# Comparisons of Spatially Downscaling TMPA and IMERG over the Tibetan Plateau
## 4 Discussion
### Anomalies in the Inland Water Bodies in TP
For GPROF 2014, the surface type was classified based on the monthly emissivity for all  
Figure 11: Spatial distribution of precipitation estimates generated from (**a**) TMPA 3b43, (**b**) IMERG Final and (**c**) inland water bodies from Global Lakes and Wetlands Database (GLWD). The black circles represent the sites for anomalies. Figure 12: Comparison of mean monthly precipitation data for the anomalies covering inland water bodies in the original TMPA 3B43 data (blue line) and the original IMERG data (red line) with the data from seven rain gauge stations (black line). SSM/I frequencies. The inland water bodies were treated as independent classes and were trained in the Bayes' model, which was beneficial for estimating precipitation over water bodies. Thus, the unified and updated PMW algorithms used in IMERG products result in improved precipitation estimates over water bodies compared to TMPA products. Another possible reason for the improvement in the precipitation estimates over water bodies was that IMERG used GMI, which had a much better resolution than TMI equipped in TRMM, thus it can better identify the inland water bodies. For the monthly downscaled results based on TMPA data and IMERG data using random forest algorithm and monthly disaggregation algorithm, we also calculated the precipitation estimates for the same seven sites for anomalies. The results were shown in Figure 13. Both the downscaled results based on TMPA data and IMERG data at 1 km resolution corresponded well with rain gauges. The bias was \(\sim\)12% and 8% for the downscaled results based on TMPA and the downscaled results based on IMERG, respectively. The downscaled results based on TMPA and IMERG also eliminated the anomalies indicate that random forest was an effective way to improve the spatial resolutions with reasonable accuracy with systematic anomalies removed. The Relationships between the Spatial Resolutions and the Accuracies of the Precipitation Estimates against Ground Observations  
Though the accuracy of the precipitation estimates improved with the finer spatial resolutions, based on the statistical results presented in Tables 1 and 2 in this study, it did not mean that the finer the spatial resolution, the better the precision. While in [50], the performances of the satellite-based precipitation products were better with decreasing spatial resolutions, in Lower Colorado River Basin (LCRB). The relationships between the spatial resolutions and the accuracies of satellite-based products might be affected by the density of rain gauge networks. For instance, over regions like LCRB, there were dense rain gauge networks, which enabled it possible to conduct the detailed assessment of the performances of the IMERG products at various resolutions. While in TP, there are sparsely and poorly constructed rain gauge networks, which made it not suitable to do researches exploring the relationships between spatial resolutions and the accuracies of remote sensing products. Generally, to compare the difference between point-based measurements (from rain gauges) and gridded estimates, the precipitation estimates from gauges located in the same pixel should be averaged, and then compared with the corresponding pixel values. More gauges would be contained in one pixel after upscaling, and thus the estimate errors at each gauge might be neutralized or alleviated. This might be one of the possible reasons to explain why the performances of remote sensing products improved after spatial resolution degradation. Further studies should be conducted  
Figure 13: Comparison of mean monthly precipitation data of the anomalies covering inland water bodies in the downscaled results based on TMPA data (blue line) and the downscaled results based IMERG data (red line) with the data from seven rain gauge stations (black line). to investigate the relationships between the spatial resolutions and the accuracies of satellite-based products, especially over regions where gauge network is coarse.