North American Land Data Assimilation System (NLDAS)

Surface stores of energy and water regulate atmospheric conditions. The characterization of the spatial and temporal variability of energy and water cycles is critical to improved understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. In addition, accurate initialization of these variables in fully-coupled models is critical for weather and climate prediction.

Recently, land surface simulation, observation, and analysis methods have become sufficiently advanced to accurately determine land surface energy and moisture stores for the initialization of prediction systems and to address land surface management issues. Such goals are the focus of the North American Land Data Assimilation System (NLDAS) Project.

NLDAS is currently running in near real-time and retrospective modes at 1/8th-degree (about 15 kilometer resolution). The systems are currently forced by observation based precipitation and radiation data, and by numerical model output. In order to create an optimal scheme, the projects have involved several Land Surface Models (LSMs) and sources of data from several institutions and may eventually include many more. Data from the project can be accessed on the NLDAS forcing pages, the NLDAS model output pages, as well as on the NLDAS Realtime Image Generator pages.

The LDAS Project is a joint collaboration of the following organizations: NOAA NWS National Centers for Environmental Prediction (NCEP); NASA Goddard Space Flight Center; Princeton University; NOAA NWS Office of Hydrologic Development (OHD); University of Washington; Rutgers University; and University of Maryland.