# Construction of Nighttime Cloud Layer Height and Classification of Cloud Types
## 4 Results and Discussion
### Performance of the NSRM Method
The trend of response to \(\beta\) value was expected, since narrower constraints lead to more aggressive screening of the potential donors. However, a very small \(\beta\) (<1.5) could result in a sharp decrease in the number of successfully matched pairs. To make a balance, \(\beta\) = 1.5 was selected to be utilized in the NSRM method. The same dataset was then used to test the performance of different values of \(\alpha\) (Figure 4). The results show that, with the additional constrain \(\beta\), \(\alpha\) = 0.3 was still an appropriate choice to apply to the algorithm. Therefore, \(\alpha\) = 0.3 and \(\beta\) = 1.5 were applied to the construction of the entire dataset. The general trend over the expanded distance can be summarized as MD and RMSE increased as the dead zone increased (Figure 5). The trend is logical because, as the distance between the donor and the recipient increased, the probability to find a good match decreased. The average MD between the original and the reconstructed CTH at 50 km was 0.97 km, which increased to 1.49 km at 200 km and 1.83 km at 400 km; the error bar shows that the standard deviation of 143 profiles increased from 0.25 at 50 km to 0.42 at 200 km and 0.49 at 400 km. The average RMSE between the original and the reconstructed CTH at 50 km was 2.49, which increased to 3.26 at 200 km and 3.76 at 400 km. The trend of CBH was similar. The average MD between the original and the reconstructed CBH at 50 km was 1.32 km, which increased to 1.81 km and 2.02 km at 200 km and 400 km, respectively; the error bar increased from 0.50 to 0.73 and 0.76, respectively. The average RMSE of CBH at 50 km was 2.92, which increased to 3.6 at 200 km and 3.95 at 400 km. Note that the constrained dataset focused on pixels that had a MODIS retrieved CTH within 2 km of the CloudSat-retrieved CTH; if all pixels were considered, these diagnostic variables would have been 10-35% larger, as shown in Figure 5.  
Figure 4: MD (**a,b**) and RMSE (**c,d**) of CTH and CBH between the original profiles and the reconstructed profiles, changing with \(\alpha\) and dead zone. Figure 5 also presents the comparison of diagnostic variables calculated among several methods. The green line shows the results from the profiles reconstructed with the SRM method, which utilized four MODIS bands (0.62-0.67, 2.105-2.155, 8.4-8.7, and 11.77-12.27 \(\upmu\)m) in the same way as Equation (1). However, note that the SRM method is not adapted to nighttime condition. Therefore, only two bands in the IR range could be used for nighttime construction. The gray line shows the results of simply selecting the nearest cloud pixel outside the dead zone as the donor, which is not supposed to be a reasonable match due to the discontinuity of clouds. It is clearly shown in the figure that the NSRM method had better performance than the SRM method at night. However, the SRM method had a higher rate of finding a matching donor, partly due to the lack of constraints. The nearest donor method, on the other hand, had high accuracy at 10 km, but the errors increased quickly as the dead zone increased. In general, it is not recommended to use the algorithm to construct scenes more than 400 km away from the ground track, since the possibility of successful construction is low and errors are large. However, some works have found good construction results at a very large range during special events, such as typhoons [22]. The performance of the NSRM method was also evaluated with MODIS measurements in the original pixel and the reconstructed one (Figures 6 and 7). MD and RMSE for both \(\alpha\) and \(\beta\) were much smaller compared to the evaluation against C-C measurements, but the trend was similar overall, but more gradual. The fact that MODIS is less sensitive to high thin clouds may have had a major influence here. Figure 5: Comparison of MD of CTH and CBH between the original profiles and the reconstructed profiles.