# Adapting Satellite Soundings for Operational Forecasting within the Hazardous Weather Testbed
## Materials and Methods  
### Datasets  
NOAA's Office of Satellite and Product Operations (OSPO) runs NUCAPS operationally to retrieve atmospheric profiles, referred to as \"soundings,\" from measurements made by the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) instruments onboard Suomi NPP and NOAA-20 polar orbiting satellites. NUCAPS sounding variables within AWIPS include profiles of temperature, moisture, and Ozone (O\({}_{3}\)) in clear and partly cloudy scenes (Figure 1). NUCAPS begins by running a microwave (MW)-only retrieval (Step A) that employs an Optimal-Estimation method [14] using the 22 ATMS channels to generate profiles of temperature, water vapor, and liquid water for all non-precipitating scenes. NUCAPS then derives a first guess estimate of temperature and moisture (respectively labelled T and q, in Figure 1) using a statistical linear regression with static coefficients trained off-line from an ensemble of historical radiance measurements from CrIS and ATMS that are collocated with modelled profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF). This combined MW and infrared (IR) regression is called the cloudy regression (Step B). The cloudy regression state is used to derive the cloud cleared radiances for CrIS (Step C) within a field of regard (FOR), which is a 3 x 3 array of collocated CrIS and ATMS footprints. Cloud clearing is described in detail elsewhere [6; 15; 16; 17], but a few things are worth noting here. Cloud clearing derives a clear-sky estimate of the IR measurements in a FOR by removing the radiative effects of clouds. By doing so, NUCAPS can retrieve soundings of the atmosphere past clouds, not through them. Cloud clearing fails when a FOR is uniformly cloudy and there is no radiative pathway past the clouds to the Earth surface. We then utilize another \"cloud cleared regression\" (Step D) that was trained on historical cloud cleared CrIS radiances, ATMS, and co-located ECMWF to derive a first guess for temperature and moisture profiles from the cloud cleared radiances for this specific scene. NUCAPS then retrieves temperature and moisture profiles (Step E) from a combination of the 22 ATMS and a subset of cloud-cleared CrIS channels, with the cloud cleared regression retrieval as first guess. We also retrieve a number of trace gas profiles (ozone, carbon monoxide, etc.) from subsets of cloud cleared CrIS channels. This step is known as the IR + MW retrieval and it employs an optimal-estimation approach that maximizes the information content of the hyper-spectral infrared radiances [6]. The MW-only retrieval is used where the cloud clearing failed due to uniform clouds or difficult surface conditions. The NUCAPS sounding product contains an IR + MW retrieved sounding at each FOR with some of them flagged as failed. The retrieval can fail for various reasons (uniform clouds, lack of convergence, etc.) but NUCAPS creates a simple \"stop-light\" approach using green, yellow, and red flags to describe the profile quality in AWIPS. We will discuss this approach in greater detail in Section 2.1. NOAA continually validates NUCAPS with in-situ measurements from field campaigns [18; 19]. In AWIPS, forecasters have access to all NUCAPS retrievals, whether they are flagged successful or not. The reason being that while retrievals may have significant errors below clouds, they can be useful in examining the middle to upper atmosphere above cloud tops. In general, the accuracy of NUCAPS temperature and moisture retrievals is well established and meet NOAA requirements (1K for temperature and 10% for water vapor). However, the accuracy of individual retrievals varies from scene to scene, depending on the amount and types of clouds. Forecasters query NUCAPS soundings one by one within and around storm systems and therefore need to understand how to interpret them correctly, given the prevailing conditions.