A novel semi data dimension reduction type weighting scheme of the multi-model ensemble for accurate assessment of twenty-first century drought

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dc.authoriddhahbi, sami/0000-0002-0126-2366
dc.authoridKartal, Veysi/0000-0003-4671-1281
dc.contributor.authorMukhtar, Alina
dc.contributor.authorAli, Zulfiqar
dc.contributor.authorNazeer, Amna
dc.contributor.authorDhahbi, Sami
dc.contributor.authorKartal, Veysi
dc.contributor.authorDeebani, Wejdan
dc.date.accessioned2024-12-24T19:24:25Z
dc.date.available2024-12-24T19:24:25Z
dc.date.issued2024
dc.departmentSiirt Üniversitesi
dc.description.abstractAccurately and reliably predicting droughts under multiple models of Global Climate Models (GCMs) is a challenging task. To address this challenge, the Multimodel Ensemble (MME) method has become a valuable tool for merging multiple models and producing more accurate forecasts. This paper aims to enhance drought monitoring modules for the twenty-first century using multiple GCMs. To achieve this goal, the research introduces a new weighing paradigm called the Multimodel Homo-min Pertinence-max Hybrid Weighted Average (MHmPmHWAR) for the accurate aggregation of multiple GCMs. Secondly, the research proposes a new drought index called the Condensed Multimodal Multi-Scalar Standardized Drought Index (CMMSDI). To assess the effectiveness of MHmPmHWAR, the research compared its findings with the Simple Model Average (SMA). In the application, eighteen different GCM models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were considered at thirty-two grid points of the Tibet Plateau region. Mann-Kendall (MK) test statistics and Steady States Probabilities (SSPs) of Markov chain were used to assess the long-term trend in drought and its classes. The analysis of trends indicated that the number of grid points demonstrating an upward trend was significantly greater than those displaying a downward trend in terms of spatial coverage, at a significance level of 0.05. When examining scenario SSP1-2.6, the probability of moderate wet and normal drought was greater in nearly all temporal scales than other categories. The outcomes of SSP2-4.5 demonstrated that the likelihoods of moderate drought and normal drought were higher than other classifications. Additionally, the results of SSP5-8.5 were comparable to those of SSP2-4.5, underscoring the importance of taking effective actions to alleviate drought impacts in the future. The results demonstrate the effectiveness of the MHmPmHWAR and CMMSDI approaches in predicting droughts under multiple GCMs, which can contribute to effective drought monitoring and management.
dc.description.sponsorshipDeanship of Scientific Research at King Khalid University [RGP2/337/44]
dc.description.sponsorshipThe authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under grant number RGP2/337/44.
dc.identifier.doi10.1007/s00477-024-02723-1
dc.identifier.endpage2973
dc.identifier.issn1436-3240
dc.identifier.issn1436-3259
dc.identifier.issue8
dc.identifier.scopus2-s2.0-85190135573
dc.identifier.scopusqualityQ1
dc.identifier.startpage2949
dc.identifier.urihttps://doi.org/10.1007/s00477-024-02723-1
dc.identifier.urihttps://hdl.handle.net/20.500.12604/5984
dc.identifier.volume38
dc.identifier.wosWOS:001201313800003
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofStochastic Environmental Research and Risk Assessment
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectGlobal Climate Models
dc.subjectDrought
dc.subjectEnsemble
dc.subjectLong term probabilities
dc.titleA novel semi data dimension reduction type weighting scheme of the multi-model ensemble for accurate assessment of twenty-first century drought
dc.typeArticle

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