An overview of the GOES-R Proving Ground: current forecaster interactions and future plans

The Geostationary Operational Environmental Satellite (GOES)-R is the first member of a next generation series of satellites that will replace the current GOES-I/M and GOES-N/O/P series. Scheduled for launch in 2015, its Advanced Baseline Imager (ABI) radiometer will provide marked improvements over the current GOES imager in terms of its spectral, radiometric, spatial, and temporal resolution. In addition, GOES-R will carry the first Geostationary Lightning Mapper (GLM). The National Oceanic and Atmospheric Administration (NOAA) conceived the GOES-R Proving Ground as a means to providing day-1 readiness to this new satellite era that will allow operational forecasters to achieve the maximum utility from the new data and products that will be provided.

The concept of the GOES-R Proving Ground was developed in part because of lessons learned from the success of a similar effort in the development of the NWS NEXRAD Program. An important goal of the GOES-R Proving Ground is to establish an early and sustained two-way dialog between forecasters who will use the GOES-R products and those who are developing new products and applications. It is important to establish this dialog early to allow time for development of useful products for operations, based on GOES-R simulated and proxy datasets.

Proving Ground efforts are spread across NOAA/NESDIS/GPO, NOAA/NWS, NOAA/OSD, NOAA/OSDPD, NOAA/NESDIS/STAR, and three NOAA Cooperative Institutes: CIMSS with the University of Wisconsin, CIRA with the Colorado State University, and the CIMMS with the University of Oklahoma. Complementary Proving Ground activities are also conducted at the NASA Short-term Prediction Research and Transition (SPoRT) Program, in Huntsville, Alabama. The Proving Ground plans to provide simulated GOES-R products for operational testing, using a variety of means including combining current GOES channels with other satellite channels, making use of analogous MODIS satellite imagery, and using synthetic, model-generated imagery to simulate GOES-R products.

CIMSS continues strong interaction with over thirty National Weather Service (NWS) Weather Forecast Offices (WFOs) across the country dating back to 2006 through providing real-time experimental satellite imagery and products to assist with operational decisions, offering relevant forecaster satellite training, and eliciting forecaster feedback. The CIRA group also has extensive background in forecaster training and has recently established special PG interaction with two nearby WFOs (Cheyenne, Wyoming, and Boulder). In addition, CIRA is also engaging west coast WFOs (Monterey and Eureka, to start) in connection with collaborations on HMT-related satellite applications. NASA/SPoRT has been engaged in Proving Ground-like activities since its inception in 2002 by transitioning unique NASA research capabilities and Earth Observing System (EOS) products to its partners to serve specific forecast needs. This approach will be extended to GOES-R ABI proxy data sets provided by the specific algorithm working groups (AWGs) and the Proving Ground Team, with emphasis by SPoRT on forecast problems of the Southern Region WFOs. One of the more significant roles that SPoRT will play in the GOES-R Proving Ground is related to its partnerships and work to transition the use of total lightning data into operations as a proxy to GLM capabilities. Proving Ground interaction is also commencing with the Storm Prediction Center (SPC), and CIMMS in Oklahoma will be testing and evaluating GOES-R products at the SPC spring forecast exercise.

The purpose of this talk is to provide an overview of the GOES-R Proving Ground activities that are currently ongoing with the operational forecasting community, as well as those planned for the future. We will detail some of the specific product development and forecaster interactions taking place at CIRA and elsewhere. We will also discuss the plans of the GOES-R Proving Ground to organize these activities into a cohesive program that will best provide the type of feedback needed to yield the most effective set of operational products and training when GOES-R is launched.