The current version of the Noah land surface model (LSM) is tested within the NLDAS framework and data from three major off-line multi-model intercomparison studies, the Rhone, PILPS-phase 2(e), and the DMIP project. All these projects have in common that they specify the atmospheric forcing for LSMs and compare the resulting fluxes and state variables with measurements.
The major part of the talk will be dedicated to the development of the NLDAS (North American Land Data Assimilation System) system by consortium of GAPP/GCIP-sponsored groups. NCEP, with partners from NASA/GSFC, NWS Hydrology Lab, NESDIS, Princeton University, University of Washington, University of Maryland, and Rutgers University has undertaken the development and prototype realtime demonstration of national, realtime, hourly, 15-km, uncoupled, distributed land-surface models forced by observed precipitation and observed GOES-derived solar insolation. This system is referred to as the NLDAS, as future enhancements will include the assimilation of satellite-derived land-surface fields such as skin temperature, soil moisture, and snowpack.
The hallmarks of this LDAS project are 4 separate realtime land-surface models (LSMs) running in parallel in the NCEP computer environment on a common 0.125 degree grid using common a) NCEP-derived hourly atmospheric forcing, b) common land-surface characteristics (to the extent possible), and c) a common streamflow routing model. The land-surface state variables (e.g. soil moisture and temperature, snowpack) of the 4 LSMs will all be continuously cycled forward in realtime. The participating LSMs so far include the Noah LSM, the MOSAIC LSM, the VIC-3L LSM, and the Sacramento Model.
This talk compares the model parameterizations and the resulting differences in runoff, streamflow and water balance computations of 3 years of retrospective forcing from Oct. 1996 to Sep. 1999. Comparisons will be done on more than 1000 medium to large river basins (100 to 1000000 km^2) within the US. Also, the highlights of a recent series of submitted papers from the NLDAS project will be shown.