2002 Annual

Monday, 14 January 2002: 11:00 AM
Forcing a global, offline land surface modeling system with observation-based fields
Matthew Rodell, NASA/GSFC, Greenbelt, MD; and P. R. Houser, U. Jambor, J. Gottschalck, J. Radakovich, K. Arsenault, C. -. J. Meng, and K. E. Mitchell
Poster PDF (3.6 MB)
The Global Land Data Assimilation System (GLDAS) drives multiple uncoupled land surface models in order to produce optimal output fields of surface states in near-real time, globally, at 1/4 degree spatial resolution. These fields are then made available for coupled atmospheric model initialization and further research. One of the unique aspects of GLDAS is its ability to ingest both modeled and observation-derived forcing for running global scale land surface models. This paper compares results of runs forced by modeled and observed precipitation and shortwave radiation fields. Differences are examined and the impact of the observations on model skill is assessed.

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