This study is based on both the recent and the predicted twenty first century climatic and hydrological changes over the mountainous Upper Indus Basin (UIB), which are influenced by snow and glacier melting. Conformal-Cubic Atmospheric Model (CCAM) data for the periods 1976-2035, 2041-2070, and 2071-2100 and Regional Climate Model (RegCM) data for the periods of 2041-2050 and 2071-2080 with RCP8.5 are used for climatic projection and, after bias correction, the same data are used as an input to the University of British Columbia (UBC) hydrological model for river flow projections. The projections of all of the future periods were compared with the results of 1976-2005 and with each other. Projections of future changes show a consistent increase in air temperature and precipitation. However, temperature and precipitation increase is relatively slow during 2071-2100 in contrast with 2041-2070. Northern parts are more likely to experience an increase in precipitation and temperature in comparison to the southern parts. A higher increase in temperature is projected during spring and winter over southern parts and during summer over northern parts. Moreover, the increase in minimum temperature is larger in both scenarios for all future periods. Future river flow is projected by both models to increase in the twenty first century (CCAM and RegCM) in both scenarios. However, the rate of increase is larger during the first half while it is relatively small in the second half of the twenty first century in RCP4.5. The possible reason for high river flow during the first half of the twenty first century is the large increase in temperature, which may cause faster melting of snow, while in the last half of the century there is a decreasing trend in river flow, precipitation, and temperature (2071-2100) in comparison to 2041-2070 for RCP4.5. Generally, for all future periods, the percentage of increased river flow is larger in winter than in summer, while quantitatively large river flow was projected, particularly during the summer monsoon. Due to high river flow and increase in precipitation in UIB, water availability is likely to be increased in the twenty first century and this may sustain water demands.

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Pakistan receives huge amount of rainfall during summer monsoon season that provides water replenishment for transition periods, helps in maintaining natural and anthropogenic ecosystems, and increased crop productivity. In this changing world, shifts in summer monsoon onset in Pakistan have been observed that seems to affect the society in general. Therefore, it is vital to address these summer monsoon onset shifts to help policy makings and implementation. The study was carried out to analyse the spatio-temporal variability in summer monsoon onset in four objectively defined regions covering all Pakistan. A total of 35 meteorological stations spreading over four regions (i.e., northern, central east, central west, and southern) were taken in to account and shifts in summer monsoon onset have been calculated for the period of 1971-2010. The analysis is based on the observational data of daily precipitation from 20th Jun-20th July for 40 years. The onset for each year and mean onset for each decade has been calculated for all stations. The data was analysed for homogeneity, spatial and temporal variability of monsoon rainfall has been calculated for all four regions, and station wise monsoon onset has been discussed in detail. The temporal analysis shows that the onset of monsoon has shift towards earlier onset from first week of July to last week of June at most of the stations in which the investigation was carried out during the studied period. The spatial analysis shows that the amount of monsoon precipitation during the onset period has decreased after 1970's in almost all regions. This variability in monsoon onset can have major impacts on rain fed agriculture and cultivation of crops like maize, soybean, rice and sugarcane etc. and will have to revisit the cropping calendar. Keywords Monsoon onset. Spatial variability. Temporal variability. Asian summer monsoon. Monsoon shifts Highlights 1-Observations at 35 meteorological stations were processed for summer monsoon onset in Pakistan 2-Temporal analysis of four decades i.e., 1971-2010 3-Mean monsoon onset has observed a shift over 40 years to an earlier time in Pakistan 4-Total amount of precipitation has decreased over the studied period 5-North eastern region of Pakistan received highest amount of precipitation among all others Responsible Editor: Ashok Karumuri.

In this study, an ensemble of statistically downscaled 14 multi-global climate models for RCP4.5 and RCP8.5 emission scenarios was employed to implement a comprehensive assessment of climate change impacts over Pakistan in order to identify the future hotspots cities in terms of changes in temperature and precipitation. The analyses focused on the minimum, maximum and average temperature and precipitation in three time-slices: 2006-2035, 2041-2070, and 2071-2,100. Average temperature is projected to increase by 2.6 C under RCP4.5 while 5.1 C under RCP8.5 by the end of this century with the north side of Pakistan (mainly over North Pakistan-NP, Monsoon Region-MR and Khyber Pakhtunkhwa-KP) presenting the highest changes in the temperatures. Wetter conditions are expected in the future over Pakistan, mainly over the MR. In general, air temperature and precipitation showed linear positive correlation over Pakistan in both RCP scenarios. Hotspot cities where extreme climate, that is, the hottest, dryer and wetter, exists were also identified. Hyderabad will likely become the hottest city of Pakistan by end century with the highest average temperature reaching 29.9 C under RCP4.5 and 32.0 C under RCP8.5 followed by Jacobabad, Bahawalnagar, and Bahawalpur. Most of the hottest cities are detected in areas on the southern side of Pakistan. On the other hand, the wettest cities, Murree, Balakot and Muzaffarabad, are located in the MR. Dry conditions are likely to be prevalent in Dalbandin followed by Khanpur and Jacobabad under both RCPs. The uncertainties of the projections were also evaluated. For precipitation, for example, there are a large number of outliers indicating the high variability/uncertainties of the projections. These uncertainties are clearer when the probability density functions are analysed for individual sub-domains in Pakistan.