Because we are targeting high spatial resolution modeling, one thrust of this research effort is to implement an elevation adjustment scheme for downscaling the 30-year, 1/8th degree NLDAS forcing to the HRAP grid. As part of this, we investigated the temporal and spatial characteristics of lapse rate versus temperature using a total of 989 in-situ stations in the western United States. The lapse rate can be quantitatively predicted from air temperature via a linear regression relationship. In combination with high-resolution digital elevation map (DEM) data, this regression equation and the resulting lapse rates will support the elevation adjustment of NLDAS temperature forcing data. Validation against gridded PRISM and in-situ temperature data is planned, as is a comparison against existing 1/8th degree NLDAS temperature data.
The 30-year (1979-2008) retrospective run on the HRAP grid was performed with temperatures adjusted using both a standard (constant) lapse rate, as well as lapse rates derived with the aforementioned regression equation. After taking into account spin-up processes, a 30-year model climatology was generated to support hydrological applications. Drought and flood monitoring is further supported through execution of real-time runs.