The performance of general circulation models (GCMs) in a region are generally assessed according to their capability to simulate historical temperature and precipitation of the region. The performance of 31 GCMs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) is evaluated in this study to identify a suitable ensemble for daily maximum, minimum temperature and precipitation for Pakistan using multiple sets of gridded data, namely: Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Berkeley Earth Surface Temperature (BEST), Princeton Global Meteorological Forcing (PGF) and Climate Prediction Centre (CPC) data. An entropy-based robust feature selection approach known as symmetrical uncertainty (SU) is used for the ranking of GCM. It is known from the results of this study that the spatial distribution of best-ranked GCMs varies for different sets of gridded data. The performance of GCMs is also found to vary for both temperatures and precipitation. The Commonwealth Scientific and Industrial Research Organization, Australia (CSIRO)-Mk3-6-0 and Max Planck Institute (MPI)-ESM-LR perform well for temperature while EC-Earth and MIROC5 perform well for precipitation. A trade-off is formulated to select the common GCMs for different climatic variables and gridded data sets, which identify six GCMs, namely: ACCESS1-3, CESM1-BGC, CMCC-CM, HadGEM2-CC, HadGEM2-ES and MIROC5 for the reliable projection of temperature and precipitation of Pakistan.

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.

The presence of long‐term persistence (LTP) in hydroclimatic time series can lead to considerable change in the significance of trend. Therefore, past findings of climatic trend analysis without considering LTP in time series has become a disputable issue. The objective of this study was to assess the spatial patterns in the trends of annual and seasonal rainfall amounts and extremes in Peninsular Malaysia considering LTP. Daily rainfall data of APHRODITE (Asian Precipitation – Highly‐Resolved Observational Data Integration Towards Evaluation) for the period 1951–2007 was used to assess the trends using the classical Mann–Kendall (MK) test and the modified version of the MK test, which can remove the influence of LTP in the significance of trends. The results indicate that significant trends in different rainfall indices of Peninsular Malaysia obtained using the MK test reduced drastically when LTP was taken into consideration. There was almost no change in annual and seasonal rainfall amounts, which contradicts the findings of previous studies. The field significance of regional trends revealed an increase in wet spells at an average rate of 4.8 and 4.9 days/decade in the southeast and the southwest respectively during the northeast monsoon, and a decrease in rainy days by −1.4 days/decade in the north and an increase both in dry spells by 1.0 day/decade in the southeast and in the maximum 1 day rainfall by 1.7 mm/decade on the west coast during the southwest monsoon. The results indicate that the trends in rainfall indices reported in the maritime continent in previous studies should be re‐evaluated as most of them are due to LTP.