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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.
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Atmos Composition
