# A Random Forest-Based Precipitation Detection Algorithm for FY-3C/3D MWTS2 over Oceanic Regions
## 4 Results
### A Time-Series Analysis
#### 4.2.1 Accuracy (ACC), Probability of Detection (POD), and False-Alarm Rate (FAR) Analysis  
The VISSR loses information in the VIS band at night, and the accuracy of the _RF_SI_ algorithm needs to be considered separately for both daytime and nighttime scenarios.  
The evaluation results shown in Figure 14 indicate that the average _ACC_ and _POD_ of the _RF_SI_ algorithm exceed 94% and 92%, respectively, and the _FAR_ is below 3%.  
The mean nighttime _ACC_ and _POD_ are slightly better than those observed during the day, with increases of less than 0.15%, and the nighttime _FAR_ is also slightly lower at 0.03%. These figures demonstrate that the precision of _RF_SI_ is stable and that its variability is low over time. The consistency in performance across different lighting conditions can be attributed to the comprehensive input data (HPF, CTT, CLC and UTH data) required for calculating _RF_SI_, which include not only VIS/IR information but also background fields, sounding data, and other relevant information. This multifaceted approach ensures that the accuracy of _RF_SI_ is not compromised by variations in day and night conditions. Furthermore, the comparison between _RF_SI_ and the _CLWP_ yields similar results to those of the comparison between the _SI_ and _CLWP_, which will not be reiterated here (the same analysis follows in the subsequent experiments).  
The distribution of paired samples in Figure 5 covers the region between 45\({}^{\circ}\)S and 45\({}^{\circ}\)N. During this period, the satellite zenith angle range of the FY-2F VISSR is 23.90\({}^{\circ}\)-56.13\({}^{\circ}\), and the satellite azimuth angle range for detecting pixels is 94.87\({}^{\circ}\)-288.26\({}^{\circ}\). To study the applicability of the _RF_SI_ method over ocean surfaces at midlatitudes, the changes exhibited by the _ACC_, _POD_, and _FAR_ of _RF_SI_ under different latitudes are shown in Figure 15a. The paired samples between 10\({}^{\circ}\)S and 40\({}^{\circ}\)S are distributed mainly across open ocean areas, totaling 7581 samples (shown in Figure 15b). The _ACC_, _POD_, and _FAR_ of the _RF_SI_ algorithm are maintained at approximately 95%, 92%, and 3.0%, respectively,  
Figure 14: Time series analysis of _RF_SI_ from 6 June 2017 to 6 July 2017. (**a**) _ACC_, (**b**) _POD_; and (**c**) _FAR_.  
with little variation. The number of paired samples between 10\({}^{\circ}\)S and 28\({}^{\circ}\)N is 20,537, with the _ACC_ and _POD_ of the _RF_SI_ algorithm remaining stable at 95% and 92%, respectively, while the _FAR_ varies between 3.7% and 5.5%. At this time, the paired samples are distributed mainly between Indonesia and the Philippines, where a substantial increase in the _FAR_ of the _RF_SI_ algorithm is observed due to the influence of land. However, the _ACC_ and _POD_ of the _RF_SI_ algorithm, which has a minimal influence on land, maintain similar levels of accuracy to those in the open ocean. Between 28\({}^{\circ}\)N and 40\({}^{\circ}\)N, the paired sample count decreases significantly to 2495 compared with that in other regions because a substantial portion of the samples are located over East Asia and the South Asia mainland, leading to inadequate representations for analysis purposes.