Analysis of Water and Energy Budgets and Trends Using the NLDAS Monthly Data Products

The North American Land Data Assimilation System (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data set, with high spatial and temporal resolutions (0.125° x 0.125°, hourly and monthly), long temporal coverage (Jan. 1979 - present), and various water- and energy-related variables (precipitation, soil moisture, evapotranspiration, radiation, latent heat, and runoff, etc.), is an excellent data source for supporting water and energy cycle studies. NLDAS hourly data, accessible from NASA Goddard Earth Sciences Data and Information Services Center (GES DISC; Hydrology Data Holdings Portal http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings), have been broadly used by various user communities in modeling, research, and applications, such as drought and flood monitoring, watershed and water quality management, and case studies for extreme events. NLDAS data sets consist of a Forcing data set for land surface models, comprising a synthesis of best available near-surface observations and reanalyses, and separate land surface model output data sets of NLDAS models driven by the Forcing. To further facilitate analysis of water and energy budgets and trends, NLDAS monthly data products have been recently released by NASA GES DISC. The NLDAS monthly data were generated from NLDAS hourly data, as monthly accumulation for precipitation and monthly average for other variables. NLDAS monthly climatology data set will further be generated based on the monthly data and become accessible also from the Hydrology Data Holdings Portal. This presentation describes the major characteristics of the NLDAS data set. Some preliminary analysis results of water and energy budgets and trends from the NLDAS monthly data are shown and discussed. The NLDAS hourly, monthly, and monthly climatology terrestrial hydrological data could play an important role in characterizing the spatial and temporal variability of water and energy cycles and, thereby, improve our understanding of land-surface-atmosphere interactions and the impact of land-surface processes on extreme weather and climate change.