Estimates of land surface states (e.g., soil moisture, surface temperature) produced by The Global Land Data Assimilation System (GLDAS) can be used to initialize short term and seasonal numerical weather prediction systems. Precipitation and temperature forecasts are sensitive to land surface conditions at the start of the prediction period. GLDAS output can be used to initialize the land surface states and hence improve forecast accuracy.
The Gravity Recovery and Climate Experiment (GRACE) satellite mission is being used to monitor terrestrial water storage, including groundwater, soil moisture, snow, and ice. Scientists rely on GLDAS to help interpret the valuable and unique but low resolution hydrological data provided by GRACE.
CEOP is an international initiative which aims to distribute, link, intercompare satellite and in situ data, towards achieving the water resources and weather/climate prediction goals of the Global Energy and Water-cycle Experiment (GEWEX). GLDAS provides CEOP with both model location time series (MOLTS) and gridded fields of land surface states and fluxes, which are crucial for interpreting the relationship between point observations and spatially diverse satellite observations.
Atmos Composition
