Climate change projection using statistical downscaling model over southern coastal Iran
Iran is highly vulnerable to climate change, particularly evident in shifting precipitation and temperature patterns, especially in its southern coastal region. With these changing climate conditions, there is an urgent need for practical and adaptive management of water resources and energy supply...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024054471 |
| _version_ | 1827261785166577664 |
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| author | Sorour Esfandeh Afshin Danehkar Abdolrassoul Salmanmahiny Hassan Alipour Majid Kazemzadeh Marina Viorela Marcu Seyed Mohammad Moein Sadeghi |
| author_facet | Sorour Esfandeh Afshin Danehkar Abdolrassoul Salmanmahiny Hassan Alipour Majid Kazemzadeh Marina Viorela Marcu Seyed Mohammad Moein Sadeghi |
| author_sort | Sorour Esfandeh |
| collection | DOAJ |
| description | Iran is highly vulnerable to climate change, particularly evident in shifting precipitation and temperature patterns, especially in its southern coastal region. With these changing climate conditions, there is an urgent need for practical and adaptive management of water resources and energy supply to address the challenges posed by future climate change. Over the next two to three decades, the effects of climate change, such as precipitation and temperature, are expected to worsen, posing greater risks to water resources, agriculture, and infrastructure stability. Therefore, this study aims to evaluate the alterations in mean daily temperature (Tmean) and total daily rainfall (rrr24) utilizing climate change scenarios from both phases 5 and 6 of the Coupled Model Inter-comparison Project (CMIP5 and CMIP6, respectively) in the southern coastal regions of Iran (Hormozgan province), specifically north of the Strait of Hormuz. The predictions were generated using the Statistical Downscaling Model (SDSM) and National Centre for Environmental Prediction (NCEP) predictors, incorporating climate change scenarios from CMIP5 with Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 and CMIP6 with Shared Socioeconomic Pathways (SSPs) 1, 2, and 5. The analysis was conducted for three distinct time periods: the early 21st century (2021–2045), middle 21st century (2046–2071), and late 21st century (2071–2095). The results indicated that the CMIP5 model outperformed the CMIP6 model in simulating and predicting Tmean and rrr24. In addition, a significant increase in Tmean was observed across all the scenarios and time periods, with the most pronounced trend occurring in the middle and late 21st century future periods. This increase was already evident during the base period of 2021–2045 across all scenarios. Moreover, the fluctuations in precipitation throughout the region and across all scenarios were significant in the three examined future periods. The results indicated that among CMIP5 scenarios, RCP8.5 had highest changes of Tmean (+1.22 °C) in Bandar Lengeh station in 2071–2095 period. The lowest change magnitude of Tmean among CMIP5 scenarios was found in RCP4.5 (−1.94 °C) in Ch station in 2046–2070 period. The results indicated that among CMIP5 scenarios, RCP8.5 had highest changes of rrr24 (+150.2 mm) in Chabahar station in 2071–2095 period. The lowest change magnitude of rrr24 among CMIP5 scenarios was found in RCP8.5 (−25.8 mm) in Bandar Abbas station in 2046–2070 period. In conclusion, the study reveals that the coastal area of Hormozgan province will experience rising temperatures and changing rainfall patterns in the future. These changes may lead to challenges such as increased water and energy consumption, heightened risks of droughts or floods, and potential damage to agriculture and infrastructure. These findings offer valuable insights for implementing local mitigation policies and strategies and adapting to emerging climate changes in Hormozgan's coastal areas. For example, utilizing water harvesting technologies, implementing watershed management practices, and adopting new irrigation systems can address challenges like water consumption, agricultural impacts, and infrastructure vulnerability. Future research should accurately assess the effect of these changes in precipitation and temperature on water resources, forest ecosystems, agriculture, and other infrastructures in the study area to implement effective management measures. |
| first_indexed | 2024-04-24T07:05:34Z |
| format | Article |
| id | doaj.art-97f2c9a392bb464e8717c0705216bda6 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2025-03-22T03:03:53Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-97f2c9a392bb464e8717c0705216bda62024-05-01T05:08:45ZengElsevierHeliyon2405-84402024-04-01108e29416Climate change projection using statistical downscaling model over southern coastal IranSorour Esfandeh0Afshin Danehkar1Abdolrassoul Salmanmahiny2Hassan Alipour3Majid Kazemzadeh4Marina Viorela Marcu5Seyed Mohammad Moein Sadeghi6Department of Environmental Science and Engineering, Faculty of Natural Resources, University of Tehran, Karaj, Iran; Corresponding author.Department of Environmental Science and Engineering, Faculty of Natural Resources, University of Tehran, Karaj, Iran; Corresponding author.Department of Environmental Science, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, IranDepartment of Arid and Mountain Reclamation Engineering, Faculty of Natural Resources, University of Tehran, Karaj, IranFaculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, IranDepartment of Forest Engineering, Forest Management Planning and Terrestrial Measurements, Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, Şirul Beethoven 1, 500123, Brasov, RomaniaSchool of Forest, Fisheries, and Geomatics Sciences University of Florida, Gainesville, FL, USAIran is highly vulnerable to climate change, particularly evident in shifting precipitation and temperature patterns, especially in its southern coastal region. With these changing climate conditions, there is an urgent need for practical and adaptive management of water resources and energy supply to address the challenges posed by future climate change. Over the next two to three decades, the effects of climate change, such as precipitation and temperature, are expected to worsen, posing greater risks to water resources, agriculture, and infrastructure stability. Therefore, this study aims to evaluate the alterations in mean daily temperature (Tmean) and total daily rainfall (rrr24) utilizing climate change scenarios from both phases 5 and 6 of the Coupled Model Inter-comparison Project (CMIP5 and CMIP6, respectively) in the southern coastal regions of Iran (Hormozgan province), specifically north of the Strait of Hormuz. The predictions were generated using the Statistical Downscaling Model (SDSM) and National Centre for Environmental Prediction (NCEP) predictors, incorporating climate change scenarios from CMIP5 with Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 and CMIP6 with Shared Socioeconomic Pathways (SSPs) 1, 2, and 5. The analysis was conducted for three distinct time periods: the early 21st century (2021–2045), middle 21st century (2046–2071), and late 21st century (2071–2095). The results indicated that the CMIP5 model outperformed the CMIP6 model in simulating and predicting Tmean and rrr24. In addition, a significant increase in Tmean was observed across all the scenarios and time periods, with the most pronounced trend occurring in the middle and late 21st century future periods. This increase was already evident during the base period of 2021–2045 across all scenarios. Moreover, the fluctuations in precipitation throughout the region and across all scenarios were significant in the three examined future periods. The results indicated that among CMIP5 scenarios, RCP8.5 had highest changes of Tmean (+1.22 °C) in Bandar Lengeh station in 2071–2095 period. The lowest change magnitude of Tmean among CMIP5 scenarios was found in RCP4.5 (−1.94 °C) in Ch station in 2046–2070 period. The results indicated that among CMIP5 scenarios, RCP8.5 had highest changes of rrr24 (+150.2 mm) in Chabahar station in 2071–2095 period. The lowest change magnitude of rrr24 among CMIP5 scenarios was found in RCP8.5 (−25.8 mm) in Bandar Abbas station in 2046–2070 period. In conclusion, the study reveals that the coastal area of Hormozgan province will experience rising temperatures and changing rainfall patterns in the future. These changes may lead to challenges such as increased water and energy consumption, heightened risks of droughts or floods, and potential damage to agriculture and infrastructure. These findings offer valuable insights for implementing local mitigation policies and strategies and adapting to emerging climate changes in Hormozgan's coastal areas. For example, utilizing water harvesting technologies, implementing watershed management practices, and adopting new irrigation systems can address challenges like water consumption, agricultural impacts, and infrastructure vulnerability. Future research should accurately assess the effect of these changes in precipitation and temperature on water resources, forest ecosystems, agriculture, and other infrastructures in the study area to implement effective management measures.http://www.sciencedirect.com/science/article/pii/S2405844024054471IranClimate change projectionSouthern coastal IranCMIP5CMIP6Mean daily temperature |
| spellingShingle | Sorour Esfandeh Afshin Danehkar Abdolrassoul Salmanmahiny Hassan Alipour Majid Kazemzadeh Marina Viorela Marcu Seyed Mohammad Moein Sadeghi Climate change projection using statistical downscaling model over southern coastal Iran Heliyon Iran Climate change projection Southern coastal Iran CMIP5 CMIP6 Mean daily temperature |
| title | Climate change projection using statistical downscaling model over southern coastal Iran |
| title_full | Climate change projection using statistical downscaling model over southern coastal Iran |
| title_fullStr | Climate change projection using statistical downscaling model over southern coastal Iran |
| title_full_unstemmed | Climate change projection using statistical downscaling model over southern coastal Iran |
| title_short | Climate change projection using statistical downscaling model over southern coastal Iran |
| title_sort | climate change projection using statistical downscaling model over southern coastal iran |
| topic | Iran Climate change projection Southern coastal Iran CMIP5 CMIP6 Mean daily temperature |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024054471 |
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