Climate change and spatio-temporal trend analysis of climate extremes in the homogeneous climatic zones of Pakistan during 1962-2019

Fig 12 shows decreasing trend in precipitation extremes except CDD and WSDI in western and eastern parts. However, CWD, R10mm, R20mm, R25mm, R95 have increasing trends while CWD and PRECPTOT show decreasing trends in the eastern-central Karakoram. 5. Discussion Zone 1 is rich with water resources (snow and glaciers). Therefore, the changes in climate and climate extremes may have significant impacts on water availability in dry summers, the fre- quency of flooding, and Glacier Lake Outburst Floods (GLOFs) in the future. Zone 2 comprise Monsoon dominated region receiving more than 60% precipitation during Monsoon season [77–79]. The seasonal changes in precipitation and temperature may affect the demand and supply of water and ultimately the crop’s production. In addition, Zone 3 is the south-west part of Pakistan receiving low amount of rainfall round the year. Precipitation extremes may contribute less to cause flooding in the region. Zone 4 faces shortage of rainfall and have severe rainfall decrease, which can further exacerbate the shortage of water for drinking, agriculture and other purposes. Zone 5 is mainly comprised of Punjab province dominating the agricul- ture production of the country. According to our results, R99P has increasing trend in this region with the likelihood of intense rainfall and may cause flash flooding in the future. As UIB is melt water dominated, therefore, the latest information of the cryosphere is important. In addition, changes in climate variables can significantly affect downstream

Table 6. Seasonal MK test results in the Karakoram region for precipitation. The table shows the Kendall τ and their significance for the 1990–1999, 2000–2009 and 2010–2019. Station DJF MAM JJA SON Station Kendall τ P-Value Kendall τ P-Value Kendall τ P-Value Kendall τ P-Value Precipitation (1990–1999) Astore -6.75e-02 0.007 -1.06e-02 0.663 -2.46e-02 0.327 -2.40e-02 0.357 Bunji 4.34e-02 0.104 8.94e-02 0.000 4.04e-02 0.121 4.50e-02 0.091 Chilas 4.21e-02 0.114 4.48e-03 0.862 1.66e-02 0.524 1.16e-03 0.965 Darosh -9.16e-0 0.000 -3.57e-02 0.140 2.14e-03 0.934 9.95e-03 0.702 Gilgit 2.46e-02 0.351 2.67e-02 0.289 6.03e-02 0.018 -1.62e-02 0.539 Gopis -1.62e-03 0.951 4.77e-02 0.069 6.50e-02 0.014 -6.71e-02 0.012 Skardu -3.37e-02 0.190 3.81e-02 0.133 7.15e-02 0.006 6.41e-02 0.016 Precipitation (2000–2009) Astore -5.21e-02 0.044 -1.02e-01 5.227e-05 -4.62e-02 0.068 -3.80e-02 0.146 Bunji 3.58e-02 0.180 -1.20e-02 0.645 2.65e-02 0.307 -3.15e-02 0.236 Chilas 1.22e-01 4.14e-06 4.03e-02 0.118 1.13e-01 1.52e-05 5.52e-02 0.038 Darosh 6.47e-02 0.011 2.31e-02 0.355 -5.41e-02 0.038 -3.77e-02 0.147 Gilgit 6.84e-02 0.009 1.31e-02 0.608 -3.86e-02 0.127 -2.61e-03 0.921 Gopis 5.69e-02 0.033 -3.12e-02 0.234 -8.10e-02 0.002 -6.50e-02 0.015 Skardu 5.38e-02 0.037 -1.41e-02 0.584 -2.92e-02 0.254 8.34e-04 0.975 Precipitation (2010–2019) Astore -1.30e-01 7.53e-06 1.34e-03 0.961 -6.15e-03 0.828 -3.59e-02 0.219

Bunji -3.37e-03 0.910 -7.70e-03 0.787 -1.60e-02 0.574 -2.59e-02 0.379 Chilas 1.57e-01 9.5e-08 -3.05e-02 0.286 -1.18e-02 0.683 -9.35e-02 0.001 Darosh 6.88e-03 0.812 -1.27e-02 0.646 -1.95e-02 0.502 -4.89e-02 0.095 Gilgit -1.03e-02 0.728 -3.62e-03 0.898 -2.35e-02 0.401 -6.59e-02 0.023 Gopis 4.52e-03 0.881 7.16e-02 0.014 6.73e-03 0.818 -7.48e-03 0.802 Skardu -1.54e-01 1.98e-07 1.26e-02 0.66 4.69e-02 0.102 -2.52e-02 0.395 https://doi.org/10.1371/journal.pone.0271626.t006 PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 18 / 27

water’s availability for millions of inhabitants [44,80]. Most of the HKHs’ glaciers are retreating since the mid-19th century [41,42,81]. In addition, some recent studies found that mass bal- ance of the glaciers in the Karakoram are nearly in balance during 1971–2010 [41,82,83]. Muhammad et al. [76] derived the mass balance of glaciers in the sub-basins of UIB with nega- tive mass balance except Shigar and Hunza in the central and western Karakoram, respectively. In another study, Muhammad et al. [84] investigated the mass balance of glaciers in Astore (a sub basin of UIB) and concluded that the glaciers in the basin (western Himalaya) are nearly in balance during 2000–2016 similar to the neighboring glaciers in the adjacent Karakoram. In addition to the direct glacier observations, climate data also show interesting signals and indi- rectly indicate glacier’s health status. For instance, [44] noted that mean temperature decreased at the stations (Bunji, Gilgit and Skardu) lying in the Karakoram region during 1961–2000. Their analysis shows that a decrease of 1˚C in mean summer temperature can cause a reduc- tion of ~20% in summer runoff. Fowler and Archer [44] concluded an expansion in contrast to the widespread retreat in the remaining parts of the HKH region. Latif et al. [85] investi- gated trends in maximum, minimum temperature in the northern part of Pakistan. They observed that maximum temperature has mixed (upward and downward) trend while the cooling in minimum temperature become stronger in the recent past. Ali et al. [86] investi-

gated temperatures’ changes in the UIB by considering meteorological data for two stations. They noted that the mean temperature increased by 0.63˚C in Skardu while decreased by Table 7. Seasonal MK test results in the Karakoram region for maximum temperature. The table shows the Ken- dall τ and their significance for the 1990–1999, 2000–2009 and 2010–2019. Station DJF MAM JJA SON Station Kendall τ P-Value Kendall τ P-Value Kendall τ P-Value Kendall τ P-Value Maximum Temperature (1990–1999) Astore 5.18e-02 0.021 9.51e-02 1.68e-05 9.22e-02 3.24e-05 -3.05e-02 0.169 Bunji 8.52e-02 0.000 6.23e-02 0.005 -1.41e-02 0.525 -4.92e-02 0.027 Chilas 1.32e-01 3.35e-09 7.49e-02 0.001 9.76e-03 0.659 -2.66e-02 0.232 Darosh 2.28e-01 2.2e-16 8.28e-02 0.000 -6.26e-02 0.005 -1.44e-02 0.515 Gilgit 1.40e-01 3.23e-10 8.06e-02 0.000 3.32e-03 0.881 -2.45e-02 0.27 Gopis 1.81e-01 1.90e-15 7.74e-02 0.000 -1.13e-01 4.14e-07 -5.00e-02 0.025 Skardu 3.85e-02 0.084 7.03e-02 0.001 -7.74e-02 0.000 -7.57e-02 0.001 Maximum Temperature (2000–2009) Astore -5.60e-02 0.012 9.88e-02 8.00e-06 6.90e-02 0.002 -6.35e-02 0.004 Bunji -8.24e-02 0.000 3.46e-02 0.119 -3.17e-02 0.156 -8.61e-02 0.000 Chilas -1.08e-01 1.53e-06 4.33e-02 0.050 -7.52e-03 0.735 -6.58e-02 0.003 Darosh -9.40e-02 2.54e-05 -1.08e-02 0.626 -3.63e-02 0.101 -8.58e-02 0.000 Gilgit -1.15e-01 3.1e-07 3.03e-02 0.171 -2.59e-02 0.244 -1.06e-01 2.01e-06 Gopis -1.17e-01 2.08e-07 5.18e-02 0.019 2.27e-03 0.919 -7.33e-02 0.001

Skardu -1.13e-02 0.614 3.27e-02 0.139 -1.47e-02 0.508 -1.18e-01 1.11e-07 Maximum Temperature (2010–2019) Astore 9.78e-02 0.000 9.92e-02 6.24e-05 9.77e-02 8.57e-05 -3.85e-02 0.122 Bunji 1.33e-01 1.54e-07 6.51e-02 0.008 1.90e-02 0.446 -8.71e-02 0.000 Chilas 1.01e-01 6.28e-05 8.18e-02 0.001 1.14e-01 4.30e-06 -7.29e-02 0.003 Darosh 1.00e-01 5.67e-05 8.03e-02 0.001 6.04e-02 0.014 -5.94e-02 0.016 Gilgit 3.87e-02 0.127 5.08e-02 0.041 -1.30e-02 0.602 -9.77e-02 9.50e-05 Gopis 9.21e-02 0.000 5.88e-02 0.018 1.17e-02 0.640 -8.01e-02 0.001 Skardu 7.72e-02 0.002 8.19e-02 0.001 1.79e-02 0.4704 -1.50e-01 1.58e-09 https://doi.org/10.1371/journal.pone.0271626.t007 PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 19 / 27

− 0.137˚C in Gilgit in the recent past. Shahzaman et al. [87] concluded in their study that drought has been observed over central and northern Pakistan during 1982–2019 by integrat- ing various data types. Proportion of South Asian population exposer to heatwaves is increas- ing under the shared socioeconomic scenarios in the twenty first century, however, the northern areas of Pakistan are unaffected presently [88]. The mass balance of the glacier is heavily dependent on the winter accumulation and sum- mer ablation strongly influenced by precipitation and temperature among other factors [89]. This study provides up to date changes in precipitation and temperature in some parts in the northern Pakistan (4 meteorological stations are in the Karakoram region). We found signifi- cant increase in winter average precipitation and decrease in summer average temperature particularly at the meteorological stations in the Karakoram region during the 1962–1990 (Table 1). However, the mMK test indicates a decreasing trend (during DJF) in precipitation and increasing trend (during JJA) in temperature in the recent period of 2010–2019 in the Kar- akoram which is not aligned with the Karakoram Anomaly. Our findings are an indication of glaciers mass loss in future in the Karakoram region. These stations are situated in the valley below the glacier terminating zones, however, an indirect clue can be inferred based on climate change and extreme events regarding future trends. Our results suggest further investigation

of glaciers mass balance in the region in future for better understanding of glaciers’ health and associated impacts. The downstream water availability in UIB is dominated by snow and Table 8. Seasonal MK test results in the Karakoram region for minimum temperature. The table shows the Ken- dall τ and their significance for the 1990–1999, 2000–2009 and 2010–2019. Station DJF MAM JJA SON Station Kendall τ P-Value Kendall τ P-Value Kendall τ P-Value Kendall τ P-Value Minimum Temperature (1990–1999) Astore 3.60e-02 0.11 1.51e-01 8.73e-12 1.61e-01 4.38e-13 -3.14e-04 0.989 Bunji -4.88e-02 0.030 7.85e-02 0.000 1.10e-03 0.960 -4.94e-02 0.026 Chilas 1.12e-01 5.79e-07 1.41e-01 3.23e-10 -7.65e-02 0.001 Darosh 1.13e-01 4.54e-07 1.03e-01 3.33e-06 6.64e-03 0.764 -5.04e-02 0.023 Gilgit -1.56e-01 2.88e-12 9.95e-02 7.01e-06 4.19e-02 0.058 -3.51e-02 0.114 Gopis 3.91e-02 0.086 1.05e-01 2.72e-06 -3.01e-02 0.178 -2.01e-02 0.368 Skardu -6.44e-02 0.004 9.08e-02 4.04e-05 -1.24e-02 0.575 -3.72e-02 0.094 Minimum Temperature (2000–2009) Astore 2.76e-03 0.902 1.07e-01 1.56e-06 7.35e-02 0.001 -7.00e-02 0.001 Bunji 7.40e-02 0.001 7.49e-02 0.001 1.13e-01 3.77e-07 5.98e-02 0.007 Chilas 1.59e-01 3.66e-12 8.46e-02 0.000 3.84e-02 0.089 -3.69e-02 0.100 Darosh -1.91e-01 2.2e-16 -5.36e-02 0.015 -2.88e-01 2.2e-16 -2.30e-01 2.2e-16 Gilgit 1.31e-01 5.39e-09 1.24e-01 2.61e-08 1.84e-01 2.2e-16 3.98e-02 0.074 Gopis -1.94e-01 2.2e-16 2.56e-02 0.250 -6.04e-02 0.007 -1.43e-01 1.46e-10

Skardu 1.05e-02 0.635 -3.29e-03 0.882 -1.48e-01 2.18e-11 -1.51e-01 9.57e-12 Minimum Temperature (2010–2019) Astore -9.41e-03 0.709 5.45e-02 0.028 1.23e-01 9.29e-07 -1.08e-01 1.55e-05 Bunji 2.65e-01 < 2.2e-16 1.41e-01 1.30e-08 1.62e-01 9.06e-11 -7.09e-03 0.777 Chilas 1.18e-01 2.90e-06 9.01e-03 0.716 -1.40e-01 1.66e-08 -1.11e-01 8.16e-06 Darosh 1.31e-03 0.958 -5.57e-03 0.822 1.57e-02 0.527 -7.7e-02 0.001 Gilgit 8.88e-02 0.000 4.42e-02 0.078 1.23e-01 1.16e-06 -9.07e-02 0.000 Gopis 2.13e-01 < 2.2e-16 6.32e-02 0.012 2.14e-02 0.397 -1.11e-01 1.05e-05 Skardu 1.08e-01 1.70e-05 4.59e-02 0.063 2.01e-02 0.418 -4.81e-02 0.053 https://doi.org/10.1371/journal.pone.0271626.t008 PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 20 / 27

glacier melt water particularly in summer, therefore, the climate change assessment can indi- cate indirect signals for water availability. In addition, climate extremes can provide guidelines to policy makers and relevant stakeholder for future climate trends and meltwater resources in the country. 6. Conclusions During DJF and MAM, average temperature increased in all climate zones. A decreasing trend during JJA in zone 1, 3, 4 and during SON in zones 1 and 2 were noted in the average tempera- ture. Precipitation indicated mixed trend in different zones. Mann-Kendal test indicated trend in maximum and minimum temperature except zone-4 where the maximum temperature has no trend. On the average, CWDs increased in all zones except in zone 3 where it decreased. The number of SU25 increased in all climate zone except zone 4. Fig 11. Station-wise climate extremes related to temperature for each climatic zone and two independent time duration in Karakoram region. Each color has specific meaning and given with Fig 12. Note: The colors represent different status for each extreme mentioned in these figures. Green color shows no changes. https://doi.org/10.1371/journal.pone.0271626.g011 PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 21 / 27

In the Karakoram region, temperature decreased significantly during JJA. Also, precipita- tion increased significantly in this region except a significant decrease in Gilgit during DJF. MK test suggested increasing trend in precipitation and decreasing trend in maximum and minimum temperature during 1962–1990 and closely in line with Karakoram Anomaly. How- ever, precipitation (in DJF) and temperature (in JJA) have decreasing and increasing trend, respectively, during the most recent period (2010–2019), which do not support the notion of Karakoram Anomaly. These findings suggested that the glacier may lose mass in future rather than gaining or stable conditions. Climate extremes have mixed trends over North Pakistan. For instance, summer days increased, and cold nights have mixed trend. Warm nights decreased except in western Karakoram. The key takeaways are: 1. A change is noted in the Climate (maximum, minimum temperature and precipitation) across the country during the analysis period. Fig 12. Station-wise climate extremes related to precipitation for each climatic zone and two independent time duration In Karakoram region. Each color has specific meaning and given below. Note: The colors represent different status for each extreme mentioned in these figures. Green color shows no changes. https://doi.org/10.1371/journal.pone.0271626.g012 PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 22 / 27

2. TN10p, TX10p and TR20, CSDI and PRECPTOT have decreasing trend particularly during the 1991–2019 in most parts of the country. 3. Precipitation has increasing trend in DJF while temperature has decreasing trend in JJA during the 1962–1990 at the stations located in the Karakoram region. 4. During the last decade (2010–2019), precipitation and temperature have decreasing and increasing trend, respectively, at the stations located in the Karakoram region. 5. Based on the points in 3 and 4, the glaciers in the Karakoram region may loses mass balance slightly in the near future, which is in contrast to the famous Karakoram Anomaly. Supporting information S1 Data. (XLSX) Acknowledgments The authors are grateful to Pakistan Meteorological Department (PMD) for providing meteo- rological data. Author Contributions Conceptualization: Firdos Khan. Data curation: Firdos Khan, Sher Muhammad. Formal analysis: Firdos Khan. Investigation: Firdos Khan. Methodology: Christoph Mayer. Software: Firdos Khan, Shaukat Ali. Visualization: Firdos Khan, Hamd Ullah. Writing – original draft: Firdos Khan. Writing – review & editing: Shaukat Ali, Christoph Mayer, Hamd Ullah, Sher Muhammad. References 1. Hegerl, G.C., et al., 2010. Good practice guidance paper on detection and attribution related to anthro- pogenic climate change. In: Stocker, T. G., et al. (Eds.), Meeting report of the Intergovernmental Panel on Climate Change Expert Meeting on Detection and Attribution of Anthropogenic Climate Change. IPCC Working Group I Technical Support Unit, University of Bern, Bern, Switzerland, p.8pps.

2. Bindoff, N., Stott, P., Achuta Rao, K. M., Allen, M., Gillett, N., Gutzler, D., et al., 2013. Detection and attribution of climate change: from global to regional in: climate change 2013. In: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P. M. (Eds.), The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment. Cambridge Uni- versity Press, Cambridge, United Kingdom, New York, NY, USA. 3. Walsh J., Wuebbles D., Hayhoe K., Kossin J., Kunkel K., Stephens G., et al., 2014a. Ch. 2: Our Chang- ing Climate. Climate Change Impacts in the United States: The Third National Climate Assessment. In: Melillo J. M., Richmond Terese (T.C.), Yohe G. W. (Eds.), U. S. Global Change Research Program, United States 2-1-2-nn. 4. Walsh K.J.E., Camargo S., Vecchi G., Daloz A.S., Elsner J., Emanuel K., et al, 2014b. Hurricanes and climate: the U. S. CLIVAR working group on hurricanes. Bull. Am. Meteor. Soc. https://doi.org/10.1175/ BAMS-D-13-00242.1. PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 23 / 27

5. Easterling A. R., Kunkel K. E., Wehner M. E., Sun L., 2016. Detection and attribution of climate extremes in the observed record. Weather and Climate Extremes 11, Pp.17–27. https://doi.org/10. 1016/j.wace.2016.01.001 6. Intergovernmental Panel on Climate Change (IPCC), 6th Assessment Report (2021). URL: https:// www.ipcc.ch/report/ar6/wg1/ (accessed on 28 January 2022). 7. Schweikert A., Chinowsky P., Espinet X., Tarbert M. (2014) Climate Change and Infrastructure Impacts: Comparing the Impact on Roads in ten Countries through 2100. Procedia Engineering, Volume 78, Pages 306–316. https://doi.org/10.1016/j.proeng.2014.07.072. 8. Forzieri G., Bianchi A., Silva FB., Herrera MAM., Leblois A., Lavalle C., et al. (2018) Escalating impacts of climate extremes on critical infrastructures in Europe. Global Environmental Change, Volume 48, Pages 97–107. https://doi.org/10.1016/j.gloenvcha.2017.11.007 PMID: 29606806 9. National Oceanic and Atmospheric Administration: Climate change impacts. URL: https://www.noaa. gov/education/resource-collections/climate/climate-change-impacts./accessed on 19 January 2022. 10. Cheng C.S., Auld H., Li Q., Li G., 2012. Possible impacts of climate change on extreme weather events at local scale in south-central Canada. Clim. Chang., Vol. 112, Pp. 963–979. 11. Sillmann J., Kharin V.V., Zwiers F.W., Zhang X., Bronaugh D., 2013 Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J. Geophys. Res. Atmos., Vol. 118, Pp. 2473–2493.

12. Zhang Q., Gu X., Singh V.P., Kong D., Chen X., 2015. Spatiotemporal behavior of floods and droughts and their impacts on agriculture in China. Glob. Planet. Chang., Vol. 131, Pp. 63–72. 13. Sun Q., Miao C., Duan Q., Wang Y., 2015. Temperature and precipitation changes over the Loess Pla- teau between 1961 and 2011, based on high-density gauge observations. Glob. Planet. Chang., Vol. 132, Pp. 1–10. 14. Moazami S., Golian S., Hong Y., Sheng C., Kavianpour M.R., 2016. Comprehensive evaluation of four high-resolution satellite precipitation products under diverse climate conditions in Iran. Hydrol. Sci. J., Vol. 61, Pp. 420–440. 15. Berardy A., Chester M.V., 2017. Climate change vulnerability in the food, energy, and water nexus: Concerns for agricultural production in Arizona and its urban export supply. Environ. Res. Lett., Vol. 12, 35004. 16. Girma A., Qin T., Wang H., Yan D., Gedefaw M., Abiyu A., Batsuren D. (2020). Study on Recent Trends of Climate Variability Using Innovative Trend Analysis: The Case of the upper Huai River Basin. Polish Journal of Environmental Studies, Vol. 29, No. 3, Pp. 2199–2210. https://doi.org/10.15244/pjoes/ 103448. 17. Bougara H., Hamed KB., Borgemeister C., Tischbein B., Kumar N. (2020) Analyzing Trend and Variabil- ity of Rainfall in The Tafna Basin (Northwestern Algeria). Atmosphere, Vol. 11, No. 4. https://doi.org/10. 3390/atmos11040347. 18. Asfaw A., Simane B., Hassen A., Bantider A. (2018) Variability and time series trend analysis of rainfall

and temperature in northcentral Ethiopia: A case study in Woleka sub-basin, Weather and Climate Extremes, Vol/ 19, Pp. 29–41. https://doi.org/10.1016/j.wace.2017.12.002. 19. Koudahe K., Kayode A.J., Samson A.O., Adebola A.A. and Djaman K. (2017) Trend Analysis in Stan- dardized Precipitation Index and Standardized Anomaly Index in the Context of Climate Change in Southern Togo. Atmospheric and Climate Sciences, 7, 401–423. https://doi.org/10.4236/acs.2017. 74030. 20. Patel GT., Libang A. (2014) Trend analysis of annual and seasonal rainfall to climate variability in North- East region of India. Journal of Applied and Natural Science 6 (2): PP. 480–483. 21. Shi P., Ma X., Chen X., Qu S., Zhang Z. (2013) Analysis of Variation Trends in Precipitation in an Upstream Catchment of Huai River", Mathematical Problems in Engineering, vol. 2013, Article ID 929383, 11 pages, 2013. https://doi.org/10.1155/2013/929383. 22. Michaels PJ., Balling RC Jr., Vose RS., Knappenberger PC. (1998) Analysis of trends in the variability of daily and monthly historical temperature measurements. Climate Research, Vol. 10, Pp. 10–33. 23. Rathnayake U. (2019) Comparison of Statistical Methods to Graphical Methods in Rainfall Trend Analy- sis: Case Studies from Tropical Catchments. Advances in Meteorology, vol. 2019, Article ID 8603586. https://doi.org/10.1155/2019/8603586. 24. Kaur N., Yousuf A., Singh MJ. (2021) Long term rainfall variability and trend analysis in lower Shivaliks of Punjab, India. MAUSAM, Vol. 72, No. 3, Pp. 571–582.

25. Alam F., Salam M., Khalil N.A. et al. (2021) Rainfall trend analysis and weather forecast accuracy in selected parts of Khyber Pakhtunkhwa, Pakistan. SN Appl. Sci. 3, 575. https://doi.org/10.1007/s42452- 021-04457-z. PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 24 / 27

26. Hussain A., Cao J., Hussain I., Begum S., Akhtar M., Wu X., et al. (2021) Observed Trends and Variabil- ity of Temperature and Precipitation and Their Global Teleconnections in the Upper Indus Basin, Hindu- kush-Karakoram-Himalaya. Atmosphere, 12, 973. https://doi.org/10.3390/atmos12080973. 27. Safdar F., Khokhar MF., Arshad M., Adil IH. (2019) Climate Change Indicators and Spatiotemporal Shift in Monsoon Patterns in Pakistan. Advances in Meteorology, Volume 2019, Article ID 8281201, https:// doi.org/10.1155/2019/8281201. 28. Samo SR., Bhatti NK., Sannd A., Keerio MA., Bangwar DK. (2017) Temporal Analysis of Temperature and Precipitation Trends in Shaheed Benazir Abad Sindh, Pakistan. Engineering, Technology & Applied Science Research Vol. 7, No. 6, PP. 2171–2176. 29. Abbas F. (2013) Analysis of a Historical (1981–2010) Temperature Record of the Punjab Province of Pakistan. Earth Interactions, Vol. 17, Pp. 1–23. https://doi.org/10.1175/2013EI000528.1. 30. Rahman G., Rahman A., Anwar MM., Muhammad Dawood M., Miandad M. (2022) Spatio-temporal analysis of climatic variability, trend detection, and drought assessment in Khyber Pakhtunkhwa, Paki- stan. Arabian Journal of Geosciences. https://doi.org/10.1007/s12517-021-09382-4. 31. Felix M.L.; Kim Y.-k.; Choi M.; Kim J.-C.; Do X.K.; Nguyen T.H.; et al (2021) Detailed Trend Analysis of Extreme Climate Indices in the Upper Geum River Basin. Water, 13, 3171. https://doi.org/10.3390/ w13223171. 32. Mahmood R., Jia S. & Zhu W. (2018) Analysis of climate variability, trends, and prediction in the most

active parts of the Lake Chad basin, Africa. Sci Rep 9, 6317. https://doi.org/10.1038/s41598-019- 42811-9. 33. Sun O., Zhang X., Zwiers F., Westra S., Alexandra LV. (2021) A Global, Continental, and Regional Analysis of Changes in Extreme Precipitation. Journal of Climate, Vol. 34, Issue 1, Pp. 243–258. https://doi.org/10.1175/JCLI-D-19-0892.1. 34. Frich P., Alexander LV., Della-Marta P., Gleason B., Haylock M., Klein Tank AMG., et al. (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Cli- mate Research, 19, 193–212. https://doi.org/10.3354/cr019193. 35. Sheikh M.M., Manzoor N., Ashraf J., Adnan M., Collins D., Hameed S., et al., 2015. Trends in extreme daily rainfall and temperature indices over South Asia. Int. J. Climatol., Vol. 35, No. 7, Pp. 1625–1637. 36. Rizvi FF., Ahmed B., Hussain S., Khan A., Raza M., Shahid M. (2021) Assessment of climate extremes from historical data (1960–2013) of Soan River Basin in Pakistan. International Journal of Global Warm- ing, 2021 Vol. 25 No.1, pp.1 – 37. https://doi.org/10.1504/IJGW.2021.117431 37. Pritchard H.D., 2019. Asia’s shrinking glaciers protect large populations from drought stress. Nature 569, 649–654. https://doi.org/10.1038/s41586-019-1240-1 PMID: 31142854 38. Lutz A.F., Immerzeel W.W., Kraaijenbrink P.D.A., Shrestha A.B., Bierkens M.F.P., 2016. Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes. PLoS ONE 11(11): e0165630. https://doi.org/10.1371/journal.pone.0165630 PMID: 27828994

39. Haeberli W., Frauenfelder R., Hoelzle M., Maisch M., 1999. On rates and acceleration trends of global glacier mass changes. Geografiska Annaler 81A(4):585–591. https://doi.org/10.1111/1468-0459. 00086. 40. Zemp M., Paul F., Hoelzle M., Haeberli W., 2008. Glacier fluctuations in the European Alps 1850–2000: an overview and spatiotemporal analysis of available data. In: Orlove B, Wiegandt E, Luckman BH (eds) The darkening peaks: Glacial retreat in scientific and social context. University of California Press, pp 152–167. https://doi.org/10.5167/uzh-9024 41. Brun F., Berthier E., Wagnon P., Ka¨a¨ b A., Treichler D., 2017. A spatially resolved estimate of High Mountain Asia glacier mass balances, 2000–2016. Nat Geosci., 10(9): 668–673. https://doi.org/10. 1038/NGEO2999 PMID: 28890734 42. Ka¨ a¨ b A., Treichler D., Nuth C., Berthier E., 2015. Brief Communication: Contending estimates of 2003– 2008 glacier mass balance over the Pamir–Karakoram–Himalaya. The Cryosphere, 9, 557–564. https://doi.org/10.5194/tc-9-557-2015 43. Hewitt K., 2005. The Karakoram anomaly? Glacier expansion and the ‘elevation effect’, Karakoram Himalaya. Mt. Res. Dev. 25, 332–340. 44. Fowler H.J., Archer D.R., 2006. Conflicting Signals of Climatic Change in the Upper Indus Basin. Jour- nal of Climate, Vol. 19, No. 17, Pp. 4276–4293. https://doi.org/10.1175/JCLI3860.1. 45. Iyakaremye V., Zeng G., Yang X., Zhang G., Ullah I., Gahigi A., et al. (2021) Increased high-tempera- ture extremes and associated population exposure in Africa by the mid-21st century. Science of the

Total Environment 790, 148162. https://doi.org/10.1016/j.scitotenv.2021.148162 PMID: 34102437 46. Iyakaremye V., Zeng G., Ullah I., Gahigi A., Mumo R., Ayugi B. (in press) Recent Observed Changes in Extreme High-Temperature Events and Associated Meteorological Conditions over Africa. International journal of climatology. https://doi.org/10.1002/joc.7485. PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 25 / 27

47. Ahmad B., Hussain A. (2017) Evaluation of Past and Projected Climate Change in Pakistan Region Based on GCM20 and RegCM4.3 Outputs. Pakistan Journal of Meteorology Vol. 13, No. 26. 48. Khan F., Pilz J., Ali S., (2017) Improved hydrological projections and reservoir management in the Upper Indus Basin under the changing climate. Water and environment journal, 31 (2), 235–244. https://doi.org/10.1111/wej.12237 49. Worldometers. URL: https://www.worldometers.info/world-population/pakistan-population/ (access on 18 April 2021). 50. Pakistan Bureau of Statistics (2021). URL: https://www.pbs.gov.pk/ (Accessed on 20 May 2021). 51. The World Bank (2021). URL: https://data.worldbank.org/indicator/SP.POP.TOTL?locations=PK/ (Accessed on 20 May 2020). 52. Azur M.J., Stuart E.A., Frangakis C., Leaf P.J., 2011. Multiple imputation by chained equations: what is it and how does it work? Int. J. Methods Psychiatr. Res. 20(1): Pp. 40–49. https://doi.org/10.1002/mpr. 329 PMID: 21499542 53. Tuomenvirta H. (2002). Homogeneity testing and adjustment of climatic time series in Finland. Geophy- sica, 38(1–2), 15–41. 54. Ullah W., Wang G., Ali G., Tawia Hagan D., Bhatti A., Lou D. (2019b) Comparing multiple precipitation products against in-situ observations over different climate regions of Pakistan. Rem. Sens. 11 (6), 628. https://doi.org/10.3390/rs11060628. 55. Arshad M., Ma X., Yin J., Ullah W., Liu M., Ullah I. (2021) Performance evaluation of ERA-5, JRA-55, MERRA-2, and CFS-2 reanalysis datasets, over diverse climate regions of Pakistan. Weather and Cli-

mate Extremes, vol. 33, 100373. https://doi.org/10.1016/j.wace.2021.100373. 56. Ullah I., Ma X., Yin J., Asfaw T. G., Azam K., Syed S., et al. (2021) Evaluating the meteorological drought characteristics over Pakistan using in situ observations and reanalysis products. International journal of climatology, Vol. 41, No. 9, Pp. 4437–4459. https://doi.org/10.1002/joc.7063. 57. Ullah I., Ma X., Yin J., Saleem F., Syed S., Omer A., et al. (2022) Observed changes in seasonal drought characteristics and their possible potential drivers over Pakistan. International journal of clima- tology, Vol. Vol. 42, No. 3, Pp. 1576–1596. https://doi.org/10.1002/joc.7321. 58. Ho Ming K., & Yusof F. (2012). Homogeneity Tests on Daily Rainfall Series in Peninsular Malaysia. Int. Journal of Contemporary Mathematics and Sciences, 7(1), 9–22. 59. Mann H.B., 1945. Nonparametric tests against trend. Econometrica 13(3):245–259. 60. Shaukat M.H., Al-Dousari A., Hussain I., Faisal M., Ismail M., Shoukry A.M., et al., 2020. Evaluation of wet and dry event’s trend and instability based on the meteorological drought index. PeerJ 8:e9729. https://doi.org/10.7717/peerj.9729 PMID: 32904207 61. Hu M., Sayama T., TRY S., Takara K., Tanaka K., 2019. Trend Analysis of Hydroclimatic Variables in the Kamo River Basin, Japan. Water, Vol. 11, No. 9. https://doi.org/10.3390/w11091782 62. Hirsch R.M., Slack J.R., Smith R.A., 1982. Techniques of trend analysis for monthly water quality data. Water Resources Research 18(1):107–121.

63. Zhang X., Hegerl G., Zwiers F.W., Kenyon J., 2005. Avoiding Inhomogeneity in Percentile-Based Indices of Temperature Extremes. Journal of Climate, pages 1641–1651. https://doi.org/10.1175/JCLI3366.1. 64. Expert Team on Detection of Climate Change and Indices (ETDCCI). URL: http://etccdi.pacificclimate. org/list_27_indices.shtml (accessed on 17 October 2021). 65. Quincey D. J., Copland L., Mayer C., Bishop M., Luckman A., Belò M. (2009) Ice velocity and climate variations for Baltoro Glacier, Pakistan. Journal of Glaciology, Vol. 55, No. 194, Pp. 1061–1071. https:// doi.org/10.3189/002214309790794913. 66. BOLCH T., KULKARNIA A., KA¨ A¨ B A., HUGGEL C., PAUL F., COGLEY J. G., et al. (2012) The State and Fate of Himalayan Glaciers. Science, VOL. 336, NO. 6079, Pp. 310–314 • https://doi.org/10.1126/ science.1215828 PMID: 22517852 67. Kalair A. R., Abas N., Hasan Q. U., Kalair E., Kalair A., Khan N. (2019) Water, energy and food nexus of Indus Water Treaty: Water governance. Water-Energy Nexus, Vol. 2, No 1, Pp. 10–24. https://doi.org/ 10.1016/j.wen.2019.04.001. 68. Bhatti A. S., Wang G., Ullah W., Ullah S. et al. (2020) Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan. Water, 12, 797. https://doi.org/10.3390/w12030797 69. Ullah S., You Q., Ullah W. et al. (2019) Daytime and nighttime heat wave characteristics based on multi- ple indices over the China–Pakistan economic corridor. Climate Dynamics, Vol. 53, Pp. 6329–6349. https://doi.org/10.1007/s00382-019-04934-7.

70. Ullah S., You Q., Ullah W., Ali A. (2018) Observed changes in precipitation in China-Pakistan economic corridor during 1980–2016. Atmospheric Research, Vol. 210, Pp. 1–14. https://doi.org/10.1016/j. atmosres.2018.04.007. PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 26 / 27

71. Khan I., Waqas T., Samiullah, Ullah S. (2020) Precipitation variability and its trend detection for monitor- ing of drought hazard in northern mountainous region of Pakistan. Arabian Journal Geosciences, Vol. 13, 698. https://doi.org/10.1007/s12517-020-05700-4. 72. Ullah S., You Q., Ali A., Ullah W., Jan M. A., Zhang Y., et al. (2018) Observed changes in maximum and minimum temperatures over China- Pakistan economic corridor during 1980–2016. Atmospheric Research, Vol. 216, Pp. 37–51. https://doi.org/10.1016/j.atmosres.2018.09.020. 73. Ullah S., You Q., Ullah W., Ali A., Xie W., Xie X. (2019) Observed changes in temperature extremes over China–Pakistan Economic Corridor during 1980–2016. International journal of climatology, Vol. 39, N. 3, Pp. 1457–1475. https://doi.org/10.1002/joc.5894 74. Archer D. (2003) ‘Contrasting hydrological regimes in Indus Basin’, Journal of Hydrology, Vol. 274, Nos. 1–4, pp.198–201. 75. Muhammad S., & Tian L. (2016). Changes in the ablation zones of glaciers in the western Himalaya and the Karakoram between 1972 and 2015. Remote Sensing of Environment, 187, 505–512. 76. Muhammad S., Tian L., & Khan A. (2019b). Early twenty-first century glacier mass losses in the Indus Basin constrained by density assumptions. Journal of Hydrology, 574, 467–475. 77. Mahmood T., Rasul G., 2012. Predictability of Summer Monsoon Rainfall by using High Resolution Regional Model (HRM). Pakistan Journal of Meteorology, Vol. 9, Issue 17, Pp. 25–36. 78. Khan F., Ali S., Pilz J., 2018. Evaluation of statistical downscaling models using pattern and depen-

dence structure in the monsoon-dominated region of Pakistan. Volume 73, Issue 6 Pages 193–203 https://doi.org/10.1002/wea.3164. 79. Ali S., Kiani R.S., Babar R., Nasir S., Rehman N., Adnan M., et al., 2020. Spatio-Temporal Variability of Summer Monsoon Onset over Pakistan. Asia-Pacific Journal of Atmospheric Sciences volume 56, pages147–172. https://doi.org/10.1007/s13143-019-00130-z. 80. Immerzeel W.W., Lutz A.F., Andrade M., Bahl A., Biemans H., Bolch T., et al., 2020. Importance and vulnerability of the world’s water towers. Nature, Vol. 577, Pp. 364–369. https://doi.org/10.1038/ s41586-019-1822-y PMID: 31816624 81. Bolch T., Shea J.M., Liu S., Azam F.M., Gao Y., Gruber S., et al., 2019. Status and Change of the Cryo- sphere in the Extended Hindu Kush Himalaya Region. In: Wester P., Mishra A., Mukherji A., Shrestha A. (eds) The Hindu Kush Himalaya Assessment. Springer, Cham. https://doi.org/10.1007/978-3-319- 92288-1_7. 82. Bolch T., Kulkarni A., Ka¨ a¨ b A., Huggel C., Paul F., Cogley J.G., et al., 2012. The State and Fate of Himalayan Glaciers. Science, Vol. 336, Issue 6079, pp. 310–314. https://doi.org/10.1126/science. 1215828 PMID: 22517852 83. Zhou Y., Li Z., Li J., 2017. Slight glacier mass loss in the Karakoram region during the 1970s to 2000 revealed by KH-9 images and SRTM DEM. Journal of Glaciology, 63(238) 331–342. https://doi.org/10. 1017/jog.2016.142 84. Muhammad S., Tian L., Nu¨ sser M., (2019c) No significant mass loss in the glaciers of Astore Basin (North-Western Himalaya), between 1999 and 2016. Journal of Glaciology, 65(250) 270–278. https://

doi.org/10.1017/jog.2019.5 85. Latif Y., Yaoming M., Yaseen M., Muhammad S., Muhammad A.W., 2020b. Spatial analysis of temper- ature time series over Upper Indus Basin (UIB). Theor Appl Climatol 139:741–758. https://doi.org/10. 1007/s00704-019-02993. 86. Ali S.H.B., Shafqat M.N., Eqani S.A.M.A.S., Shah S.T.A., 2019. Trends of climate change in the upper Indus basin region, Pakistan: implications for cryosphere. Environ Monit Assess (2019) 191: 51. https:// doi.org/10.1007/s10661-018-7184-3 PMID: 30612331 87. Shahzaman M., Zhu W., Ullah I., Mustafa F., Bilal M., Ishfaq S., et al. (2021) Comparison of Multi-Year Reanalysis, Models, and Satellite Remote Sensing Products for Agricultural Drought Monitoring over South Asian Countries. Remote Sens. 2021, 13, 3294. https://doi.org/10.3390/rs13163294. 88. Ullah I., Saleem F., Iyakaremye V., Yin J., Ma X., Syed S., et al. (2022) Projected Changes in Socioeco- nomic Exposure to Heatwaves in South Asia Under Changing Climate. Earth’s Future, Vol. 10, No. 2, e2021EF002240. https://doi.org/10.1029/2021EF002240. 89. Guo H.D., Zhang L. Zhu L.W., 2015. Earth observation big data for climate change research. Advances in Climate Change Research, Volume 6, Issue 2, Pages 108–117. https://doi.org/10.1016/j.accre. 2015.09.007. PLOS ONE Climate change and extremes analysis using observed data (1962-2019) over Pakistan PLOS ONE | https://doi.org/10.1371/journal.pone.0271626 July 27, 2022 27 / 27