Constraining CloudSat-based snowfall profiles using surface observations and C-band ground radar

摘要

The CloudSat Precipitation Radar, launched in 2006, provides vertical profiles of W-band (94 GHz) reflectivity and is sensitive to falling snow through all but the most intense precipitating cloud structures. Precipitation retrievals of falling snow are affected by a wide diversity of factors describing the medium, such as snow particle shape, size, and composition, which in turn are controlled by ambient factors including the environmental temperature and humidity. Because satellite-based radiometric sounders such as the Microwave Humidity Sounder (MHS) operate without the benefit of coordinated space radar observations, microphysical descriptions of the snow particle medium derived from CloudSat or other radar observations are beneficial to passive microwave (PMW) radiometer-only snowfall retrieval methods. At the coarse scale of these PMW observations, the radiative signal due to the snow is relatively weak compared to the contributions from the atmosphere and the land surface emissivity. Using the C-band (5 GHz) polarization-agile King City radar (WKR) operated by Environment Canada, we examined the vertical structure of winter precipitation events from coordinated overpasses of CloudSat and NOAA 18 (MHS). Two-dimensional video disdrometer observations are used to limit (constrain) the range of the drop-size distribution parameters that are provided through a priori databases to dual-frequency (C/W-band) radar retrieval. Bayesian retrievals using the constrained database produce water content profiles that more closely replicate the observed radar reflectivity profiles and transition smoothly between the single-frequency (CloudSat only) and dual-frequency regions.