Abstract
Global warming can lead to a more frequent occurrence of hot days and heat waves and fewer cold days and cold waves. In this paper, the daily mean temperature (TM) was divided into 7 range categories (TM < − 15 °C, − 15 °C ≤ TM < − 5 °C, … TM ≥ 35 °C). Then, the temperature days (TDs) were obtained and expressed as TD1, TD2, …, TD6, and TD7, which correspond well to climate zones. The changes in future TDs are obvious, especially for TD1 and TD6. Under the Representative Concentration Pathway (RCP) 8.5 scenario, TD1 will decrease the most in the polar climate zone, from 162 to 102, while TD6 in warm tropical countries and regions, such as Brazil, Nigeria, and Congo, will increase by more than 70 days, reaching at least 300 days per year after 2066. By summarizing the anomalies of TD1, TD2, TD6, and TD7 in combination into 12 templates, the changes in TD1 and TD2 were determined to be more pronounced than those in TD6 and TD7. Although carbon dioxide emissions will remain basically stable from 2066 to 2095 under the RCP4.5 scenario, both TD1 and TD2 will decrease in central Antarctica, Eastern Europe, and northern Russia, and the melting of ice and snow will be irreversible. Countries such as Saudi Arabia and Australia will still face a continuous increase in both TD6 and TD7. Temperature range changes also affect the humidity of the climate: in the projected future, humid climate areas will decrease, while arid climate areas will increase. The boreal drylands in the middle and high latitudes will be replaced by temperate drylands.
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Data availability
The IPCC-based NEX-GDDP data used in this work are available from https://ds.nccs.nasa.gov/thredds/catalog/NEX-GDDP/IND/BCSD/catalog.html. The global climate zones used in this work are available from the FAO (http://www.fao.org/geonetwork/srv/en/metadata.show?id=37139&currTab=distribution).
References
Almazroui M, Islam MN, Saeed S, Saeed F, Ismail M, (2020). Future changes in climate over the Arabian Peninsula based on CMIP6 multimodel simulations. Earth Syst Environ. https://doi.org/10.1007/s41748-020-00183-5
Basu R, Ostro BD (2008) A multicounty analysis identifying the populations vulnerable to mortality associated with high ambient temperature in California. Am J Epidemiol 168(6):632–637. https://doi.org/10.1093/aje/kwn170
Chen J, Brissette FP, Lucas-Picher P (2016) Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology. Climate Dynamic 47:3359–3372. https://doi.org/10.1007/s00382-016-3030-x
Díaz J, López-Bueno JA, Sáez M, Carmona R, Mirón IJ, Barceló MA, Luna MY, Linares C (2019). Will there be cold-related mortality in Spain over the 2021–2050 and 2051–2100 time horizons despite the increase in temperatures as a consequence of climate change? Environmental Research, 176, 108557. https://doi.org/10.1016/j.envres.2019.108557
Dunne JP, Stouffer RJ, John JG (2013) Reductions in labor capacity from heat stress under climate warming. Nat Clim Chang 3(6):563. https://doi.org/10.1038/nclimate1827
Food and Agriculture Organization (FAO) (2011) United Nations Environment Programme (UNEP) Land Degradation Assessment in Drylands(LDAD) Project, Global climate zones.
Garcia RA, Cabeza M, Rahbek C, Araujo MB (2014) Multiple dimensions of climate change and their implications for biodiversity. Science 344(6183):1247579–1247579. https://doi.org/10.1126/science.1247579
Giorgi F (2006). Climate change hot‐spots. Geophysical Research Letters, 33(8):101029. https://doi.org/10.1029/2006GL025734
Graczyk D, Pinnskwar I, Kundzewicz ZW, Hov Ø, Førland EJ, Szwed M, Chorynski A (2017) The heat goes on—changes in indices of hot extremes in Poland. Theoret Appl Climatol 129(1–2):459–471. https://doi.org/10.1007/s00704-016-1786-x
Haensler A, Saeed F, Jacob D (2013) Assessing the robustness of projected precipitation changes over central Africa on the basis of a multitude of global and regional climate projections. Climate Change 121:349–363. https://doi.org/10.1007/s10584-013-0863-8
Hawkins E, Sutton R (2011) The potential to narrow uncertainty in projections of regional precipitation change. Climate Dynamic 37:407–418. https://doi.org/10.1007/s00382-010-0810-6
Intergovernmental Panel on Climate Change (2022). Climate Change 2022: impacts, adaptation and vulnerability. https://www.ipcc.ch/report/sixth-assessment-report-working-group-ii/
Lhotka O, Kyselý J, Plavcova E (2018) Evaluation of major heat waves’ mechanisms in EURO-CORDEX RCMs over Central Europe. Clim Dyn 50(11–12):4249–4262. https://doi.org/10.1007/s00382-017-3873-9
López-Bueno JA, Díaz J, Navas MA, Mirón IJ, Follos F, Vellón JM, Ascaso MS, Luna MY, Martínez GS, Linares C (2022). Temporal evolution of threshold temperatures for extremely cold days in Spain. Science of The Total Environment, 844:157183. https://doi.org/10.1016/j.scitotenv.2022.157183
Minville M, Brissette F, Leconte R (2008) Uncertainty of the impact of climate change on the hydrology of a nordic watershed. J Hydrol 358(1–2):70–83
Muthers S, Laschewski L, Matzarakis A (2017) The summers 2003 and 2015 in South-West Germany: heat waves and heat-related mortality in the context of climate change. Atmosphere 8:224. https://doi.org/10.3390/atmos8110224
Russo S, Sillmann J, Sterl A (2017) Humid heat waves at different warming levels. Sci Rep 7(1):7477. https://doi.org/10.1038/s41598-017-07536-7
Sangelantoni L, Russo A, Gennaretti F (2019) Impact of bias correction and downscaling through quantile mapping on simulated climate change signal: a case study over Central Italy. Theor Appl Climatol 135(1–2):725–740. https://doi.org/10.1007/s00704-018-2406-8
Schwingshackl C, Sillmann J, Vicedo-Abrera AM, Sandstad M, Aunan K (2021) Heat stress indicators in CMIP6: estimating future trends and exceedances of impact-relevant thresholds. Earth’s Future. https://doi.org/10.1029/2020EF001885
Seneviratne S, Nicholls N, Easterling D, Goodess C, Kanae S, Kossin J, Zwiers F (2012). Changes in climate extremes and their impacts on the natural physical environment. In C. Field, V. Barros, T. Stocker, & Q. Dahe (Eds.), Managing the risks of extreme events and disasters to advance climate change adaptation: Special Report of the Intergovernmental Panel on Climate Change (pp. 109–230). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139177245.006
Shen M, Chen J, Zhuan M, Chen H, Xu C, Xiong L (2018) Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology. J Hydrol 556(10–24):0022–1694. https://doi.org/10.1016/j.jhydrol.2017.11.004
Sillmann J, Kharin VV, Zhang XB (2013a) Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate. J Geophysical Res Atmos 118:1–18. https://doi.org/10.1002/jgrd.50203
Sillmann J, Kharin VV, Zwiers FW et al (2013) Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J Geophysical Res: Atmos 118(6):2473–2493. https://doi.org/10.1002/jgrd.50188
Slingo JM, Sperber KR, Boyle JS et al (1996) Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject. Climate Dynamic 12:325–357. https://doi.org/10.1007/BF00231106
Thrasher B, Maurer EP, Duffy PB et al (2012) Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol Earth Syst Sci 16(9):3309–3314. https://doi.org/10.5194/hess-16-3309-2012
Tripathi A, Kumar D, Chauhan DK, Kumar N et al (2016) Paradigms of climate change impacts on some major food sources of the world: a review on current knowledge and future prospects. Agr Ecosyst Environ. https://doi.org/10.1016/j.agee.2015.09.034
Wei T, Cherry TL, Glomrød S, Zhang T (2014) Climate change impacts on crop yield: evidence from China. Sci Total Environ 499:133–140. https://doi.org/10.1016/j.scitotenv.2014.08.035
White G (2011) Climate change and migration: security and borders in a warming world. Oxford Univ. Press, Oxford, U. K.
Zhang YE, Yan CY, Kan HD et al (2014) Effect of ambient temperature on emergency department visits in Shanghai, China:a time series study. Environ Health 13(1):100–107. https://doi.org/10.1186/1476-069X-13-100
Zhang WX, Zhou TJ (2021) The effect of modeling strategies on assessments of differential warming impacts of 0.5°C. Earth’s Future 9(4) e2020EF001640. https://doi.org/10.1029/2020EF001640
Zwiers FW, Alexander LV, Hegerl GC, Knutson TR, Kossin JP, Naveau P, Nicholls N, Schär C, Seneviratne SI, Zhang X (2013). Challenges in estimating and understanding recent changes in the frequency and intensity of extreme climate and weather events, climate science for serving Society: Research, Modelling and Prediction Priorities. Springer, Dordrecht, NL, in press. https://doi.org/10.1007/978-94-007-6692-1_13
Acknowledgements
The authors thank the Intergovernmental Panel on Climate Change (IPCC), NEX-GDDP, FAO, all organizations listed in Table 1 who provided GCM datasets and Qingyuan Ma from Beijing Normal University for valuable discussion.
Funding
This study was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP No. 2019QZKK0906 and 2019QZKK0606).
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Yuxin Li: methodology, software, writing- original draft preparation, and visualization.
Ying Wang: conceptualization and supervision.
Xia Wang: writing-reviewing and editing.
Xinren Zhang: investigation.
Xiaojuan Chen: data curation.
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Li, Y., Wang, Y., Wang, X. et al. The impacts of climate change on regional temperature characteristics and climate zones. Theor Appl Climatol 152, 45–56 (2023). https://doi.org/10.1007/s00704-023-04368-6
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DOI: https://doi.org/10.1007/s00704-023-04368-6