Evaluation of Gridded Precipitation Datasets over Arid Regions of Pakistan

Abstract

The rough topography, harsh climate, and sparse monitoring stations have limited hydro-climatological studies in arid regions of Pakistan. Gauge-based gridded precipitation datasets provide an opportunity to assess the climate where stations are sparsely located. Though, the reliability of these datasets heavily depends on their ability to replicate the observed temporal variability and distribution patterns. Conventional correlation or error analyses are often not enough to justify the variability and distribution of precipitation. In the present study, mean bias error, mean absolute error, modified index of agreement, and Anderson-Darling test have been used to evaluate the performance of four widely used gauge-based gridded precipitation data products, namely, Global Precipitation Climatology Centre (GPCC), Climatic Research Unit (CRU); Asian Precipitation Highly Resolved Observational Data Integration towards Evaluation (APHRODITE), Center for Climatic Research-University of Delaware (UDel) at stations located in semi-arid, arid, and hyper-arid regions in the Balochistan province of Pakistan. The result revealed that the performance of different products varies with climate. However, GPCC precipitation data was found to perform much better in all climatic regions in terms of most of the statistical assessments conducted. As the temporal variability and distribution of precipitation are very important in many hydrological and climatic applications, it can be expected that the methods used in this study can be useful for the better assessment of gauge-based data for various applications.

Precipitation Trends over the Indus Basin

“…Our comparison of precipitation data sets with station observations over the Indus basin suggests that GPCC is the best-performing long-term data set. Consistent with our study, Ahmed et al [82] found that, compared with other station-based gridded precipitation data sets, including APHRODITE V1101 and CRU, GPCC was better correlated with station data in arid southwestern Pakistan. Adnan et al [83] concluded that "GPCC data are very close to real-time station data and hence may be used in the absence of station data in Pakistan".…”

Analysis of Long-Term Trends of Annual and Seasonal Rainfall in the Awash River Basin, Ethiopia

“…Asfaw et al [17] also found that data from the CRU dataset did not follow the probability distribution of observed data over some locations in northern central Ethiopia. Ahmed et al [51] found that data from CRU datasets have shown similar distribution with observation data over some months and regions. However, the data have also shown different distribution with observation data over some other months and regions in Pakistan.…”

Uncertainty in Estimated Trends Using Gridded Rainfall Data: A Case Study of Bangladesh

“…A flowchart showing an overview of the methodology used in this study is presented in Figure 3. There are two general ways to compare gridded data with station observation: (i) areal average precipitation for each grid box is computed from available station data and then a grid-to-grid comparison is conducted; (ii) gridded data is interpolated to station location and then compared with observed data [1,10,33]. Both the methods were used in this study for the comparison of the performance of gridded data.…”