## 4 Results and Discussion
### Rain Cell Retrieval by Network of ESLs and HMLs
However, there are significant differences in the overall structure of the rain cells. Most notably, the retrieved results for rain cell 2 and rain cell 3 show obvious distortions in local areas compared to the initial rain cells. The reason for this is mainly due to the fact that the distribution of links at these locations is too sparse and hence causes more significant errors in the OK algorithm during the interpolation process. In addition, the structural distribution of the rain cells retrieved by the RBF neural network is generally consistent with the structure of the initial rain cells on the whole. However, the rain rate peak at the center of rain cell 2 is not accurately retrieved. Figure 6: The set of different rain cells in the area. (**a**) is rain cell 1, indicating that the rain cluster has not yet fully entered the area. (**b**) is rain cell 2, indicating that the rain cluster has fully moved into the area. Additionally, (**c**) is rain cell 3, indicating that the rain cluster has split into two centers of rain rate. Figure 7: The results of the joint network of ESLs and HMLs retrieving the set of different rain cells. (**a–c**) represent the rain cells reconstructed by the OK algorithm, and (**d–f**) represent the rain cells reconstructed by RBF neural network. To further evaluate the retrieval results quantitatively, the rain rates of the rain cell retrieved by the OK algorithm and the RBF neural network are compared with the rain rate signals of the 1225 grid points of the initial rain cell. In Figure 8, it can be observed that the rain rate signals retrieved by the OK algorithm and the RBF neural network are overall close to those of the initial rain cells. However, there are still significant deviations for the retrieval of a small number of rain rate signals. As can be seen from Table 3, the RMSE of the OK algorithm for retrieving rain cell 1 and rain cell 2 is lower than the results of the RBF neural network, which indicates that the accuracy of the OK algorithm for retrieving the rain rate signals of rain cell 1 and rain cell 2 is better than that of the RBF neural network. However, for rain cell 3, the results of the RBF neural network outperformed the OK algorithm. For the MB of retrieval results, the OK algorithm is essentially unbiased for rain cell 2 and rain cell 3, but it underestimates rain cell 1. Additionally, the RBF neural network underestimates rain cell 1 and rain cell 2, and it overestimates rain cell 3. In addition, the retrieved rain cells of the RBF neural network all have higher CC than that retrieved by the OK algorithm, which indicates that the similarity between the rain cells retrieved by the RBF neural network and the initial rain cells is better. It is further verified that the distribution of the structures of the rain cells retrieved by the RBF neural network in Figure 7 is in better consistency with the initial rain cells in general. Figure 8: The results of joint net of ESLs and HMLs retrieving the rain rates of the different rain cells. (**a**,**c**,**e**) are the rain rates of the different rain cells retrieved by the OK algorithm, and (**b**,**d**,**f**) are the rain rates of the different rain cells retrieved by the RBF neural network. Based on the above results, it can be seen that the RMSE and MB of the OK algorithm for retrieval of the different rain cells are lower than 0.75 mm/h and 0.14 mm/h, respectively, and the CC of the retrieved results is above 0.985. In contrast, the RMSE and MB of the RBF neural network are lower than 0.69 mm/h and 0.29 mm/h, respectively, and the CC of the retrieved rain cells is higher than 0.994. Moreover, the structural distribution of the rain cells retrieved by the RBF neural network is generally in better consistency with the initial rain cells. Furthermore, the results indicate that after the distribution of sparse rain rates in the area is measured by the joint network of ESLs and HMLs, the distribution of rain cells in the area can be accurately retrieved by the OK algorithm and the RBF neural network.