# The Spatiotemporal Variability of Temperature and Precipitation Over the Upper Indus Basin:
## 3 Results
### Station-averaged Precipitation Trends  
This section describes the extent to which WRF was accurate in reproducing the spatio-temporal variability of precipitation in the three domains. The annual and seasonal mean precipitation trends for WRF, TRMM, and station data for all domains are shown in Figure 2. In addition, the Pearson correlation coefficient was computed between WRF and both observed datasets. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Station** & **Lat** & **Lon** & **Station Elevation (m)** & **Data** & **Data Range** & **Source** \\ \hline Astore & 35.33 & 74.90 & 2168 & P, T & 2000–2014 & PMD \\ Bunji & 35.67 & 74.63 & 1372 & P, T & 2000–2014 & PMD \\ Chillas & 35.42 & 74.10 & 1250 & P, T & 2000–2014 & PMD \\ Chitral & 35.85 & 71.83 & 1497 & P, T & 2000–2014 & PMD \\ Gilgit & 35.92 & 74.33 & 1460 & P, T & 2000–2014 & PMD \\ Gupis & 36.17 & 73.40 & 2156 & P, T & 2000–2014 & PMD \\ Hunza & 36.32 & 74.65 & 2156 & P, T & 2007–2014 & PMD \\ Skardu & 35.30 & 75.68 & 2317 & P, T & 2000–2014 & PMD \\ Khunjerab & 36.85 & 75.40 & 4707 & P, T & 2000–2015 & WAPDA \\ Rama & 35.36 & 74.81 & 3140 & P, T & 2000–2012 & WAPDA \\ Rattu & 35.15 & 74.82 & 2920 & P, T & 2000–2015 & WAPDA \\ Ushkore & 36.03 & 73.40 & 3353 & P & 2000–2015 & WAPDA \\ Yasin & 36.37 & 73.30 & 3353 & P & 2000–2015 & WAPDA \\ Ziarat & 36.83 & 74.42 & 3688 & P & 2000–2015 & WAPDA \\ Naltar & 36.13 & 74.18 & 2810 & P & 2000–2015 & WAPDA \\ Ganji & 35.45 & 74.31 & 1576 & P & 2000–2015 & WAPDA \\ Daggar & 34.51 & 72.49 & 732 & P & 2005–2015 & WAPDA \\ Kachura & 35.45 & 75.42 & 2340 & P & 2005–2015 & WAPDA \\ Kandia & 35.47 & 73.15 & 858 & P & 2005–2015 & WAPDA \\ Karimabad & 36.33 & 74.70 & 3048 & P & 2005–2015 & WAPDA \\ Phulra & 34.31 & 73.08 & 915 & P & 2005–2015 & WAPDA \\ Yugo & 35.18 & 76.10 & 2469 & P & 2005–2015 & WAPDA \\ Besham Qila & 34.93 & 72.88 & 580 & P & 2005–2015 & WAPDA \\ \hline \hline \end{tabular}
\end{table} 
Table 2: PMD stations, their locations, elevation, and the respective domain. PMD, Pakistan Meteorological Department; WAPDA, Water and Power Development Authority. P and T represent precipitation and average temperature, respectively. There were twenty-three stations (given at Table 2) operated by PMD and WAPDA above Tarbella Reservoir, and WRF and TRMM data were interpolated at these stations. When WRF, TRMM, and gauge data at these stations were averaged and compared in d01, WRF tended to overpredict the total annual precipitation relative to TRMM (115%) and the gauge data (132%) (left column, Figure 2). In addition, the results showed that the winter season had more bias (PBIAS--206%; RMSE--214 mm) and the summer season had less bias (PBIAS--70%; RMSE--91 mm) to the stations' data in the outer domain. For seasonal precipitation variation from 2001 to 2015, WRF showed a positive correlation with TRMM and station data for all seasons (Table 3). Similarly, WRF annual precipitation was significantly correlated with TRMM and gauge data (\(p<0.05\)). However, trend analyses for WRF, TRMM, and gauge stations located in d01 did not show any statistically significant trends except the summer season, where station data showed a statistically significant trend. Moreover, the annual TRMM showed a statistically significant trend. Figure 2: Time series comparisons between WRF (red), TRMM (green), and the mean of stations (“observed”; blue) for Domain 01 (d01; left column), Domain 02 (d02; middle column), and Domain 03 (d03; right column). From top to bottom, the five rows correspond to winter (DJF), spring (MAM), summer (JJA), autumn (SON), and annual. The straight lines are least-squares linear regressions. When WRF and TRMM data were interpolated at the twenty-three gauge locations in d02 and compared, WRF still overpredicted total annual precipitation compared with the TRMM (35%) and gauge data (45%) (middle column, Figure 2). In addition, the results showed that the winter season had more bias (73%) and the summer season had less bias (3%) to the stations' data in the middle domain.