HR: 0800h
AN: C31A-1101    [Abstracts]
TI: Spatial Assessment of Performance of Hemispheric Permafrost Models Using a Multiscale,Hierarchical Approach to Model Validation: Results for North-Central Alaska
AU: * Shiklomanov, N I
EM: shiklom@udel.edu
AF: Nikolay I. Shiklomanov, Department of Geography University of Delaware, Newark, DE 19716 United States
AU: Anisimov, O A
EM: oleg@oa7661.spb.edu
AF: Oleg A. Anisimov, State Hydrological Institute 23, Second Line VO, St. Petersburg, 199053 Russian Federation
AU: Zhang, T
EM: tzhang@nsidc.org
AF: Tingjun Zhang, National Snow and Ice Data Center 1540 30th Street, Boulder, CO 80309 United States
AB: The past two decades have seen a dramatic rise in the number of permafrost models used to evaluate permafrost parameters over geographic space, as well as spatial changes in permafrost-related phenomena that may follow from global climate change. However, there has been little effort to develop an explicit hierarchy of permafrost models, to evaluate their performance using standardized validation tools and data sets, to rank the performance of various models in different applications, or to explicitly link modeling results with observations. At present, spatial permafrost models operating at small geographic scales (circumarctic, continental) are usually evaluated at sets of point locations. Often, such approaches to validation do not correspond to the resolution at which models are applied. The high spatial variability of permafrost parameters requires careful selection of validation points. However, observational locations rarely represent generalized conditions prescribed for the model's grid cells. Correspondence between the scale of observations and modeling resolution is necessary to compare observed and simulated patterns of permafrost parameters. We addressed this problem by developing a hierarchical scheme for evaluation of spatial permafrost models. This scheme includes empirical data from point locations and observational plots provided by current permafrost observational networks, regional characterization of permafrost conditions, and circumpolar-scale models. The developed approach was applied to compare results from the National Snow and Ice Data Center and State Hydrological Institute/University of Delaware permafrost models with observed patterns of permafrost parameters within a 29,000 km2 region of North-Central Alaska. A regional high-resolution spatial data set of permafrost parameters was used to evaluate circumarctic-scale models on the basis of their ability to represent the spatial behavior of the permafrost system and to quantitatively estimate uncertainties introduced by such representations.
DE: 0702 Permafrost (0475)
DE: 0706 Active layer
DE: 0768 Thermal regime
DE: 0772 Distribution
DE: 0798 Modeling
SC: Cryosphere [C]
MN: Fall Meeting 2005