Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models

Climate change impacts are among the many challenges facing management of large cities. This study assesses the important climate variables under climate change impacts in Tehran, Iran, for 2021–2040. Eight Coupled Model Intercomparison Project, Phase 5 (CMIP5) models under the scenarios of Represen...

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Autores principales:	Hossein Shakeri, Homayoun Motiee, Edward McBean
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	climate change cmip5 fuzzy downscaling rcp sdsm tehran Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/58eb2f284f7749cfa282c628252c5ae4
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spelling	oai:doaj.org-article:58eb2f284f7749cfa282c628252c5ae42021-11-05T19:02:00ZProjection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models2040-22442408-935410.2166/wcc.2020.332https://doaj.org/article/58eb2f284f7749cfa282c628252c5ae42021-08-01T00:00:00Zhttp://jwcc.iwaponline.com/content/12/5/1802https://doaj.org/toc/2040-2244https://doaj.org/toc/2408-9354Climate change impacts are among the many challenges facing management of large cities. This study assesses the important climate variables under climate change impacts in Tehran, Iran, for 2021–2040. Eight Coupled Model Intercomparison Project, Phase 5 (CMIP5) models under the scenarios of Representative Concentration Pathway 2.6 (RCP2.6), RCP4.5, and RCP8.5 were used, and seven climate variables were projected utilizing the Fuzzy DownScaling Model (FDSM) and the Statistical DownScaling Model (SDSM). The FDSM and SDSM results underline the high performance of both models and the important capability of the FDSM, showing the increasing trend of annual changes in mean temperature (Tmean) and maximum temperature (Tmax), precipitation, and the mean wind speed (Wmean). The maximum increase of annual average in Tmean and Tmax and the Wmean among all scenarios will be in the order of 1.29 °C, 1.57 °C, and 0.8 m/s (for RCP8.5), and also the maximum increases of annual average precipitation will be 10 mm (for RCP2.6). Furthermore, the monthly long-term averages of Tmean and Tmax in all three scenarios show significant increases in summer. For precipitation, relative stability in summer, and increases in winter and early spring are predicted, but the changes in minimum temperature, relative humidity, and sunshine hours indicate relative stability. HIGHLIGHTS Projection of seven Tehran climate variables by eight CMIP5 models under RCP2.6, RCP4.5 and RCP8.5 in 2021-2040.; Downscaling by both SDSM and FDSM demonstrate there is no single model better than all other models, for all climate variables.; The performance of FDSM in downscaling of the temperature was shown to be the best model for Tehran.; FDSM in this research proved to be innovative and superior to other downscaling models which use the Sugeno system.; Predicted increases in annual temperature, precipitation, mean wind speed and relative stability in changes of relative humidity and sunshine for Tehran in 2021–2040 are provided.;Hossein ShakeriHomayoun MotieeEdward McBeanIWA Publishingarticleclimate changecmip5fuzzy downscalingrcpsdsmtehranEnvironmental technology. Sanitary engineeringTD1-1066Environmental sciencesGE1-350ENJournal of Water and Climate Change, Vol 12, Iss 5, Pp 1802-1823 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	climate change cmip5 fuzzy downscaling rcp sdsm tehran Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
spellingShingle	climate change cmip5 fuzzy downscaling rcp sdsm tehran Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Hossein Shakeri Homayoun Motiee Edward McBean Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models
description	Climate change impacts are among the many challenges facing management of large cities. This study assesses the important climate variables under climate change impacts in Tehran, Iran, for 2021–2040. Eight Coupled Model Intercomparison Project, Phase 5 (CMIP5) models under the scenarios of Representative Concentration Pathway 2.6 (RCP2.6), RCP4.5, and RCP8.5 were used, and seven climate variables were projected utilizing the Fuzzy DownScaling Model (FDSM) and the Statistical DownScaling Model (SDSM). The FDSM and SDSM results underline the high performance of both models and the important capability of the FDSM, showing the increasing trend of annual changes in mean temperature (Tmean) and maximum temperature (Tmax), precipitation, and the mean wind speed (Wmean). The maximum increase of annual average in Tmean and Tmax and the Wmean among all scenarios will be in the order of 1.29 °C, 1.57 °C, and 0.8 m/s (for RCP8.5), and also the maximum increases of annual average precipitation will be 10 mm (for RCP2.6). Furthermore, the monthly long-term averages of Tmean and Tmax in all three scenarios show significant increases in summer. For precipitation, relative stability in summer, and increases in winter and early spring are predicted, but the changes in minimum temperature, relative humidity, and sunshine hours indicate relative stability. HIGHLIGHTS Projection of seven Tehran climate variables by eight CMIP5 models under RCP2.6, RCP4.5 and RCP8.5 in 2021-2040.; Downscaling by both SDSM and FDSM demonstrate there is no single model better than all other models, for all climate variables.; The performance of FDSM in downscaling of the temperature was shown to be the best model for Tehran.; FDSM in this research proved to be innovative and superior to other downscaling models which use the Sugeno system.; Predicted increases in annual temperature, precipitation, mean wind speed and relative stability in changes of relative humidity and sunshine for Tehran in 2021–2040 are provided.;
format	article
author	Hossein Shakeri Homayoun Motiee Edward McBean
author_facet	Hossein Shakeri Homayoun Motiee Edward McBean
author_sort	Hossein Shakeri
title	Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models
title_short	Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models
title_full	Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models
title_fullStr	Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models
title_full_unstemmed	Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models
title_sort	projection of important climate variables in large cities under the cmip5–rcp scenarios using sdsm and fuzzy downscaling models
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/58eb2f284f7749cfa282c628252c5ae4
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Projection of important climate variables in large cities under the CMIP5–RCP scenarios using SDSM and fuzzy downscaling models

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