HR: 0800h
AN: C41A-0171    [Abstracts]
TI: Estimation of Arctic Land Surface Conditions and Fluxes via a Suite of Land Surface Models
AU: * Bohn, T J
EM: tbohn@hydro.washington.edu
AF: Department of Civil and Environmental Engineering, Box 352700 University of Washington, Seattle, WA 98195-2700 United States
AU: Slater, A G
EM: aslater@cires.colorado.edu
AF: Cooperative Institute for Research in Environmental Sciences, 216 UCB University of Colorado, Boulder, CO 80309-0216 United States
AU: Lettenmaier, D P
EM: dennisl@u.washington.edu
AF: Department of Civil and Environmental Engineering, Box 352700 University of Washington, Seattle, WA 98195-2700 United States
AU: Serreze, M C
EM: serreze@kryos.colorado.edu
AF: Cooperative Institute for Research in Environmental Sciences, 216 UCB University of Colorado, Boulder, CO 80309-0216 United States
AB: River runoff from the Arctic terrestrial drainage system is thought to exert a significant influence over global climate, contributing to the global thermohaline circulation via its effects on salinity, sea ice, and surface freshening in the North Atlantic. Changes in these freshwater fluxes, as well as other components of the Arctic terrestrial hydrologic cycle such as snow cover and albedo, have the potential to amplify the Arctic's response to global climate change. However, the extent to which the Arctic terrestrial hydrological cycle is changing or may contribute to change through feedback processes is still not well understood, in part due to the sparseness of observations of such variables as stream flow, soil moisture, soil temperature, snow water equivalent, and energy fluxes. The objective of this project is to assemble the best possible time series (covering a 20+ year period) of these and other prognostic variables for the Arctic terrestrial drainage basin. While these variables can be estimated with a single land surface model (LSM), the predictions are often subject to biases and errors in the input atmospheric forcings and limited by the accuracy of the model physics. To reduce these errors, we have implemented an ensemble of five LSMs: VIC, CLM, ECMWF, NOAH and CHASM, all of which have been used previously to simulate Arctic hydrology under the Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) Experiment 2e. Model predictions of land surface state variables (snow water content, soil moisture, permafrost active layer depth) and fluxes (latent, sensible, and ground heat fluxes; runoff) are averaged both across the ensemble and over multiple runs, using the best available atmospheric forcing data with and without added random perturbations. Here we evaluate the multi-model ensemble averages in comparison with individual model simulations of variables including snow water equivalent, evaporation, total runoff, and soil thaw depth over the pan-arctic domain, and attempt to evaluate the hypothesis that the ensemble-averaged results are superior to those from any single LSM. In addition, we evaluate individual and multi-model performance in comparison with observations of stream flow, snow areal extent, and other variables as available.
DE: 9315 Arctic region
DE: 1655 Water cycles (1836)
DE: 1836 Hydrologic budget (1655)
DE: 1620 Climate dynamics (3309)
SC: Cryosphere [C]
MN: 2004 AGU Fall Meeting