Satellite-derived multivariate lake physical variable timeseries for climate studies
Multi-variable time series for 2,024 lakes worldwide including surface water temperature, water extent, water level, and ice cover from multiple satellite instruments.
doi.org
At a glance
- Region
- Global
- Coverage
- Global
- Access
- Free
- Category
- Research
- Last updated
- 2023
What's inside
- Temperature
- Cryosphere
- Remote Sensing
- Lakes & Reservoirs
What you can do with it
Typical work that data of this type supports.
- 01
Storage tracking
Follow storage and releases through the season.
Because it has: Lakes & Reservoirs
- 02
Change over time
See how lakes and wetlands have grown or shrunk.
- 03
Risk screening
Screen projects and assets for climate risk.
Because it has: Temperature
Where AI adds value
Ideas for machine learning and AI agents built on this kind of data.
- 01
Storage from space
Estimate volume from satellite water area and altimetry.
- 02
Release decisions
Optimise releases against inflow forecasts.
- 03
Bias correction
Correct and downscale climate model output for a site.
Machine access and documentation
Data paper
Satellite-derived multivariate lake physical variable timeseries for climate studies
Scientific Data 2023
Read the paperRelated water data
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- ESGF CMIP6 Data PortalGlobal | Free
- A database of chlorophyll and water chemistry in freshwater lakesGlobal | Free
- A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000-2018Global | Free
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