{"title":"Investigating the skills of HighResMIP in capturing historical and future mean precipitation shifts over Pakistan","authors":"Kanzul Eman, Eun-Sung Chung, Brian Odhiambo Ayugi","doi":"10.1002/joc.8558","DOIUrl":null,"url":null,"abstract":"<p>Climatic change over the globe due to global warming affects the characteristics of climate variables that have critical implications on large fraction of population that depends on agriculture for livelihood like Pakistan. Consequently, this study examined how high horizontal grid resolution CMIP6 models simulate the observed precipitation variability during 1981–2014 and further explored the future changes during 2017–2050 under high emission scenario SSP5-8.5 over Pakistan region. The performances of 12 (CMIP6) High Resolution Model Inter-comparison Project version 1.0 (hereafter; HighResMIP) GCMs and their ensemble means in reproducing the observed climate were calculated at each station in the study domain and formed the basis for deriving HighResMIP ranking. Further, the study employed Shannon's Entropy and a modified version of Criteria Importance through Inter-Criteria Correlation (D-CRITIC) method to build an ensemble mean from the best performing models. Evaluation of HighResMIP GCMs performance revealed that most models showed mixed signals in the region, with fewer models such as HadGEM3-GC31-HH, HadGEM3-GC31-HM and HadGEM3-GC31-MM showing good agreement with the observed precipitation. Overall, HighResMIP multi-model ensemble outperforms precipitation distribution over individual models. D-CRITIC based ensemble mean implies higher increase in precipitation than entropy approach. Future changes depict an increase in mean annual in the northern region relative to the historical period. A pronounced increase of about 16%–18% in precipitation was noted in HadGEM3-GC31-HH and HiRAM-SIT-HR. Conversely, FGOAL-f3-H project noteworthy reduction (21%) in precipitation in the near future (2017–2050). The projected seasonal precipitation shows upsurge pattern of 5%–28% in pre-monsoon season, whereas the reduction in monsoon precipitation is projected to be 29%–40%. The findings of this study can help in building future climate resilience and developing strategic policies in Pakistan.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"44 11","pages":"3888-3911"},"PeriodicalIF":3.5000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8558","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Climatology","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/joc.8558","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Climatic change over the globe due to global warming affects the characteristics of climate variables that have critical implications on large fraction of population that depends on agriculture for livelihood like Pakistan. Consequently, this study examined how high horizontal grid resolution CMIP6 models simulate the observed precipitation variability during 1981–2014 and further explored the future changes during 2017–2050 under high emission scenario SSP5-8.5 over Pakistan region. The performances of 12 (CMIP6) High Resolution Model Inter-comparison Project version 1.0 (hereafter; HighResMIP) GCMs and their ensemble means in reproducing the observed climate were calculated at each station in the study domain and formed the basis for deriving HighResMIP ranking. Further, the study employed Shannon's Entropy and a modified version of Criteria Importance through Inter-Criteria Correlation (D-CRITIC) method to build an ensemble mean from the best performing models. Evaluation of HighResMIP GCMs performance revealed that most models showed mixed signals in the region, with fewer models such as HadGEM3-GC31-HH, HadGEM3-GC31-HM and HadGEM3-GC31-MM showing good agreement with the observed precipitation. Overall, HighResMIP multi-model ensemble outperforms precipitation distribution over individual models. D-CRITIC based ensemble mean implies higher increase in precipitation than entropy approach. Future changes depict an increase in mean annual in the northern region relative to the historical period. A pronounced increase of about 16%–18% in precipitation was noted in HadGEM3-GC31-HH and HiRAM-SIT-HR. Conversely, FGOAL-f3-H project noteworthy reduction (21%) in precipitation in the near future (2017–2050). The projected seasonal precipitation shows upsurge pattern of 5%–28% in pre-monsoon season, whereas the reduction in monsoon precipitation is projected to be 29%–40%. The findings of this study can help in building future climate resilience and developing strategic policies in Pakistan.
期刊介绍:
The International Journal of Climatology aims to span the well established but rapidly growing field of climatology, through the publication of research papers, short communications, major reviews of progress and reviews of new books and reports in the area of climate science. The Journal’s main role is to stimulate and report research in climatology, from the expansive fields of the atmospheric, biophysical, engineering and social sciences. Coverage includes: Climate system science; Local to global scale climate observations and modelling; Seasonal to interannual climate prediction; Climatic variability and climate change; Synoptic, dynamic and urban climatology, hydroclimatology, human bioclimatology, ecoclimatology, dendroclimatology, palaeoclimatology, marine climatology and atmosphere-ocean interactions; Application of climatological knowledge to environmental assessment and management and economic production; Climate and society interactions