## 3 Results
### The Impact of Soil Moisture Sampling Interval  
The impact of satellite soil moisture original sampling interval was detected by comparing SM2 RAIN estimates using soil moisture inputs from the same source but with different  
Figure 10: Improvement in precipitation estimate (in terms of \(RMSE\)) with the aid of reduced retrieval uncertainty and smaller sampling interval of soil moisture inputs. \(RMSE\_Diff\) represents the difference of RMSE with regard to default and referenced soil moisture input. Data_A, Data_D, and Data_AD represent the ascending, descending, and combined soil moisture inputs, respectively.  
Taking ascending orbit as an example, SM2 RAIN-derived precipitation based on OBS_A demonstrates relatively good agreement with the rain gauge observations. However, it tends to largely underestimate those intensive precipitation (see days around July 2018 and August 2018 in Figure 11(a1)), resulting in an estimated accumulated precipitation amount of 805 mm, which is lower than that of rain gauge observations of 812 mm (Figure 11(a2)). The statistical metrics \(R\), \(RMSE\), and \(BIAS\) are 0.73, 9.73 mm/5 d, and \(-0.16\) mm/5 d, respectively, while categorical metrics \(POD\), \(FAR\), and \(TS\) are 0.45, 0.02, and 0.44, respectively (Figure 7a). However, by substituting OBS_A with OBS_Daily_A, both the underestimation of intensive precipitation and evaluation metrics are further improved. This is evidenced by (1) better consistency with the rain gauge observations as supported by a better distribution along the 1:1 line and a higher \(R\) value of 0.83 (0.73 for OBS_A, Figure 11); (2) superior metrics with \(RMSE\), \(BIAS\), \(POD\), \(FAR\), and \(TS\) values of 8.06 mm/5 d, \(-0.92\) mm/5 d, 1.00, 0.02 and 0.98, respectively (Figure 7a).  
For the descending orbit, SM2 RAIN-derived precipitation based on OBS_D tends to underestimate those precipitation events with intensity larger than 30 mm/5 d (see days around June-August 2016, Jun 2018 and Aug 2018 in Figure 12(a1)). The accumulated precipitation amount obtained from OBS_D is 1222 mm, which is lower than the rain gauge observations of 1238 mm. The evaluation metrics, \(R\), \(RMSE\), \(BIAS\), \(POD\), \(FAR\), and \(TS\) are 0.71, 8.53 mm/5 d, \(-0.23\) mm/5 d, 0.73, 0.44 and 0.71, respectively. When OBS_Daily_D is used as input, better performance is obtained as evidenced by higher consistency with the rain gauge observations (Figure 12(b2)) as well as superior metrics except for \(BIAS\) (0.78, 7.81 mm/5 d, 1, 0.96 for \(R\), \(RMSE\), \(POD\) and \(TS\), respectively) (Figure 7b).  
For the combined orbit, despite the improved sampling interval of OBS_AD, underestimation of intensive precipitation (see days around Jun-Aug 2016, Jul 2018, and Aug 2018 in Figure 13(a1)) and overestimation of light precipitation (see days around Aug 2015) are still observed. The accumulated precipitation amount is 1330 mm, which is lower than that of rain gauge observations 1382 mm (Figure 13(a2)). The metrics \(R\), \(RMSE\), \(BIAS\), \(POD\), \(FAR\), and \(TS\) are 0.76, 8.92 mm/5 d, \(-0.69\) mm/5 d, 0.78, 0.07, and 0.73, respectively. Nevertheless, OBS_Daily_AD improves the performance of SM2 RAIN  
Figure 13: Similar to Figure 6, but for OBS_AD (**a1,a2**) and OBS_Daily_AD (**b1,b2**), respectively.  
as indicated by higher consistency with the rain gauge observations (Figure 13(b2)) and marginally improved metrics except for _BIAS_ (0.80, 8.44 mm/5 d, 1, 0.93 for \(R\), _RMSE_, _POD_ and _TS_, respectively) (Figure 7c).  
In general, the improvements of the SM2 RAIN algorithm introduced by reducing the sampling interval of soil moisture input in terms of _RMSE_ are approximately 1.67 mm/5 d, 0.72 mm/5 d, and 0.48 mm/5 d for ascending, descending, and combined orbit, respectively (Figure 10), with 0.96 mm/5 d on average.