• Energy Research

AbstractGlaciers in the northern Pakistan are a distinctive source of freshwater for the irrigation, drinking and industrial water supplies of the people living in those regions and downstream. These glaciers are under a direct global warming impact as indicated in many previous studies. In this study, we estimated the glacier dynamics in terms of Equilibrium Line Altitude (ELA), mass balance and the snout position variation using remote sensing data between 2001 and 2018. Six glaciers, having area ≥ 20 km2 each, situated in the Chitral region (Hindukush Mountains) were investigated in this study. Digital Elevation Model (DEM) and available cloud-free continuous series of Landsat and Sentinel the entire study area was a retreat of -231 ± 140 m. No obvious relationship was found between the glacier variation trends and the available gauged climatic data possibly due to the presence of debris cover in ablation zones of all the studied glaciers which provides insulation and reduces the immediate climatic effects.

Climate change has a significant impact on the intensity and spread of dengue outbreaks. The objective of this study is to assess the number of dengue transmission suitable days (DTSD) in Pakistan for the baseline (1976-2005) and future (2006-2035, 2041-2070, and 2071-2099) periods under Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios. Moreover, potential spatiotemporal shift and future hotspots of DTSD due to climate change were also identified. The analysis is based on fourteen CMIP5 models that have been downscaled and bias-corrected with quantile delta mapping technique, which addresses data stationarity constraints while preserving future climate signal. The results show a higher DTSD during the monsoon season in the baseline in the study area except for Sindh (SN) and South Punjab (SP). In future periods, there is a temporal shift (extension) towards pre- and post-monsoon. During the baseline period, the top ten hotspot cities with a higher frequency of DTSD are Karachi, Hyderabad, Sialkot, Jhelum, Lahore, Islamabad, Balakot, Peshawar, Kohat, and Faisalabad. However, as a result of climate change, there is an elevation-dependent shift in DTSD to high-altitude cities, e.g. in the 2020s, Kotli, Muzaffarabad, and Drosh; in the 2050s, Garhi Dopatta, Quetta, and Zhob; and in the 2080s, Chitral and Bunji. Karachi, Islamabad, and Balakot will remain highly vulnerable to dengue outbreaks for all the future periods of the twenty-first century. Our findings also indicate that DTSD would spread across Pakistan, particularly in areas where we have never seen dengue infections previously. The good news is that the DTSD in current hotspot cities is projected to decrease in the future due to climate change. There is also a temporal shift in the region during the post- and pre-monsoon season, which provides suitable breeding conditions for dengue mosquitos due to freshwater; therefore, local authorities need to take adaption and mitigation actions.

In the present study, hydro-meteorological variables of Chitral Basin in Hindukush region of Pakistan were studied to predict the changes in climatic components such as temperature, precipitation, humidity and river flow based on observed data from 1990 to 2019. Uncertainties in climate change projection were studied using various statistical methods, such as trend variability analysis via stationarity test and validation of regression assumptions prior to fitting of regression estimates. Also, multiple regression models were estimated for each hydro-meteorological variables for the given 30 years of observed data. Results demonstrated that temperature and, precipitation were inversely related with one another. It was observed from the regression model that temperature is decreases by 0.309 °C on the average increases in precipitation by one unit. Temperature also decreases for the increase in humidity by average 0.086 °C. Since, precipitation is negatively related with temperature, thus for increases in temperature the annual precipitation decreases by 0.278 mm annually. Humidity on the other hand, increases by 0.207% by increasing in precipitation and the temperature that causes humidity to decrease by 0.99%. Thus, it demonstrated that the flow in Chitral river increases due to precipitation by 0.306 m3/s for the change in precipitation by one unit. Findings from the present study negated the general perceptions that flow in the Chitral river has increased due to recession of glaciers with increase in the intensity of temperature.

AbstractMany efforts have been made by the scientific community to produce gridded datasets with high spatial resolution because they are essential for climate change assessment, impact studies, decision‐making, etc. This study fits into this context and describes the methods used to prepare a 5‐km gridded product of precipitation and minimum and maximum temperatures by merging observed data from meteorological stations, from 1981 to 2016, of Bangladesh, Nepal, and Pakistan with ERA5 reanalysis. The step‐by‐step methods for station data quality control and the development of the 5‐km gridded data are presented. Additionally, we use the 5‐km dataset to show the main climate features of the three countries, which facilitate comparison with other data sources in the literature.

Climate extremes, such as heat waves, droughts, extreme rainfall can lead to harvest failures, flooding and consequently threaten the food security worldwide. Improving our understanding about climate extremes can mitigate the worst impacts of climate change and extremes. The objective here is to investigate the changes in climate and climate extremes by considering two time slices (i.e., 1962–1990 and 1991–2019) in all climate zones of Pakistan by utilizing observed data from 54 meteorological stations. Different statistical methods and techniques were applied on observed station data to assess changes in temperature, precipitation and spatio-temporal trends of climatic extremes over Pakistan from 1962 to 2019. The Mann-Kendal test demonstrated increasing precipitation (DJF) and decreasing maximum and minimum temperatures (JJA) at the meteorological stations located in the Karakoram region during 1962–1990. The decadal analysis, on the other hand, showed a decrease in precipitation during 1991–2019 and an increase in temperature (maximum and minimum) during 2010–2019, which is consistent with the recently observed slight mass loss of glaciers related to the Karakoram Anomaly. These changes are highly significant at 5% level of significance at most of the stations. In case of temperature extremes, summer days (SU25) increased except in zone 4, TX10p (cold days) decreased across the country during 1962–1990, except for zones 1 and 2. TX90p (warm days) increased between 1991–2019, with the exception of zone 5, and decreased during 1962–1990, with the exception of zones 2 and 5. The spatio-temporal trend of consecutive dry days (CDD) indicated a rising tendency from 1991 to 2019, with the exception of zone 4, which showed a decreasing trend. PRCPTOT (annual total wet-day precipitation), R10 (number of heavy precipitation days), R20 (number of very heavy precipitation days), and R25mm (very heavy precipitation days) increased (decreased) considerably in the North Pakistan during 1962–1990 (1991–2019). The findings of this study can help to address some of the sustainable development goals related climate action, hunger and environment. In addition, the findings can help in developing sustainable adaptation and mitigation strategies against climate change and extremes. As the climate and extremes conditions are not the uniform in all climate zone, therefore, it is suggested to the formers and agriculture department to harvest crops resilient to the climatic condition of each zone. Temperature has increasing trend in the northern Pakistan, therefore, the concerned stakeholders need to make rational plans for higher river flow/flood situation due to snow and glacier melt.

La zone d'étude comprenant le Pakistan est répartie en cinq zones climatiques homogènes. Une approche intégrée en cinq étapes a été utilisée pour l'analyse extrême du climat zonal. Sept des treize modèles climatiques mondiaux (MCG) les plus appropriés ont été sélectionnés en utilisant la probabilité d'inclusion postérieure dans l'approche de calcul de la moyenne du modèle bayésien. La sortie des GCM sélectionnés est ensuite réduite à l'aide d'une réduction d'échelle statistique. Les extrêmes climatiques sont projetés pour la période de référence et les périodes futures. Une analyse de la tendance spatio-temporelle et de la signification statistique a été effectuée pour les extrêmes climatiques. La plupart des extrêmes climatiques ont des tendances hétérogènes pour les précipitations sous RCP4.5 et RCP8.5. Les tendances à la hausse des extrêmes climatiques sont notées dans la région du nord, la région de la mousson et le sud-ouest du Pakistan. Une tendance à la hausse significative est observée dans TMAXmean et TMINmean à travers le pays. Les TN10P (nuits fraîches) et TX10P (jours frais) ont des tendances à la baisse à l'avenir pour la plupart des GCM à travers le pays pour RCP4.5 et RCP8.5. En revanche, TN90P (nuits chaudes) et TX90P (journées chaudes) ont des tendances à la hausse pour tous les GCM à l'avenir dans les deux scénarios. Pour RCP8.5, les températures extrêmes ont considérablement augmenté, sauf TN10P et TX10P, ce qui indique une tendance à la baisse significative. Il y a une augmentation notable du nombre de jours d'été à l'avenir dans les deux scénarios. El área de estudio que comprende Pakistán se distribuye en cinco zonas climáticas homogéneas. Se ha utilizado un enfoque integrado de cinco pasos para el análisis extremo del clima zonal. Siete de los trece modelos climáticos globales (GCM) más apropiados se seleccionaron utilizando la probabilidad de inclusión posterior en el enfoque de promediado del modelo bayesiano. A continuación, se reduce la escala de salida de los GCM seleccionados utilizando una reducción de escala estadística. Los extremos climáticos se proyectan para la línea de base y periodos de tiempo futuros. Se realizaron análisis de tendencia espacio-temporal y significación estadística para los extremos climáticos. La mayoría de los extremos climáticos tienen tendencias heterogéneas para la precipitación bajo RCP4.5 y RCP8.5. Las tendencias crecientes en el clima extremo se observan en la región norte, la región del monzón y las partes suroccidentales de Pakistán. Se observa una tendencia significativamente creciente en TMAXmean y TMINmean en todo el país. TN10P (noches frescas) y TX10P (días frescos) tienen tendencias decrecientes en el futuro para la mayoría de los GCM en todo el país para RCP4.5 y RCP8.5. Por el contrario, TN90P (noches cálidas) y TX90P (días cálidos) tienen tendencias crecientes para todos los mcg en el futuro en ambos escenarios. Para RCP8.5, las temperaturas extremas han aumentado significativamente, excepto que TN10P y TX10P indican tendencias significativamente decrecientes. Hay un aumento notable en el número de días de verano en el futuro en ambos escenarios. The study area comprising Pakistan is distributed in five homogeneous climatic zones. An integrated five step approach has been used for zonal climate extreme analysis. Seven out of thirteen most appropriate Global Climate Models (GCMs) were selected using Posterior Inclusion Probability in the Bayesian model averaging approach. The output of selected GCMs is then downscaled using statistical downscaling. Climate extremes are projected for the baseline and future time periods. Spatio-temporal trend and statistical significance analysis were performed for climate extremes. Most of the climate extremes have heterogeneous trends for the precipitation under RCP4.5 and RCP8.5. The increasing trends in climate extreme are noted in the northern region, monsoon region, and south-west parts of Pakistan. Significantly increasing trend is observed in TMAXmean and TMINmean across the country. TN10P (Cool nights) and TX10P (Cool days) have decreasing trends in the future for most of the GCMs across the country for RCP4.5 and RCP8.5. In contrast, TN90P (warm nights) and TX90P (warm days) have increasing trends for all GCMs in future under both scenarios. For RCP8.5, temperature extremes have significantly increased except TN10P and TX10P indicating significantly decreasing trends. There is notable increase in the number of summer days in future under both scenarios. تتوزع منطقة الدراسة التي تضم باكستان في خمس مناطق مناخية متجانسة. تم استخدام نهج متكامل من خمس خطوات لتحليل المناخ المتطرف في المناطق. تم اختيار سبعة من أصل ثلاثة عشر نموذجًا للمناخ العالمي الأكثر ملاءمة (GCMs) باستخدام احتمالية الشمول الخلفي في نهج متوسط النموذج البايزي. ثم يتم تصغير نطاق مخرجات GCMs المختارة باستخدام تصغير النطاق الإحصائي. من المتوقع حدوث تطرف مناخي لخط الأساس والفترات الزمنية المستقبلية. تم إجراء تحليل للاتجاه المكاني والزماني والأهمية الإحصائية للظواهر المناخية المتطرفة. معظم الظواهر المناخية المتطرفة لها اتجاهات غير متجانسة لهطول الأمطار بموجب RCP4.5 و RCP8.5. لوحظت الاتجاهات المتزايدة في المناخ المتطرف في المنطقة الشمالية والمنطقة الموسمية والأجزاء الجنوبية الغربية من باكستان. لوحظ اتجاه متزايد بشكل كبير في TMAXmean و TMINmean في جميع أنحاء البلاد. لدى TN10P (الليالي الباردة) و TX10P (الأيام الباردة) اتجاهات متناقصة في المستقبل لمعظم GCMs في جميع أنحاء البلاد لـ RCP4.5 و RCP8.5. على النقيض من ذلك، فإن TN90P (الليالي الدافئة) و TX90P (الأيام الدافئة) لهما اتجاهات متزايدة لجميع GCMs في المستقبل في ظل كلا السيناريوهين. بالنسبة لـ RCP8.5، ارتفعت درجات الحرارة القصوى بشكل كبير باستثناء TN10P و TX10P مما يشير إلى انخفاض كبير في الاتجاهات. هناك زيادة ملحوظة في عدد أيام الصيف في المستقبل في ظل كلا السيناريوهين.

Pakistan is amongst the most water-stressed countries in the world, with changes in the frequency of extreme events, notably droughts, under climate change expected to further increase water scarcity. This study examines the impacts of climate change and anthropogenic activities on the runoff of the Kunhar River Basin (KRB) in Pakistan. The Mann Kendall (MK) test detected statistically significant increasing trends in both precipitation and evapotranspiration during the period 1971–2010 over the basin, but with the lack of a statistically significant trend in runoff over the same time-period. Then, a change-point analysis identified changes in the temporal behavior of the annual runoff time series in 1996. Hence, the time series was divided into two time periods, i.e., prior to and after that change: 1971–1996 and 1997–2010, respectively. For the time-period prior to the change point, the analysis revealed a statistically significant increasing trend in precipitation, which is also reflected in the runoff time series, and a decreasing trend in evapotranspiration, albeit lacking statistical significance, was observed. After 1996, however, increasing trends in precipitation and runoff were detected, but the former lacked statistical significance, while no trend in evapotranspiration was noted. Through a hydrological modelling approach reconstructing the natural runoff of the KRB, a 16.1 m3/s (or 15.3%) reduction in the mean flow in the KRB was simulated for the period 1997–2010 in comparison to the period 1971–1996. The trend analyses and modeling study suggest the importance of anthropogenic activities on the variability of runoff over KRB since 1996. The changes in streamflow caused by irrigation, urbanization, and recreational activities, in addition to climate change, have influenced the regional water resources, and there is consequently an urgent need to adapt existing practices for the water requirements of the domestic, agricultural and energy sector to continue being met in the future.

Global temperature has been increasing at unprecedented rates during the Anthropocene, impacting both natural and human systems. Alpine biomes, among the most sensitive natural ecosystems to climate warming, show rapid shifts of species distribution ranges and modulations of species interactions. The Himalayas (also known as the "water tower" of Asia and a global biodiversity hot spot) are highly sensitive and vulnerable to global warming as this is one of the fastest-warming regions in the world. Such rapid warming is expected to trigger upward shifts of alpine vegetation, because cold temperature limitations on growth and recruitment are being alleviated. However, increasing drought stress may dampen or even reverse this positive response of alpine ecosystems to warming climate. In addition, interactions between alpine plants co-determine the structure and function of subnival vegetation, and thereby stabilize their distribution range