Results from the 2018 Satellite Proving Ground Experiment in the Hazardous Weather Testbed (HWT)

Since the launch of the first satellite in the Geostationary Operational Environmental Satellite - R (GOES-R) series in November of 2016, the next generation of satellite data began flowing to forecasters across the United States. The increases in temporal and spatial resolution, along with vast improvements in spectral coverage have made GOES-R, now GOES-16, very important in monitoring severe convection across the contiguous United States. A prime user and evaluator of the GOES-16 imagery and products is the Hazardous Weather Testbed, or HWT, located adjacent to the SPC in Norman, Oklahoma. Each year for most of the last decade the GOES-R Proving Ground has held experiments in the HWT, called the Experimental Warning Program (EWP) Spring Experiment, to test out new products and familiarize forecasters with the vast amount of new products available in the GOES-R era. During the Experimental Warning Program (EWP) Spring Experiment, the Satellite Proving Ground conducts a demonstration of recently developed experimental products and capabilities alongside a forecaster's standard operational datasets and products. These experimental products are associated with next generation geostationary (GOES-R) and polar orbiting (JPSS) satellites. This experiment was initially designed to increase forecaster familiarity with the future GOES-R capabilities that would be available across the National Weather Service. In this way, EWP forecasters were readied for receipt and use of the GOES-R data prior to the launch of the first satellite in the series (GOES-R) which occurred on November 19, 2016. Now that the satellite is operational, the focus of the experiment has shifted to evaluating the products and capabilities of the satellite in a real time simulated operational environment and providing feedback to the product developers and to the National Weather Service. Additionally, feedback received from participants each year is utilized in the continued development of GOES-R/JPSS algorithms to improve the products for future operational use by forecasters in the local forecast offices as part of their daily routine. The results and feedback from the use of this data in the HWT to improve operational use of GOES-16 will be presented.