Convective Snow Quantitative Precipitation Estimation Using GOES/POES, NEXRAD, and Ground-Based Observations

The primary objective of this project is to build the foundation for an operational satellite-based product that improves forecaster situational awareness for hazardous terrestrial convective snow squalls. Convective snow squalls are generally short duration events that can produce intense snowfall rates, reduced visibilities, and can initiate flash freeze events on highway surfaces. Furthermore, the shallow nature of convective snow squalls creates NEXRAD observational deficiencies at longer distances from radar sites as the lowest elevation radar scan overshoots the convective snow cores. This project will first investigate the location and frequency of Snow Squall Warnings issued by National Weather Service Weather Forecast Offices over a multi-year period to provide a geographical census of where and when hazardous snow squalls occur. A merged dataset composed of GOES-16 observations and derived cloud products, NEXRAD radar reflectivity and derived snowfall rates, surface visibility, and model-derived environmental conditions will also be developed and interrogated to identify relationships between relevant variables derived from the respective datasets. Different in situ and model-derived visibility datasets will also be exploited to create an operationally viable enhanced gridded visibility product. The ultimate project goal will be to produce a robust training database using all available remote sensing, in situ, and modeling datasets that can be deployed in an Artificial Intelligence (AI)/Machine Learning (ML) setting. This satellite product will provide quantitative precipitation rates and/or a probabilistic hazardous threat level for convective snow squall events that can be easily interpreted for nowcasting purposes and will augment NEXRAD observations in regions prone to radar observational deficiencies for convective snow events.