Confronting data delivery challenges of the future via the GOES-R Proving Ground

The Geostationary Operational Environmental Satellite R-Series (GOES-R) Proving Ground is a preparedness exercise between multiple government agencies and academia which aims to prepare National Weather Service (NWS) operations for the capabilities and applications of GOES-R, such that field use of imagery and products derived from GOES-R observations are maximized as soon as data is transmitted after launch. The advantages and enhanced capabilities of GOES-R compared to current GOES are numerous. Based on the spatial, temporal, and spectral improvements of the Advanced Baseline Imager (ABI) compared to the existing imager, data amounts will increase by a factor of 60.

There are many components to a successful proving ground effort and research to operations transfer exercise, including: relevant training, consistent and reliable delivery, and user interactions and feedback. Challenges lie ahead in effectively delivering data to NWS forecasters such that the received information from GOES-R is timely and useful. A new paradigm for data delivery is needed and functional data implementations and interrogation applications into the new Advanced Weather Interactive Processing System (AWIPS) are necessary.

As part of the GOES-R Proving Ground, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) is confronting this problem. This presentation focuses on the satellite imagery and products demonstrated as part of the GOES-R Proving Ground, how the implementation is performed, demonstrations and feedback resulting from testbeds, and plans for the future. Blended products and satellite data assimilation into local numerical weather prediction models are two relatively new ways that effective decision aids can be derived from satellite data and delivered to the forecasters to help with, among other tasks, thunderstorm forecasting and anticipating sea breeze development.