IN43C-1743
ATMS Snowfall Rate Product and Its Applications

Thursday, 17 December 2015
Poster Hall (Moscone South)
Huan Meng1, Cezar Kongoli2, Jun Dong2, Nai-Yu Wang3, Ralph R Ferraro4, Bradley Zavodsky5 and Banghua Banghua Yan6, (1)NOAA Camp Springs, Camp Springs, MD, United States, (2)Earth System Science Interdisciplinary Center, COLLEGE PARK, MD, United States, (3)University of Maryland, College Park, MD, United States, (4)Univ Maryland-ESSIC/CICS and NOAA/NESDIS, College Park, MD, United States, (5)NASA Marshall Space Flight Center, Huntsville, AL, United States, (6)NOAA/NESDIS, College Park, MD, United States
Abstract:
A snowfall rate (SFR) algorithm has been developed for the Advanced Technology Microwave Sounder (ATMS) aboard S-NPP and future JPSS satellites. The product is based on the NOAA/NESDIS operational Microwave Humidity Sounder (MHS) SFR but with several key advancements. The algorithm has benefited from continuous development to improve accuracy and snowfall detection efficiency. The enhancements also expand the applicable temperature range for the algorithm and allow significantly more snowfall to be detected than the operational SFR. Another major improvement is the drastically reduced product latency by using Direct Broadcast (DB) data. The new developments have also been implemented in the MHS SFR to ensure product consistency across satellites.

Currently, there are five satellites that carry either ATMS or MHS: S-NPP, NOAA-18/-19 and Metop-A/-B. The combined satellites deliver up to ten SFR estimates a day at any location over land in mid-latitudes. The product provides much needed winter precipitation estimates for applications such as weather forecasting and hydrology. Both ATMS and MHS SFR serve as input to a global precipitation analysis product, the NOAA/NCEP CMORPH-Snow. SFR is the sole satellite-based snowfall estimates in the blended product. In addition, ATMS and MHS SFR was assessed at several NWS Weather Forecast Offices (WFOs) and NESDIS/Satellite Analysis Branch (SAB) for its operational values in winter 2015. This is a joint effort among NASA/SPoRT, NOAA/NESDIS, University of Maryland/CICS, and the WFOs. The feedback from the assessment indicated that SFR provides useful information for snowfall forecast. It is especially valuable for areas with poor radar coverage and ground observations. The feedback also identified some limitations of the product such as inadequate detection of shallow snowfall. The algorithm developers will continue to improve product quality as well as developing SFR for new microwave sensors and over ocean in a project supported by the JPSS Proving Ground and Risk Reduction Program. The outcome of the new project is expected to considerably increase the value of the SFR product in operations.

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