Retrieving Surface Snowfall With the GPM Microwave Imager: A New Module for the SLALOM Algorithm

Jean-François Rysman (1) , Giulia Panegrossi , Paolo Sanò , Anna Cinzia Marra , Stefano Dietrich , Lisa Milani , Mark S. Kulie , Daniele Casella , Andrea Camplani , Chantal Claud (1) , Léo. Edel (1)

1 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)

In this study, we present a new module for the Snow retrievaL ALgorithm fOr gMi (SLALOM) that retrieves surface snowfall rate using Global Precipitation Measurement (GPM) Microwave Imager measurements together with humidity and temperature vertical profiles. This module, named Surface Snowfall Rate Module, is tuned using colocated surface snowfall observations of the Cloud Profiling Radar onboard CloudSat. Using this new module, the SLALOM algorithm is able to predict surface snowfall rate with a relative bias of -13%, a root-mean-square error of 0.08 mm/hr, and a correlation coefficient of 0.7. Surface Snowfall Rate Module is then used to retrieve snowfall rate for three case studies and to provide a unique, 70°S to 70°N high-resolution distribution of average surface snowfall rate from 2014 to 2017. This new product will be useful for surface precipitation analyses, global water budget estimation, and climatological analyses.

Keywords: Snowfall; Remote Sensing; Passive Microwave; GMI; CPR

Domains: Sciences of the Universe [physics]

Jean-François Rysman, Giulia Panegrossi, Paolo Sanò, Anna Cinzia Marra, Stefano Dietrich, et al.. Retrieving Surface Snowfall With the GPM Microwave Imager: A New Module for the SLALOM Algorithm. Geophysical Research Letters, 2019, 46, pp.13,593-13,601. ⟨10.1029/2019GL084576⟩. ⟨insu-03727009⟩