Determining Snowfall Rate and Ice Water Contents from Reflectivity for Winter Nowcasting of Precipitation and Visibility

Faisal S. Boudala and George A. Isaac

Cloud Physics and Severe Weather Research Section Environment Canada, Toronto, Ontario, Canada

Weather conditions that are associated with winter snow storms affect daily human activities, including air and ground transportation, by reducing visibility and causing other severe weather phenomena such as blowing snow and heavy snow precipitation. Radar technology is increasing being used for remotely retrieving snow precipitation rates and ice water content (IWC). This information can be used for both short term (0-6 hr) nowcasting and validation of numerical weather prediction (NWP) models. However, radar measures the equivalent reflectivity factor (Ze) of the cloud particles, but not their mass or bulk mass flux directly. The accuracy of the retrieved ice mass or snow precipitation rate based on radar reflectivity is highly dependent on the algorithms used. Ice particles are mainly non-spherical and vary in density and thus don't obey the Rayleigh scattering assumption that most radar retrieval algorithms are based on. The precipitation and IWC retrieval algorithms normally include just one variable, Ze. Recently Boudala et al. (2006) have developed two algorithms for retrieving ice water content (IWC) and ice precipitation rate (S) as a function of temperature and Ze using ice particle spectra measured in stratiform ice clouds in midlatitude and Arctic regions. These algorithms have been tested using reflectivity measured by a vertically pointing bi-static X-band Doppler radar which is normally referred to as the Precipitation Occurrence Sensor System (POSS). The retrieved precipitation rates have also been compared with snowfall rates determined with VISALA FD12P and HotPlate sensors and a Geonor precipitation gauge. The results indicate that inclusion of temperature in the algorithms significantly improves the retrieval of snowfall rate. In this talk, the development, testing , and applications of these algorithms for nowcasting snow precipitation rates and visibility will be discussed. Possible application of these schemes in NWP models will also be explored.