SNOWFALL DETECTABILITY OF NASA'S CLOUDSAT: THE FIRST CROSS-INVESTIGATION OF ITS 2C-SNOW-PROFILE PRODUCT AND NATIONAL MULTI-SENSOR MOSAIC QPE (NMQ) SNOWFALL DATA

Abstract

This study investigates snowfall detectability and snowfall rate estimation with NASA's CloudSat through the first evaluation of its newly released 2C-SNOW-PROFILE products using the National Mosaic and Multisensor QPE System (NMQ) snowfall products. The primary focus is on the detection and estimation of surface snowfall. The results show that the CloudSat product has good detectability of light snow (snow water equivalent less than 1 mm/h) but degrades in moderate and heavy snow (heavier than 1 mm/h). The analysis suggests that the new 2C-SNOW-PROFILE algorithm is insufficient in correcting signal losses due to attenuation. Its underestimation is well correlated to snowfall intensity. Issues of sensitivity and data sampling with ground radars, which may affect the interpretation of the results, are also discussed. This evaluation of the new 2C-SNOW-PROFILE algorithm provides guidance for applications of the product and identifies particular error sources that can be addressed in future versions of the CloudSat snowfall algorithm.