92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Monday, 23 January 2012
Enhancement of High Resolution Hydrological Modeling on the CONUS HRAP Grid Using Operational NOAA NCEP and NOAA OHD Models
Hall E (New Orleans Convention Center )
Jiarui Dong, NOAA/NCEP/EMC, Camp Springs, MD; and B. Cosgrove, M. Ek, and K. C. Mo

This work centers on supporting NOAA/NCEP's, NOAA/OHD's, and NOAA/CPC's operational hydrological and land surface modeling missions, as well as furthering their support of the NOAA Hydrology Test Bed, the NOAA Climate Test Bed, and the National Integrated Drought Information System (NIDIS). New capabilities resulting from this joint NOAA NCEP/OHD/CPC effort will allow for the execution of enhanced Noah and Sacramento Heat Transfer (SAC-HT) models on the 4km HRAP grid over the Continental United States (CONUS). Enhancements will impact all stages of modeling operations and will include improved downscaled forcing data, spin-up strategies, data assimilator modules, model physics, and model validation procedures, and will enable national runoff routing of both Noah and SAC-HT output.

One thrust of high spatial resolution land surface modeling is to accurately downscale coarse resolution atmospheric forcing data. Supporting this need for downscaling, we will present the results of our study where we investigate the temporal and spatial characteristics of lapse rate versus temperature using a total of 989 in-situ stations in the western United States. For the first time, we demonstrate a linear relationship between the surface lapse rate and temperature. When used in combination with high-resolution digital elevation map (DEM) data, this regression equation and the resulting lapse rates will support a wide range of applications in downscaling atmospheric forcing data. One such application will be the creation of more accurate temperature forcing data within the North American Land Data Assimilation System (NLDAS).

Additionally, the accurate initialization of land surface and hydrological models is critical for the production of accurate hydrological predictions, because the process of a model adjusting to its forcing can severely bias land surface simulations. We will present a technique that we have developed to generate optimal initial conditions for the 32-year (1979-2010) 4km Noah and SAC-HT retrospective simulations and to provide guidance for real-time simulations.

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