# Evaluating Satellite Sounding Temperature Observations for Cold Air Aloft Detection  
[PERSON]  
1 Cold Air Aloft (CAA) can impact commercial flights when cold air descends below 12,192 m (40,000 ft) and temperatures drop dramatically. A CAA event is identified when air temperature falls below \(-65\)\({}^{\circ}\)C, which decreases fuel efficiency and poses a safety hazard. This manuscript assesses the performance of the National Oceanic and Atmospheric Administration Unique Combined Atmospheric Processing System (NUCAPS) in detecting CAA events using sounders on polar-orbiting satellites. We compare NUCAPS air temperature profiles with those from Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) for January-March 2018. Of 1311 collocated profiles, 236 detected CAA. Our results showed that NUCAPS correctly detects CAA in 48.1% of profiles, while 17.2% are false positives and 34.7% are false negatives. To identify the reason for these detection states, we used a logistic regression trained on NUCAPS diagnostic parameters. We found that cloud cover can impact the skill even at higher vertical levels. This work indicates that a CAA-specific quality flag is feasible and may be useful to help forecasters to diagnose NUCAPS in real-time. Furthermore, the inclusion of an additional sounder data source (e.g., NOAA-20) may increase CAA forecast accuracy. Cloud scenes change rapidly, so additional observations provide more opportunities for correct detection.  
12 December  
are available in real-time as a skew-T diagrams and pressure-dependent gridded 2-D maps [7] in the operational forecasting tool, AWIPS (Advanced Weather Interactive Processing System). NUCAPS has value beyond detecting CAA events and specifically for hazardous weather forecasting, as was demonstrated through the Joint Polar Satellite System (JPSS) Proving Ground and Risk Reduction (PGRR) Program [8]. The PGRR program fosters interaction between NUCAPS developers and forecasters to identify new applications, improve understanding and facilitate the value of satellite soundings in operations.  
In their a PGRR study [3], [PERSON] et al. explored the value of NUCAPS from the forecaster's perspective for the Anchorage Center Weather Service Unit (CWSU), which provides aviation forecasts for Alaska and regions North and to the West, including the North Pole, Russia, and Japan. They evaluated NUCAPS success in detecting CAA by comparing NUCAPS to Meteorological Impact Statements (MIS), pilot responses, and other data for the boreal winters in 2016-2017 and 2017-2018. Their work describes how the partnership between developers and forecasters helped to fine-tune NUCAPS for use in an operational forecast setting. Our objective in this paper is to (1) quantitatively evaluate the skill of NUCAPS to detect CAA, (2) investigate some of the CAA observational errors by evaluating diagnostic parameters and measures of information content in the algorithm, and (3) discuss a pathway to improve the utility of NUCAPS for operational CAA detection. As an operational product at NOAA, NUCAPS is routinely validated with conventional in situ observations and during field campaigns [9; 10]. In general, validation is used to rigorously determine if NUCAPS meets global statistical requirements. In contrast, this study seeks to specifically evaluate NUCAPS temperature retrievals with respect to detecting CAA, an operational application with regional scope and specific forecaster requirements.