1. MSRD FA Continuous overlapping period: 1972-1999 Comparison spatial extention: Northern Emisphere 2. METHODS GLOBAL SNOW COVER: COMPARISON OF MODELING RESULTS WITH SATELLITE-DERIVED SNOW COVER MAPS E. Bartolini (1), J. C. Adam (2), P. Claps (1) (1)Dipartimento di Idaulica, Trasporti e Infrastrutture Civili, Politecnico di Torino, Italy; (2)Department of Civil and Environmental Engineering, Washington State University, Pullman, WA, USA elisa.bartolini@polito.it and jcadam@wsu.edu ID C33C-0550 Monitoring, measuring and modeling snow processes Snow processes play an important role in the hydrologic cycle. Snowpack accumulation and depletion not only influence annual water availability and runoff seasonality, but also the functioning of ecosystems and the interactions between human activities and surface water systems. Moreover, at the large scale, snow cover influences the climate system due to its high albedo which affects the surface energy balance. Therefore, a global-scale hydrologic model that is able to predict snow cover extent (SCE) and snow water equivalent (SWE) in response to changes in climate can provide crucial information that is needed to plan for changes in water resources availability but also on potential feedbacks to the climate system. In this study, snow depth time series are simulated for the period 1950-1999 using the Variable Infiltration Capacity (VIC) model. In order to evaluate the performance of the VIC model in simulating SCE, results from the VIC model over the northern hemisphere (NH) are compared with satellite-derived SCE from the National Snow and Ice Data Center (NSIDC) NH EASE-Grid Weekly Snow Cover and Sea Ice Extent database. The comparison is focused on both temporal and spatial agreement between model and satellite-derived SCE. NSIDC NH EASE GRID Weekly snow cover and sea ice extent: 1.Temporal extention: 03/10/1966-24/06/2007 2.Temporal resolution: weekly 3. Spatial Extention: Northern Emisphere 4.Spatial resolution: 25 km The Variable Infiltration Capacity (VIC) hydrology model, implemented at ½ ° resolution over global land areas 1.Historical meteorological forcing (1950-1999) from Adam and Lettenmaier, 2003; 2.Vegetation: University of Mariland AVHHR land cover product; 3.Soil: FAO/UNESCO with calibrated parameters by Nijssen et al., 2001 4.Topography: SRTM30 1.Mean week of ONSET/END of the snow season 2.Snowcover regime for selected basins 3.MTFD: mean fraction of days with snow cover for each cell 4.MSRD: fraction of days with snow cover for the area 5.FA: fraction of area with snow cover for different durations (1, 15, 30, 60, 90 days) j = the j-th cell k = the k-th year m = number of cells n = number of years d snow = number of days with snow cover d tot = number of days in the period A snow = area with snow cover A tot = total area d = duration (days) 1. DATA 3.1. MEAN ONSET of the SNOW SEASON NSIDC 3.2. MEAN END of the SNOW SEASON NSIDC VIC 4. SNOWCOVER REGIME 5. WINTER (DEC-FEB) 6. SPRING (MAR-MAY) 7. SUMMER (JUN-AUG) 8. FALL (SEP-NOV) Monthly fraction of basin area with snowcover Columbia Colorado Yenisei Danube Lena VIC weekly mean snowdepth > 1 cm is classified as snow cover MSRD FA NSIDC MTFD FA MSRD NSIDC MTFD VIC MTFD 9. CONCLUSION * There is a reasonable agreement between modeled and satellite SCE. For example, the modeled SCE seasonality, obtained as the average fraction of snow-covered area in selected basins, reasonably reproduce those from the satellite. * There are some discrepancies, however. During the snowmelt season (March-May), the VIC model predicts a faster ablation than the satellite data; however, this is balanced by the slightly larger snow accumulation during the fall (September-November). * It is possible that biases may be attributed to the VIC simulations, but also to the satellite data, particularly in regards to a coarser spatial resolution than the VIC model results, as well as the pre-processing of the satellite data. * Overall, the discrepancies between the model and satellite-derived data are fairly small, which indicates that the VIC model can be used to explore the impacts of climate change on snow cover variability, snowmelt runoff and surface albedo. References: Adam, J. C., and Lettenmaier, D. P.:Adjustment of global gridded precipitation for systematic bias, J. Geophys. Res., 108, 1-14, doi: 10.1029/2002JD002499, 2003. Wood, E. F., Lettenmaier D. P, and Zartarian, V. G.: A Land-Surface Hydrology Parameterization With Subgrid Variability for General Circulation Models, J. Geophys. Res., 97(D3), 2717–2728, doi:10.1029/91JD01786, 1992. Armstrong, R. L., and Brodzik, M. J.: Northern hemisphere EASE-Grid weekly snow cover and sea ice extent, version 3, National Snow and Ice Data Center (NSIDC), Digital media, Boulder, Colorado, USA, 2005. Nijssen, B., Schnur, R., and Lettenmaier, D. P.: Global retrospective estimation of soil moisture using the Variable Infiltration Capacity land surface model, 1980-1993, J. Climate, 14, 1790-1808, 2001., k