Abstract
This study investigates the near-term future changes of temperature extremes in summer (June–August) and winter (December–February) seasons over mainland China in the mid-twenty-first century (FP; 2045–2055) under representative concentration pathway (RCP) 4.5 scenario relative to the present day (PD; 1994–2011) by using an atmosphere–ocean-mixed-layer coupled model MetUM-GOML1. The projected changes in hot extremes exhibit a rise in hottest day temperature (TXx) and warmest night temperature (TNx) and an increase in frequencies of summer days (SU) and tropical nights (TR). The projected changes in cold extremes show a rise in coldest day temperature (TXn) and coldest night temperature (TNn) and a decrease in frequencies of ice days (ID) and frost days (FD). The projected changes in temperature extremes in both seasons are primarily determined by changes in seasonal mean daily maximum and minimum temperature while changes in temperature variability from daily to sub-seasonal time scales play a minor role. The future changes in temperature extremes over China, being consistent with the rise in seasonal temperature, are partly due to the increase in surface downward clear sky longwave radiation through the increased greenhouse gas concentrations and enhanced water vapor in the atmosphere, and partly due to the increase in net surface shortwave radiation as a result of the decreased aerosol emissions over Asia via aerosol-radiation interactions. Moreover, the seasonal mean surface warming can further be amplified with positive feedbacks by reducing the cloud cover, leading to positive changes in shortwave radiative effect through aerosol-cloud interactions and surface-atmosphere feedbacks during summer, and by positive changes in surface clear sky shortwave radiation through snow-albedo feedbacks over northern China and southwestern China during winter.
Similar content being viewed by others
References
Alexander LV et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. https://doi.org/10.1029/2005JD006290
Argueso D, Di Luca A, Perkins-Kirkpatrick SE, Evans JP (2016) Seasonal mean temperature changes control future heat waves. Geophys Res Lett 43(14):7653–7660. https://doi.org/10.1002/2016GL069408
Arribas A, Glover M, Maidens A, Peterson K, Gordon M, MacLachlan C, Graham R, Fereday D, Camp J, Scaife A (2011) The GloSea4 ensemble prediction system for seasonal forecasting. Mon Weather Rev 139(6):1891–1910. https://doi.org/10.1175/2010MWR3615.1
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(3–4):683–699. https://doi.org/10.1007/s00382-013-1868-8
Bony S et al (2006) How well do we understand and evaluate climate change feedback processes? J Clim 19(15):3445–3482. https://doi.org/10.1175/jcli3819.1
Chen W, Dong B (2018a) Anthropogenic impacts on recent decadal change in temperature extremes over China: relative roles of greenhouse gases and anthropogenic aerosols. Clim Dyn 1:1. https://doi.org/10.1007/s00382-018-4342-9
Chen W, Dong B (2018b) Drivers of the severity of the extreme hot summer of 2015 in western China. J Meteor Res 32(6):1–9. https://doi.org/10.1007/s13351-018-8004-y
Chen W, Dong B, Wilcox L, Luo FF, Dunstone N, Highwood EJ (2019a) Attribution of recent trends in temperature extremes over China: role of changes in anthropogenic aerosol emissions over Asia. J Clim 32:7539–7560. https://doi.org/10.1175/JCLI-D-18-0777.1
Chen Y, Chen W, Su Q, Luo F, Sparrow S, Tian F, Dong B, Tett SFB, Lott FC, Wallom D (2019b) Anthropogenic warming has substantially increased the likelihood of July 2017-like heat waves over Central-Eastern China [in “Explaining Extremes of 2017 from a Climate Perspective”]. Bull Am Meteor Soc 100(1):S91–S95. https://doi.org/10.1175/BAMS-D-18-0087.1
Dong B, Sutton RT, Shaffrey L (2017) Understanding the rapid summer warming and changes in temperature extremes since the mid-1990s over Western Europe. Clim Dyn 48(5–6):1537–1554. https://doi.org/10.1007/s00382-016-3158-8
Dong B, Sutton RT, Chen W, Liu XD, Lu RY, Sun Y (2016) Abrupt summer warming and changes in temperature extremes over Northeast Asia since the mid-1990s: drivers and physical processes. Adv Atmos Sci 33(9):1005–1023. https://doi.org/10.1007/s00376-016-5247-3
Donat MG, Alexander LV (2012) The shifting probability distribution of global daytime and night-time temperatures. Geophys Res Lett 39:L14707. https://doi.org/10.1029/2012GL052459
Freychet N, Tett S, Wang J, Hegerl G (2017) Summer heat waves over Eastern China: dynamical processes and trend attribution. Environ Res Lett 12(2):024015. https://doi.org/10.1088/1748-9326/aa5ba3
Freychet N, Sparrow S, Tett SFB, Mineter MJ, Hegerl GC, Wallom DCH (2018) Impacts of anthropogenic forcings and El Niño on Chinese extreme temperatures. Adv Atmos Sci 35(8):994–1002. https://doi.org/10.1007/s00376-018-7258-8
Gershunov A, Cayan DR, Iacobellis SF (2009) The great 2006 heat wave over California and Nevada: signal of an increasing trend. J Clim 22(23):6181–6203. https://doi.org/10.1175/2009JCLI2465.1
Guan Y, Zhang X, Zheng F, Wang B (2015) Trends and variability of daily temperature extremes during 1960–2012 in the Yangtze River Basin, China. Glob Planet Chang 124:79–94. https://doi.org/10.1016/j.gloplacha.2014.11.008
Guo X, Huang J, Luo Y, Zhao Z, Xu Y (2017) Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models. Theor Appl Climatol 128(3–4):507–522. https://doi.org/10.1007/s00704-015-1718-1
Gross MH, Donat MG, Alexander LV, Sherwood SC (2020) Amplified warming of seasonal cold extremes relative to the mean in the northern hemisphere extratropics. Earth Syst Dyn 11:97–111. https://doi.org/10.5194/esd-11-97-2020
Hirons L, Klingaman N, Woolnough S (2015) MetUM-GOML: a nearglobally coupled atmosphere–ocean-mixed-layer model. Geosci Model Dev 8:363–379. https://doi.org/10.5194/gmd-8-363-2015
IPCC (2013) Climate Change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, New York
IPCC (2020) AR6 Climate Change 2021: Impacts, Adaptation and Vulnerability. https://www.ipcc.ch/report/sixth-assessment-report-working-group-ii/
Jones C, Hughes JK, Bellouin N, Hardiman SC, Jones GS, Knight J, Boo KO et al (2011) The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci Model Dev 4(3):543–570. https://doi.org/10.5194/gmd-4-543-2011
Lamarque JF et al (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application. Atmos Chem Phys 10:7017–7039. https://doi.org/10.5194/acp-10-7017-2010
Lamarque JF et al (2011) Global and regional evolution of short lived radiatively-active gases and aerosols in the representative concentration pathways. Clim Change 109:191–212. https://doi.org/10.1007/s10584-011-0155-0
Lau NC, Nath MJ (2012) A model study of heat waves over North America: meteorological aspects and projections for thetwenty-first century. J Clim 25(14):4761–4784. https://doi.org/10.1175/JCLI-D-11-00575.1
Leng G, Tang Q, Huang S, Zhang X (2016) Extreme hot summers in china in the CMIP5 climate models. Clim Change 135(3–4):669–681. https://doi.org/10.1007/s10584-015-1576-y
Li Z, Cao LJ, Zhu YN, Yan ZW (2016) Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013. J Meteor Res 30(1):53–66. https://doi.org/10.1007/s13351-016-5054-x
Luo F, Wilcox L, Dong B et al (2020) Projected near-term changes of temperature extremes in Europe and China under different aerosol emissions. Environ Res Lett 15:034013. https://doi.org/10.1088/1748-9326/ab6b34
Meehl GA, Tebaldi C (2004) More intense, more frequent, and longer lasting heat waves in the 21st Century. Science 305(5686):994–997. https://doi.org/10.1126/science.1098704
Qi L, Wang Y (2012) Changes in the observed trends in extreme temperatures over china around 1990. J Clim 25(15):5208–5222. https://doi.org/10.1175/jcli-d-11-00437.1
Qu X, Hall A (2007) What controls the strength of snow-albedo feedback? J Clim 20(15):3971–3981. https://doi.org/10.1175/JCLI4186.1
Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of SST, sea ice and night marine air temperature since the late nineteenth century. J Geophys Res 108:D144407. https://doi.org/10.1029/2002JD002670
Robock A (1983) Ice and snow feedbacks and the latitudinal and seasonal distribution of climate sensitivity. J Atmos Sci 40(4):986–997. https://doi.org/10.1175/1520-0469(1983)0402.0.CO2
Schär C, Vidale PL, Lüthi D, Frei C, Häberli C, Liniger MA, Appenzeller C (2004) The role of increasing temperature variability in European summer heatwaves. Nature 427(6972):332–336. https://doi.org/10.1038/nature02300
Schiermeier Q (2011) Extreme measures. Nature 477(7363):148–149
Schoetter R, Cattiaux J, Douville H (2015) Changes of western European heat wave characteristics projected by the CMIP5 ensemble. Clim Dyn 45(5–6):1601–1616. https://doi.org/10.1007/s00382-014-2434-8
Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture-climate interactions in a changing climate: a review. Earth Sci Rev 99:125–161
Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013) Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J Geophys Res 118:2473–2493. https://doi.org/10.1002/jgrd.50188
Smith DM, Murphy JM (2007) An objective ocean temperature and salinity analysis using covariances from a global climate model. J Geophys Res 112:C02022. https://doi.org/10.1029/2005JC003172
Shi J, Cui L, Ma Y, Du H, Wen K (2018) Trends in temperature extremes and their association with circulation patterns in china during 1961–2015. Atmos Res 212:259–272. https://doi.org/10.1016/j.atmosres.2018.05.024
Stocker TF et al (2013) Climate change 2013 the physical science basis. Cambridge University Press, Cambridge
Su Q, Dong B (2019a) Recent decadal changes in heat waves over China: drivers and mechanisms. J Clim 32:4215–4234. https://doi.org/10.1175/JCLI-D-18-0479.1
Su Q, Dong B (2019b) Projected near-term changes in three types of heat waves over China under RCP4.5. Clim Dyn 53:3751–3769. https://doi.org/10.1007/s00382-019-04743-y
Sun Y, Song LC, Yin H et al (2016) Human influence on the 2015 extreme high temperature events in western China. Bull Am Meteor Soc 97:S102–S106. https://doi.org/10.1175/BAMS-D-16-0158.1
Thackeray CW, Fletcher CG (2016) Snow albedo feedback: current knowledge, importance, outstanding issues and future directions. Prog Phys Geogr 40(3):392–408. https://doi.org/10.1177/0309133315620999
Tian F, Dong B, Robson J, Sutton R, Wilcox L (2020) Processes shaping the spatial pattern and seasonality of the surface air temperature response to anthropogenic forcing. Clim Dyn 54:3959–3975. https://doi.org/10.1007/s00382-020-05211-8
Vannière BE, Guilyardi G, Madec FJ, Doblas R, Woolnough S (2013) Using seasonal hindcasts to understand the origin of the equatorial cold tongue bias in CGCMs and its impact on ENSO. Clim Dyn 40(3–4):963–981
Walters DN, Best MJ, Bushell AC, Copsey D, Edwards JM, Falloon PD, Roberts MJ (2011) The met office unified model global atmosphere 3.0/3.1 and JULES global land 3.0/3.1 configurations. Geosci Model Dev 4(4):919–941
Wang C, Zhang L, Lee S-K, Wu L, Mechoso CR (2014) A global perspective on CMIP5 climate model biases. Nat Clim Change 4:201–205. https://doi.org/10.1038/nclimate2118
Wang Z, Lin L, Yang M, Xu YY (2016) The effect of future reduction in aerosol emissions on climate extremes in China. Clim Dyn 47(9–10):1–15
Whan K, Zscheischler J, Orth R et al (2015) Impact of soil moisture on extreme maximum temperatures in Europe. Weather Clim Extrem. https://doi.org/10.1016/j.wace.2015.05.001
Wilcox LJ, Dong B, Sutton RT, Highwood EJ (2015) The 2014 hot, dry summer in Northeast Asia [in “Explaining Extremes of 2014 from a Climate Perspective”]. Bull Am Meteor Soc 96(12):S105–S110. https://doi.org/10.1175/bams-d-15-00123.1
Williams KD et al (2015) The met office global coupled model 2.0 (GC2) configuration. Geosci Model Dev 8(5):1509–1524
Xu Y, Wu J, Shi Y et al (2015) Change in extreme climate events over China based on CMIP5. Atmos Ocean Sci Lett 8:185–192. https://doi.org/10.3878/AOSL20150006
Yang FL et al (2001) Snow-albedo feedback and seasonal climate variability over North America. J Clim 14(22):4245–4248. https://doi.org/10.1175/1520-0442(2001)0142.0.CO2
Yin H, Sun Y, Wan H, Zhang XB, Lu CH (2016) Detection of anthropogenic influence on the intensity of extreme temperatures in China. Int J Climatol 37:1229–1237. https://doi.org/10.1002/joc.4771
Yu Z, Li X (2015) Recent trends in daily temperature extremes over northeastern China (1960–2011). Quat Int 380:35–48. https://doi.org/10.1016/j.quaint.2014.09.010
Zhou B, Wen QH, Xu Y, Song L, Zhang X (2014) Projected changes in temperature and precipitation extremes in China by the CMIP5 multimodel ensembles. J Clim 27(17):6591–6611. https://doi.org/10.1175/jcli-d-13-00761.1
Zhou BT, Xu Y, Wu J, Dong S, Shi Y (2016) Changes in temperature and precipitation extreme indices over China: analysis of a highresolution grid dataset. Int J Climatol 36:1051–1066. https://doi.org/10.1002/joc.4400
Zhou CL, Wang K, Qi D et al (2019) Attribution of a record-breaking heatwave event in summer 2017 over the Yangtze river delta. Bull Am Meteor Soc 100(1):S97–S103. https://doi.org/10.1175/BAMS-D-18-0134.1
Acknowledgements
This study is supported by the National Natural Science Foundation of China (Grant 41675078), by the National Key R&D Program of China (Grant 2019YFA0606703), by the Youth Innovation Promotion Association of CAS (No. 2018102) and by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. BD is supported by the U.K. National Centre for Atmospheric Science–Climate (NCAS-Climate) at the University of Reading. We like to thank anonymous reviewers for their constructive comments and suggestions that help to improve this paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Chen, W., Dong, B. Projected near-term changes in temperature extremes over China in the mid-twenty-first century and underlying physical processes. Clim Dyn 56, 1879–1894 (2021). https://doi.org/10.1007/s00382-020-05566-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-020-05566-y