H51D-1402
Space-time downscaling of precipitation for high resolution LDAS experiment
Friday, 18 December 2015
Poster Hall (Moscone South)
Roshan K Shrestha1,2, Michael B Ek1, Jiarui Dong3, Jesse Meng4, Pingping Xie5 and Youlong Xia3, (1)NOAA NWS NCEP/EMC, College Park, MD, United States, (2)IMSG, Rockville, MD, United States, (3)Environmental Modeling Center, College Park, MD, United States, (4)IMSG, College Park, MD, United States, (5)NOAA/NCEP, College Park, MD, United States
Abstract:
Land Data Assimilation System (LDAS) experiments provide opportunities to reproduce more accurate and climatologically consistent data sets. The next generation LDAS is expected to take advantages of high resolution model runs, upgraded versions of Land Surface Models (LSMs), enhanced meteorological forcing data sets, more robust soil moisture initialization and updated model specific parameter sets. In this experiment, we are investigating space-time downscaling of precipitation using NCEP CPC’s one of the latest precipitation data sets, which has utilized a long-term climatology of outgoing longwave radiation (OLR) estimated from satellite observations to produce a blended precipitation product. This data set is 0.25-degree at a daily interval, which we downscale to hourly interval in time and approximately 3-km resolution in space through a hybrid-stochastic precipitation downscaling method. The downscaling model is an integration of random cascade disaggregation and two-dimensional translation model. We will present results of downscaling experiment and demonstrate the fluxes and water budget components from a newly run high resolution LDAS experiment over CONUS.
