', 'standard_name': 'gross_primary_productivity_of_carbon', 'units': 'gC m-2 day-1', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
- project_name :
- FLUXCOM
- time_coverage_end :
- 2015-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - interception_loss(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 58
- esa_cci_path :
- nan
- long_name :
- Interception Loss
- orig_attrs :
- {'long_name': 'Interception Loss', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Ei', 'standard_name': 'interception_loss', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - iwp(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 33
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Ice Water Path
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud ice water path', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'iwp', 'spatial_resolution': '0.50 degree', 'standard_name': 'iwp', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'g/m2', 'url': 'http://www.dwd.de', 'valid_max': 32000.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - land_surface_temperature(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 69
- esa_cci_path :
- nan
- long_name :
- Land Surface Temperature
- orig_attrs :
- {'comment': 'Advanced Along Track Scanning Radiometer pixel land surface temperature product', 'long_name': 'Land Surface Temperature', 'orig_attrs': {}, 'project_name': 'GlobTemperature', 'references': 'Jiménez, C., et al. "Inversion of AMSR‐E observations for land surface temperature estimation: 1. Methodology and evaluation with station temperature." Journal of Geophysical Research: Atmospheres 122.6 (2017): 3330-3347.', 'source_name': 'LST', 'standard_name': 'surface_temperature', 'units': 'K', 'url': 'http://data.globtemperature.info/'}
- orig_version :
- nan
- project_name :
- GlobTemperature
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2002-05-21
- url :
- http://data.globtemperature.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - latent_energy(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 48
- esa_cci_path :
- nan
- long_name :
- Latent Energy
- orig_attrs :
- {'comment': 'Latent heat flux from the surface.', 'long_name': 'Latent Energy', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'LE', 'standard_name': 'surface_upward_latent_heat_flux', 'units': 'W m-2', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
- project_name :
- FLUXCOM
- time_coverage_end :
- 2015-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - leaf_area_index(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 73
- esa_cci_path :
- nan
- long_name :
- Effective Leaf Area Index
- orig_attrs :
- {'long_name': 'Effective Leaf Area Index', 'orig_attrs': {}, 'project_name': 'QA4ECV', 'source_name': 'Lai', 'standard_name': 'leaf_area_index', 'units': '1', 'url': 'http://www.qa4ecv.eu/'}
- orig_version :
- nan
- project_name :
- QA4ECV
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1982-01-05
- url :
- http://www.qa4ecv.eu/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - lrt_c(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 24
- esa_cci_path :
- nan
- long_name :
- Tropospheric Ozone Column (Lapse Rate)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropospheric ozone column (based on lapse rate definition) in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'lrt_c', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - lrt_p(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 16
- esa_cci_path :
- nan
- long_name :
- Tropopause Air Pressure (Lapse Rate)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'tropopause_air_pressure for the lapse rate tropopause', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'lrt_p', 'standard_name': 'tropopause_air_pressure', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'hPa', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - lwp(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 34
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Cloud Liquid Water Path
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'cloud liquid water path', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'orig_attrs': {}, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'lwp', 'spatial_resolution': '0.50 degree', 'standard_name': 'lwp', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'g/m2', 'url': 'http://www.dwd.de', 'valid_max': 32000.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - mask(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 46
- esa_cci_path :
- /neodc/esacci/sst/data/lt/Analysis/L4/v01.1/
- long_name :
- Sea/Land/Lake/Ice Field Composite Mask
- orig_attrs :
- {'Conventions': 'CF-1.5, Unidata Observation Dataset v1.0', 'Metadata_Conventions': 'Unidata Dataset Discovery v1.0', 'acknowledgment': 'Funded by ESA', 'cdm_data_type': 'grid', 'comment': 'WARNING Some applications are unable to properly handle signed byte values. If values are encountered > 127, please subtract 256 from this reported value', 'creator_email': 'science.leader@esa-sst-cci.org', 'creator_name': 'ESA SST CCI', 'creator_processing_institution': 'These data were produced at the Met Office as part of the ESA SST CCI project.', 'creator_url': 'http://www.esa-sst-cci.org', 'date_created': '20130309T132046Z', 'easternmost_longitude': 180.00001525878906, 'file_quality_level': 3, 'gds_version_id': '2.0', 'geospatial_lat_max': 90.0, 'geospatial_lat_min': -90.0, 'geospatial_lat_resolution': 0.05000000074505806, 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 180.0, 'geospatial_lon_min': -180.0, 'geospatial_lon_resolution': 0.05000000074505806, 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': -0.20000000298023224, 'geospatial_vertical_min': -0.20000000298023224, 'history': 'Created using OSTIA reanalysis system v2.0', 'id': 'OSTIA-ESACCI-L4-v01.1', 'institution': 'ESACCI', 'keywords': 'Oceans > Ocean Temperature > Sea Surface Temperature', 'keywords_vocabulary': 'NASA Global Change Master Directory (GCMD) Science Keywords', 'license': 'GHRSST protocol describes data use as free and open', 'long_name': 'sea/land/lake/ice field composite mask', 'metadata_link': 'http://www.esa-cci.org', 'naming_authority': 'org.ghrsst', 'netcdf_version_id': '4.1.3', 'northernmost_latitude': 90.0, 'orig_attrs': {}, 'platform': 'ERS-<1,2>, Envisat, NOAA-<12,14,15,16,17,18>, MetOpA', 'processing_level': 'L4', 'product_version': '1.1', 'project': 'Climate Change Initiative - European Space Agency', 'publisher_email': 'science.leader@esa-sst-cci.org', 'publisher_name': 'ESACCI', 'publisher_url': 'http://www.esa-sst-cci.org', 'references': 'http://www.esa-sst-cci.org', 'sensor': 'ATSR, AATSR, AVHRR_GAC', 'source': 'ATSR<1,2>-ESACCI-L3U-v1.0, AATSR-ESACCI-L3U-v1.0, AVHRR<12,14,15,16,17,18>_G-ESACCI-L2P-v1.0, AVHRRMTA-ESACCI-L2P-v1.0, EUMETSAT_OSI-SAF-ICE-v1.1, EUMETSAT_OSI-SAF-ICE-v2.2', 'source_dir': '/neodc/esacci/sst/data/lt/Analysis/L4/v01.1', 'source_name': 'mask', 'source_version': 'v01.1', 'southernmost_latitude': -90.0, 'spatial_resolution': '0.05 degree', 'standard_name': 'mask', 'standard_name_vocabulary': 'NetCDF Climate and Forecast (CF) Metadata Convention', 'start_time': '20100101T000000Z', 'stop_time': '20100101T235959Z', 'summary': 'OSTIA L4 product from the ESA SST CCI project, produced using OSTIA reanalysis system v2.0. Ice field corrected in v1.1 (v1.0 had ice from day-1). Static ice field between 20080101-20080229 and 20080501-20080521 also fixed in v1.1', 'time_coverage_duration': 'P1D', 'time_coverage_end': '20100101T235959Z', 'time_coverage_resolution': 'P1D', 'time_coverage_start': '20100101T000000Z', 'title': 'ESA SST CCI OSTIA L4 product', 'tracking_id': '19b1f7a4-d8d1-44eb-9cfa-37cc33c4c2c1', 'url': 'http://www.esa-sst-cci.org', 'uuid': '19b1f7a4-d8d1-44eb-9cfa-37cc33c4c2c1', 'valid_max': 31.0, 'valid_min': 1.0, 'westernmost_longitude': -180.0}
- orig_version :
- v01.1
- project_name :
- ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI)
- time_coverage_end :
- 2010-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1991-09-02
- url :
- http://www.esa-sst-cci.org
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- ID :
- 6
- esa_cci_path :
- nan
- long_name :
- Maximum 2 Metre Air Temperature
- orig_attrs :
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- ID :
- 7
- esa_cci_path :
- nan
- long_name :
- Minimum 2 Metre Air Temperature
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- {'comment': 'Air temperature at 2m from the ERA5 reanalysis product.', 'long_name': 'Minimum 2 metre air temperature', 'orig_attrs': {}, 'project_name': 'ERA5', 'references': '', 'source_name': 'min_air_temperature_2m', 'units': 'K', 'url': 'https://confluence.ecmwf.int//display/CKB/ERA5+data+documentation'}
- orig_version :
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- url :
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- ID :
- 9
- esa_cci_path :
- nan
- long_name :
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- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'residual MSR-FLT_stratospheric_part partial ozone column in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'msr_flt', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
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- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
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- url :
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- ID :
- 11
- esa_cci_path :
- nan
- long_name :
- Residual MSR-LRT (Stratospheric Part Partial)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'residual MSR-LRT_stratospheric_part partial ozone column in mole per square meter', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'msr_lrt', 'standard_name': 'troposphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
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- P8D
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- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - net_ecosystem_exchange(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 49
- esa_cci_path :
- nan
- long_name :
- Net Ecosystem Exchange
- orig_attrs :
- {'comment': 'Net carbon exchange between the ecosystem and the atmopshere.', 'long_name': 'Net Ecosystem Exchange', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'NEE', 'standard_name': 'net_primary_productivity_of_carbon', 'units': 'gC m-2 day-1', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
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- time_coverage_end :
- 2015-12-31
- time_coverage_resolution :
- P8D
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- ID :
- 50
- esa_cci_path :
- nan
- long_name :
- Net Radiation
- orig_attrs :
- {'comment': 'Net radiation to the surface', 'long_name': 'Net Radiation', 'orig_attrs': {}, 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'Rn', 'standard_name': 'surface_net_radiation_flux', 'units': 'W m-2', 'url': 'http://www.fluxcom.org/'}
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - open_water_evaporation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 59
- esa_cci_path :
- nan
- long_name :
- Open-Water Evaporation
- orig_attrs :
- {'long_name': 'Open-water Evaporation', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Ew', 'standard_name': 'water_evaporation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
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- url :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - ozone(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 72
- esa_cci_path :
- /neodc/esacci/ozone/data/total_columns/l3/merged/v0100/
- long_name :
- Mean Total Ozone Column in dobson units
- orig_attrs :
- {'comment': 'Atmospheric ozone based on the Ozone CCI data.', 'long_name': 'Mean total ozone column in dobson units', 'orig_attrs': {}, 'project_name': 'Ozone CCI', 'references': 'Laeng, A., et al. "The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)." Remote Sensing of Environment 162 (2015): 316-343.', 'source_name': 'atmosphere_mole_content_of_ozone', 'standard_name': 'atmosphere_mole_content_of_ozone', 'units': 'DU', 'url': 'http://www.esa-ozone-cci.org/'}
- orig_version :
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- project_name :
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- time_coverage_end :
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- time_coverage_start :
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- url :
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- ID :
- 3
- esa_cci_path :
- nan
- long_name :
- Photosynthetically Active Radiation
- orig_attrs :
- {'long_name': 'Photosynthetically active radiation', 'orig_attrs': {}, 'project_name': 'BESS', 'references': 'Ryu, Y.*, Jiang, C., Kobayashi, H., & Detto, M. (2018). MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000. Remote Sensing of Environment, 204, 812-825', 'source_name': 'surface_downwelling_photosynthetic_radiative_flux_in_air', 'standard_name': 'surface_downwelling_photosynthetic_radiative_flux_in_air', 'units': 'W m-2', 'url': 'http://environment.snu.ac.kr/bess_rad/'}
- orig_version :
- 15.10.2017
- project_name :
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- time_coverage_end :
- 2016-12-30
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- 2000-03-01
- url :
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- ID :
- 1
- esa_cci_path :
- nan
- long_name :
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- orig_version :
- 15.10.2017
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- 2016-12-30
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - potential_evaporation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 60
- esa_cci_path :
- nan
- long_name :
- Potential Evaporation
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- {'long_name': 'Potential Evaporation', 'orig_attrs': {}, 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Ep', 'standard_name': 'potential_water_evaporation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - precipitation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 71
- esa_cci_path :
- nan
- long_name :
- Precipitation
- orig_attrs :
- {'comment': 'Precipitation based on the GPCP dataset.', 'long_name': 'Precip - RealTime [RT] (see documentation for more information)', 'orig_attrs': {}, 'project_name': 'GPCP', 'references': 'Adler, Robert F., et al. "The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present)." Journal of hydrometeorology 4.6 (2003): 1147-1167.', 'source_name': 'Precip', 'standard_name': 'precipitation_flux', 'units': 'mm/day', 'url': 'http://precip.gsfc.nasa.gov/'}
- orig_version :
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- url :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - precipitation_era5(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 5
- esa_cci_path :
- nan
- long_name :
- ERA5 Precipitation
- orig_attrs :
- {'comment': 'Total precipitation from the ERA5 reanalysis product.', 'long_name': 'ERA 5 Precipitation', 'orig_attrs': {}, 'project_name': 'ERA5', 'references': '', 'source_name': 'precipitation', 'units': 'K', 'url': 'https://confluence.ecmwf.int//display/CKB/ERA5+data+documentation'}
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- ERA5
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- url :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - psurf(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 12
- esa_cci_path :
- nan
- long_name :
- Surface Air Pressure
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- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'surface_air_pressure', 'orig_attrs': {}, 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'psurf', 'standard_name': 'surface_air_pressure', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'hPa', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
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- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - root_moisture(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 61
- esa_cci_path :
- nan
- long_name :
- Root-Zone Soil Moisture
- orig_attrs :
- {'long_name': 'Root-Zone Soil Moisture', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'SMroot', 'standard_name': 'soil_moisture_content', 'units': 'm3/m3', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
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- url :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - sea_ice_fraction(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 45
- esa_cci_path :
- /neodc/esacci/sst/data/lt/Analysis/L4/v01.1/
- long_name :
- Sea Ice Area Fraction
- orig_attrs :
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- url :
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Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - sensible_heat(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 51
- esa_cci_path :
- nan
- long_name :
- Sensible Heat
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- orig_version :
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- time_coverage_start :
- 2001-01-05
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - snow_sublimation(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 62
- esa_cci_path :
- nan
- long_name :
- Snow Sublimation
- orig_attrs :
- {'long_name': 'Snow Sublimation', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Es', 'standard_name': 'snow_sublimation_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - snow_water_equivalent(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 67
- esa_cci_path :
- nan
- long_name :
- Daily Snow Water Equivalent
- orig_attrs :
- {'certain_values': '-2 == mountains, -1 == water bodies, 0 == either SWE, or missing data in the southern hemisphere', 'comment': 'Grid cell fractional snow cover based on the Globsnow CCI product.', 'long_name': 'Daily Snow Water Equivalent', 'project_name': 'GlobSnow', 'references': 'Luojus, Kari, et al. "ESA DUE Globsnow-Global Snow Database for Climate Research." ESA Special Publication. Vol. 686. 2010.', 'source_name': 'SWE', 'units': 'mm', 'url': 'http://www.globsnow.info/'}
- orig_version :
- v2.0
- project_name :
- GlobSnow
- time_coverage_end :
- 2012-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- url :
- http://www.globsnow.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - soil_moisture(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 78
- esa_cci_path :
- /neodc/esacci/soil_moisture/data/daily_files/COMBINED/v04.2/
- long_name :
- Soil Moisture
- orig_attrs :
- {'comment': 'Soil moisture based on the SOilmoisture CCI project', 'long_name': 'Soil Moisture', 'project_name': 'SoilMoisture CCI', 'references': 'Liu, Y.Y., Parinussa, R.M., Dorigo, W.A., De Jeu, R.A.M., Wagner, W., McCabe, M.F., Evans, J.P., and van Dijk, A.I.J.M. (2012): Trend-preserving blending of passive and active microwave soil moisture retrievals; Liu, Y.Y., Parinussa, R.M., Dorigo, W.A., De Jeu, R.A.M., Wagner, W., van Dijk, A.I.J.M., McCabe, M.F., & Evans, J.P. (2011): Developing an improved soil moisture dataset by blending passive and active microwave satellite based retrievals. Hydrology and Earth System Sciences, 15, 425-436.', 'source_name': 'SoilMoisture', 'standard_name': 'soil_moisture_content', 'units': 'm3', 'url': 'http://www.esa-soilmoisture-cci.org'}
- orig_version :
- v04.2
- project_name :
- SoilMoisture CCI
- time_coverage_end :
- 2014-01-29
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- url :
- http://www.esa-soilmoisture-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - srex_mask(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 77
- esa_cci_path :
- nan
- long_name :
- Mask for SREX Regions
- orig_attrs :
- {'ds_method': 'MODE', 'long_name': 'Mask for SREX regions', 'source_name': 'layer', 'standard_name': 'srex_mask', 'units': '-'}
- orig_version :
- nan
- project_name :
- regionmask - SREX Regions
- time_coverage_end :
- 1980-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- url :
- https://regionmask.readthedocs.io/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - stemp(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 40
- esa_cci_path :
- /neodc/esacci/cloud/data/phase-2/L3C/MODIS-TERRA/v2.0/
- long_name :
- Surface Temperature
- orig_attrs :
- {'Conventions': 'CF-1.6,ACDD-1.3', 'cdm_data_type': 'Grid', 'comment': 'These data were produced at ESACCI as part of the ESA Cloud CCI project.', 'creator_email': 'contact.cloudcci@dwd.de', 'creator_name': 'Deutscher Wetterdienst', 'creator_url': 'http://www.dwd.de', 'date_created': '2016-04-25T17:07:07+0000', 'geospatial_lat_max': 89.75, 'geospatial_lat_min': -89.75, 'geospatial_lat_resolution': '0.50', 'geospatial_lat_units': 'degrees_north', 'geospatial_lon_max': 179.75, 'geospatial_lon_min': -179.75, 'geospatial_lon_resolution': '0.50', 'geospatial_lon_units': 'degrees_east', 'geospatial_vertical_max': '0.0', 'geospatial_vertical_min': '0.0', 'history': 'Dataset produced by DWDs CC4CL retrieval system installed at ECMWF in second phase of ESA Cloud CCI.', 'id': '200002-ESACCI-L3C_CLOUD-CLD_PRODUCTS-MODIS_TERRA-fv2.0.nc', 'institution': 'Deutscher Wetterdienst', 'keywords': 'EARTH SCIENCE > ATMOSPHERE > SATELLITES > CLOUDS > CLOUD PROPERTIES', 'keywords_vocabulary': 'GCMD Science Keywords, Version 8.1', 'license': 'ESA CCI Data Policy: free and open access', 'long_name': 'surface temperature', 'naming_authority': 'de.dwd', 'number_of_processed_orbits': 1516, 'platform': 'TERRA', 'product_version': '2.0', 'project': 'Climate Change Initiative - European Space Agency', 'references': 'http://www.esa-cloud-cci.info', 'sensor': 'MODIS', 'source': 'MODIS_TERRA_Collection 6', 'source_name': 'stemp', 'spatial_resolution': '0.50 degree', 'standard_name': 'stemp', 'standard_name_vocabulary': 'NetCDF Climate Forecast (CF) Metadata Convention version 18', 'summary': 'This dataset contains monthly Level-3 global cloud property products from satellite observations. Averaged onto a regular grid.', 'time_coverage_duration': 'P1M', 'time_coverage_end': '20000229T235959Z', 'time_coverage_resolution': 'P1M', 'time_coverage_start': '20000201T000000Z', 'title': 'ESA Cloud CCI Retrieval Products L3 Output File', 'tracking_id': '1b6a5bee-afad-43e5-a326-67a76df184a7', 'units': 'K', 'url': 'http://www.dwd.de', 'valid_max': 320.0, 'valid_min': 0.0}
- orig_version :
- v2.0
- project_name :
- ESA Cloud Climate Change Initiative (Cloud_cci)
- time_coverage_end :
- 2014-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2000-01-29
- url :
- http://www.dwd.de
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - surface_moisture(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 63
- esa_cci_path :
- nan
- long_name :
- Surface Soil Moisture
- orig_attrs :
- {'long_name': 'Surface Soil Moisture', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'SMsurf', 'standard_name': 'soil_moisture_content', 'units': 'mm3/mm3', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - terrestrial_ecosystem_respiration(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 52
- esa_cci_path :
- nan
- long_name :
- Terrestrial Ecosystem Respiration
- orig_attrs :
- {'comment': 'Total carbon release of the ecosystem through respiration.', 'long_name': 'Terrestrial Ecosystem Respiration', 'project_name': 'FLUXCOM', 'references': 'Tramontana, Gianluca, et al. "Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms." (2016).', 'source_name': 'TERall', 'standard_name': 'ecosystem_respiration_carbon_flux', 'units': 'gC m-2 day-1', 'url': 'http://www.fluxcom.org/'}
- orig_version :
- v1
- project_name :
- FLUXCOM
- time_coverage_end :
- 2012-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2001-01-05
- url :
- http://www.fluxcom.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - totcol_assim(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 13
- esa_cci_path :
- nan
- long_name :
- Total Ozone Column (Assimilated TM5 data)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'total ozone column derived from assimilated TM5 data', 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'totcol_assim', 'standard_name': 'atmosphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - totcol_free(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 14
- esa_cci_path :
- nan
- long_name :
- Total Ozone Column (Assimilated TM5 data)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'total ozone column derived from assimilated TM5 data', 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'totcol_free', 'standard_name': 'atmosphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - totcol_msr(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 15
- esa_cci_path :
- nan
- long_name :
- Total Ozone Column (MSR data)
- orig_attrs :
- {'Conventions': 'CF-1.6', 'comment': 'The global tropospheric ozone column from 0 to 6 km is presented here. The column is derived by simultaneous assimlating ozone profiles of GOME-2 and OMI.', 'creator_email': 'peet@knmi.nl', 'creator_name': 'J.C.A. van Peet', 'creator_url': 'KNMI, http://www.kmnmi.nl/', 'institution': 'Royal Netherlands Meteorological Institute, KNMI', 'long_name': 'total ozone column derived from MSR data', 'project_name': 'Tropospheric ozone column', 'references': 'Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt (2018),Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments, Atmospheric Chemistry and Physics, doi:10.5194/acp-18-1685-2018', 'source_name': 'totcol_msr', 'standard_name': 'atmosphere_mole_content_of_ozone', 'title': 'Tropospheric ozone columns from assimilated satellite data.', 'units': 'mol m-2', 'url': 'http://www.temis.nl/protocols/tropo.html'}
- orig_version :
- v.1.2.3.1
- project_name :
- ESA - Near-real time total ozone column (OMI)
- time_coverage_end :
- 2011-12-31
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2008-01-05
- url :
- http://www.temis.nl/protocols/tropo.html
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - transpiration(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 64
- esa_cci_path :
- nan
- long_name :
- Transpiration
- orig_attrs :
- {'long_name': 'Transpiration', 'project_name': 'GLEAM', 'references': 'Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.', 'source_name': 'Et', 'standard_name': 'transpiration_flux', 'units': 'mm/day', 'url': 'http://www.gleam.eu'}
- orig_version :
- Version 3.2
- project_name :
- GLEAM
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-05
- url :
- http://www.gleam.eu
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - water_mask(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 43
- esa_cci_path :
- /neodc/esacci/land_cover/data/water_bodies/v4.0/
- long_name :
- Terrestrial or Water Pixel Classification
- orig_attrs :
- {'long_name': 'Terrestrial or water pixel classification', 'project_name': 'Climate Change Initiative - European Space Agency', 'source_name': 'wb_class', 'standard_name': 'land_cover_lccs', 'units': '-', 'url': 'http://www.esa-landcover-cci.org'}
- orig_version :
- v4.0
- project_name :
- ESA Land Cover Climate Change Initiative (Land_Cover_cci)
- time_coverage_end :
- 1980-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1980-01-05
- url :
- http://www.esa-landcover-cci.org
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - water_vapour(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 70
- esa_cci_path :
- nan
- long_name :
- Total Column Water Vapour
- orig_attrs :
- {'comment': 'Total column water vapour based on the GlobVapour CCI product.', 'long_name': 'Total Column Water Vapour', 'project_name': 'GlobVapour', 'references': 'Schneider, Nadine, et al. "ESA DUE GlobVapour water vapor products: Validation." AIP Conference Proceedings. Vol. 1531. No. 1. 2013.', 'source_name': 'tcwv_res', 'standard_name': 'atmosphere_mass_content_of_water_vapor', 'units': 'kg m-2', 'url': 'http://www.globvapour.info/'}
- orig_version :
- nan
- project_name :
- GlobVapour
- time_coverage_end :
- 2008-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1996-01-05
- url :
- http://www.globvapour.info/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - white_sky_albedo(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 66
- esa_cci_path :
- nan
- long_name :
- White Sky Albedo for Visible Wavebands
- orig_attrs :
- {'comment': 'White sky albedo derived from the GlobAlbedo CCI project dataset', 'long_name': 'White Sky Albedo for Visible Wavebands', 'project_name': 'GlobAlbedo', 'references': 'Muller, Jan-Peter, et al. "The ESA GLOBALBEDO project for mapping the Earth’s land surface albedo for 15 years from European sensors." Geophysical Research Abstracts. Vol. 13. 2012.', 'source_name': 'BHR_VIS', 'standard_name': 'surface_albedo_white_sky', 'units': '-', 'url': 'http://www.globalbedo.org/'}
- orig_version :
- nan
- project_name :
- GlobAlbedo
- time_coverage_end :
- 2012-01-05
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1998-01-05
- url :
- http://www.globalbedo.org/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - white_sky_albedo_avhrr(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 75
- esa_cci_path :
- nan
- long_name :
- Bi-Hemisphere Reflectance Albedo - VIS band
- orig_attrs :
- {'comment': 'White sky albedo derived from the QA4ECV Albedo Product', 'long_name': 'Bi-Hemisphere Reflectance albedo - VIS band', 'project_name': 'QA4ECV - European Union Framework Program 7', 'source_name': 'BHR_VIS', 'standard_name': 'surface_albedo_white_sky', 'units': '1', 'url': 'http://www.qa4ecv.eu/'}
- orig_version :
- nan
- project_name :
- QA4ECV - European Union Framework Program 7
- time_coverage_end :
- 2016-12-30
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 1982-01-05
- url :
- http://www.qa4ecv.eu/
Array Chunk Bytes 7.06 GB 4.15 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float32 numpy.ndarray - xch4(time, lat, lon)float64dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 42
- esa_cci_path :
- /neodc/esacci/ghg/data/obs4mips/crdp_3/CO2/v100/
- long_name :
- Column Average Dry-air Mole Fraction Methane
- orig_attrs :
- {'Conventions': 'CF-1.6', 'associated_files': 'obs4mips_co2_crdp3_v100.sav', 'cell_methods': 'time: mean', 'comment': 'Satellite retrieved column-average dry-air mole fraction of atmospheric carbon dioxide (XCO2)', 'contact': 'maximilian.reuter@iup.physik.uni-bremen.de', 'creation_date': '20160303T111125Z', 'data_structure': 'grid', 'frequency': 'mon', 'institute_id': 'IUP', 'institution': 'Institute of Environmental Physics, University of Bremen', 'long_name': 'column-average dry-air mole fraction of atmospheric carbon dioxide', 'mip_specs': 'CMIP5', 'product': 'observations', 'project_id': 'obs4MIPs', 'project_name': 'Ozone CCI', 'realm': 'atmos', 'references': 'Laeng, A., et al. "The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)." Remote Sensing of Environment 162 (2015): 316-343.', 'source': 'ESA GHG CCI XCO2 CRDP3', 'source_id': 'XCO2_CRDP3', 'source_name': 'xch4', 'source_type': 'satellite_retrieval', 'standard_name': 'dry_atmosphere_mole_fraction_of_carbon_dioxide', 'tracking_id': '60972082-05c2-4a04-947a-99042c642c68', 'units': '1', 'url': 'http://www.esa-ghg-cci.org/'}
- orig_version :
- v100
- project_name :
- ESA Greenhouse Gases Climate Change Initiative (GHG_cci)
- time_coverage_end :
- 2014-12-15
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-13
- url :
- http://www.esa-ghg-cci.org/
Array Chunk Bytes 14.12 GB 8.29 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float64 numpy.ndarray - xco2(time, lat, lon)float64dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- ID :
- 41
- esa_cci_path :
- /neodc/esacci/ghg/data/obs4mips/crdp_3/CO2/v100/
- long_name :
- Column Average Dry-air Mole Fraction Carbon Dioxide
- orig_attrs :
- {'Conventions': 'CF-1.6', 'associated_files': 'obs4mips_co2_crdp3_v100.sav', 'cell_methods': 'time: mean', 'comment': 'Satellite retrieved column-average dry-air mole fraction of atmospheric carbon dioxide (XCO2)', 'contact': 'maximilian.reuter@iup.physik.uni-bremen.de', 'creation_date': '20160303T111125Z', 'data_structure': 'grid', 'frequency': 'mon', 'institute_id': 'IUP', 'institution': 'Institute of Environmental Physics, University of Bremen', 'long_name': 'column-average dry-air mole fraction of atmospheric carbon dioxide', 'mip_specs': 'CMIP5', 'product': 'observations', 'project_id': 'obs4MIPs', 'project_name': 'Ozone CCI', 'realm': 'atmos', 'references': 'Laeng, A., et al. "The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS)." Remote Sensing of Environment 162 (2015): 316-343.', 'source': 'ESA GHG CCI XCO2 CRDP3', 'source_id': 'XCO2_CRDP3', 'source_name': 'xco2', 'source_type': 'satellite_retrieval', 'standard_name': 'dry_atmosphere_mole_fraction_of_carbon_dioxide', 'tracking_id': '60972082-05c2-4a04-947a-99042c642c68', 'units': '1', 'url': 'http://www.esa-ghg-cci.org/'}
- orig_version :
- v100
- project_name :
- ESA Greenhouse Gases Climate Change Initiative (GHG_cci)
- time_coverage_end :
- 2014-12-15
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 2003-01-13
- url :
- http://www.esa-ghg-cci.org/
Array Chunk Bytes 14.12 GB 8.29 MB Shape (1702, 720, 1440) (1, 720, 1440) Count 1703 Tasks 1702 Chunks Type float64 numpy.ndarray
- Metadata_conventions :
- Unidata Dataset Discovery v1.0
- acknowledgment :
- The ESDL team acknowledges all data providers!
- chunking :
- 1x720x1440
- comment :
- none.
- contributor_name :
- Max Planck Institute for Biogeochemistry
- contributor_role :
- ESDL Science Lead
- creator_email :
- info@earthsystemdatalab.net
- creator_name :
- Brockmann Consult GmbH
- creator_url :
- www.earthsystemdatalab.net
- date_created :
- 17.12.2018
- date_issued :
- 19.12.2018
- date_modified :
- 17.12.2018
- geospatial_lat_max :
- 89.75
- geospatial_lat_min :
- -89.75
- geospatial_lon_max :
- 179.75
- geospatial_lon_min :
- -179.75
- geospatial_resolution :
- 1/4deg
- history :
- - processing with esdl cube v0.1 (https://github.com/esa-esdl/esdl-core/)
- id :
- v2.0.0
- institution :
- Brockmann Consult GmbH
- keywords :
- Earth Science, Geophysical Variables
- license :
- Please refer to individual variables
- naming_authority :
- Earth System Data Lab team
- processing_level :
- Level 4
- project :
- ESA Earth System Data Lab
- publisher_email :
- info@earthsystemdatalab.net
- publisher_name :
- Brockmann Consult GmbH & Max Planck Institute for Biogechemistry
- publisher_url :
- www.brockmann-consult.de
- standard_name_vocabulary :
- CF-1.7
- summary :
- This data set contains a data cube of Earth System variables created by the ESA project Earth System Data Lab.
- time_coverage_duration :
- P37Y
- time_coverage_end :
- 30.12.2016
- time_coverage_resolution :
- P8D
- time_coverage_start :
- 05.01.1980
- title :
- Earth System Data Cube
# again subset only the ones we require
variables = [
'gross_primary_productivity',
'soil_moisture'
]
cubes = datacube[variables]
cubes
And we're done. That's it, there's nothing more to it.
Experimental Regions¶
So we're going to be look
# Experiment Functions
from src.data.esdc import get_dataset
from src.features.spatial import select_region, get_spain, get_europe
from src.features.temporal import select_period, TimePeriod
# MATPLOTLIB Settings
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
# SEABORN SETTINGS
import seaborn as sns
sns.set_context(context='talk',font_scale=0.7)
import cartopy
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
def plot_xarray_on_map(da, borders=True, coastlines=True, **kwargs):
""" Plot the LOCATION of an xarray object """
# create the base layer
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(1, 1, 1, projection=cartopy.crs.Robinson())
# ax = plt.axes(projection=cartopy.crs.Orthographic(mid_lon, mid_lat))
vmin = kwargs.pop("vmin", None)
vmax = kwargs.pop("vmax", None)
cmap = kwargs.pop("cmap", None)
cb_title = kwargs.pop("title", '')
robust = kwargs.pop("robust", None)
da.plot(
ax=ax,
# transform=cartopy.crs.PlateCarree(),
vmin=vmin,
vmax=vmax,
cmap=cmap,
robust=robust,
cbar_kwargs={"shrink": 0.9, "label": cb_title},
)
ax.coastlines()
ax.add_feature(cartopy.feature.BORDERS, linestyle=":")
ax.add_feature(cartopy.feature.LAKES, facecolor=None)
fig = plt.gcf()
ax.outline_patch.set_visible(False)
return fig, ax
Spain¶
Low Resolution¶
# Get DataCube
variable = 'gross_primary_productivity'
datacube = get_dataset(variable, 'low')
# subset datacube (spatially)
region = get_spain()
datacube = select_region(
xr_data=datacube, bbox=region
)[variable]
# subset datacube (temporally)
period = TimePeriod(name="201007", start="July-2010", end="July-2010")
datacube = select_period(xr_data=datacube, period=period)
# Plot datacube
# fig, ax = plot_xarray_on_map(datacube.mean(dim='time'))
datacube.mean(dim='time').plot(vmin=0)
plt.tight_layout()
plt.savefig( FIG_PATH.joinpath('demos/spain_lo_gpp.png'))
/home/emmanuel/.conda/envs/rbig_eo/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
High Resolution¶
# Get DataCube
variable = 'gross_primary_productivity'
datacube = get_dataset(variable, 'high')
# subset datacube (spatially)
region = get_spain()
datacube = select_region(
xr_data=datacube, bbox=region
)[variable]
# subset datacube (temporally)
period = TimePeriod(name="201007", start="July-2010", end="July-2010")
datacube = select_period(xr_data=datacube, period=period)
# Plot Datacube
# fig, ax = plot_xarray_on_map(datacube.mean(dim='time'))
datacube.mean(dim='time').plot(vmin=0)
plt.tight_layout()
plt.savefig( FIG_PATH.joinpath('demos/spain_hi_gpp.png'))
/home/emmanuel/.conda/envs/rbig_eo/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
Europe¶
# Get DataCube
variable = 'gross_primary_productivity'
datacube = get_dataset(variable, 'low')
# subset datacube (spatially)
region = get_europe()
datacube = select_region(
xr_data=datacube, bbox=region
)[variable]
# subset datacube (temporally)
period = TimePeriod(name="201007", start="July-2010", end="July-2010")
datacube = select_period(xr_data=datacube, period=period)
# Plot datacube
# fig, ax = plot_xarray_on_map(datacube.mean(dim='time'))
datacube.mean(dim='time').plot(vmin=0)
plt.tight_layout()
plt.savefig( FIG_PATH.joinpath('demos/europe_lo_gpp.png'))
/home/emmanuel/.conda/envs/rbig_eo/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
# Get DataCube
variable = 'gross_primary_productivity'
datacube = get_dataset(variable, 'high')
# subset datacube (spatially)
region = get_europe()
datacube = select_region(
xr_data=datacube, bbox=region
)[variable]
# subset datacube (temporally)
period = TimePeriod(name="201007", start="July-2010", end="July-2010")
datacube = select_period(xr_data=datacube, period=period)
# Plot datacube
# fig, ax = plot_xarray_on_map(datacube.mean(dim='time'))
datacube.mean(dim='time').plot(vmin=0)
plt.tight_layout()
plt.savefig( FIG_PATH.joinpath('demos/europe_hi_gpp.png'))
/home/emmanuel/.conda/envs/rbig_eo/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
