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Journal of Geographical Sciences

, Volume 29, Issue 1, pp 29–48 | Cite as

Sensitivity of arid/humid patterns in China to future climate change under a high-emissions scenario

  • Danyang Ma
  • Haoyu Deng
  • Yunhe Yin
  • Shaohong Wu
  • Du Zheng
Article
  • 11 Downloads

Abstract

Changes in regional moisture patterns under the impact of climate change are an important focus for science. Based on the five global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), this paper projects trends in the area of arid/humid climate regions of China over the next 100 years. It also identifies the regions of arid/humid patterns change and analyzes their temperature sensitivity of responses. Results show that future change will be characterized by a significant contraction in the humid region and an expansion of arid/humid transition zones. In particular, the sub-humid region will expand by 28.69% in the long term (2070–2099) relative to the baseline period (1981–2010). Under 2°C and 4°C warming, the area of the arid/humid transition zones is projected to increase from 10.17% to 13.72% of the total of China. The humid region south of the Huaihe River Basin, which is affected mainly by a future increase in evapotranspiration, will retreat southward and change to a sub-humid region. In general, the sensitivity of responses of arid/humid patterns to climate change in China will intensify with accelerating global warming.

Keywords

arid/humid patterns climate change sensitivity aridity index China 

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References

  1. Alessandri A, de Felice M, Zeng N et al., 2014. Robust assessment of the expansion and retreat of Mediterranean climate in the 21st century. Scientific Reports, 4(3): 7211. doi: 10.1038/srep07211.Google Scholar
  2. Allen R G, Pereira L S, Raes D et al., 1998. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. United Nations Food and Agriculture Organization, Rome.Google Scholar
  3. Bailey R G, 2009. Ecosystem Geography: From Ecoregions to Sites. New York: Springer-Verlag.Google Scholar
  4. Belda M, Holtanová E, Halenka T et al., 2015. Evaluation of CMIP5 present climate simulations using the Köppen- Trewartha climate classification. Climate Research, 64(3): 201–212.Google Scholar
  5. Belda M, Holtanová E, Kalvová J et al., 2016. Global warming-induced changes in climate zones based on CMIP5 projections. Climate Research, 71(1): 17–31.Google Scholar
  6. Budyko M I, 1974. Climate and Life. New York: Academic Press.Google Scholar
  7. Chan D, Wu Q G, 2015. Significant anthropogenic-induced changes of climate classes since 1950. Scientific Reports, 5: 13487. doi: 10.1038/srep13487.Google Scholar
  8. Chan D, Wu Q G, Jiang G X et al., 2016. Projected shifts in Köppen climate zones over China and their temporal evolution in CMIP5 multi-model simulations. Advances in Atmospheric Sciences, 33(3): 283–293.Google Scholar
  9. Chen H P, Sun J Q, 2015. Changes in climate extreme events in China associated with warming. International Journal of Climatology, 35(10): 2735–2751.Google Scholar
  10. Cheng Z G, Zhang Y M, Xu Y, 2015. Projection of climate zone shifts in the 21st century in China based on CMIP5 models data. Climate Change Research, 11(2): 93–101. (in Chinese)Google Scholar
  11. Ci L J, Yang X H, Chen Z X, 2002. The potential impacts of climate change scenarios on desertification in China. Earth Science Frontiers, 9(2): 287–294. (in Chinese)Google Scholar
  12. Cook B I, Smerdon J E, Seager R et al., 2014. Global warming and 21st century drying. Climate Dynamics, 43(9/10): 2607–2627.Google Scholar
  13. Crosbie R S, Pollock D W, Mpelasoka F S et al., 2012. Changes in Köppen-Geiger climate types under a future climate for Australia: Hydrological implications. Hydrology & Earth System Sciences, 16(9): 3341–3349.Google Scholar
  14. Dai A, 2013. Increasing drought under global warming in observations and models. Nature Climate Change, 3(1): 52–58.Google Scholar
  15. Elguindi N, Grundstein A, Bernardes S et al., 2014. Assessment of CMIP5 global model simulations and climate change projections for the 21st century using a modified Thornthwaite climate classification. Climatic Change, 122(4): 523–538.Google Scholar
  16. Engelbrecht C J, Engelbrecht F A, 2016. Shifts in Köppen-Geiger climate zones over southern Africa in relation to key global temperature goals. Theoretical & Applied Climatology, 123(1/2): 247–261.Google Scholar
  17. Feng S, Ho C H, Hu Q et al., 2012. Evaluating observed and projected future climate changes for the Arctic using the Köppen-Trewartha climate classification. Climate Dynamics, 38(7/8): 1359–1373.Google Scholar
  18. Feng S, Hu Q, Huang W et al., 2014. Projected climate regime shift under future global warming from multi-model, multi-scenario CMIP5 simulations. Global & Planetary Change, 112(1): 41–52.Google Scholar
  19. Fu C, 1992. Transitional Climate Zones and Biome Boundaries: A Case Study from China. New York: Springer.Google Scholar
  20. Fu Y H, Zhao H, Piao S et al., 2015. Declining global warming effects on the phenology of spring leaf unfolding. Nature, 526(7571): 104. doi: 10.1038/nature15402.Google Scholar
  21. Gao X J, Giorgi F, 2008. Increased aridity in the Mediterranean region under greenhouse gas forcing estimated from high resolution simulations with a regional climate model. Global & Planetary Change, 62(3): 195–209.Google Scholar
  22. Gerstengarbe F W, Werner P C, 2009. A short update on Koeppen climate shifts in Europe between 1901 and 2003. Climatic Change, 92(1/2): 99–107.Google Scholar
  23. Gnanadesikan A, Stouffer R J, 2006. Diagnosing atmosphere-ocean general circulation model errors relevant to the terrestrial biosphere using the Köppen climate classification. Geophysical Research Letters, 33(22): 2832–2849.Google Scholar
  24. Greve P, Seneviratne S I, 2015. Assessment of future changes in water availability and aridity. Geophysical Research Letters, 42(13): 5493–5499.Google Scholar
  25. Grundstein A, 2008. Assessing climate change in the contiguous United States using a modified Thornthwaite climate classification scheme. Professional Geographer, 60(3): 398–412.Google Scholar
  26. Hanf F, Körper J, Spangehl T et al., 2012. Shifts of climate zones in multi-model climate change experiments using the Köppen climate classification. Meteorologische Zeitschrift, 21(2): 111–123.Google Scholar
  27. Hempel S, Frieler K, Warszawski L et al., 2013. A trend-preserving bias correction–The ISI-MIP approach. Earth System Dynamics, 4(2): 219–236.Google Scholar
  28. Huang J P, Ji M X, Xie Y K et al., 2016a. Global semi-arid climate change over last 60 years. Climate Dynamics, 46(3/4): 1131–1150.Google Scholar
  29. Huang J P, Yu H P, Guan X D et al., 2016b. Accelerated dryland expansion under climate change. Nature Climate Change, 6(2): 166–171.Google Scholar
  30. 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, United Kingdom and New York, USA: Cambridge University PressGoogle Scholar
  31. Jiang J, Jiang D B, Lin Y H, 2017. Changes and projection of dry/wet areas over China. Chinese Journal of Atmospheric Sciences, 41(1): 43–56. (in Chinese)Google Scholar
  32. Joshi M, Hawkins E, Sutton R et al., 2011. Projections of when temperature change will exceed 2°C above pre-industrial levels. Nature Climate Change, 1(8): 407–412.Google Scholar
  33. Knutti R, Furrer R, Tebaldi C et al., 2010. Challenges in combining projections from multiple climate models. Journal of Climate, 23(10): 2739–2758.Google Scholar
  34. Leng G Y, Tang Q H, Rayburg S, 2015. Climate change impacts on meteorological, agricultural and hydrological droughts in China. Global & Planetary Change, 126: 23–34.Google Scholar
  35. Li M X, Ma Z G, 2013. Soil moisture-based study of the variability of dry-wet climate and climate zones in China. Chinese Science Bulletin, 58(Suppl.1): 531–544.Google Scholar
  36. Lohmann R, 1993. The Koppen climate classification as a diagnostic tool for general circulation models. Climate Research, 3(3): 177–193.Google Scholar
  37. Ma Z G, Fu C B, Dan L, 2005. Decadal variations of arid and semi-arid boundary in China. Chinese Journal of Geophysics, 48(3): 519–525. (in Chinese)Google Scholar
  38. Mahlstein I, Daniel J S, Solomon S, 2013. Pace of shifts in climate regions increases with global temperature. Nature Climate Change, 3(8): 739–743.Google Scholar
  39. Mcevoy D J, Huntington J L, Mejia J F et al., 2016. Improved seasonal drought forecasts using reference evapotranspiration anomalies. Geophysical Research Letters, 43(1): 377–385.Google Scholar
  40. Moral F J, Paniagua L L, Rebollo F J et al., 2016. Spatial analysis of the annual and seasonal aridity trends in Extremadura, southwestern Spain. Theoretical & Applied Climatology, 130(3/4): 917–932.Google Scholar
  41. Moss R H, Edmonds J A, Hibbard K A et al., 2010. The next generation of scenarios for climate change research and assessment. Nature, 463(7282): 747–756.Google Scholar
  42. Pierce D W, Barnett T P, Santer B D et al., 2009. Selecting global climate models for regional climate change studies. Proceedings of the National Academy of Sciences, 106(21): 8441–8446.Google Scholar
  43. Piontek F, Müller C, Pugh T A et al., 2014. Multisectoral climate impact hotspots in a warming world. Proceedings of the National Academy of Sciences, 111(9): 3233–3238.Google Scholar
  44. Qian W H, Ding T, Hu H R et al., 2009. An overview of dry-wet climate variability among monsoon-westerly regions and the monsoon northernmost marginal active zone in China. Advances in Atmospheric Sciences, 26(4): 630–641.Google Scholar
  45. Reid P C, Hari R E, Beaugrand G et al., 2015. Global impacts of the 1980s regime shift. Global Change Biology, 22(2): 682–703.Google Scholar
  46. Rohli R V, Joyner T A, Reynolds S J et al., 2015. Globally extended K?ppen-Geiger climate classification and temporal shifts in terrestrial climatic types. Physical Geography, 36(2): 142–157.Google Scholar
  47. Roudier P, Andersson J C M, Donnelly C et al., 2016. Projections of future floods and hydrological droughts in Europe under a +2°C global warming. Climatic Change, 135(2): 341–355.Google Scholar
  48. Schlaepfer D R, Bradford J B, Lauenroth W K et al., 2017. Climate change reduces extent of temperate drylands and intensifies drought in deep soils. Nature Communications, 8: 14196. doi: 10.1038/ncomms14196.Google Scholar
  49. Schleussner C F, Lissner T K, Fischer E M et al., 2016. Differential climate impacts for policy-relevant limits to global warming: the case of 1.5°C and 2°C. Earth System Dynamics, 7(2): 327–351.Google Scholar
  50. Sherwood S, Fu Q, 2014. A drier future? Science, 343(6172): 737–739.Google Scholar
  51. Shi Z T, 1996. Regional characters of natural disaster in marginal monsoon belt of China. Journal of Arid Land Resources & Environment, 10(4): 1–7. (in Chinese)Google Scholar
  52. Swain S, Hayhoe K, 2015. CMIP5 projected changes in spring and summer drought and wet conditions over North America. Climate Dynamics, 44(9/10): 2737–2750.Google Scholar
  53. Sylla M B, Elguindi N, Giorgi F et al., 2015. Projected robust shift of climate zones over West Africa in response to anthropogenic climate change for the late 21st century. Climatic Change, 134(1/2): 1–13.Google Scholar
  54. Taylor K E, Stouffer R J, Meehl G A, 2012. An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4): 485–498.Google Scholar
  55. Trenberth K E, Dai A, van der Schrier G et al., 2013. Global warming and changes in drought. Nature Climate Change, 4(1): 17–22.Google Scholar
  56. Vautard R, Gobiet A, Sobolowski S et al., 2014. The European climate under a 2°C global warming. Booklist, 9(3): 034006. doi: 10.1088/1748-9326/9/3/034006.Google Scholar
  57. Wang L, Chen W, 2014. A CMIP5 multimodel projection of future temperature, precipitation, and climatological drought in China. International Journal of Climatology, 34(6): 2059–2078.Google Scholar
  58. Wang L, Chen W, Huang G et al., 2016. Changes of the transitional climate zone in East Asia: past and future. Climate Dynamics, 49(4): 1463–1477.Google Scholar
  59. Warszawski L, Frieler K, Huber V et al., 2014. The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework. Proceedings of the National Academy of Sciences, 111(9): 3228–3232.Google Scholar
  60. Wu S H, Yin Y H, Zheng D et al., 2005. Aridity/humidity status of land surface in China during the last three decades. Science in China Ser D Earth Sciences, 48(9): 1510–1518.Google Scholar
  61. Wu S H, Yin Y H, Zheng D et al., 2010. Moisture conditions and climate trends in China during the period 1971–2000. International Journal of Climatology, 26(2): 193–206.Google Scholar
  62. Wu S H, Yin Y H, Zheng D et al., 2016. Advances in terrestrial system research in China. Journal of Geographical Sciences, 26(7): 791–802.Google Scholar
  63. Yang J P, Ding Y J, Chen R S et al., 2002. The interdecadal fluctuation of dry and wet climate boundaries in China in recent 50 years. Acta Geographica Sinica, 57(6): 655–661. (in Chinese)Google Scholar
  64. Yin Y H, Ma D Y, Wu S H et al., 2015. Projections of aridity and its regional variability over China in the mid-21st century. International Journal of Climatology, 35(14): 4387–4398.Google Scholar
  65. Yin Y H, Wu S H, Zhao D S, 2013. Past and future spatiotemporal changes in evapotranspiration and effective moisture on the Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 118(19): 10850–10860.Google Scholar
  66. Yin Y H, Wu S H, Zheng D et al., 2008. Radiation calibration of FAO56 Penman–Monteith model to estimate reference crop evapotranspiration in China. Agricultural Water Management, 95(1): 77–84.Google Scholar
  67. Zeng N, Yoon J H, 2009. Expansion of the world's deserts due to vegetation-albedo feedback under global warming. Geophysical Research Letters, 36(17): L17401.Google Scholar
  68. Zhang X L, Yan X D, 2016. Deficiencies in the simulation of the geographic distribution of climate types by global climate models. Climate Dynamics, 46(9/10): 2749–2757.Google Scholar
  69. Zhao T B, Chen L, Ma Z G, 2014. Simulation of historical and projected climate change in arid and semiarid areas by CMIP5 models. Science Bulletin, 59(4): 412–429.Google Scholar
  70. Zheng J Y, Bian J J, Ge Q S et al., 2013. The climate regionalization in China for 1981–2010. Chinese Science Bulletin, 58(30): 3088–3099. (in Chinese)Google Scholar
  71. Zhu G R, Li Y, 2015. Types and changes of Chinese climate zones from 1961 to 2013 based on Köppen climate classification. Arid Land Geography, 38(6): 1121–1132. (in Chinese)Google Scholar

Copyright information

© Science in China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Danyang Ma
    • 1
    • 2
    • 3
  • Haoyu Deng
    • 1
    • 2
  • Yunhe Yin
    • 1
  • Shaohong Wu
    • 1
    • 2
  • Du Zheng
    • 1
    • 2
  1. 1.Key Laboratory of Land Surface Pattern and SimulationInstitute of Geographic Sciences and Natural Resources Research, CASBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Henan Province Development and Reform CommissionZhengzhouChina

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