Journals / Ege Coğrafya Dergisi / 2023 / Cilt: 32 Sayı: 2

2040 Modeling of Maximum-Minimum Temperature Averages and Precipitation Amount in Turkey with Google Earth Engine

Türkiye’de Maksimum-Minimum Sıcaklık Ortalamaları ve Yağış Tutarının Google Earth Engine ile 2040 Yılı Modellemesi

Mücahit Coşkun(KARABÜK ÜNİVERSİTESİ)0000-0002-7881-6742
Hüseyin Şahiner(SİNOP ÜNİVERSİTESİ)0000-0002-3191-1590
Onur Canbulat(KARABÜK ÜNİVERSİTESİ)0000-0002-9269-4219
Ahmet Öztürk(KARABÜK ÜNİVERSİTESİ)0000-0002-4074-0201
Enes Taşoğlu(NİĞDE ÜNİVERSİTESİ)0000-0002-6365-6926
Ferhat Toprak(KARABÜK ÜNİVERSİTESİ)0000-0001-5452-5855
Pages
253–271
Publication Date
2023-12-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In general, there is no positive or negative trend when the average precipitation of the whole area of Turkey is taken into consideration.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Global climate change, which has been increasing its impact in recent years, has become a problem that humanity must take precautions and increase its adaptation efforts.
📊
Key Findings & Data:The most prominent indicators of the differences in climatic parameters are heat waves that last longer, forest fires, droughts, heavy rainfall, floods and landslides that increase in frequency with heat waves.
💡
Conclusion & Impact:In general, there is no positive or negative trend when the average precipitation of the whole area of Turkey is taken into consideration.
🔬Design:Modeling & Simulation
📍Scope:2005-2040 Verileri
⚙️Variables:CMIP5 · iklim modellemesi · Google Earth Engine

Abstract

Global climate change, which has been increasing its impact in recent years, has become a problem that humanity must take precautions and increase its adaptation efforts. The most prominent indicators of the differences in climatic parameters are heat waves that last longer, forest fires, droughts, heavy rainfall, floods and landslides that increase in frequency with heat waves. Although climate change has different consequences in different parts of the world, the Mediterranean Basin, in which Turkey is located, is one of the areas expected to be most affected by these changes. The aim of this study is to provide future projections on Turkey's temperature and precipitation climate variables and to determine the possible differentiations. Models developed by scientific organizations and emission scenarios applied are important methods for predicting possible future changes. In the study, multiple model averages of the models and scenarios included in the Coupled Model Intercomparison Project Phase 5 (CMIP5) project were used. The emission scenarios included in the analysis are RCP4.5 and RCP8.5. The analyses of the study were carried out with Google Earth Engine cloud operating system and mapped with ArcGIS 10.4 program. As a result of the analysis, Turkey will face warmer days in the period 2005-2040 compared to today's averages. The upward trend in maximum temperature averages is stronger. The climatic conditions observed on the Mediterranean coasts will expand their sphere of influence towards the Aegean and Marmara regions in the coming years. Eastern Anatolia will experience stronger increases in minimum temperature averages. Precipitation will decrease in the Mediterranean-Aegean coasts and inland regions, and partially increase in the Eastern Black Sea coasts. In general, there is no positive or negative trend when the average precipitation of the whole area of Turkey is taken into consideration.

Özet

Son yıllarda etkisini giderek artıran küresel iklim değişikliği, artık insanlığın önlem alması ve uyum çabalarını artırması gereken bir problem haline gelmiştir. Daha uzun süre maruz kalınan sıcak hava dalgaları, sıcak hava dalgaları ile birlikte sıklığı giderek artan orman yangınları, kuraklık, şiddetli yağışlar, sel ve heyelan olayları iklimsel parametrelerdeki farklılaşmaların en belirgin göstergeleridir. İklim değişikliğinin Dünya’nın farklı alanlarında farklı sonuçları ortaya çıksa da, Türkiye’nin içinde bulunduğu Akdeniz Havzası bu değişikliklerden en fazla etkilenmesi beklenen sahalardandır. Türkiye'nin sıcaklık ve yağış iklim değişkenleri üzerine gelecek öngörüsü sunmak ve olası farklılaşmaları belirlemek çalışmanın amacını oluşturmaktadır. Bilimsel kuruluşlar tarafından geliştirilen modeller ve uygulanan emisyon senaryoları, gelecekte yaşanabilecek olası değişikliklerin tahmini için önemli metotlardır. Araştırmada Coupled Model Intercomparison Project Phase 5 (CMIP5) projesi kapsamında yer alan modellere ve senaryolara ait çoklu model ortalaması kullanılmıştır. Analizlere dahil edilen emisyon senaryoları RCP4.5 ve RCP8.5’tir. Çalışmaya ait analizler Google Earth Engine bulut işletim sistemi ile gerçekleştirilmiş ve ArcGIS 10.4 programı ile haritalanmıştır. Yapılan analizler sonucunda 2005-2040 döneminde Türkiye, bugünkü ortalamalara göre daha sıcak günler ile karşı karşıya kalacaktır. Maksimum sıcaklık ortalamalarındaki artış trendi daha kuvvetlidir. Akdeniz kıyılarında görülen iklim şartları ilerleyen yıllarda etki sahasını Ege ve Marmara bölgelerine doğru genişletecektir. Doğu Anadolu Bölgesi’nde minimum sıcaklık ortalamalarında daha kuvvetli artışlar yaşanacaktır. Yağış miktarlarında Akdeniz-Ege kıyıları ve iç bölgelerde azalma, Doğu Karadeniz kıyılarında kısmen artışlar görülecektir. Genel olarak bütün Türkiye arazisinin ortalama yağışı dikkate alındığında, pozitif ya da negatif yönde bir eğilim mevcut değildir.

🔖

Cite This Article

Coşkun, M., Şahiner, H., Canbulat, O., Öztürk, A., Taşoğlu, E., Toprak, F. (2023). 2040 Modeling of Maximum-Minimum Temperature Averages and Precipitation Amount in Turkey with Google Earth Engine. Ege Coğrafya Dergisi, Cilt: 32 Sayı: 2, 253–271. https://doi.org/10.51800/ecd.1296895

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References (76)

  1. Akçakaya, A., Atay, H., ve Demir, Ö. (2013). İklim Değişikliği Senaryolarında Yeni Dönem: Paralel Yaklaşım ve Temsili Konsantrasyon Rotaları. 6th Atmospheric Science Symposium - ATMOS. 3 - 5 Haziran 2013, İstanbul. İstanbul.
  2. Alexeeff, S. E., Nychka, D., Sain, S. R., ve Tebaldi, C. (2018). Emulating mean patterns and variability of temperature across and within scenarios in anthropogenic climate change experiments. Climatic Change, 146(3–4), 319–333. https://doi.org/10.1007/S10584-016-1809-8/FIGURES/3
  3. Alonso, A., Muñoz-Carpena, R., Kennedy, R. E., ve Murcia, C. (2016). Wetland landscape spatio-temporal degradation dynamics using the new google earth engine cloud-based platform: Opportunities for non-specialists in remote sensing. Transactions of the ASABE, 59(5), 1333–1344. https://doi.org/10.13031/trans.59.11608
  4. Anderson, L. S., Flowers, G. E., Jarosch, A. H., Aðalgeirsdóttir, G. T., Geirsdóttir, Á., Miller, G. H., … Pálsson, F. (2018). Holocene glacier and climate variations in Vestfirðir, Iceland, from the modeling of Drangajökull ice cap. Quaternary Science Reviews, 190, 39–56. https://doi.org/10.1016/J.QUASCIREV.2018.04.024
  5. Badino, F., Ravazzi, C., Vallè, F., Pini, R., Aceti, A., Brunetti, M., … Orombelli, G. (2018). 8800 years of high-altitude vegetation and climate history at the Rutor Glacier forefield, Italian Alps. Evidence of middle Holocene timberline rise and glacier contraction. Quaternary Science Reviews, 185, 41–68. https://doi.org/10.1016/J.QUASCIREV.2018.01.022
  6. Bağçaci, S. Ç., Yucel, I., Duzenli, E., ve Yilmaz, M. T. (2021). Intercomparison of the expected change in the temperature and the precipitation retrieved from CMIP6 and CMIP5 climate projections: A Mediterranean hot spot case, Turkey. Atmospheric Research, 256, 105576. https://doi.org/https://doi.org/10.1016/j.atmosres.2021.105576
  7. Bala, G. (2013). Digesting 400 ppm for global mean CO 2 concentration Conserving the endangered Mahseers ( Tor spp.) of India: the positive role of recreational fisheries. Current Science, 104(11), 1471.
  8. Böhringer, C. (2003). The Kyoto Protocol: A Review and Perspectives. Oxford Review of Economic Policy, 19(3), 451–466. https://doi.org/10.1093/OXREP/19.3.451
  9. Carbonbrief. (2023). Timeline History of Climate Modelling. 4 Nisan 2023 tarihinde adresinden erişildi https://www.carbonbrief.org/timeline-history-climate-modelling/
  10. Chen, B., Xiao, X., Li, X., Pan, L., Doughty, R., Ma, J., … Giri, C. (2017). A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform. ISPRS Journal of Photogrammetry and Remote Sensing, 131, 104–120. https://doi.org/10.1016/j.isprsjprs.2017.07.011
  11. Coşkun, M. (2022). İklim değişmeleri, küresel ısınma ve Türkiye. S. Doğanay ile M. Alım (Editör). Türkiye’nin Fiziki Coğrafyası içinde (ss. 322-351). Ankara: Pegem Akademi.
  12. Crowley, T. J., ve Berner, R. A. (2001). CO2 and Climate Change. Science, 292(5518), 870–872. https://doi.org/10.1126/SCIENCE.1061664
  13. Daloz, A. S., Schwingshackl, C., Mooney, P., Strada, S., Rechid, D., Davin, E. L., … Lund, M. T. (2022). Land-atmosphere interactions in sub-polar and alpine climates in the CORDEX flagship pilot study Land Use and Climate Across Scales (LUCAS) models-Part 1: Evaluation of the snow-albedo effect. Cryosphere, 16(6), 2403–2419. https://doi.org/10.5194/TC-16-2403-2022
  14. Demircan, M., Gürkan, H., Eskioğlu, O., Arabacı, H., ve Coşkun, M. (2017). Climate Change Projections for Turkey: Three Models and Two Scenarios. Türkiye Su Bilimi ve Yönetimi Dergisi, 1(1), 22–43. https://doi.org/10.31807/TJWSM.297183
  15. ESRI (2023) What is ArcMap? 8 Mart 2023 tarihinde https://desktop.arcgis.com/en/arcmap/latest/map/main/what-is-arcmap-.htm adresinden erişildi.
  16. Eyring, V., Cox, P. M., Flato, G. M., Gleckler, P. J., Abramowitz, G., Caldwell, P., … Williamson, M. S. (2019). Taking climate model evaluation to the next level. Nature Climate Change 2019 9:2, 9(2), 102–110. https://doi.org/10.1038/s41558-018-0355-y
  17. Field, C. B., Lobell, D. B., Peters, H. A., ve Chiariello, N. R. (2007). Feedbacks of Terrestrial Ecosystems to Climate Change*. https://doi.org/10.1146/annurev.energy.32.053006.141119, 32, 1–29. https://doi.org/10.1146/ANNUREV.ENERGY.32.053006.141119
  18. Gao, Y., Gao, X., ve Zhang, X. (2017). The 2 °C Global Temperature Target and the Evolution of the Long-Term Goal of Addressing Climate Change—From the United Nations Framework Convention on Climate Change to the Paris Agreement. Engineering, 3(2), 272–278. https://doi.org/10.1016/J.ENG.2017.01.022
  19. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., ve Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
  20. Gorguner, M., Kavvas, M. L., ve Ishida, K. (2019). Assessing the impacts of future climate change on the hydroclimatology of the Gediz Basin in Turkey by using dynamically downscaled CMIP5 projections. Science of The Total Environment, 648, 481–499. https://doi.org/https://doi.org/10.1016/j.scitotenv.2018.08.167
  21. Gürkan, H., Arabacı, H., Mesut, D., Osman, E., Şensoy, S., ve Yazıcı, B. (2016). GFDL-ESM2M Modeli Temelinde RCP4.5 ve RCP8.5 Senaryolarına Göre Türkiye İçin Sıcaklık ve Yağış Projeksiyonları. Coğrafi Bilimler Dergisi, 14(2), 77–88.
  22. Hao, B., Ma, M., Li, S., Li, Q., Hao, D., Huang, J., … Han, X. (2019). Land use change and climate variation in the three gorges reservoir catchment from 2000 to 2015 based on the google earth engine. Sensors (Switzerland), 19(9). https://doi.org/10.3390/s19092118
  23. Hoffmann, D. (2009). Black Body. Compendium of Quantum Physics, 36–39. https://doi.org/10.1007/978-3-540-70626-7_13
  24. Huang, H., Chen, Y., Clinton, N., Wang, J., Wang, X., Liu, C., … Zhu, Z. (2017). Mapping major land cover dynamics in Beijing using all Landsat images in Google Earth Engine. Remote Sensing of Environment, 202, 166–176. https://doi.org/10.1016/j.rse.2017.02.021
  25. Hungate, B. A., Dukes, J. S., Shaw, M. R., Luo, Y., ve Field, C. B. (2003). Nitrogen and Climate Change. Science, 302(5650), 1512–1513. https://doi.org/10.1126/SCIENCE.1091390/SUPPL_FILE/HUNGATE.SOM.PDF
  26. IPCC. (2023). IPCC AR6 Sentez Raporu. Tarihinde adresinden erişildi https://www.ipcc.ch/report/sixth-assessment-report-cycle/
  27. Johnson, R. J., Sánchez-Lozada, L. G., Newman, L. S., Lanaspa, M. A., Diaz, H. F., Lemery, J., … Roncal-Jimenez, C. A. (2019). Climate Change and the Kidney. Annals of Nutrition and Metabolism, 74(3), 38–44. https://doi.org/10.1159/000500344
  28. Jubb, I., Canadell, P., ve Dix, M. (2013). Representative Concentration Pathways.Australian Government, Department of the Environment.
  29. Kelm, M. (1999). Nitric oxide metabolism and breakdown. Biochimica et Biophysica Acta (BBA) - Bioenergetics, 1411(2–3), 273–289. https://doi.org/10.1016/S0005-2728(99)00020-1
  30. Kemp, L., Xu, C., Depledge, J., Ebi, K. L., Gibbins, G., Kohler, T. A., … Lenton, T. M. (2022). Climate Endgame: Exploring catastrophic climate change scenarios. Proceedings of the National Academy of Sciences of the United States of America, 119(34), e2108146119. https://doi.org/10.1073/PNAS.2108146119/SUPPL_FILE/PNAS.2108146119.SAPP.PDF
  31. Kivi, R., ve Heikkinen, P. (2016). Fourier transform spectrometer measurements of column CO2 at Sodankylä, Finland. Geoscientific Instrumentation, Methods and Data Systems, 5(2), 271–279. https://doi.org/10.5194/GI-5-271-2016
  32. Kozun, Y. S., Kazeev, K. S., ve Kolesnikov, S. I. (2022). Climate Effect on the Enzymatic Activity of Northern Caucasian Forest Soils. Contemporary Problems of Ecology, 15(7), 759–764. https://doi.org/10.1134/S1995425522070162
  33. Kumar, L., ve Mutanga, O. (2018). Google Earth Engine applications since inception: Usage, trends, and potential. Remote Sensing, 10(10), 1–15. https://doi.org/10.3390/rs10101509
  34. Lamb, W. F., Wiedmann, T., Pongratz, J., Andrew, R., Crippa, M., Olivier, J. G. J., … Minx, J. (2021). A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018. Environmental Research Letters, 16(7), 073005. https://doi.org/10.1088/1748-9326/ABEE4E
  35. Liang, S., Wang, D., He, T., ve Yu, Y. (2019). Remote sensing of earth’s energy budget: synthesis and review. https://doi.org/10.1080/17538947.2019.1597189, 12(7), 737–780. https://doi.org/10.1080/17538947.2019.1597189 Manabe, S. (2019). Role of greenhouse gas in climate change. New pub: Stockholm uni Press, 71(1), 1–13. https://doi.org/10.1080/16000870.2019.1620078
  36. Mansouri Daneshvar, M. R., Ebrahimi, M., ve Nejadsoleymani, H. (2019). An overview of climate change in Iran: facts and statistics. Environmental Systems Research 2019 8:1, 8(1), 1–10. https://doi.org/10.1186/S40068-019-0135-3
  37. Maria, C., Góis, J., ve Leitão, A. (2020). Challenges and perspectives of greenhouse gases emissions from municipal solid waste management in Angola. Energy Reports, 6, 364–369. https://doi.org/10.1016/J.EGYR.2019.08.074
  38. Martin, C., Ménot, G., Thouveny, N., Peyron, O., Andrieu-Ponel, V., Montade, V., … Bard, E. (2020). Early Holocene Thermal Maximum recorded by branched tetraethers and pollen in Western Europe (Massif Central, France). Quaternary Science Reviews, 228, 106109. https://doi.org/10.1016/J.QUASCIREV.2019.106109
  39. Meehl, G. A., Covey, C., McAvaney, B., Latif, M., ve Stouffer, R. J. (2005). Overview of the Coupled Model Intercomparison Project. Bulletin of the American Meteorological Society, 86(1), 89–93. https://doi.org/10.1175/BAMS-86-1-89
  40. Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J.-F., … van Vuuren, D. P. P. (2011). The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109(1), 213. https://doi.org/10.1007/s10584-011-0156-z
  41. Meyssignac, B., Boyer, T., Zhao, Z., Hakuba, M. Z., Landerer, F. W., Stammer, D., … Zilberman, N. (2019). Measuring global ocean heat content to estimate the earth energy imbalance. Frontiers in Marine Science, 6(JUL), 432. https://doi.org/10.3389/FMARS.2019.00432/BIBTEX
  42. MGM (2022a). IPCC İklim Değişikliği Senaryoları ve Tarihsel Gelişimi. 16 Ekim 2022 tarihinde https://www.mgm.gov.tr/iklim/iklim-degisikligi.aspx?s=senaryolar adresinden erişildi.
  43. MGM (2022b). Küresel İklim Modellemesi. 16 Ekim 2022 tarihinde, https://www.mgm.gov.tr/iklim/iklim-degisikligi.aspx?s=kuresel adresinden erişildi.
  44. MGM (2022c). İllere Ait Mevsim Normalleri (1991-2020). 30 Aralık 2022 tarihinde https://www.mgm.gov.tr/veridegerlendirme/il-ve-ilceler-istatistik.aspx?m adresinden erişildi.
  45. Montzka, S. A., Dlugokencky, E. J., ve Butler, J. H. (2011). Non-CO2 greenhouse gases and climate change. Nature, 476(7358), 43–50. https://doi.org/10.1038/nature10322
  46. Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., … Wilbanks, T. J. (2010). The next generation of scenarios for climate change research and assessment. Nature, 463(7282), 747–756. https://doi.org/10.1038/nature08823
  47. Muir, J. (1999). Nitrogen oxides (NOx), Why and How They are Controlled. EPA.
  48. Mutanga, O., ve Kumar, L. (2019). Google Earth Engine Applications. Remote Sensing, C. 11. https://doi.org/10.3390/rs11050591
  49. NASA (2022, Kasım 4) NEX-GDDP: NASA Earth Exchange Global Daily Downscaled Climate Projections. Kasım 4, 2022 tarihinde https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-GDDP#bands adresinden erişildi.
  50. NOAA. (2023). The First Climate Model. 4 Nisan 2023 tarihinde adresinden erişildi https://celebrating200years.noaa.gov/breakthroughs/climate_model/welcome.html#vision
  51. Önol, B., Bozkurt, D., Turuncoglu, U. U., Sen, O. L., ve Dalfes, H. N. (2014). Evaluation of the twenty-first century RCM simulations driven by multiple GCMs over the Eastern Mediterranean–Black Sea region. Climate Dynamics, 42(7), 1949–1965. https://doi.org/10.1007/s00382-013-1966-7
  52. Özturk, T., Ceber, Z. P., Türkeş, M., ve Kurnaz, M. L. (2015). Projections of climate change in the Mediterranean Basin by using downscaled global climate model outputs. International Journal of Climatology, 35(14), 4276–4292. https://doi.org/https://doi.org/10.1002/joc.4285
  53. Padarian, J., Minasny, B., ve McBratney, A. B. (2015). Using Google’s cloud-based platform for digital soil mapping. Computers and Geosciences, 83, 80–88. https://doi.org/10.1016/j.cageo.2015.06.023
  54. Pedersen, J. S. T., Duarte Santos, F., van Vuuren, D., Gupta, J., Encarnação Coelho, R., Aparício, B. A., ve Swart, R. (2021). An assessment of the performance of scenarios against historical global emissions for IPCC reports. Global Environmental Change, 66, 102199. https://doi.org/10.1016/J.GLOENVCHA.2020.102199
  55. Rosenthal, Y., Kalansky, J., Morley, A., ve Linsley, B. (2017). A paleo-perspective on ocean heat content: Lessons from the Holocene and Common Era. Quaternary Science Reviews, 155, 1–12. https://doi.org/10.1016/J.QUASCIREV.2016.10.017
  56. Sandén, B. A., ve Karlström, M. (2007). Positive and negative feedback in consequential life-cycle assessment. Journal of Cleaner Production, 15(15), 1469–1481. https://doi.org/10.1016/J.JCLEPRO.2006.03.005
  57. Seker, M., ve Gumus, V. (2022). Projection of temperature and precipitation in the Mediterranean region through multi-model ensemble from CMIP6. Atmospheric Research, 280, 106440. https://doi.org/https://doi.org/10.1016/j.atmosres.2022.106440
  58. Sen, O., Bozkurt, D., Göktürk, O. M., Dündar, B., Altürk, B., Üniversitesi, S., … Enstitüsü, B. (2017). Türkiye’de İklim Değişikliği ve Olası Etkileri.
  59. Seo, S. N. (2017). Beyond the Paris Agreement: Climate change policy negotiations and future directions. Regional Science Policy & Practice, 9(2), 121–140. https://doi.org/10.1111/RSP3.12090
  60. Shallcross, D. E., ve Harrison, T. G. (2007). Climate change made simple. Physics Education, 42(6), 592. https://doi.org/10.1088/0031-9120/42/6/005
  61. Singh, J., Schädler, M., Demetrio, W., Brown, G. G., ve Eisenhauer, N. (2019). Climate change effects on earthworms - a review. Soil organisms, 91(3), 114. https://doi.org/10.25674/SO91ISS3PP114
  62. Stips, A., MacIas, D., Coughlan, C., Garcia-Gorriz, E., ve Liang, X. S. (2016). On the causal structure between CO2 and global temperature. Scientific Reports 2016 6:1, 6(1), 1–9. https://doi.org/10.1038/srep21691
  63. Tamiminia, H., Salehi, B., Mahdianpari, M., Quackenbush, L., Adeli, S., ve Brisco, B. (2020a). Google Earth Engine for geo-big data applications: A meta-analysis and systematic review. ISPRS Journal of Photogrammetry and Remote Sensing, 164(January), 152–170. https://doi.org/10.1016/j.isprsjprs.2020.04.001
  64. Tamiminia, H., Salehi, B., Mahdianpari, M., Quackenbush, L., Adeli, S., ve Brisco, B. (2020b). Google Earth Engine for geo-big data applications: A meta-analysis and systematic review. ISPRS Journal of Photogrammetry and Remote Sensing. https://doi.org/10.1016/j.isprsjprs.2020.04.001
  65. Tayanç, M., İm, U., Doğruel, M., ve Karaca, M. (2009). Climate change in Turkey for the last half century. Climatic Change, 94(3–4), 483–502. https://doi.org/10.1007/S10584-008-9511-0/METRICS
  66. Taylor, K. E., Stouffer, R. J., ve Meehl, G. A. (2012). An Overview of CMIP5 and the Experiment Design. Bulletin of the American Meteorological Society, 93(4), 485–498. https://doi.org/10.1175/BAMS-D-11-00094.1
  67. Taylor, P. C., Hegyi, B. M., Boeke, R. C., ve Boisvert, L. N. (2018). On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review. Atmosphere, 9(2), 41. https://doi.org/10.3390/ATMOS9020041
  68. Thrasher, B., Maurer, E. P., McKellar, C., ve Duffy, P. B. (2012). Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrology and Earth System Sciences, 16(9), 3309–3314. https://doi.org/10.5194/hess-16-3309-2012
  69. Türkeş, M., ve Tolunay, D. (2023). İklim Değişikliği ve Orman Yangınları.
  70. Turp, M. T., Türkeş, M., Kurnaz, M. L., ve Öztürk, T. (2014). RegCM4.3.5 Bölgesel İklim Modelini Kullanarak Türkiye ve Çevresi Bölgelerin Yakın Gelecekteki Hava Sıcaklığı ve Yağış Klimatolojileri İçin Öngörülen Değişikliklerin İncelenmesi. Aegean Geographical Journal, 23(1), 1–24.
  71. UN. (2022). United Nations Office for Outer Space Affairs UN-SPIDER Knowledge Portal. 07 Aralık 2021 tarihinde, https://www.un-spider.org/links-and-resources/gis-rs-software/google-earth-engine-google adresinden erişildi
  72. Van Leeuwen, C., Destrac-Irvine, A., Dubernet, M., Duchêne, E., Gowdy, M., Marguerit, E., … Ollat, N. (2019). An Update on the Impact of Climate Change in Viticulture and Potential Adaptations. Agronomy 2019, Vol. 9, Page 514, 9(9), 514. https://doi.org/10.3390/AGRONOMY9090514
  73. Xiao, X., Yao, A., Hillman, A., Shen, J., ve Haberle, S. G. (2020). Vegetation, climate and human impact since 20 ka in central Yunnan Province based on high-resolution pollen and charcoal records from Dianchi, southwestern China. Quaternary Science Reviews, 236, 106297. https://doi.org/10.1016/J.QUASCIREV.2020.106297
  74. Xiong, J., Thenkabail, P. S., Tilton, J. C., Gumma, M. K., Teluguntla, P., Oliphant, A., … Gorelick, N. (2017). Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 data on google earth engine. Remote Sensing, 9(10), 1–27. https://doi.org/10.3390/rs9101065
  75. Zhao, Q., Yu, L., Li, X., Peng, D., Zhang, Y., ve Gong, P. (2021). Progress and trends in the application of google earth and google earth engine. Remote Sensing, 13(18), 1–21. https://doi.org/10.3390/rs13183778
  76. Bala, G. (2013). Digesting 400 ppm for global mean CO 2 concentration Conserving the endangered Mahseers ( Tor spp.) of India: the positive role of recreational fisheries. Current Science, 104(11), 1471.