Data Assimilation for the Earth System

Abstract

Land surface temperature and wetness conditions affect and are affected by numerous climatological, meteorological, ecological, and geophysical phenomena. Therefore, accurate, high resolution estimates of terrestrial water and energy storages are valuable for predicting climate change, weather, biological and agricultural productivity, and flooding, and for performing a wide array of studies in the broader biogeosciences. In particular, terrestrial stores of energy and water modulate fluxes between the land and atmosphere and exhibit persistence on diurnal, seasonal, and interannual timescales. Furthermore, because soil moisture, temperature, and snow are integrated states, errors in land surface forcing and parametrization accumulate in the representations of these variables in operational numerical weather forecast models, which lead to incorrect surface water and energy partitioning. Therefore, accurate re-initialization of water and energy state variables in these models is crucial.