# Adapting Satellite Soundings for Operational Forecasting within the Hazardous Weather Testbed
## 1 Introduction  
National Weather Service (NWS) forecasters have access to over 300 satellite data sets within the Advanced Weather Interactive Processing System (AWIPS), their data visualization and decision support platform. For robust hazard prediction, it is paramount that these satellite data sets give forecasters information that is easily accessible, timely, and relevant. To transition satellite data from research into useful weather forecasting and decision-making, the National Oceanic and Atmospheric Administration (NOAA) administers several annual testbeds ([[https://www.testbeds.noaa.gov/](https://www.testbeds.noaa.gov/)]([https://www.testbeds.noaa.gov/](https://www.testbeds.noaa.gov/))) thateach focus on scenarios encountered in areas such as aviation, hydrometeeorology, space weather, hurricanes, and severe storms. Of the testbeds, the Hazardous Weather Testbed (HWT) fosters an environment where researchers and forecasters collaboratively assess new technology for issuing warnings and forecasting severe weather [1]. Three goals of the HWT are to (1) train forecasters in new technology (2) allow forecasters to evaluate new technology ahead of their release into operations and (3) refine and improve data according to forecaster feedback. Forecasters participating in the HWT provide feedback through surveys, written descriptions and screenshots of scenarios they encountered (e.g., blog.nssl.noaa.gov/ewp), and through direct communication with the researchers who are present during testing. Since the experiment simulates the forecaster work environment, this feedback guides researchers to make improvements that are relevant to operational forecasting [2; 3; 4]. The phrase \"operational forecasting,\" or more colloquially, operations, refers to the active and non-stop data collection and weather prediction needed to protect human life and property. In this paper, we focus on how the satellite sounding datasets generated by the NOAA Unique Combined Atmospheric Processing System (NUCAPS) [5; 6; 7; 8] were transitioned from a technology primarily used by scientific researchers to one that could also be used for severe weather forecasting. These activities were conducted as part of the Satellite Sounding Initiative within the Joint Polar Satellite System (JPSS) Proving Ground and Risk Reduction Program ([[https://www.jpss.noaa.gov/proving_ground.html](https://www.jpss.noaa.gov/proving_ground.html)]([https://www.jpss.noaa.gov/proving_ground.html](https://www.jpss.noaa.gov/proving_ground.html))) and represent a multi-organizational and agency partnership. We refer to NUCAPS and NUCAPS-derived datasets as satellite data products, a general term that describes observational data acquired by satellite instruments which are calibrated and geolocated prior to being processed with a retrieval algorithm and before distribution to the users. Like many products, NUCAPS was repeatedly tested to evaluate incremental improvements and to adjust to changing forecaster needs. From the 2014 to 2019 HWTs, forecasters provided feedback and identified case studies that led to refinements of NUCAPS accuracy through retrieval algorithm improvements. Additionally, forecaster-researcher interactions improved how NUCAPS was displayed to the forecaster and how quickly the data were delivered following a satellite overpass. For example, in the first HWT, NUCAPS developers participated by answering questions via email. The following year, developers were physically present during the HWT, developers improved the usefulness of NUCAPS by displaying it as a Skew-T, the primary way forecasters inspect data from radiosondes. This back-and-forth communication and resulting product improvement are referred to as \"operations to research\" and \"research to operations\" [2]. Without this partnership, we could not have successfully implemented NUCAPS for severe weather prediction. When NUCAPS was configured for AWIPS, it was the first time that forecasters could visualize satellite soundings in real-time.