Collaborative Research: A Land surface Model Hind- Cast for the Terrestrial Arctic Drainage System

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This study will combine data synthesis and land surface modeling to assemble the best possible time series (20+ years) for the Arctic terrestrial drainage of land surface state variables (snow water equivalent, soil moisture, soil temperature) and moisture and energy fluxes (sensible, latent, and ground heat; radiation). Development of forcing fields will draw in part from an ongoing NSF effort known as Arctic-RIMS, geared at historical analysis and monitoring of the Arctic terrestrial hydrologic budget. The present effort both complements Arctic-RIMS and lays groundwork for a next-generation monitoring and prediction capability. The generated time series will be used to address spatial-temporal variability in sensible heat flux and evapo-transpiration, land surface feedbacks on precipitation, and development of the summer Arctic frontal zone. This study will attempt to produce the best possible quality model forcing over the pan-Arctic domain by blending output from the new ERA-40 atmospheric reanalysis project with gridded in-situ observations and satellite data streams. Major challenges include maintaining physical consistency between time series of variables at different native spatial and temporal resolutions and providing realistic diurnal cycles. A particularly novel aspect of the proposed work will be use of a multi-model ensemble approach. Five different Land Surface Models will be used, all of which have been extensively tested for Arctic applications under the Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS) Experiment 2e. The multi-model LSM ensemble average for each output variable should be superior to the values provided by a single run with any one LSM.The data will also be useful for model validation efforts, such as the Arctic Regional Climate Model Inter-comparison Project, and in providing a source of high latitude evaluation data for the Atmospheric Model Inter-comparison Project. The project will contribute to educational goals through support of a graduate student and post-docs. Results from this study and related projects will be used as part of seminar course on the Arctic climate system to be taught at University of Colorado.