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Climate change increased extreme monsoon rainfall, flooding highly vulnerable communities in Pakistan

أدى تغير المناخ إلى زيادة هطول الأمطار الموسمية الغزيرة، مما أدى إلى إغراق المجتمعات الضعيفة للغاية في باكستان
Authors: Friederike E. L. Otto; Mariam Zachariah; Fahad Saeed; Ayesha Siddiqi; Shahzad Kamil; Haris Mushtaq; T. Arulalan; +19 Authors

Climate change increased extreme monsoon rainfall, flooding highly vulnerable communities in Pakistan

Abstract

Abstract As a direct consequence of extreme monsoon rainfall throughout the summer 2022 season Pakistan experienced the worst flooding in its history. We employ a probabilistic event attribution methodology as well as a detailed assessment of the dynamics to understand the role of climate change in this event. Many of the available state-of-the-art climate models struggle to simulate these rainfall characteristics. Those that pass our evaluation test generally show a much smaller change in likelihood and intensity of extreme rainfall than the trend we found in the observations. This discrepancy suggests that long-term variability, or processes that our evaluation may not capture, can play an important role, rendering it infeasible to quantify the overall role of human-induced climate change. However, the majority of models and observations we have analysed show that intense rainfall has become heavier as Pakistan has warmed. Some of these models suggest climate change could have increased the rainfall intensity up to 50%. The devastating impacts were also driven by the proximity of human settlements, infrastructure (homes, buildings, bridges), and agricultural land to flood plains, inadequate infrastructure, limited ex-ante risk reduction capacity, an outdated river management system, underlying vulnerabilities driven by high poverty rates and socioeconomic factors (e.g. gender, age, income, and education), and ongoing political and economic instability. Both current conditions and the potential further increase in extreme peaks in rainfall over Pakistan in light of anthropogenic climate change, highlight the urgent need to reduce vulnerability to extreme weather in Pakistan.

Countries
United Kingdom, New Zealand, Netherlands, Denmark, New Zealand, Netherlands
Keywords

floodings, 550, extreme, Climate Change and Variability Research, Urban Flooding, 551, Vulnerability (computing), Computer security, Meteorology. Climatology, SDG 13 - Climate Action, Climate change, Psychology, 4101 Climate Change Impacts and Adaptation, monsoon, GE1-350, extreme event, Environmental resource management, Climatology, Global and Planetary Change, Extreme weather, Geography, Ecology, Geology, attribution, FOS: Psychology, Archaeology, Physical Sciences, 3701 Atmospheric Sciences, Monsoon, Climate Change, 41 Environmental Sciences, Flooding (psychology), 333, Environmental science, Global Flood Risk Assessment and Management, Meteorology, Climate-Related Exposures and Conditions, climate, Biology, 13 Climate Action, 37 Earth Sciences, FOS: Earth and related environmental sciences, Flood myth, Computer science, Environmental sciences, FOS: Biological sciences, rainfalls, Environmental Science, Global Drought Monitoring and Assessment, Psychotherapist, QC851-999, Flood Inundation Modeling, Precipitation Extremes, Climate Modeling

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    67
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
67
Top 10%
Top 10%
Top 1%
Green
gold