## 3 Results
### Spatial Variability
#### 3.2.4 Gpm  
The daily precipitation estimates by the GPM had the highest correlation and Willmott coefficients and the lowest error in NXV (r = 0.59; d = 0.75; and RMSE = 9.17 mm day\({}^{-1}\)).  
Figure 8: Taylor diagrams showing the comparisons of (**A**) daily (mm day\({}^{-1}\)), (**B**) monthly (mm month\({}^{-1}\)), and (**C**) annual (mm year\({}^{-1}\)) measured and estimated precipitation, as well as (**D**) the performance diagram of the **TRMM** product at each of the weather stations in the state of Mato Grosso, Brazil. In panels (**A**–**C**), the Pearson correlation coefficient (r) was represented by the azimuth angle (black outlines), the RMSE was represented by the red dashed outlines, and the standard deviation (SD) was indicated by the x and y axes, respectively. In panel (**D**), the probability of detection (POD) is represented on the x and y axes; the BIAS was indicated by the dashed black lines; and the critical success index (CSI) was represented by continuous black lines. For (**A**), the daily values for the entire study period were averaged, while for (**B**), the total monthly values for all months during the study period were averaged, and the annual values in (**C**) were the annual values averaged for all years during the study period.  
The lowest correlation coefficients and the highest error in DMT (r = 0.39; d = 0.59; and RMSE = 12.74 mm day\({}^{-1}\)) (Figure 9A). In contrast, the monthly precipitation estimates had the highest correlation and Willmott coefficients with error in DMT (r = 0.95; d = 0.97; and RMSE = 37.35 mm month\({}^{-1}\)) (Figure 9B). The annual precipitation estimates had the highest correlation and Willmott coefficients in CBA (r = 0.99 and d = 0.87) and DMT (r = 0.90 and d = 0.94), and the lowest ones in PRR (r = 0.02) and PXR (r = 0.21) (Figure 9C).  
The best performance of the GPM in detecting the occurrence of daily precipitation events was in MTP as indicated by the categorical indices with CSI = 0.55, FAR = 0.03, BIAS = 0.58, and POD = 0.56 and the lowest was in PXR (CSI = 0.42, POD = 0.43, FAR = 0.03, and BIAS = 0.44) (Figure 9D).  
Figure 9: Taylor diagrams showing the comparisons of (**A**) daily (mm day\({}^{-1}\)), (**B**) monthly (mm month\({}^{-1}\)), and (**C**) annual (mm year\({}^{-1}\)) measured and estimated precipitation, as well as (**D**) the performance diagram of the **GPM** product at each of the weather stations in the state of Mato Grosso, Brazil. In panels (**A–C**), the Pearson correlation coefficient (r) was represented by the azimuth angle (black outlines), the RMSE was represented by the red dashed outlines, and the standard deviation (SD) was indicated by the x and y axes, respectively. In panel (**D**), the detection probability (POD) is represented on the x and y axes; the BIAS was indicated by the dashed black lines; and the critical success index (CSI) was represented by continuous black lines. For (**A**), the daily values for the entire study period were averaged, while for (**B**), the total monthly values for all months during the study period were averaged, and the annual values in (**C**) were the annual values averaged for all years during the study period.