A Review of Snow Cover Analysis: Potential Technologies for Planning and Risk-Based Assessment (Invited Presentation) (Centennial)

In snow-dominated basins across the globe, requirements of tactical land surface applications, water resource management, and flood control have increased due to the needs of more precise planning and disaster preparedness. While long-range and short-term quantitative precipitation forecasting has come a long way, particularly in the last decade, cold-season forecasts do not suffice as input to snow cover modeling for mission analysis, resource planning, or disaster readiness. Thus, research driven by these applications over the last few decades has increasingly focused on improved methods for direct detection of snow properties from airborne and spaceborne sensors, fusing data sources through assimilation into feed-forward models, and forensic reanalysis, or reconstruction, to produce diagnostic data sets. While progress in remote sensing, snow modeling, and reconstruction has become somewhat more incremental, the snow community has begun to explore the spatio-temporal domain from the perspective of fine-scale distributed snow “climatology” and machine learning with current indicators to gain insights on “What could happen”. This presentation reviews the state of science, particularly as report through the AMS journals, to set the stage for the session to follow.