The development of precipitation retrieval techniques, as well as the quality assessment of satellite-based global precipitation estimates, can now benefit from the availability of unique cloud and precipitation observations by the two spaceborne radars: the Dual-frequency Precipitation Radar (DPR) on board the NASA/JAXA Global Precipitation Measurement (GPM) Core Observatory, available since March 2014, and the NASA CloudSat Cloud Profiling Radar (CPR), available since 2006. The multi-year, quasi-global, and complementary DPR and CPR measurements offer a unique and extensive resource to analyze spaceborne microwave radiometer precipitation observational capabilities. This can be particularly useful in
remote areas and/or where ground-based observations are sparse or not available (e.g., high latitudes), and in conditions and regimes where PMW precipitation retrieval is more challenging (e.g., light precipitation and snowfall). A recent study (Panegrossi et al., 2017) illustrated the potential of the use of these observational datasets to improve snowfall detection and retrieval techniques for passive MW radiometers at higher latitudes. The analysis of matched GPM Microwave Imager (GMI) and CloudSat CPR snowfall observations (mainly occurring at latitudes between 55° and 65°N) provided insights on microwave multi-frequency signals associated with snowfall. The analysis quantitatively showed the complex interconnection of high-frequency channel response to snowfall with background surface and environmental conditions (e.g., snow cover over land, sea ice concentration over ocean, water vapor content), and with the presence of supercooled droplets (as inferred from CPR/CALIPSO observations). The study also showed how such response depends on cloud vertical structure and snowfall intensity. Based on these findings, SLALOM (Rysman et al., 2018), a new algorithm for GMI to retrieve snow water path (SWP) and surface snowfall rate (SSR), has been developed. SLALOM exploits multi-platform (GPM/CloudSat/CALIPSO) snowfall coincidence dataset, and is based on random forest approach for snowfall and supercooled water detection, and multi-linear regression for SWP and SSR retrieval. Results show very good skills of
SLALOM compared to CPR, both in terms of surface
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Abstract Submission 12/11/18 13:04
SLALOM compared to CPR, both in terms of surface
snowfall occurrence and quantification. A similar approach is being recently applied to cross-track scanning MW radiometers, such as the Microwave Humidity Sounder (MHS) on board MetOp and NOAA satellites, and the Advanced Technology Microwave Sounder (ATMS), on board Suomi NPP and JPSS-1 platforms, both equipped with high-frequency MW channels, to analyze their potential to detect snowfall at high latitudes.
These findings pave the way towards the definition of future missions for snowfall global monitoring by combining a core satellite equipped with a multi-frequency radar in synergy with current and future MW radiometers (such as the EPS-SG Microwave Imager and Microwave
Sounder). This is the topic of the on-going Raincast ESA- ITT. The initial results of the study based on the analysis of the state-of the-art instrumentation, and on exploitation of the recent advancements in inversion methods for the estimation of precipitation variables, focused at identifying and consolidating the science requirements for such a satellite mission, will also be presented.
References
Panegrossi G., J-F. Rysman, D. Casella, A. C. Marra, P. Sanò, and M. S. Kulie, CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities, Rem. Sensing, 9(12), 1263; doi:10.3390/rs9121263, 2017.
Jean-François Rysman, G. Panegrossi, P. Sanò, A. C. Marra, S. Dietrich, L. Milani, M. S. Kulie, (2018), SLALOM: A snow water path retrieval algorithm for GPM Microwave Imager, Rem. Sensing, 2018, 10, 1278; doi:10.3390/rs10081278
PanegrossiG1 ,SanòP1 ,LaviolaS1 ,LevizzaniV1 , CattaniE1 ,MontopoliM1 ,BaldiniL1 ,WoldeM2 ,Kollias P 3 , Battaglia A 4
1 Institute of Atmospheric Sciences and Climate - National Research Council (ISAC-CNR), Italy
2 National Research Council Canada (NRC), Ottawa, Canada
3 McGill University, Montreal, Canada
4 University of Leicester, Leicester, Great Britain