# A Random Forest-Based Precipitation Detection Algorithm for FY-3C/3D MWTS2 over Oceanic Regions
## 4 Results
### A Single-Case Analysis
#### 4.1.2. Matching \(RF\_SI\) to MWTS2 and MWTS3 Pixels  
MWTS2 lacks window channels at 23, 31, and 89 GHz, which precludes the computation of the \(SI\) or \(CLWP\). Consequently, quantitatively assessing the precipitation detection performance of \(RF\_SI\) within MWTS2 is challenging. Therefore, this paper compares the cloud classification results derived from the VISSR CLC for MWTS2. Figure 12 presents the precipitation detection results obtained with MWTS2 for Typhoon Sula on 31 August 2023 at 05:00 UTC. Specifically, Figure 12a displays the coincidental VISSR CLC product, which delineates the distribution of the cloud bodies at that moment. Figure 12b shows the precipitation detection results produced when the \(RF\_SI\) method is applied to MWTS2. The \(RF\_SI\) precipitation detection scheme proposed in this study more accurately discerns the MWTS2 pixels within cumulonimbus regions as precipitation pixels, whereas other areas, including clear skies and nonprecipitation cloud regions, are categorized as nonprecipitation pixels. The future sections on data assimilation applications will assess the efficacy of the \(RF\_SI\) precipitation detection method in MWTS2 from the perspectives of assimilation and forecasting. MWTS-III only has observation channels at 23 and 31 GHz but lacks an 89 GHz observation channel, thus preventing the calculation of the \(SI\) for MWTS-III. To quantitatively assess the precipitation detection capabilities of the \(RF\_SI\) method, this study employs the \(CLWP\) detection outcomes as the 'ground truths'. As demonstrated by [PERSON] et al. [5], the \(CLWP\) algorithm exhibits a \(RMSE\) of 0.05 mm when validated against ground-based microwave radiometer measurements. This study aligns the \(RF\_SI\) product with MWTS3 pixels and, by evaluating the precipitation detection performance of \(RF\_SI\) relative to that of the \(CLWP\) method, indirectly verifies the applicability of the \(RF\_SI\) precipitation method to MWTS2. For the precipitation test case, this study selects an extremely intense typhoon,  
Figure 12. Precipitation detection results obtained with FY-3D MWTS2 for Typhoon Sula on 31 August 2023 at 05:00 UTC: (**a**) VISSR cloud classification products and (**b**) the precipitation detection results yielded by MWTS2/\(RF\_SI\). \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \(ACC\) & POD & \(FAR\) \\ \hline \(RF\_SI/SI\) & 96.77\% & 92.67\% & 2.02\% \\ \(RF\_SI/CLWP\) & 95.89\% & 95.70\% & 6.13\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: \(ACC\), POD, and FAR results produced by the \(RF\_SI\) method relative to those of the traditional \(SI\) and \(CLWP\) methods. Tynboon Sora, that occurred on 1 September 2023 at 20:00 UTC, and the results are depicted in Figure 13. Figure 13a presents the VISSR cloud classification product, which reveals a substantial amount of deep convective clouds within the typhoon system, and these clouds are typically associated with heavy precipitation. Figure 13b shows the precipitation detection results obtained via the FY-3E MWTS3 _CLWP_ method, where pink denotes precipitation pixels, yellow signifies nonprecipitation pixels, and the background color represents the brightness temperature of the cloud top. Figure 13c displays the precipitation detection results produced after the _RF_SI_ data are matched with the MWTS3 data. Overall, both the _CLWP_ and _RF_SI_ methods demonstrate the ability to identify typhoon precipitation regions, particularly within the latitudinal range of 13\({}^{\circ}\) to 15\({}^{\circ}\)N. In this zone, both methods accurately detect nonprecipitation pixels within the convective cloud system, providing clear-sky brightness temperature data between cloud systems. A comparison between Figures 13a and 13b reveals that the _CLWP_ method has a lower degree of sensitivity to convective clouds. In the latitudinal ranges of 11\({}^{\circ}\) to 12\({}^{\circ}\)N and 20\({}^{\circ}\) to 24\({}^{\circ}\)N, certain areas covered by convective clouds are not identified as precipitation by the _CLWP_ method.