Satellite Radiometer Remote Sensing of High Latitude Falling Snow

Retrievals of falling snow from space represent one of the next important challenges for the atmospheric, hydrological, and energy budget scientific communities. The Global Precipitation Measurement (GPM) mission has a requirement to detect falling snow. Historically, retrievals of falling snow have been difficult due to the relative insensitivity of satellite rain-based channels as used in the past. We emphasize the use of high frequency passive microwave channels (85-200 GHz) since these are more sensitive to the ice in clouds. Here we focus on testing the sensitivity of brightness temperatures from falling snow events to surface emission, cloud characteristics, and environmental state. This work also allows for an improved understanding of the relationships between radiative properties associated with radar reflectivities, brightness temperatures (TB), and the physical properties of frozen precipitation within a cloud. This analysis relies on data from the Canadian CloudSat/CALIPSO Validation Program (C3VP) field campaign held from October 31, 2006 through March 1, 2007. The C3VP field campaign provided an opportunity for the CloudSat/CALIPSO and GPM mission teams to participate in cold-season northern latitude data collection activities. It was located 80 km north of Toronto, in a rural agricultural and forested region and had regular CloudSat and AMSU-B overpasses. The field campaign was heavily instrumented on the ground (Parsivel, 2-Dimensional Video Disdrometers, etc), with aircraft (4 intensive operating one-week operating periods of in-situ sampling of cloud microphysics) and with CloudSat and AMSU-B satellite overpasses. In addition, Weather Research Forecast (WRF) models were generated for 20-22 January 2007 that simulated the Lake Effect (20 January) and Synoptic (22 January) falling snow events captured by the ground, aircraft, and satellite observations. We have found that the surface emission (emissivity*Tsurface) and cloud characteristics (IWP, cloud depth/top) affect the TB seen from space. The surface emission (if not accounted for) can contaminate the TB signal from the atmospheric falling snow and cause errors in the retrievals. The C3VP data set is especially challenging since the climatology supports shallow snow cloud events and light synoptic frozen precipitation. The cloud characteristics of these shallower/light storms do not necessarily provide enough signal to noise ratio between the atmospheric snow signal and the surface emission/environmental profile noise. We will show how we validate our results using CloudSat data and other C3VP observations. This preliminary work to understand the relationships between high frequency passive microwave observations of falling snow and the microphysics of falling snow are important areas of research to prepare for the upcoming GPM mission.