230 CICS-MD Contributions to NOAA Satellite Water Cycle Products and Services

Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Patrick C. Meyers, Univ. of Maryland, College Park, MD; and R. R. Ferraro, E. H. Berbery, N. Y. Wang, H. Meng, S. D. Rudlosky, J. Dong, and Y. You

The Cooperative Institute for Climate and Satellites at the University of Maryland (CICS-MD) is supporting the JPSS and GOES-R Risk Reduction Program (GOES-R3) by focusing on research and development of water cycle products for the National Weather Service (NWS). The projects exploit the improved temporal and spatial resolution of the GOES-R Advanced Baseline Imager (ABI), as well as the revolutionary Geostationary Lightning Mapper (GLM). A key component for the success of the project has been the establishment and expansion of the CICS-MD Proving Ground and Training Center (PGTC), where CICS-MD scientists and NWS forecasters collaborate to develop and improve hydrological satellite products. This presentation highlights three JPSS and GOES-R3 water cycle projects.

The PGTC is supporting the GLM roll-out by optimizing data display tools within the Advanced Weather Interactive Processing System – II (AWIPS-II). An AWIPS-II plug-in under development will consolidate GLM observations to provide forecasters with a technique to access storm life-cycle information. Collaborations with the NWS Ocean Prediction Center focus on monitoring storm cells capable of producing maritime hazards in areas where GLM and ABI serve as proxies for radar.

A regional precipitation algorithm is under development to address the unique characteristics of storms in the Central Pacific. Himawari-8 radiances were collocated with lightning and satellite precipitation radar observations to determine persistent multi-channel characteristics of heavily precipitating convective storms in the area of interest. Lightning location and intensity provides useful location information of intense convection. Similarities between geostationary imagers enable the portability of the Himawari-8 algorithm design to the GOES-R series for applications in the tropical Atlantic.

NESDIS currently runs an operational snowfall rate (SFR) retrieval using POES and Metop passive microwave radiometers. The JPSS Proving Ground and Risk Reduction program also supported the development of S-NPP ATMS SFR product which is being transitioned to NESDIS operations. The PGTC successfully incorporated the NESDIS SFR product into NWS forecasting software, and provides a platform to address user requests for product improvement. The SFR development established a baseline procedure to integrate CICS-MD products into a proxy for the NWS operational framework. Future development under the GOES-R3 program will leverage ABI observations to estimate snowstorm trajectory and intensity changes based on cloud-derived information.

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