## 3 Results
### Statistical Evaluation  
Figure 4 examines the performance of all the flights combined for clear to partly cloudy scenes (quality flag green, Figure 4a,c) and cloudy but not precipitating scenes (quality flag yellow, Figure 4b,d) using the statistical metrics defined in Section 2.3. Each panel has a profile count (N) and a cloud fraction (CF%) in the upper right corner. The clear to partly cloudy scenes had an average cloud fraction of 27%, while cloudy scenes had an average of 83%. The IR + MW retrieval (blue lines) performed similarly to the MW-only retrieval (orange lines) in the mid-troposphere temperature retrievals (800-300 mb); however, the IR + MW has a lower RMSE and bias closer to the surface (<800 mb; Figure 4a). For scenes where the MW-only retrieval succeeded but the IR + MW was rejected (Figure 4b), the IR + MW retrieval has a larger RMSE than the MW-only retrieval above 800 mb, although the bias is somewhat lower. It is sensible to wonder why the IR + MW retrieval has a lower mean bias than the MW-only retrieval, even though cloud clearing (Section 2.1) likely failed. The reason for this is that the first guess of the NUCAPS uses all available channels, including MW. So, even if the information content of the IR measurements is low, it may perform similarly to the MW-only retrieval. When the IR + MW water vapor retrieval was successful (Figure 4c), it met or outperformed the MW-only retrieval. In cases where the IR + MW water vapor retrieval was rejected and the MW-only passed (Figure 4d), the RMSE value was again lower than the IR + MW retrieval, while the bias of both was similar. Tables 1 and 2 show the pressure layer average statistics. The Joint Polar Satellite System (JPSS) has established targeted performance statistics for NUCAPS. The performance requirements were established for global retrievals on co  
Figure 4: RMSE, bias, and standard deviation of IR + MW and MW-only retrievals for (**a**) temperature (K) over clear to partly cloudy scenes, (**b**) temperature (K) over cloudy scenes, (**c**) water vapor (%) over clear to partly cloudy scenes, and (**d**) water vapor (%) over cloudy scenes. Profile count (N) and cloud fraction (CF%) is indicated in the top right corner. Section 2.3), so it is not expected that individual retrievals, 100-level statistics, and smaller studies exactly meet these thresholds. However, we make the comparison to the global requirements to provide context. The JPSS requirements for temperature are an RMSE at or below 1.6 K over clear to partly cloudy scenes and 2.5 K over cloudy scenes when averaged from the surface to 300 mb. The IR + MW retrieval temperature RMSE (1.04 K) meets the JPSS global threshold for clear to partly cloudy scenes. The MW-only temperature RMSE (2.7 K) almost meets cloudy scene requirements, although the RMSE is significantly higher below 600 mb than between 600 and 300 mb. The JPSS requirement for water vapor retrievals has a percent average requirement of 20% below 600 mb. The IR + MW retrieval for water vapor retrieval over clear to partly cloudy scenes is 26% near the surface for the IR + MW retrieval and 23% for the MW-only retrieval over cloudy scenes, so neither make this threshold. In mid-levels (600-300 mb), the RMSE is 46% and 43% for these same two combinations of scenes and retrievals, respectively. Again, these do not meet the JPSS percent average requirements. The lower-than-usual performance is likely due to the small sample size compared (130 profiles) with global validation studies (hundreds of thousands of profiles) and because we focused on the tropical cyclone environment, which are challenging retrieval scenes. A caveat in this analysis is that we removed two instances of supersaturation, which is a documented problem where the NUCAPS algorithm produces unrealistic mixing ratios. The 2018 and 2019 flights used NUCAPS version 2, while the 2021 flight was processed using version 3, which corrected the problem.