A multi-source interactive analysis approach for Northern hemispheric snow depth estimation

This paper presents a new approach to operational snow depth analysis. The analysis uses 2-dimensional optimal interpolation to blend various snow depth data weighted against their errors relative to a first guess and spatial correlations. The blended analysis is applied operationally within the National Oceanic and Atmospheric Administration (NOAA)´s Interactive Multi-Sensor Snow and Ice Mapping System (IMS) at its snow cover-classified grid points over the Northern Hemisphere. The 4-km snow depth estimates are blended from satellite-derived estimates of the Advanced Microwave Scanning Radiometer 2 (AMSR2) or the Advanced Technology Microwave Sounder (ATMS), in-situ surface reports and analyst estimates. Unique to the production is the application of snow depth estimates with the associated confidence values generated interactively from the analyst that are also ingested into the objective analysis and fully consistent with optimal interpolation method.