{"title":"Regional ensemble of CMIP6 global climate models for Sakha (Yakutia) Republic, Northern Eurasia","authors":"","doi":"10.1016/j.polar.2024.101066","DOIUrl":null,"url":null,"abstract":"<div><p><span>Future climate projections based on multi-model ensemble approach are seen as more reliable, but not all models are equally performant at reproducing climate features at a regional scale. An optimal regional GCM ensemble was developed for Sakha (Yakutia) Republic based on error statistics and spatial correlation metrics. Historical Coupled Model Intercomparison Project, version 6 (CMIP6) simulations from 48 global climate models (GCMs) were used to evaluate model quality compared to mean annual air temperature (MAAT) reanalysis data for 1961–1990, 1971–2000 and 1981–2010 reference periods, and the MAAT change between 1961-1990 and 1981–2010, ΔT</span><sub>81-61</sub>. The best-performing reanalysis, GHCN-CAMS, was validated using observational data. This five-member ensemble includes CESM2-WACCM, CMCC-ESM2, CNRM-CM6-1-HR, INM-CM5-0, MPI-ESM1-2-HR models, weighted by Pearson's coefficient of spatial correlation between observed and modeled ΔT<sub>81-61</sub><span> fields. Model weighting based on spatial correlation metrics improved the performance of the developed multi-model regional ensemble, which can be used in projecting future climate under different climate change scenarios.</span></p></div>","PeriodicalId":20316,"journal":{"name":"Polar Science","volume":"41 ","pages":"Article 101066"},"PeriodicalIF":1.5000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Polar Science","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1873965224000355","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Future climate projections based on multi-model ensemble approach are seen as more reliable, but not all models are equally performant at reproducing climate features at a regional scale. An optimal regional GCM ensemble was developed for Sakha (Yakutia) Republic based on error statistics and spatial correlation metrics. Historical Coupled Model Intercomparison Project, version 6 (CMIP6) simulations from 48 global climate models (GCMs) were used to evaluate model quality compared to mean annual air temperature (MAAT) reanalysis data for 1961–1990, 1971–2000 and 1981–2010 reference periods, and the MAAT change between 1961-1990 and 1981–2010, ΔT81-61. The best-performing reanalysis, GHCN-CAMS, was validated using observational data. This five-member ensemble includes CESM2-WACCM, CMCC-ESM2, CNRM-CM6-1-HR, INM-CM5-0, MPI-ESM1-2-HR models, weighted by Pearson's coefficient of spatial correlation between observed and modeled ΔT81-61 fields. Model weighting based on spatial correlation metrics improved the performance of the developed multi-model regional ensemble, which can be used in projecting future climate under different climate change scenarios.
期刊介绍:
Polar Science is an international, peer-reviewed quarterly journal. It is dedicated to publishing original research articles for sciences relating to the polar regions of the Earth and other planets. Polar Science aims to cover 15 disciplines which are listed below; they cover most aspects of physical sciences, geosciences and life sciences, together with engineering and social sciences. Articles should attract the interest of broad polar science communities, and not be limited to the interests of those who work under specific research subjects. Polar Science also has an Open Archive whereby published articles are made freely available from ScienceDirect after an embargo period of 24 months from the date of publication.
- Space and upper atmosphere physics
- Atmospheric science/climatology
- Glaciology
- Oceanography/sea ice studies
- Geology/petrology
- Solid earth geophysics/seismology
- Marine Earth science
- Geomorphology/Cenozoic-Quaternary geology
- Meteoritics
- Terrestrial biology
- Marine biology
- Animal ecology
- Environment
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- Humanities and social sciences.