CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts
Abstract While it is widely believed that the intense rainfall in summer 2022 over Pakistan was substantially exacerbated by anthropogenic climate change1,2, climate models struggled to confirm this3,4. Using a high-resolution operational seasonal forecasting system that successfully predicted the e...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-025-01136-3 |
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| author | Antje Weisheimer Tim N. Palmer Nicholas J. Leach Myles R. Allen Christopher D. Roberts Muhammad Adnan Abid |
| author_facet | Antje Weisheimer Tim N. Palmer Nicholas J. Leach Myles R. Allen Christopher D. Roberts Muhammad Adnan Abid |
| author_sort | Antje Weisheimer |
| collection | DOAJ |
| description | Abstract While it is widely believed that the intense rainfall in summer 2022 over Pakistan was substantially exacerbated by anthropogenic climate change1,2, climate models struggled to confirm this3,4. Using a high-resolution operational seasonal forecasting system that successfully predicted the extreme wet conditions, we perform counterfactual experiments simulating pre-industrial and future conditions. Both experiments also exhibit strong anomalous rainfall, indicating a limited role of CO2-induced forcing. We attribute 10% of the total rainfall to historical increases in CO2 and ocean temperature. However, further increases in the future suggest a weak mean precipitation reduction but with increased variability. By decomposing rainfall and large-scale circulation into CO2 and SST-related signals, we illustrate a tendency for these signals to compensate each other in future scenarios. This suggests that historical CO2 impacts may not reliably predict future responses. Accurately capturing local dynamics is therefore essential for regional climate adaptation planning and for informing loss and damage discussions. |
| format | Article |
| id | doaj-art-7131ec6cc61b42fb9b358fa4259e3213 |
| institution | Kabale University |
| issn | 2397-3722 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Climate and Atmospheric Science |
| spelling | doaj-art-7131ec6cc61b42fb9b358fa4259e32132025-08-20T03:42:30ZengNature Portfolionpj Climate and Atmospheric Science2397-37222025-07-018111510.1038/s41612-025-01136-3CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecastsAntje Weisheimer0Tim N. Palmer1Nicholas J. Leach2Myles R. Allen3Christopher D. Roberts4Muhammad Adnan Abid5National Centre for Atmospheric Science (NCAS), Department of Physics, University of OxfordDepartment of Physics, University of OxfordNational Centre for Atmospheric Science (NCAS), Department of Physics, University of OxfordDepartment of Physics, University of OxfordECMWFNational Centre for Atmospheric Science (NCAS), Department of Physics, University of OxfordAbstract While it is widely believed that the intense rainfall in summer 2022 over Pakistan was substantially exacerbated by anthropogenic climate change1,2, climate models struggled to confirm this3,4. Using a high-resolution operational seasonal forecasting system that successfully predicted the extreme wet conditions, we perform counterfactual experiments simulating pre-industrial and future conditions. Both experiments also exhibit strong anomalous rainfall, indicating a limited role of CO2-induced forcing. We attribute 10% of the total rainfall to historical increases in CO2 and ocean temperature. However, further increases in the future suggest a weak mean precipitation reduction but with increased variability. By decomposing rainfall and large-scale circulation into CO2 and SST-related signals, we illustrate a tendency for these signals to compensate each other in future scenarios. This suggests that historical CO2 impacts may not reliably predict future responses. Accurately capturing local dynamics is therefore essential for regional climate adaptation planning and for informing loss and damage discussions.https://doi.org/10.1038/s41612-025-01136-3 |
| spellingShingle | Antje Weisheimer Tim N. Palmer Nicholas J. Leach Myles R. Allen Christopher D. Roberts Muhammad Adnan Abid CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts npj Climate and Atmospheric Science |
| title | CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts |
| title_full | CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts |
| title_fullStr | CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts |
| title_full_unstemmed | CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts |
| title_short | CO2-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts |
| title_sort | co2 induced climate change assessment for the extreme 2022 pakistan rainfall using seasonal forecasts |
| url | https://doi.org/10.1038/s41612-025-01136-3 |
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