The NASA Global Hydrology Resource Center (GHRC) DAAC published the GPM Ground Validation Micro Rain Radar (MRR) ICE POP dataset. This dataset was collected during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP) field campaign in South Korea. The two major objectives of ICE-POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to Global Precipitation Measurement mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. This dataset consists of precipitation data collected by two MRR instruments from November 1, 2017 to March 1, 2018. These data are available in netCDF-3 and ASCII text formats. It should be noted that the MRR-2 averaged (AVE) data were processed using software designed for liquid precipitation. This lead to accuracy issues with mixed and frozen precipitation, which were corrected using a new processing algorithm developed by Maahn and Kollias (2012).GHRC Published GPM GV MRR ICE POP
The NASA Global Hydrology Resource Center (GHRC) DAAC published the GPM Ground Validation Micro Rain Radar (MRR) ICE POP dataset. This dataset was collected during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP) field campaign in South Korea. The two major objectives of ICE-POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to Global Precipitation Measurement mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. This dataset consists of precipitation data collected by two MRR instruments from November 1, 2017 to March 1, 2018. These data are available in netCDF-3 and ASCII text formats. It should be noted that the MRR-2 averaged (AVE) data were processed using software designed for liquid precipitation. This lead to accuracy issues with mixed and frozen precipitation, which were corrected using a new processing algorithm developed by Maahn and Kollias (2012).
