No abstract

Extreme events have gained considerable scientific attention recently due to their potentially catastrophic impacts. Heat waves are thought to be more pronounced now in most parts of the world, and especially in South Asia, but doubts remain. The aim of this study is to calculate the frequency and intensity of heat waves in South Asia, focusing on Pakistan and identifying the regions within Pakistan that are most vulnerable to heat waves. Analyses have been performed both at provincial and country levels from 1961 to 2009. The provincial level analysis shows positive trends for heat waves of magnitudes ≥40°C and ≥45°C for 5 and 7 consecutive days. Events of magnitude ≥40°C and ≥45°C for 10 consecutive days also increased in frequency in Punjab, Sindh, and Balochistan. These regions are therefore considered to be the regions most vulnerable to heat wave events in Pakistan. The Balochistan region shows a consistently increasing trend throughout the study period, which may lead to more frequent drought in the future. The country level analysis indicates an increase in the frequency of 5 and 7 consecutive days heat waves at all defined temperature thresholds. The 10-days heat waves spells show a slight increase at ≥40°C and no significant change at ≥45°C. The Gilgit Baltistan and Azad Jammu & Kashmir areas reported no events at ≥45°C for 5, 7 and 10 continuous days. It is anticipated that with a long term rise in temperatures around the globe, heat waves will become more frequent and intense in all parts of the world, including Pakistan.

This research work is designed to carry out the annual and seasonal thermal classification of Pakistan to provide better understanding to all the stake holders like farmers and scientists etc for obtaining maximum crop yield. The data of Climatic Normal’s (1971-2000) has been used to calculate Thornthwaites’s Thermal efficiency index for thermal classification of Pakistan. The results of annual thermal classification reveals that Pakistan’s northern half experiences Tundra to Microthermal climate type and southern half experiences all types of Mesothermal to Megathermal climate type. Seasonal analysis showed large variations like in winters the whole country ranges from Microthermal to Frost Type of climate except the extremely southern parts of the country which have Mild Mesothermal climate. In spring the northern half of the country lies between Tundra to Microthermal climate and southern half from Mesothermal to Megathermal climate. During summer and monsoon majority of the regions in the country experience Megathermal except Northern areas which show Moderate Mesothermal to Mesothermal climate. The autumn season mostly have Mild Mesothermal to Tundra climate excluding southern half which showed Moderate Mesothermal to Mesothermal climate

Abstract. Southern Pakistan (Sindh) is one of the hottest regions in the world and is highly vulnerable to temperature extremes. In order to improve rural and urban planning, it is useful to gather information about the recurrence of temperature extremes. In this work, return levels of the daily maximum temperature T max are estimated, as well as the daily maximum wet-bulb temperature TW max extremes. We adopt the peaks over threshold (POT) method, which has not yet been used for similar studies in this region. Two main datasets are analyzed: temperatures observed at nine meteorological stations in southern Pakistan from 1980 to 2013, and the ERA-Interim (ECMWF reanalysis) data for the nearest corresponding locations. The analysis provides the 2-, 5-, 10-, 25-, 50-, and 100-year return levels (RLs) of temperature extremes. The 90 % quantile is found to be a suitable threshold for all stations. We find that the RLs of the observed T max are above 50 • C at northern stations and above 45 • C at the southern stations. The RLs of the observed TW max exceed 35 • C in the region, which is considered as a limit of survivability. The RLs estimated from the ERA-Interim data are lower by 3 to 5 • C than the RLs assessed for the nine meteorological stations. A simple bias correction applied to ERA-Interim data improves the RLs remarkably, yet discrepancies are still present. The results have potential implications for the risk assessment of extreme temperatures in Sindh.

No abstract