# Comparisons of Spatially Downscaling TMPA and IMERG over the Tibetan Plateau
## 3 Results
### Downscaled Results and Validations Using Ground Observations  
The annual downscaled results at 1 km resolution using random forest models based on TMPA and IMERG data were presented in Figure 9b,c, respectively. We additionally obtained the downscaled results at 0.1\({}^{\circ}\) based on TMPA which was displayed in Figure 9a. Both the downscaled results based on TMPA and IMERG captured the spatial distribution of annual precipitation compared to the original TMPA, original IMERG and gauge precipitation, showing a decreasing trend from south to north, and from west to east. It was notable that the downscaled results based TMPA data shown contiguous precipitation map with anomalies removed which appeared in the original TMPA data, in western and northern parts of the TP. The downscaled results based on IMERG data still displayed continuous variation and gradual trend without outliers. The performances of the downscaled results were validated against ground observations. Both the downscaled results still overestimated precipitation compared to ground observations but in lower degrees with reduced positive bias. The values of MAE and RMSE also decreased and R\({}^{2}\) values increased in the downscaled results compared with the corresponding satellite products indicating the improved accuracy of downscaled results. Figure 10a shown the validation of the downscaled results based on TMPA data at 10 km resolution, while Figure 10b,c shown the validations  
Figure 9: Spatial distribution of precipitation maps generated from (**a**) downscaled results based on TMPA data at 0.1\({}^{\circ}\), (**b**) downscaled results based on TMPA data at 1 km and (**c**) downscaled results based on IMERG data at 1 km, over the TP in 2015.  
of the downscaled results based on TMPA and IMERG data at 1 km, respectively, against ground observations. The downscaled results based on IMERG at 1 km had the best performance (R\({}^{2}\)\(\sim\) 0.86, bias \(\sim\) 7.73%) among the three downscaled results based on TMPA and IMERG data and shown improved accuracy compared with the original IEMRG data (R\({}^{2}\) - 0.74, bias \(\sim\) 12.23%). The downscaled results based on TMPA at 1 km and at 1 km also shown improvements compared with the original TMPA data (R\({}^{2}\)\(\sim\) 0.67, bias \(\sim\) 22.40%), while the downscaled results based on TMPA at 1 km (R\({}^{2}\)\(\sim\) 0.82, bias \(\sim\) 11.63%) performed better that the downscaled results at 10 km resolution based on TMPA data (R\({}^{2}\)\(\sim\) 0.77, bias \(\sim\) 14.13%). Regrading to the comparison between the original IMERG data and the downscaled results based on TMPA at 10 km resolution, their performances were remarkably close compared to ground observations with R\({}^{2}\) - 0.75 and bias \(\sim\) 13%. Based on the disaggregation algorithm introduced in Section 3.3, the monthly downscaled results based on TMPA and IMERG were obtained. Table 2 presented the statistical results at monthly scale. The downscale results based on IMERG at 1 km shown the best accuracy at monthly scale with R\({}^{2}\)\(\sim\) 0.82 and bias \(\sim\) 7% during wet seasons and R\({}^{2}\)\(\sim\) 0.62 and bias \(\sim\) 10% during dry seasons. The downscaled results based on TMPA at 1 km also corresponded well with ground observations during wet seasons (R\({}^{2}\)\(\sim\) 0.79 and bias \(\sim\) 10%) and shown relatively poorer performance during dry seasons (R\({}^{2}\)\(\sim\) 0.58 and bias \(\sim\) 15%). Regrading to the downscaled results based on TMPA at 10 km resolution, the performance was equivalent to the original IMERG data at 10 km but better than the original TMPA data at 0.25\({}^{\circ}\). Generally, the accuracy of the downscaled results based on TMPA and IMERG performed better than those of the original satellite-based precipitation products, in each month.