Future risk assessment by estimating historical heat wave trends with projected heat accumulation using SimCLIM climate model in Pakistan

Nasim, Wajid; Amin, Asad; Fahad, Shah; Awais, Muhammad; Khan, Naeem; Mubeen, Muhammad; Wahid, Abdul; Turan, Veysel; Rehman, Muhammad Habibur; Ihsan, Muhammad Zahid; Ahmad, Shakeel; Hussain, Sajjad; Mian, Ishaq Ahmad; Khan, Bushra; Jamal, Yousaf

doi:10.1016/j.atmosres.2018.01.009

Cited by 100 publications

(42 citation statements)

References 31 publications

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“…Most of the RCP8.5 scenarios show a higher increase compared with RCP4.5. This also supports the previous findings in the literature (Xin et al 2013;Nasim et al 2018). However, for some GCMs and return periods, it is possible to see higher intensities under RCP4.5 compared with RCP8.5 as in the study of Singh et al (2016).…”

Section: Changes In Rainfall Intensities Under Future Climate Conditionssupporting

confidence: 92%

Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

Tayşi

Özger

2021

Journal of Water and Climate Change

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Urbanization and industrialization cause an increase in greenhouse gas emissions, which in turn causes changes in the atmosphere. Climate change is causing extreme rainfalls and these rainfalls are getting stronger day after day. Floods are threatening urban areas, and short-duration rainfall and outdated drainages are responsible for urban floods. Intensity–Duration–Frequency (IDF) curves are crucial for both drainage system design and assessment of flood risk. Once IDF curves are determined from historical data, they are assumed to be stationary. However, IDF curves must be non-stationary and time varying based on preparation for extreme events. This study generates future IDF curves with short-duration rainfalls under climate change. To represent future rainfall, an ensemble of four Global Climate Models generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 were used in this study. A new approach to the HYETOS disaggregation model was applied to disaggregate daily future rainfall into sub-hourly using disaggregation parameters of hourly measured rainfalls. Hence, sub-hourly future rainfalls will be obtained capturing historical rainfall patterns instead of random rainfall characteristics. Finally, historical and future IDF curves were compared. The study concludes that increases in short-duration rainfalls will be highly intensified in both the near and distant futures with a high probability.

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Section: Changes In Rainfall Intensities Under Future Climate Conditionssupporting

confidence: 92%

Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

Tayşi

Özger

2021

Journal of Water and Climate Change

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“…Temperature over Pakistan ranges from as low as <0 °C in northern regions to the soaring temperatures of >35 °C over southern regions (Nasim et al, 2018). In recent decades, the seasonal trend of temperature has increased over northern Pakistan in all seasons (Asmat et al, 2018;Ullah et al, 2019a).…”

Section: Study Areamentioning

confidence: 99%

Future Changes in Seasonal Temperature Over Pakistan in CMIP6

Karim¹,

Tan²,

Ayugi³

et al. 2021

Preprint

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The present study analyzed seasonal (i.e., Dec-Jan [DJF] and June – August [JJA]) temperature change for the near (2025-2054) and far future (2070-2099) under SSP245, SSP370, and SSP585 scenarios over Pakistan. The anomalies, Mann-Kendall trend tests, Sequential Mann-Kendall trend test (SQMK), and probability density frequency (PDF) analysis were used to investigate future mean temperature variations. The DJF season projected higher increase in temperature in the northern (3.8 oC, 5.1 oC and 6.5 oC), followed by central regions (3.8 oC, 4.9 oC and 6.4 oC) under SSP245, SSP370 and SSP585 scenarios, respectively. The central region is likely to record significant increase in JJA (3.0 oC, 4.4 oC and 5.4 oC) mean temperature in far future under the given SSP scenarios. Compared to historical (PDF), the far future DJF temperature changes revealed significant higher warming over northern, central and then over southern regions under most of SSP scenarios. The southern regions are projected to possible rise in far future JJA temperatures by 2.7 oC, 3.3 oC and 4.3 oC, under SSP245, SSP370 and SSP585, respectively. The PDFs for JJA further verify the highest positive abrupt shift in temperature across the central region and then southern region. The future diverse seasonal temperature changes supports further examination of the associated mechanisms and factors responsible for temperature changes to address climate change.

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“…Impact of climate change directly and indirectly on agriculture worldwide (Akram et al, 2018;Hashim et al, 2020;Kawo et al, 2021;Nasim et al, 2018;Sabagh et al, 2020). Climatic and environmental changes negatively influenced the health of the crops with the passage of time in the following ways: variations in the rainfall (Kimuku & Ngigi, 2017), extreme heat stress, change in the land surface temperature (LST), and migration of the peoples from rural to urban areas (Hussain et al, 2020a;Mukherjee & Singh, 2020).…”

Section: Introductionmentioning

confidence: 99%

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Hussain

Karuppannan

2021

Geology, Ecology, and Landscapes

Self Cite

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The aim of this research was to assess the land use/land cover (LULC) changes and its impact on land surface temperature (LST) using remote-sensing (RS) technique in the district Khanewal, Punjab, Pakistan. Data were pre-processed using ERDAS imagine 15 and Arc GIS 10.4 software for layer stacking, mosaicking, and sub-setting of Landsat images. After pre-processing, the supervised classification scheme was applied for the years 1980, 2000, and 2020, which explains the maximum likelihood algorithm to identify LULC changes observed in the study area. "Built-up area" in 1980 occupied 1.75% but in 2020, the build-up area increased (5.27%) compared to 2020. Vegetation area was decreased by 4.12% from 1980 to 2020 in district Khanewal. It was observed that there has been a rapid change in vegetation area to build-up area. The LST values were increased by 0.50°C from 1980 to 2020 due to the increasing build-up area from East to West direction in district Khanewal. Maximum and minimum normalized difference vegetation index (NDVI) values were observed 0.72 and −0.2 for 1980 and 2020. The regression line produced a definitive explanation, showing a strong negative correlation with NDVI and LST. The outcomes of this study indicated that a dramatic transformation took place in district Khanewal regarding a decrease in greenness due to a rapid increase in population density, urban growth, and other infrastructural developments. Thus, these results will be used in regional and urban planning and will be used for managing agriculture in the coming years of rapid environmental changes.

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Future risk assessment by estimating historical heat wave trends with projected heat accumulation using SimCLIM climate model in Pakistan

Cited by 100 publications

References 31 publications

Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

Future Changes in Seasonal Temperature Over Pakistan in CMIP6

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

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