## 4 Results
### Comparison on an Interannual Scale for Different Seasons  
To assess long term variation, GPPs and in-situ precipitation datasets were further compared on an interannual scale for different seasons. In Figure 8, during winter, MSWEP produced R values of \(\leq\)0.20 in the northern parts of the study area, while in the central and southern parts of the study area relatively higher R values of \(\geq\)0.40 and \(\geq\)0.80 can be seen, respectively. CHIRPS, PERISANN-CDR and TMPA have shown relatively similar precipitation variations as those of in-situ precipitation. The R values for CHIRPS, PERISANN-CDR and TMPA were in the range of \(\geq\)0.80 in the north and \(\geq\)0.60 in central and southern regions, suggesting that these three products had similar dynamics for producing winter precipitation over the different parts of the study area. During the pre--monsoon season, MSWEP performance in depicting precipitation was similar to its winter performance, with low R values in the north (\(\leq\)0.60) and high values in central (\(\geq\)0.60) and southern (\(\leq\)0.80) regions. CHIRPS and PERISANN-CDR were less effective at capturing precipitation  
Figure 8: Interannual correlation of in-situ and GPPs precipitation for different seasons. variability. For TMPA there were also low R values in the north, while in the central and southern regions R values were observed to be \(\geq\)0.80 for most stations. In the monsoon season, MSWEP reached a higher level of agreement \(\geq\) 0.80 in the southern and eastern parts of the study region. The CHIRPS precipitation product clearly indicated a monsoonal precipitation pattern, with large R values of \(\geq\)0.60 to 0.80 in the monsoon regions. The interannual monsoon precipitation variability was well captured by PERSIANN-CDR, with high R (0.80) values. For monsoonal precipitation, TMPA outperformed all GPPs with R values of \(\geq\) 0.80 in all parts of the study region under monsoon influence. In autumn, there was an obvious pattern in the R values, with higher values in the north and south, while central regions had relatively low R values. Both MSWEP and TMPA had similar R values of \(\geq\)0.80 in these regions, while CHIRPS and PERSIANN-CDR also produced a similar pattern; however, their R value of \(\geq\)0.60 were lower than that of MSWEP and TMPA. The precipitation seasons of the study regions are determined by the westerly disturbances that are mostly active during the winter/cold season and the pre--monsoon and monsoonal precipitation during warm summer season [14]. There were stronger correlations between the GPPs and in-situ in the cold season, while in the monsoon season MSWEP and TMPA produced higher R values than CHIRPS and PERSIANN-CDR. The strength of the correlation varied with magnitude in precipitation during different seasons, however orographic influence is also obvious in the boundary regions of low lands and high terrain and thus need to be further investigated. The RMSD values (Figure 9) shows a decreasing tendency from the north of the country towards the south. In winter, MSWEP had the highest RMSD values of \(>\)16 to \(<\)32 mm in the northwest, which persisted at all stations located in the northern region of the study area. In the central and southern parts of the country, the RMSD was less than 10 mm. CHIRPS and PERSIANN-CDR had slightly higher RMSD values in the northern parts of the region, ranging from 10 mm to \(<\) 30 mm among the different stations. In central and southern areas, RMSD values were consistent with those of MSWEP, with a magnitude of around 10 mm. TMPA followed the same pattern of RMSD values as observed for MSWEP, with higher values in northern parts but these values were smaller than those of MSWEP, CHIRPS and PERSIANN-CDR. In the pre--monsoon season, MSWEP had a high RMSD of \(>\)20 mm for stations located in northern regions, CHIRPS and PERSIANN--CDR produced the same pattern as MSWEP, with relatively low values in southern parts of the study region, while TMPA produced smaller RMSD values than rest of the GPPs.