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İklim Değişikliğinin Maksimum ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi

Year 2023, Volume: 12 Issue: 1, 141 - 156, 30.06.2023

Sinan Nacar

Abstract

İklim değişikliği ve küresel ısınmanın çevre üzerindeki etkilerinin her geçen gün artması iklim krizini tüm dünyada tartışılan en önemli konulardan birisi haline getirmiştir. Gelecekteki iklimin belirlenmesi ve değerlendirilmesi, iklim değişikliği etkilerini azaltmak ve bu değişikliklere uyum sağlamak açısından hayati öneme sahiptir. Bu çalışma, iklim değişikliğinin Tokat ilinin gelecek dönem maksimum ve minimum sıcaklıkları üzerindeki olası etkilerini belirlemeyi amaçlamaktadır. Bu amaçla CMIP5 arşivinde yer alan GFDL-ESM2M, HadGEM2-ES ve MPI-ESM-2M genel dolaşım modellerinin (GDM) dinamik ölçek indirgeme yöntemi ile bölgesel ölçeğe indirgenmiş RCP4.5 ve RCP8.5 senaryo çıktıları ve Tokat meteoroloji istasyonu maksimum ve minimum sıcaklık verileri kullanılmıştır. GDM çıktılarının 1975-2000 dönemi sıcaklık verileri yapay sinir ağları (YSA) tabanlı istatistiksel ölçek indirgeme modelinin girdileri olarak kullanılarak birleştirilmiş bir model kurulmuştur. Daha sonra bu model yardımı ile aynı istasyonun 2023-2092 dönemi maksimum ve minimum sıcaklık değerleri her iki senaryo için üretilmiş ve onar yıllık periyotlar için geçmiş dönemle karşılaştırılmıştır. Çalışma sonucunda Tokat meteoroloji istasyonu maksimum sıcaklıklarının gelecek dönemlerde RCP4.5 senaryosuna göre -0.7 ile 2.9 °C arasında, RCP8.5 senaryosuna göre ise -1.2 ile 4.4 °C arasında, minimum sıcaklıkların ise RCP4.5 senaryosuna göre -2.6 ile 5.2 °C arasında, RCP8.5 senaryosuna göre ise -4.8 ile 7.8 °C arasında değişiklik gösterebileceği tahmin edilmiştir.

Keywords

İklim değişikliği Tokat RCP Sıcaklık Yapay sinir ağları

Supporting Institution

Yok

Project Number

Yok

Thanks

Çalışma kapsamında kullanılan verilerin temin edilmesinde desteğini esirgemeyen Gaye Oğuztürk’e ve verileri temin eden Meteoroloji Genel Müdürlüğü yetkililerine ve çalışanlarına teşekkür ederim.

References

  • Anilan, T., Nacar, S., Kankal, M., Yuksek, O. 2020. Prediction of maximum annual flood discharges using artificial neural network approaches. Građevinar, 72(03.), 215-224.
  • Baghanam, A. H., Eslahi, M., Sheikhbabaei, A., Seifi, A. J. 2020. Assessing the impact of climate change over the northwest of Iran: an overview of statistical downscaling methods. Theoretical and Applied Climatology, 141, 1135-1150.
  • Bermúdez, M., Cea, L., Van Uytven, E., Willems, P., Farfán, J. F., Puertas, J. 2020. A robust method to update local river inundation maps using global climate model output and weather typing based statistical downscaling. Water Resources Management, 34, 4345-4362.
  • Byun, K., Chiu, C. M., Hamlet, A. F. 2019. Effects of 21st century climate change on seasonal flow regimes and hydrologic extremes over the Midwest and Great Lakes region of the US. Science of the Total Environment, 650, 1261-1277.
  • Chen, S. T., Yu, P. S., Tang, Y. H. 2010. Statistical downscaling of daily precipitation using support vector machines and multivariate analysis. Journal of hydrology, 385(1-4), 13-22.
  • Chu, J. L., Kang, H., Tam, C. Y., Park, C. K., Chen, C. T. 2008. Seasonal forecast for local precipitation over northern Taiwan using statistical downscaling. Journal of Geophysical Research: Atmospheres, 113(D12).
  • Crane, R. G., Hewitson, B. C. 1998. Doubled CO2 precipitation changes for the Susquehanna Basin: Down‐scaling from the Genesis general circulation model. International Journal of Climatology: A Journal of the Royal Meteorological Society, 18(1), 65-76.
  • Feng, K. 2020. Characteristics and Comparison of Different Downscaling Methods in Global Climate Model. Meteorological & Environmental Research, 11(1).
  • Fistikoglu, O., Okkan, U. 2011. Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for Tahtali River Basin in Turkey. Journal of Hydrologic Engineering, 16(2), 157-164.
  • Fowler, H. J., Ekström, M., Kilsby, C. G., Jones, P. D. 2005. New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 1. Assessment of control climate. Journal of Hydrology, 300(1-4), 212-233.
  • Hassan, W. H., Nile, B. K. 2021. Climate change and predicting future temperature in Iraq using CanESM2 and HadCM3 modeling. Modeling Earth Systems and Environment, 7, 737-748.
  • Huang, Y., Ma, Y., Liu, T., Luo, M. 2020. Climate change impacts on extreme flows under IPCC RCP scenarios in the mountainous Kaidu watershed, Tarim River basin. Sustainability, 12(5), 2090.
  • Legates, D. R., McCabe Jr, G. J. 1999. Evaluating the use of “goodness‐of‐fit” measures in hydrologic and hydroclimatic model validation. Water resources research,35(1), 233-241.
  • Mete B., Nacar, S., Bayram, A., Baki, O. T. 2023. Regresyon ve Yapay Sinir Ağları Yöntemleri ile Akarsularda Askıda Katı Madde Konsantrasyonu Tahmini. Doğal Afetler ve Çevre Dergisi, 9(1), 125-135.
  • Monier, E., Gao, X. 2015. Climate change impacts on extreme events in the United States: an uncertainty analysis. Climatic Change, 131, 67-81.
  • Nacar, S., Hınıs, M. A., Kankal, M. 2018. Forecasting daily streamflow discharges using various neural network models and training algorithms. KSCE Journal of Civil Engineering, 22, 3676-3685.
  • Nacar, S., Kankal, M., Okkan, U. 2021. EraInterim Re-analiz verileri kullanılarak istatistiksel ölçek indirgeme yöntemi ile doğu Karadeniz havzası aylık ortalama sıcaklık değerlerinin tahmin edilmesi. Doğal Afetler ve Çevre Dergisi, 7(1), 136-148.
  • Nacar, S., Kankal, M., Okkan, U. 2022a. Evaluation of the suitability of NCEP/NCAR, ERA-Interim and, ERA5 reanalysis data sets for statistical downscaling in the Eastern Black Sea Basin, Turkey. Meteorology and Atmospheric Physics, 134(2), 39.
  • Nacar, S., Kankal, M., Okkan, U. 2022b. Doğu Karadeniz Havzası Lokal Meteorolojik Değişkenleri İçin Bir Ölçek İndirgeme Uygulaması ve Senaryo Esaslı Öngörüler. Teknik Dergi, 33(6).
  • Nair, A. V., Wi, S., Gleason, C., Kayastha, R. B., Nikolopoulos, E. I. 2022. Climate change impact on precipitation-phase partitioning and streamflow for glacierized catchments in Nepal (No. EGU22-10735). Copernicus Meetings.
  • Nourani, V., Razzaghzadeh, Z., Baghanam, A. H., Molajou, A. 2019. ANN-based statistical downscaling of climatic parameters using decision tree predictor screening method. Theoretical and Applied Climatology, 137, 1729-1746.
  • Okkan, U., Inan, G. 2015a. Bayesian learning and relevance vector machines approach for downscaling of monthly precipitation. Journal of Hydrologic Engineering, 20(4), 04014051.
  • Okkan, U., Inan, G. 2015b. Statistical downscaling of monthly reservoir inflows for Kemer watershed in Turkey: use of machine learning methods, multiple GCMs and emission scenarios. International Journal of Climatology, 35(11), 3274-3295.
  • Okkan, U., Kirdemir, U. 2016. Downscaling of monthly precipitation using CMIP5 climate models operated under RCPs. Meteorological Applications, 23(3), 514-528.
  • Salimi, A. H., Masoompour Samakosh, J., Sharifi, E., Hassanvand, M. R., Noori, A., von Rautenkranz, H. 2019. Optimized artificial neural networks-based methods for statistical downscaling of gridded precipitation data. Water, 11(8), 1653.
  • Seker, M., Gumus, V. 2022. Projection of temperature and precipitation in the Mediterranean region through multi-model ensemble from CMIP6. Atmospheric Research, 280, 106440.
  • Sharafati, A., Pezeshki, E. 2020. A strategy to assess the uncertainty of a climate change impact on extreme hydrological events in the semi-arid Dehbar catchment in Iran. Theoretical and Applied Climatology, 139, 389-402.
  • Sillmann, J., Kharin, V. V., Zwiers, F. W., Zhang, X., Bronaugh, D. 2013. Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. Journal of geophysical research: atmospheres, 118(6), 2473-2493.
  • Şan, M., Nacar, S., Kankal, M., Bayram, A. 2022. Daily precipitation performances of regression-based statistical downscaling models in a basin with mountain and semi-arid climates. Stochastic Environmental Research and Risk Assessment, 1-25.
  • Tarek, M., Brissette, F., Arsenault, R. 2021. Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies. Hydrology and Earth System Sciences, 25(6), 3331-3350.
  • Timbal, B., Dufour, A., McAvaney, B. 2003. An estimate of future climate change for western France using a statistical downscaling technique. Climate Dynamics, 20, 807-823.
  • Tisseuil, C., Vrac, M., Lek, S., Wade, A. J. 2010. Statistical downscaling of river flows. Journal of Hydrology, 385(1-4), 279-291.
  • Uluer, O., Kırmacı, V., Ataş, Ş. 2009. Using the artificial neural network model for modeling the performance of the counter flow vortex tube. Expert Systems with Applications,36(10), 12256-12263.
  • Vu, M. T., Aribarg, T., Supratid, S., Raghavan, S. V., Liong, S. Y. 2016. Statistical downscaling rainfall using artificial neural network: significantly wetter Bangkok?. Theoretical and applied climatology, 126, 453-467.
  • Wilby, R. L., Wigley, T. M. L., Conway, D., Jones, P. D., Hewitson, B. C., Main, J., Wilks, D. S. 1998. Statistical downscaling of general circulation model output: A comparison of methods. Water resources research, 34(11), 2995-3008.
  • Yilmaz, B., Aras, E., Kankal, M., Nacar, S. 2019. Prediction of suspended sediment loading by means of hybrid artificial intelligence approaches. Acta Geophysicvunacara, 67, 1693-1705.

Year 2023, Volume: 12 Issue: 1, 141 - 156, 30.06.2023

Sinan Nacar

Abstract

Project Number

Yok

References

  • Anilan, T., Nacar, S., Kankal, M., Yuksek, O. 2020. Prediction of maximum annual flood discharges using artificial neural network approaches. Građevinar, 72(03.), 215-224.
  • Baghanam, A. H., Eslahi, M., Sheikhbabaei, A., Seifi, A. J. 2020. Assessing the impact of climate change over the northwest of Iran: an overview of statistical downscaling methods. Theoretical and Applied Climatology, 141, 1135-1150.
  • Bermúdez, M., Cea, L., Van Uytven, E., Willems, P., Farfán, J. F., Puertas, J. 2020. A robust method to update local river inundation maps using global climate model output and weather typing based statistical downscaling. Water Resources Management, 34, 4345-4362.
  • Byun, K., Chiu, C. M., Hamlet, A. F. 2019. Effects of 21st century climate change on seasonal flow regimes and hydrologic extremes over the Midwest and Great Lakes region of the US. Science of the Total Environment, 650, 1261-1277.
  • Chen, S. T., Yu, P. S., Tang, Y. H. 2010. Statistical downscaling of daily precipitation using support vector machines and multivariate analysis. Journal of hydrology, 385(1-4), 13-22.
  • Chu, J. L., Kang, H., Tam, C. Y., Park, C. K., Chen, C. T. 2008. Seasonal forecast for local precipitation over northern Taiwan using statistical downscaling. Journal of Geophysical Research: Atmospheres, 113(D12).
  • Crane, R. G., Hewitson, B. C. 1998. Doubled CO2 precipitation changes for the Susquehanna Basin: Down‐scaling from the Genesis general circulation model. International Journal of Climatology: A Journal of the Royal Meteorological Society, 18(1), 65-76.
  • Feng, K. 2020. Characteristics and Comparison of Different Downscaling Methods in Global Climate Model. Meteorological & Environmental Research, 11(1).
  • Fistikoglu, O., Okkan, U. 2011. Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for Tahtali River Basin in Turkey. Journal of Hydrologic Engineering, 16(2), 157-164.
  • Fowler, H. J., Ekström, M., Kilsby, C. G., Jones, P. D. 2005. New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 1. Assessment of control climate. Journal of Hydrology, 300(1-4), 212-233.
  • Hassan, W. H., Nile, B. K. 2021. Climate change and predicting future temperature in Iraq using CanESM2 and HadCM3 modeling. Modeling Earth Systems and Environment, 7, 737-748.
  • Huang, Y., Ma, Y., Liu, T., Luo, M. 2020. Climate change impacts on extreme flows under IPCC RCP scenarios in the mountainous Kaidu watershed, Tarim River basin. Sustainability, 12(5), 2090.
  • Legates, D. R., McCabe Jr, G. J. 1999. Evaluating the use of “goodness‐of‐fit” measures in hydrologic and hydroclimatic model validation. Water resources research,35(1), 233-241.
  • Mete B., Nacar, S., Bayram, A., Baki, O. T. 2023. Regresyon ve Yapay Sinir Ağları Yöntemleri ile Akarsularda Askıda Katı Madde Konsantrasyonu Tahmini. Doğal Afetler ve Çevre Dergisi, 9(1), 125-135.
  • Monier, E., Gao, X. 2015. Climate change impacts on extreme events in the United States: an uncertainty analysis. Climatic Change, 131, 67-81.
  • Nacar, S., Hınıs, M. A., Kankal, M. 2018. Forecasting daily streamflow discharges using various neural network models and training algorithms. KSCE Journal of Civil Engineering, 22, 3676-3685.
  • Nacar, S., Kankal, M., Okkan, U. 2021. EraInterim Re-analiz verileri kullanılarak istatistiksel ölçek indirgeme yöntemi ile doğu Karadeniz havzası aylık ortalama sıcaklık değerlerinin tahmin edilmesi. Doğal Afetler ve Çevre Dergisi, 7(1), 136-148.
  • Nacar, S., Kankal, M., Okkan, U. 2022a. Evaluation of the suitability of NCEP/NCAR, ERA-Interim and, ERA5 reanalysis data sets for statistical downscaling in the Eastern Black Sea Basin, Turkey. Meteorology and Atmospheric Physics, 134(2), 39.
  • Nacar, S., Kankal, M., Okkan, U. 2022b. Doğu Karadeniz Havzası Lokal Meteorolojik Değişkenleri İçin Bir Ölçek İndirgeme Uygulaması ve Senaryo Esaslı Öngörüler. Teknik Dergi, 33(6).
  • Nair, A. V., Wi, S., Gleason, C., Kayastha, R. B., Nikolopoulos, E. I. 2022. Climate change impact on precipitation-phase partitioning and streamflow for glacierized catchments in Nepal (No. EGU22-10735). Copernicus Meetings.
  • Nourani, V., Razzaghzadeh, Z., Baghanam, A. H., Molajou, A. 2019. ANN-based statistical downscaling of climatic parameters using decision tree predictor screening method. Theoretical and Applied Climatology, 137, 1729-1746.
  • Okkan, U., Inan, G. 2015a. Bayesian learning and relevance vector machines approach for downscaling of monthly precipitation. Journal of Hydrologic Engineering, 20(4), 04014051.
  • Okkan, U., Inan, G. 2015b. Statistical downscaling of monthly reservoir inflows for Kemer watershed in Turkey: use of machine learning methods, multiple GCMs and emission scenarios. International Journal of Climatology, 35(11), 3274-3295.
  • Okkan, U., Kirdemir, U. 2016. Downscaling of monthly precipitation using CMIP5 climate models operated under RCPs. Meteorological Applications, 23(3), 514-528.
  • Salimi, A. H., Masoompour Samakosh, J., Sharifi, E., Hassanvand, M. R., Noori, A., von Rautenkranz, H. 2019. Optimized artificial neural networks-based methods for statistical downscaling of gridded precipitation data. Water, 11(8), 1653.
  • Seker, M., Gumus, V. 2022. Projection of temperature and precipitation in the Mediterranean region through multi-model ensemble from CMIP6. Atmospheric Research, 280, 106440.
  • Sharafati, A., Pezeshki, E. 2020. A strategy to assess the uncertainty of a climate change impact on extreme hydrological events in the semi-arid Dehbar catchment in Iran. Theoretical and Applied Climatology, 139, 389-402.
  • Sillmann, J., Kharin, V. V., Zwiers, F. W., Zhang, X., Bronaugh, D. 2013. Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. Journal of geophysical research: atmospheres, 118(6), 2473-2493.
  • Şan, M., Nacar, S., Kankal, M., Bayram, A. 2022. Daily precipitation performances of regression-based statistical downscaling models in a basin with mountain and semi-arid climates. Stochastic Environmental Research and Risk Assessment, 1-25.
  • Tarek, M., Brissette, F., Arsenault, R. 2021. Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies. Hydrology and Earth System Sciences, 25(6), 3331-3350.
  • Timbal, B., Dufour, A., McAvaney, B. 2003. An estimate of future climate change for western France using a statistical downscaling technique. Climate Dynamics, 20, 807-823.
  • Tisseuil, C., Vrac, M., Lek, S., Wade, A. J. 2010. Statistical downscaling of river flows. Journal of Hydrology, 385(1-4), 279-291.
  • Uluer, O., Kırmacı, V., Ataş, Ş. 2009. Using the artificial neural network model for modeling the performance of the counter flow vortex tube. Expert Systems with Applications,36(10), 12256-12263.
  • Vu, M. T., Aribarg, T., Supratid, S., Raghavan, S. V., Liong, S. Y. 2016. Statistical downscaling rainfall using artificial neural network: significantly wetter Bangkok?. Theoretical and applied climatology, 126, 453-467.
  • Wilby, R. L., Wigley, T. M. L., Conway, D., Jones, P. D., Hewitson, B. C., Main, J., Wilks, D. S. 1998. Statistical downscaling of general circulation model output: A comparison of methods. Water resources research, 34(11), 2995-3008.
  • Yilmaz, B., Aras, E., Kankal, M., Nacar, S. 2019. Prediction of suspended sediment loading by means of hybrid artificial intelligence approaches. Acta Geophysicvunacara, 67, 1693-1705.
There are 36 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Araştırma Makaleleri
Authors

Sinan Nacar

Project Number Yok
Early Pub Date June 23, 2023
Publication Date June 30, 2023
Published in Issue Year 2023 Volume: 12 Issue: 1

Cite

APA Nacar, S. (2023). İklim Değişikliğinin Maksimum ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi. Gaziosmanpaşa Bilimsel Araştırma Dergisi, 12(1), 141-156.
AMA Nacar S. İklim Değişikliğinin Maksimum ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi. GBAD. June 2023;12(1):141-156.
Chicago Nacar, Sinan. “İklim Değişikliğinin Maksimum Ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi”. Gaziosmanpaşa Bilimsel Araştırma Dergisi 12, no. 1 (June 2023): 141-56.
EndNote Nacar S (June 1, 2023) İklim Değişikliğinin Maksimum ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi. Gaziosmanpaşa Bilimsel Araştırma Dergisi 12 1 141–156.
IEEE S. Nacar, “İklim Değişikliğinin Maksimum ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi”, GBAD, vol. 12, no. 1, pp. 141–156, 2023.
ISNAD Nacar, Sinan. “İklim Değişikliğinin Maksimum Ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi”. Gaziosmanpaşa Bilimsel Araştırma Dergisi 12/1 (June 2023), 141-156.
JAMA Nacar S. İklim Değişikliğinin Maksimum ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi. GBAD. 2023;12:141–156.
MLA Nacar, Sinan. “İklim Değişikliğinin Maksimum Ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi”. Gaziosmanpaşa Bilimsel Araştırma Dergisi, vol. 12, no. 1, 2023, pp. 141-56.
Vancouver Nacar S. İklim Değişikliğinin Maksimum ve Minimum Sıcaklıklar Üzerindeki Olası Etkilerinin Belirlenmesi. GBAD. 2023;12(1):141-56.
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