Snow Melt on Sea Ice from Multispectral Satellite Data

Snow cover on sea ice plays an integral role in governing the Arctic's energy budget, due to its influence on albedo, insulating effects, and its considerable spatial and temporal variability. Studies point to a significant reduction in the amount of ice cover and ice thickness and suggest correspondingly substantial changes in the thermal state of the Arctic Ocean. These changes have important implications for ice cover and the ice-albedo feedback. Therefore, in order to monitor changes in snow cover over sea ice, a case study was conducted to develop a snow melt index and surface energy balance data set using a multi-parameter approach from remotely sensed data. This snow melt index is based on a combination of passive microwave brightness temperatures, surface albedo and temperature data, similar to heating degree-days, and can be used as a proxy climate indicator. The snow melt index represents variations in surface albedo, temperature, melt onset, melt duration as well as atmospheric conditions. The multispectral satellite data used to generate the snow melt index consists of the 25 km gridded EASE-grid format Advanced Very High Resolution (AVHRR) Polar Pathfinder surface temperatures and albedos and passive microwave brightness temperatures from the Special Sensor Microwave/Imager (SSM/I). Independently, these data have been used to represent snow melt conditions. However, this is a new approach to integrate multispectral data together to generate the snow melt index. The Beaufort Sea region was chosen for this study because of ancillary data available during the period. For example, SHEBA observations were used for validation with the melt index. Using the knowledge gained in the case study, a snow melt index could be developed from the multispectral satellite data to determine seasonal and interannual variations in snow and ice conditions over a 25 year period.