878 Analysis of Land Surface States Obtained from High-Resolution LDAS Experiment Using URMA and GLDAS Products

Wednesday, 10 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Roshan Shrestha, IMSG and NOAA/NCEP/EMC, College Park, MD; and M. B. Ek, M. Pondeca, P. Shafran, G. DiMego, and A. M. Gibbs

Land Data Assimilation System (LDAS) aims for producing data sets more consistent with ongoing observation system as well as climatologically records. LDAS has become a useful tool to address multiple purposes in hydrological application areas. We have recently conducted re-analysis of the UnRestricted Mesoscale Analysis (URMA) covering NCEP’s High Resolution Rapid Refresh (HRRR) era period. This re-analysis includes the latest upgrades in the URMA system to analyze meteorological observations and modeled products. And it provides more accurate and high resolution (2.5 km, hourly) forcing datasets, for example temperature, specific humidity, surface pressure, and wind data sets, to run the LDAS. We have run high resolution (2.5-km) LDAS for CONUS, Alaska, Hawaii and Puerto Rico extending the coverage of currently operational LDAS runs in 1/8-degree resolution. Additional required forcings are used from GLDAS analysis. The products aim to serve the needs of gridded weather dataset for US Forest Service (USFS) fire models as well as other users. Short-term variability in diurnal and seasonal cycles have been investigated. We will present results of land surface states (energy fluxes and water budget components) from the newly run high resolution LDAS experiment and analyze the outcomes with respect to the existing North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) outcomes.
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