HR: 0800h
AN: U41A-0813    [Abstracts]
TI: Freshwater input to the Arctic: Uncertainty in model forcing vs. model structure
AU: * Slater, A G
EM: aslater@cires.colorado.edu
AF: Coop Inst. for Research in Environ. Science(CIRES)/NSIDC, Campus Box 449 University of Colorado, Boulder, CO 80309-0449 United States
AU: Bohn, T
EM: tbohn@hydro.washington.edu
AF: Dept. Civil & Environ. Engineering, Box 352700 University of Washington, Seattle, WA 98195-2700 United States
AU: McCreight, J L
EM: mccreigh@kryos.colorado.edu
AF: Coop Inst. for Research in Environ. Science(CIRES)/NSIDC, Campus Box 449 University of Colorado, Boulder, CO 80309-0449 United States
AU: Serreze, M C
EM: serreze@kryos.colorado.edu
AF: Coop Inst. for Research in Environ. Science(CIRES)/NSIDC, Campus Box 449 University of Colorado, Boulder, CO 80309-0449 United States
AU: Lettenmaier, D P
EM: dennisl@u.washington.edu
AF: Dept. Civil & Environ. Engineering, Box 352700 University of Washington, Seattle, WA 98195-2700 United States
AU: Wang, X
EM: xuanjiw@ssec.wisc.edu
AF: Coop. Inst. for Meteorological Satellite Studies, University of Wisconsin-Madison, 1225 West Dayton Street, Madison, WI 53706 United States
AU: Key, J
EM: jkey@ssec.wisc.edu
AF: Coop. Inst. for Meteorological Satellite Studies, University of Wisconsin-Madison, 1225 West Dayton Street, Madison, WI 53706 United States
AB: In an effort to estimate the large scale freshwater budget from the Pan-arctic drainage basins to the Arctic oceans we use several land surface models to simulate expected runoff and evaporation fluxes. Two areas of uncertainty in this approach include 1) the forcing data used to drive the models and 2) the structure and parameters of the models. In this study we apply an ensemble of forcing data to two land surface models (CHASM and VIC) to look at the relative impacts of forcing vs. structure on the resulting fluxes. Precipitation is perhaps the most important driving variable when simulating hydrology, thus we apply three estimates of this variable; one being ERA-40 data, another being purely station based precipitation and the thrid being an optimally interpolated assimilation based product of the former two datasets. Additionally, we use radiative fluxes, both short- and longwave, that are partially derived from satellite estimates. The relative errors from the model simulations can guide where future efforts shall be required.
DE: 0740 Snowmelt
DE: 1833 Hydroclimatology
DE: 1854 Precipitation (3354)
SC: Union [U]
MN: Fall Meeting 2005