## 3 Results
### A Rainstorm Forecast Result Analysis
#### 3.2.1 Accumulated Rainfall Evolution  
In order to compare the performance of different experiments, the accumulated rainfall evolution is displayed in Figure 9. Precipitation is accumulated for 3, 6, 12, and 24 h from the first row to the fourth row, initialized at 0000 UTC 30 June 2017. The left column in Figure 9 is the observed precipitation from the Climate Prediction Center morphing method (CMORPH) products [31], the middle column is the simulated precipitation in CON, and the right column is for POD. The observed precipitation of 3-h accumulation (Figure 9a) is mainly in northern and central Hunan Province, and the border between Jiangxi and Hubei. There are two precipitation cores with the amount of 30 mm. The precipitation in CON also has two cores, but the left one is more to the west than the observation, and the right one is more to the northeast. Furthermore, the amount of the precipitation core in CON is 20 mm, clearly weaker than the observations. Including satellite and radar data, POD obviously captures the precipitation on the border between Jiangxi and Hubei. POD strengths the intensity of rainfall compared to CON, but overpredicts the amount of 3-h accumulated precipitation by 40 mm.  
For 6-h forecast, a clear northeast to southwest zone precipitation area is observed in the northeastern Hunan and northwestern Jiangxi Province (Figure 9d), with a maximum precipitation of 50 mm. The distribution of rainfall in CON (Figure 9e) is on the west of observations, with the location of precipitation cores mismatching the observations. One core area is in the central of Hunan, and another is on the border between Hubei and Jiangsu for CON. POD (Figure 9f) clearly improves the location of precipitation forecast, such as the rainfall in the northeastern Hunan and northwestern Jiangxi. In addition, the spatial distribution of precipitation in POD better agrees with observations compared with CON.  
The location of 12-h accumulated rainfall (Figure 9g) is similar to 6-h accumulated, but with larger coverage area, showing a precipitation core area in northeastern Hunan with the amount of 80 mm. In comparison, POD improves the intensity and location of precipitation forecast in Hunan and Jiangxi Province. Figure 9j-l shows the 24-h accumulated rainfall, with a larger area and stronger intensity in Hunan, Jiangxi, and Hubei. The maximum precipitation exceeds 100 mm. Without assimilation, CON underestimates the coverage of rainfall, with the precipitation core only in Hunan Province. However, POD is of better agreement with observation in the intensity, as well as the shape and location of the precipitation.  
In order to evaluate the precipitation results objectively, the Structure, Amplitude and Location (SAL) method is applied [32]. The forecast results with smaller absolute value of S, A and L are better. Figure 10 shows the SAL evaluation scores of 24-h accumulated precipitation at different thresholds. For the threshold \(>\)0 mm, the S value in POD is close to CON, slightly smaller than CON. The location forecast is similar to structure, in which POD is slightly smaller than CON. For intensity evaluation, A \(>\) 0 means that forecast results are stronger than the observations, A \(<\) 0 means the contrary. For 0 mm threshold, POD yields stronger precipitation than the observations, while CON shows a weaker forecast. However, the precipitation intensity forecast is clearly improved, since POD has a smaller absolute value. For the precipitation threshold 50 mm and 100 mm, the structure of the precipitation forecast is significantly improved with assimilation. Similarly, obvious smaller values are found for A and L in POD, which means better intensity and location forecast with satellite and radar data assimilated.  
Figure 9: Rainfall accumulation from (**a**,**d**,**g**,**j**) Climate Prediction Center morphing method (CMORPH) products, (**b**,**e**,**h**,**k**) CON and (**c**,**f**,**i**,**i**) POD. Rainfall is accumulated for 3, 6, 12, and 24 h, initialized at 0000 UTC 30 June 2017.