17C.5a
Implementation of a coupled hurricane-land surface prediction system for improving hurricane prediction during landfall (Formerly Paper P1.10)
Weixing Shen, NOAA/NWS/NCEP, Camp Springs, MD; and R. E. Tuleya, S. Lord, N. Surgi, and K. E. Mitchell
Hurricane-land surface interaction is a little investigated topic in hurricane landfall. Currently, a slab land surface model is coupled with the operational GFDL hurricane prediction system. This land surface model only predicts land surface temperature with other land conditions, such as the land moisture and heat capacity, fixed. The use of fixed land moisture and heat capacity may also cause the land surface temperature prediction significantly biased where the changes of these conditions are large. For an example, rainfall under the storm core may result in large changes of land surface water availability and albedo. In addition, the current GFDL prediction system uses the land surface water availability derived from a surface vegetation dataset which is fixed in time, while in reality it is largely dependent of the precipitation which has large temporal and spatial variabilities. These deficiencies of the operational hurricane system may limit the predictive skills of the current GFDL prediction system for landfalling hurricanes. The NOAH land surface model is a comprehensive land surface model and is currently coupled with the global (AVN) and meso-scale (Eta) prediction systems at NOAA/NCEP. The operational hurricane prediction system will be coupled with the NOAH land surface model. The implementation of this coupled system will lead to better representation of surface heat exchanges over land surface and enable the hurricane system to use the more accurate initial land surface conditions from the Eta assimilation. Preliminary results on hurricane-land surface interaction from both sensitivity experiments and real case simulations will be reported.
Session 17C, Tropical Cyclone Air-Sea Interaction IV (Parallel with Sessions 17A and 17B)
Friday, 3 May 2002, 11:00 AM-12:30 PM
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