Seminars & Workshops

Global Snow Cover Mapping Using Combined Optical and Passive Microwave Satellite Data

Richard L. Armstrong
Mary J. Brodzik, Matthew H. Savoie and Kenneth W. Knowles (National Snow and Ice Data Center (NSIDC), Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO, USA, email rlax@nsidc.org)

Abstract:
Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Over the past several decades both optical and passive microwave satellite data have been utilized for snow mapping at the regional to global scale. Snow mapping using optical data is based primarily on the magnitude of the surface reflectance, and in some cases on specific spectral signatures, while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. For the Northern Hemisphere, passive microwave and optical data sets indicate a similar pattern of inter-annual variability, although annual maximum snow extents and monthly variability derived from the optical data consistently exceed that provided by the microwave data. This results from the fact that current microwave algorithms often fail to accurately detect the shallow and intermittent snow located at the frequently fluctuating perimeter of the more persistent regions of the seasonal snow cover. We describe the respective advantages and disadvantages of these two types of satellite data for snow cover mapping and demonstrate how a multi-sensor product is optimal. We present multi-sensor snow products based both on historical data as well as data from current NASA EOS sensors. For the period 1978 to 2004 we combine data from the NOAA weekly snow charts with passive microwave data from the SMMR and SSM/I brightness temperature record. For the period since 2002 we blend NASA EOS MODIS and AMSR-E data sets. Our current blended product incorporates MODIS data from the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) with microwave-derived SWE at 25 km, resulting in a blended product that includes percent snow cover in the larger grid cell whenever the microwave SWE signal is absent. Relationships between the percent area covered by snow as indicated by the MODIS data and the threshold for the appearance of snow as indicated by the passive microwave data are presented. Both MODIS and AMSR-E data have enhanced spatial resolution compared to the earlier sensor systems and examples of how this results in more accurate snow cover maps are presented. We also describe new work in the application of the higher frequency microwave channels (85 and 89 GHz) to improve the capability of mapping shallow snow.