A few resources for quickly accessing datasets via python. Often times for larger experiments, we would need to download the entire dataset. However, for quickly prototyping, it’s sufficient to have a simple dataset.
Geoscience Data Anatomy¶
- Coordinates
- Domain
- Field
Data Structures¶
- Unstructured Data - Points
- Irregularly Structured Data - Polygons
- Regularly Structured Data - Rasters
Data Types¶
In general, there are three different data types we will see within the geoscience community: observations, simulations, reanalysis data.
- Observations
- Simulations
- Reanalysis
Data Readiness¶
- Level 1
- Level 2
- Level 3
- Level 4
- Level 5
Data Access¶
Google Earth Engine.
This is the first most famous way to download data.
There are many known add-on packages that are useful, e.g, xee, eemount, and wxee.
There is a guide for downloading . They include reanalysis datasets like ERA5, ERA5 Climatology, IFS HRES t=0 “Analysis”. They also include some forecast datasets like IFS and all of the AI-based datasets available on the metrics webpage.
Case Studies¶
Sea Surface Height¶
- Sensor Type - NADIR AlongTrack
- L2 - MDS - AlongTrack Satellite Data (
7x7 km,5Hz) - L3 - MDS - Interpolated Satellite Data (
0.25 x 0.25 deg, Daily) - ARGO - ARGO Floats
Temperature¶
- Variable - LST/SST
- Sensor Type - Infrared
- L2 - MDS - Multi-Sensor Fusion (ODYSSEA) (
0.1 x 0.1 deg, daily) - L3
- MDS - Multi-Sensor Fusion (ODYSSEA)(
0.1 x 0.1 deg, daily) - MDS - oSTIa (
0.05 x 0.05 deg, daily)
- MDS - Multi-Sensor Fusion (ODYSSEA)(
- ARGO - ARGO Floats
Precipitation¶
- Variable - Precipitation
- Sensor Type - Weather Station