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Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios

Yıl 2025, Cilt: 8 Sayı: 6, 1739 - 1747, 15.11.2025
https://doi.org/10.34248/bsengineering.1746627

Öz

This study explores projected climate change within a Mediterranean basin, with a particular focus on Ermenek Creek in southern Türkiye. The assessment utilizes precipitation, maximum temperature, and minimum temperature simulations from 24 Global Circulation Models (GCMs) belonging to the latest, sixth phase of the Coupled Model Intercomparison Project (CMIP6) to develop multi-model ensemble (MME) projections under both the CMIP6 historical experiment and two shared socio-economic pathway (SSP) scenarios: the mid-range SSP2-4.5 and the high-end SSP5-8.5. The MMEs are constructed using the best-performing CMIP6 GCMs at the Alanya and Hadim meteorological stations (MSs), which serve as representative synoptic points for the Ermenek watershed. To adequately represent model projection uncertainty, ensemble means are computed for each climate variable using bias-corrected simulations of one to eight models, with the optimal ensemble size determined through a multi-criteria basin-wide performance assessment relative to observed data. Findings reveal that incorporating more than three GCMs yields only peripheral improvements in simulation performance across evaluation metrics. Consequently, climate projections are derived using MMEs composed of the top three performing models and are analyzed over three 25-year periods between the years 2025 and 2099, relative to the historical baseline of 1968-2014. By reaching the end of the century, annual average maximum/minimum temperatures are expected to rise by up to 3.04 °C/2.74 °C at the Alanya MS and 3.34 °C/2.94 °C at the Hadim MS under SSP2-4.5, and by up to 5.21 °C/4.52 °C and 5.98 °C/4.84 °C, respectively, under SSP5-8.5. Concurrently, annual mean daily precipitation is expected to decline by as much as 10.6% and 8.9% at the Alanya and Hadim MSs, respectively, under SSP2-4.5, and by 24.9% and 23.4% under SSP5-8.5.

Etik Beyan

Ethics committee approval was not required for this study because of there was no study on animals or humans.

Kaynakça

  • Ahmadalipour A, Rana A, Moradkhani H, Sharma A. 2017. Multi‐criteria evaluation of CMIP5 GCMs for climate change impact analysis. Theor Appl Climatol, 128: 71-87.
  • Ahmed K, Sachindra DA, Shahid S, Demirel MC, Chung E-S. 2019. Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics. Hydrol Earth Syst Sci, 23(11): 4803-4824.
  • Almeida MP, Perpiñán O, Narvarte L. 2015. PV power forecast using a nonparametric PV model. Sol Energy, 115: 354-368.
  • Bağçaci SÇ, Yucel I, Duzenli E, Yilmaz MT. 2021. Intercomparison of the expected change in the temperature and the precipitation retrieved from CMIP6 and CMIP5 climate projections: a Mediterranean hot spot case, Türkiye. Atmos Res, 256: 105576.
  • Boé J, Terray L. 2014. Land-sea contrast, soil-atmosphere and cloud-temperature interactions: interplays and roles in future summer European climate change. Clim Dyn, 42(3): 683-699.
  • Cannon AJ. 2018. Multivariate quantile mapping bias correction: an N‐dimensional probability density function transform for climate model simulations of multiple variables. Clim Dyn, 50: 31-49.
  • Chen W, Jiang Z, Li L. 2011. Probabilistic projections of climate change over China under the SRES A1B scenario using 28 AOGCMs. J Climate, 24: 4741-4756.
  • Cos J, Doblas-Reyes F, Jury M, Marcos R, Bretonnière P-A, Samsó M. 2022. The Mediterranean climate change hotspot in the CMIP5 and CMIP6 projections. Earth Syst Dynam, 13(1): 321-340.
  • Cramer W, Guiot J, Fader M, Garrabou J, Gattuso J-P, Iglesias A, Lange MA, Lionello P, Llasat MC, Paz S, Peñuelas J, Snoussi M, Toreti A, Tsimplis MN, Xoplaki E. 2018. Climate change and interconnected risks to sustainable development in the Mediterranean. Nature Clim Change, 8: 972-980.
  • DSI. 2023. General Directorate of State Hydraulic Works: Flow gauging yearbooks (1959-2015). General Directorate of State Hydraulic Works, Ankara, Türkiye.
  • ESGF. 2022. Earth System Grid Federation: WCRP Coupled Model Intercomparison Project (Phase 6). URL: https://esgf-node.llnl.gov/projects/cmip6/ (accessed date: May 15, 2022).
  • Evans JP, Ji F, Abramowitz G, Ekström M. 2013. Optimally choosing small ensemble members to produce robust climate simulations. Environ Res Lett, 8: 044050.
  • Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE. 2016. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci Model Dev, 9:1937-1958.
  • Eyring V, Cox PM, Flato GM, Gleckler PJ, Abramowitz G, Caldwell P, Collins WD, Gier BK, Hall AD, Hoffman FM, Hurtt GC, Jahn A, Jones CD, Klein SA, Krasting JP, Kwiatkowski L, Lorenz R, Maloney E, Meehl GA, Pendergrass AG, Pincus R, Ruane AC, Russell JL, Sanderson BM, Santer BD, Sherwood SC, Simpson IR, Stouffer RJ, Williamson MS. 2019. Taking climate model evaluation to the next level. Nat Clim Change, 9: 102-110.
  • Giorgi F. 2006. Climate change hot-spots. Geophys Res Lett, 33(8): L08707.
  • Gleick PH. 2014. Water, drought, climate change, and conflict in Syria. Weather Clim Soc, 6(3): 331-340.
  • Gorguner M, Kavvas ML. 2020. Modeling impacts of future climate change on reservoir storages and irrigation water demands in a Mediterranean basin. Sci Total Environ, 748: 141246.
  • Gupta HV, Kling H, Yilmaz KK, Martinez GF. 2009. Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modelling. J Hydrol, 377(1-2): 80-91.
  • Hui Y, Chen J, Xu C-Y, Xiong L, Chen H. 2019. Bias nonstationarity of global climate model outputs: the role of internal climate variability and climate model sensitivity. Int J Climatol, 39(4): 2278-2294.
  • Iturbide M, Gutiérrez JM, Alves LM, Bedia J, Cerezo-Mota R, Cimadevilla E, Cofiño AS, Di Luca A, Faria SH, Gorodetskaya IV, Hauser M, Herrera S, Hennessy K, Hewitt HT, Jones RG, Krakovska S, Manzanas R, Martínez-Castro D, Narisma GT, Nurhati IS, Pinto I, Seneviratne SI, van den Hurk B, Vera CS. 2020. An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets. Earth Syst Sci Data, 12(4): 2959-2970.
  • Jones PW. 1999. First- and second-order conservative remapping schemes for grids in spherical coordinates. Mon Weather Rev, 127(9): 2204-2210.
  • Kim J, Ivanov VY, Fatichi S. 2016. Climate change and uncertainty assessment over a hydroclimatic transect of Michigan. Stoch Environ Res Risk Assess, 30(3): 923-944.
  • Knutti R, Baumberger C, Hirsch Hadorn G. 2019. Uncertainty quantification using multiple models - prospects and challenges. In: Beisbart C, Saam NJ, editors. Computer simulation validation: fundamental concepts, methodological frameworks, and philosophical perspectives. Springer, Cham, Switzerland, pp: 835-855.
  • Knutti R, Furrer R, Tebaldi C, Cermak J, Meehl GA. 2010. Challenges in combining projections from multiple climate models. J Clim, 23: 2739-2758.
  • Legates DR, McCabe GJ. 1999. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour Res, 35(1): 233-241.
  • Lenderink G, Buishand A, van Deursen W. 2007. Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrol Earth Syst Sci, 11: 1145-1159.
  • Lionello P, Scarascia L. 2018. The relation between climate change in the Mediterranean region and global warming. Reg Environ Change, 18: 1481-1493.
  • Mendez M, Maathuis B, Hein-Griggs D, Alvarado-Gamboa L-F. 2020. Performance evaluation of bias correction methods for climate change monthly precipitation projections over Costa Rica. Water, 12(2): 482.
  • MGM. 2023a. Turkish State Meteorological Service: Daily precipitation, maximum temperature, and minimum temperature records of the Alanya meteorological station (Station ID: 17310). Turkish State Meteorol Service, Ankara, Türkiye.
  • MGM. 2023b. Turkish State Meteorological Service: Daily precipitation, maximum temperature, and minimum temperature records of the Hadim meteorological station (Station ID: 17928). Turkish State Meteorol Service, Ankara, Türkiye.
  • MGM. 2023c. Turkish State Meteorological Service: Long-term all parameters bulletin for the Alanya meteorological station (Station ID: 17310). Turkish State Meteorol Service, Ankara, Türkiye.
  • MGM. 2023d. Turkish State Meteorological Service: Long-term all parameters bulletin for the Hadim meteorological station (Station ID: 17928). Turkish State Meteorol Service, Ankara, Türkiye.
  • Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA. 2004. Quantification of modeling uncertainties in a large ensemble of climate change simulations. Nature, 430: 768-772.
  • O’Neill BC, Tebaldi C, van Vuuren DP, Eyring V, Friedlingstein P, Hurtt G, Knutti R, Kriegler E, Lamarque J-F, Lowe J, Meehl GA, Moss R, Riahi K, Sanderson BM. 2016. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci Model Dev, 9: 3461-3482.
  • Raju KS, Kumar DN. 2014. Ranking of global climate models for India using multicriterion analysis. Clim Res, 60: 103-117.
  • Rathjens H, Bieger K, Srinivasan R, Chaubey I, Arnold JG. 2016. CMhyd user manual: documentation for preparing simulated climate change data for hydrologic impact studies. URL: https://swat.tamu.edu/media/115265/bias_cor_man.pdf (accessed date: May 25, 2022).
  • Roberts NM, Lean HW. 2008. Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon Weather Rev, 136(1): 78-97.
  • Santer BD, Taylor KE, Gleckler PJ, Bonfils C, Barnett TP, Pierce DW, Wigley TML, Mears C, Wentz FJ, Brüggemann W, Gillett NP, Klein SA, Solomon S, Stott PA, Wehner MF. 2009. Incorporating model quality information in climate change detection and attribution studies. P Natl Acad Sci USA, 106: 14778-14783.
  • Schulzweida U. 2021. CDO user guide version 2.0.5. Max Planck Institute for Meteorology, Hamburg, Germany, pp: 2-5.
  • Seker M, Gumus V. 2022. Projection of temperature and precipitation in the Mediterranean region through multi-model ensemble from CMIP6. Atmos Res, 280:106440.
  • Sun C, Zhu L, Liu Y, Wei T, Guo Z. 2022. CMIP6 model simulation of concurrent continental warming holes in Eurasia and North America since 1990 and their relation to the Indo-Pacific SST warming. Global Planet Change, 213: 103824.
  • Tan ML, Juneng L, Tangang FT, Samat N, Chan NW, Yusop Z, Ngai ST. 2020. SouthEast Asia HydrO-meteorological droughT (SEA-HOT) framework: a case study in the Kelantan River Basin, Malaysia. Atmos Res, 246: 105155.
  • van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque J-F, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose SK. 2011. The representative concentration pathways: an overview. Clim Change, 109: 5-31.
  • Wang H‐M, Chen J, Cannon AJ, Xu C‐Y, Chen H. 2018. Transferability of climate simulation uncertainty to hydrological impacts. Hydrol Earth Syst Sci, 22: 3739-3759.
  • Wang H‐M, Chen J, Xu C‐Y, Zhang J, Chen H. 2020. A framework to quantify the uncertainty contribution of GCMs over multiple sources in hydrological impacts of climate change. Earths Future, 8: e2020EF001602.
  • Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O, Schewe J. 2014. The Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP): project framework. P Natl Acad Sci, 111(9): 3228-3232.
  • Yalcin E. 2023. Quantifying climate change impacts on hydropower production under CMIP6 multi-model ensemble projections using SWAT model. Hydrolog Sci J, 68: 1915-1936.
  • Yalcin E. 2024. A CMIP6 multi-model ensemble-based analysis of potential climate change impacts on irrigation water demand and supply using SWAT and CROPWAT models: a case study of Akmese Dam, Türkiye. Theor Appl Climatol, 155: 679-699.
  • Yip S, Ferro CAT, Stephenson DB, Hawkins E. 2011. A simple, coherent framework for partitioning uncertainty in climate predictions. J Clim, 24: 4634-4643.
  • Yolsu. 2010. Yalnizardic Hydroelectric Power Plant revised feasibility report. Yolsu Engineering Services Limited Company, Ankara, Türkiye, pp: 1-7.

Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios

Yıl 2025, Cilt: 8 Sayı: 6, 1739 - 1747, 15.11.2025
https://doi.org/10.34248/bsengineering.1746627

Öz

This study explores projected climate change within a Mediterranean basin, with a particular focus on Ermenek Creek in southern Türkiye. The assessment utilizes precipitation, maximum temperature, and minimum temperature simulations from 24 Global Circulation Models (GCMs) belonging to the latest, sixth phase of the Coupled Model Intercomparison Project (CMIP6) to develop multi-model ensemble (MME) projections under both the CMIP6 historical experiment and two shared socio-economic pathway (SSP) scenarios: the mid-range SSP2-4.5 and the high-end SSP5-8.5. The MMEs are constructed using the best-performing CMIP6 GCMs at the Alanya and Hadim meteorological stations (MSs), which serve as representative synoptic points for the Ermenek watershed. To adequately represent model projection uncertainty, ensemble means are computed for each climate variable using bias-corrected simulations of one to eight models, with the optimal ensemble size determined through a multi-criteria basin-wide performance assessment relative to observed data. Findings reveal that incorporating more than three GCMs yields only peripheral improvements in simulation performance across evaluation metrics. Consequently, climate projections are derived using MMEs composed of the top three performing models and are analyzed over three 25-year periods between the years 2025 and 2099, relative to the historical baseline of 1968-2014. By reaching the end of the century, annual average maximum/minimum temperatures are expected to rise by up to 3.04 °C/2.74 °C at the Alanya MS and 3.34 °C/2.94 °C at the Hadim MS under SSP2-4.5, and by up to 5.21 °C/4.52 °C and 5.98 °C/4.84 °C, respectively, under SSP5-8.5. Concurrently, annual mean daily precipitation is expected to decline by as much as 10.6% and 8.9% at the Alanya and Hadim MSs, respectively, under SSP2-4.5, and by 24.9% and 23.4% under SSP5-8.5.

Etik Beyan

Ethics committee approval was not required for this study because of there was no study on animals or humans.

Kaynakça

  • Ahmadalipour A, Rana A, Moradkhani H, Sharma A. 2017. Multi‐criteria evaluation of CMIP5 GCMs for climate change impact analysis. Theor Appl Climatol, 128: 71-87.
  • Ahmed K, Sachindra DA, Shahid S, Demirel MC, Chung E-S. 2019. Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics. Hydrol Earth Syst Sci, 23(11): 4803-4824.
  • Almeida MP, Perpiñán O, Narvarte L. 2015. PV power forecast using a nonparametric PV model. Sol Energy, 115: 354-368.
  • Bağçaci SÇ, Yucel I, Duzenli E, Yilmaz MT. 2021. Intercomparison of the expected change in the temperature and the precipitation retrieved from CMIP6 and CMIP5 climate projections: a Mediterranean hot spot case, Türkiye. Atmos Res, 256: 105576.
  • Boé J, Terray L. 2014. Land-sea contrast, soil-atmosphere and cloud-temperature interactions: interplays and roles in future summer European climate change. Clim Dyn, 42(3): 683-699.
  • Cannon AJ. 2018. Multivariate quantile mapping bias correction: an N‐dimensional probability density function transform for climate model simulations of multiple variables. Clim Dyn, 50: 31-49.
  • Chen W, Jiang Z, Li L. 2011. Probabilistic projections of climate change over China under the SRES A1B scenario using 28 AOGCMs. J Climate, 24: 4741-4756.
  • Cos J, Doblas-Reyes F, Jury M, Marcos R, Bretonnière P-A, Samsó M. 2022. The Mediterranean climate change hotspot in the CMIP5 and CMIP6 projections. Earth Syst Dynam, 13(1): 321-340.
  • Cramer W, Guiot J, Fader M, Garrabou J, Gattuso J-P, Iglesias A, Lange MA, Lionello P, Llasat MC, Paz S, Peñuelas J, Snoussi M, Toreti A, Tsimplis MN, Xoplaki E. 2018. Climate change and interconnected risks to sustainable development in the Mediterranean. Nature Clim Change, 8: 972-980.
  • DSI. 2023. General Directorate of State Hydraulic Works: Flow gauging yearbooks (1959-2015). General Directorate of State Hydraulic Works, Ankara, Türkiye.
  • ESGF. 2022. Earth System Grid Federation: WCRP Coupled Model Intercomparison Project (Phase 6). URL: https://esgf-node.llnl.gov/projects/cmip6/ (accessed date: May 15, 2022).
  • Evans JP, Ji F, Abramowitz G, Ekström M. 2013. Optimally choosing small ensemble members to produce robust climate simulations. Environ Res Lett, 8: 044050.
  • Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE. 2016. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci Model Dev, 9:1937-1958.
  • Eyring V, Cox PM, Flato GM, Gleckler PJ, Abramowitz G, Caldwell P, Collins WD, Gier BK, Hall AD, Hoffman FM, Hurtt GC, Jahn A, Jones CD, Klein SA, Krasting JP, Kwiatkowski L, Lorenz R, Maloney E, Meehl GA, Pendergrass AG, Pincus R, Ruane AC, Russell JL, Sanderson BM, Santer BD, Sherwood SC, Simpson IR, Stouffer RJ, Williamson MS. 2019. Taking climate model evaluation to the next level. Nat Clim Change, 9: 102-110.
  • Giorgi F. 2006. Climate change hot-spots. Geophys Res Lett, 33(8): L08707.
  • Gleick PH. 2014. Water, drought, climate change, and conflict in Syria. Weather Clim Soc, 6(3): 331-340.
  • Gorguner M, Kavvas ML. 2020. Modeling impacts of future climate change on reservoir storages and irrigation water demands in a Mediterranean basin. Sci Total Environ, 748: 141246.
  • Gupta HV, Kling H, Yilmaz KK, Martinez GF. 2009. Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modelling. J Hydrol, 377(1-2): 80-91.
  • Hui Y, Chen J, Xu C-Y, Xiong L, Chen H. 2019. Bias nonstationarity of global climate model outputs: the role of internal climate variability and climate model sensitivity. Int J Climatol, 39(4): 2278-2294.
  • Iturbide M, Gutiérrez JM, Alves LM, Bedia J, Cerezo-Mota R, Cimadevilla E, Cofiño AS, Di Luca A, Faria SH, Gorodetskaya IV, Hauser M, Herrera S, Hennessy K, Hewitt HT, Jones RG, Krakovska S, Manzanas R, Martínez-Castro D, Narisma GT, Nurhati IS, Pinto I, Seneviratne SI, van den Hurk B, Vera CS. 2020. An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets. Earth Syst Sci Data, 12(4): 2959-2970.
  • Jones PW. 1999. First- and second-order conservative remapping schemes for grids in spherical coordinates. Mon Weather Rev, 127(9): 2204-2210.
  • Kim J, Ivanov VY, Fatichi S. 2016. Climate change and uncertainty assessment over a hydroclimatic transect of Michigan. Stoch Environ Res Risk Assess, 30(3): 923-944.
  • Knutti R, Baumberger C, Hirsch Hadorn G. 2019. Uncertainty quantification using multiple models - prospects and challenges. In: Beisbart C, Saam NJ, editors. Computer simulation validation: fundamental concepts, methodological frameworks, and philosophical perspectives. Springer, Cham, Switzerland, pp: 835-855.
  • Knutti R, Furrer R, Tebaldi C, Cermak J, Meehl GA. 2010. Challenges in combining projections from multiple climate models. J Clim, 23: 2739-2758.
  • Legates DR, McCabe GJ. 1999. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour Res, 35(1): 233-241.
  • Lenderink G, Buishand A, van Deursen W. 2007. Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrol Earth Syst Sci, 11: 1145-1159.
  • Lionello P, Scarascia L. 2018. The relation between climate change in the Mediterranean region and global warming. Reg Environ Change, 18: 1481-1493.
  • Mendez M, Maathuis B, Hein-Griggs D, Alvarado-Gamboa L-F. 2020. Performance evaluation of bias correction methods for climate change monthly precipitation projections over Costa Rica. Water, 12(2): 482.
  • MGM. 2023a. Turkish State Meteorological Service: Daily precipitation, maximum temperature, and minimum temperature records of the Alanya meteorological station (Station ID: 17310). Turkish State Meteorol Service, Ankara, Türkiye.
  • MGM. 2023b. Turkish State Meteorological Service: Daily precipitation, maximum temperature, and minimum temperature records of the Hadim meteorological station (Station ID: 17928). Turkish State Meteorol Service, Ankara, Türkiye.
  • MGM. 2023c. Turkish State Meteorological Service: Long-term all parameters bulletin for the Alanya meteorological station (Station ID: 17310). Turkish State Meteorol Service, Ankara, Türkiye.
  • MGM. 2023d. Turkish State Meteorological Service: Long-term all parameters bulletin for the Hadim meteorological station (Station ID: 17928). Turkish State Meteorol Service, Ankara, Türkiye.
  • Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA. 2004. Quantification of modeling uncertainties in a large ensemble of climate change simulations. Nature, 430: 768-772.
  • O’Neill BC, Tebaldi C, van Vuuren DP, Eyring V, Friedlingstein P, Hurtt G, Knutti R, Kriegler E, Lamarque J-F, Lowe J, Meehl GA, Moss R, Riahi K, Sanderson BM. 2016. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci Model Dev, 9: 3461-3482.
  • Raju KS, Kumar DN. 2014. Ranking of global climate models for India using multicriterion analysis. Clim Res, 60: 103-117.
  • Rathjens H, Bieger K, Srinivasan R, Chaubey I, Arnold JG. 2016. CMhyd user manual: documentation for preparing simulated climate change data for hydrologic impact studies. URL: https://swat.tamu.edu/media/115265/bias_cor_man.pdf (accessed date: May 25, 2022).
  • Roberts NM, Lean HW. 2008. Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon Weather Rev, 136(1): 78-97.
  • Santer BD, Taylor KE, Gleckler PJ, Bonfils C, Barnett TP, Pierce DW, Wigley TML, Mears C, Wentz FJ, Brüggemann W, Gillett NP, Klein SA, Solomon S, Stott PA, Wehner MF. 2009. Incorporating model quality information in climate change detection and attribution studies. P Natl Acad Sci USA, 106: 14778-14783.
  • Schulzweida U. 2021. CDO user guide version 2.0.5. Max Planck Institute for Meteorology, Hamburg, Germany, pp: 2-5.
  • Seker M, Gumus V. 2022. Projection of temperature and precipitation in the Mediterranean region through multi-model ensemble from CMIP6. Atmos Res, 280:106440.
  • Sun C, Zhu L, Liu Y, Wei T, Guo Z. 2022. CMIP6 model simulation of concurrent continental warming holes in Eurasia and North America since 1990 and their relation to the Indo-Pacific SST warming. Global Planet Change, 213: 103824.
  • Tan ML, Juneng L, Tangang FT, Samat N, Chan NW, Yusop Z, Ngai ST. 2020. SouthEast Asia HydrO-meteorological droughT (SEA-HOT) framework: a case study in the Kelantan River Basin, Malaysia. Atmos Res, 246: 105155.
  • van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque J-F, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose SK. 2011. The representative concentration pathways: an overview. Clim Change, 109: 5-31.
  • Wang H‐M, Chen J, Cannon AJ, Xu C‐Y, Chen H. 2018. Transferability of climate simulation uncertainty to hydrological impacts. Hydrol Earth Syst Sci, 22: 3739-3759.
  • Wang H‐M, Chen J, Xu C‐Y, Zhang J, Chen H. 2020. A framework to quantify the uncertainty contribution of GCMs over multiple sources in hydrological impacts of climate change. Earths Future, 8: e2020EF001602.
  • Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O, Schewe J. 2014. The Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP): project framework. P Natl Acad Sci, 111(9): 3228-3232.
  • Yalcin E. 2023. Quantifying climate change impacts on hydropower production under CMIP6 multi-model ensemble projections using SWAT model. Hydrolog Sci J, 68: 1915-1936.
  • Yalcin E. 2024. A CMIP6 multi-model ensemble-based analysis of potential climate change impacts on irrigation water demand and supply using SWAT and CROPWAT models: a case study of Akmese Dam, Türkiye. Theor Appl Climatol, 155: 679-699.
  • Yip S, Ferro CAT, Stephenson DB, Hawkins E. 2011. A simple, coherent framework for partitioning uncertainty in climate predictions. J Clim, 24: 4634-4643.
  • Yolsu. 2010. Yalnizardic Hydroelectric Power Plant revised feasibility report. Yolsu Engineering Services Limited Company, Ankara, Türkiye, pp: 1-7.
Toplam 50 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Su Kaynakları Mühendisliği, Su Kaynakları ve Su Yapıları
Bölüm Research Articles
Yazarlar

Emrah Yalcin 0000-0002-3742-8866

Kubra Koparal Bozkurt 0000-0002-9836-5133

Erken Görünüm Tarihi 12 Kasım 2025
Yayımlanma Tarihi 15 Kasım 2025
Gönderilme Tarihi 20 Temmuz 2025
Kabul Tarihi 17 Eylül 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 8 Sayı: 6

Kaynak Göster

APA Yalcin, E., & Koparal Bozkurt, K. (2025). Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios. Black Sea Journal of Engineering and Science, 8(6), 1739-1747. https://doi.org/10.34248/bsengineering.1746627
AMA Yalcin E, Koparal Bozkurt K. Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios. BSJ Eng. Sci. Kasım 2025;8(6):1739-1747. doi:10.34248/bsengineering.1746627
Chicago Yalcin, Emrah, ve Kubra Koparal Bozkurt. “Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios”. Black Sea Journal of Engineering and Science 8, sy. 6 (Kasım 2025): 1739-47. https://doi.org/10.34248/bsengineering.1746627.
EndNote Yalcin E, Koparal Bozkurt K (01 Kasım 2025) Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios. Black Sea Journal of Engineering and Science 8 6 1739–1747.
IEEE E. Yalcin ve K. Koparal Bozkurt, “Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios”, BSJ Eng. Sci., c. 8, sy. 6, ss. 1739–1747, 2025, doi: 10.34248/bsengineering.1746627.
ISNAD Yalcin, Emrah - Koparal Bozkurt, Kubra. “Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios”. Black Sea Journal of Engineering and Science 8/6 (Kasım2025), 1739-1747. https://doi.org/10.34248/bsengineering.1746627.
JAMA Yalcin E, Koparal Bozkurt K. Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios. BSJ Eng. Sci. 2025;8:1739–1747.
MLA Yalcin, Emrah ve Kubra Koparal Bozkurt. “Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios”. Black Sea Journal of Engineering and Science, c. 8, sy. 6, 2025, ss. 1739-47, doi:10.34248/bsengineering.1746627.
Vancouver Yalcin E, Koparal Bozkurt K. Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios. BSJ Eng. Sci. 2025;8(6):1739-47.

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