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Changes of the time-varying percentiles of daily extreme temperature in China

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Abstract

Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961–1985 to 1986–2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (Tmax) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50year), and the greatest warming for daily minimum air temperature (Tmin) occurred with very strong trends exceeding 4 °C/50year. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961–1985 to 1986–2010 was found in Tmax. More than half part of the frequency distribution show negative trends less than −0.5 °C/50year in 1961–1985, while showing trends less than 2.5 °C/50year in 1986–2010.

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References

  • Alexander LV et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. doi:10.1029/2005JD006290

    Google Scholar 

  • Caesar J, Alexander L, Vose R (2006) Large-scale changes in observed daily maximum and minimum temperatures: creation and analysis of a new gridded data set. J Geophys Res 111:D05101. doi:10.1029/2005JD006280

    Article  Google Scholar 

  • DaSilva VPR (2004) On climate variability in northeast of Brazil. J Arid Environ 58:575–559

    Article  Google Scholar 

  • Furió D, Meneu V (2011) Analysis of extreme temperatures for four sites across Peninsular Spain. Theor Appl Climatol 104:83–99. doi:10.1007/s00704-010-0324-5

    Article  Google Scholar 

  • Gershunov A, Cayan RD, Iacobellis FS (2009) The great 2006 heat wave over California and Nevada: signal of an increasing trend. J Clim 22:6181–6203

    Article  Google Scholar 

  • Gong D, Pan Y, Wang J (2004) Changes in extreme daily mean temperatures in summer in eastern China during 1955–2000. Theor Appl Climatol 77:25–37. doi:10.1007/s00704-003-0019-2

    Article  Google Scholar 

  • Grant F, Stefan R (2011) Global temperature evolution 1979–2010. Environ Res Lett 6:044022

    Article  Google Scholar 

  • IPCC (2007) Climate change 2007: impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK, p 976

  • Kyselý J (2010) Recent severe heat waves in central Europe: how to view them in a long term prospect? Int J Climatol 30:89–109

    Google Scholar 

  • Li H, Feng L, Zhou T (2011) Multi-model projection of July-August climate extreme changes over China under CO2 doubling. Part II: temperature. Advan Atmos Sci 28:448–463. doi:10.1007/s00376-010-0052-x

    Article  Google Scholar 

  • Liu X, Luo Y, Zhang D et al (2011) Recent changes in pan-evaporation dynamics in China[J]. Geophys Res Lett 38(13)

  • Liu X, Liu C, Luo Y et al (2012) Dramatic decrease in streamflow from the headwater source in the central route of China’s water diversion project: climatic variation or human influence?[J]. Journal of Geophysical Research: Atmospheres, 2012, 117(D6)

  • Liu X, Luo Y, Yang T et al (2015) Investigation of the probability of concurrent drought events between the water source and destination regions of China’s water diversion project[J]. Geophys Res Lett 42(20):8424–8431

    Article  Google Scholar 

  • Min E, Hazeleger W, van Oldenborgh GJ, Sterl A (2013) Evaluation of trends in high temperature extremes in north-western Europe in regional climate models. Environ Res Lett 8:014011

    Article  Google Scholar 

  • Nicholls N, Alexander L (2007) Has the climate become more variable or extreme? Progress 1992–2006. Prog Phys Geogr 31:77–87

  • Robeson SM (2004) Trends in time-varying percentiles of daily minimum and maximum temperature over North America. Geophys Res Lett 31:L04203. doi:10.1029/ 2003GL019019

    Article  Google Scholar 

  • Savić S, Milovanović B, Lužanin Z et al (2014) The variability of extreme temperatures and their relationship with atmospheric circulation: the contribution of applying linear and quadratic models. Theor Appl Climatol. doi:10.1007/s00704-014-1263-3

    Google Scholar 

  • Semenza JC, Rubin CH, Falter KH, et al. (1996) Heat-related deaths during the July 1995 heat wave in Chicago. N Engl J Med 335:84–90

  • Siliverstovs B, Ötsch R, Kemfer C, Jaeger C, Haas A, Kremers H (2008) climate change and modelling of extreme temperatures in Switzerland. DIW Berlin. Discussion Paper 840

  • Simolo C, Brunetti M, Maugeri M, Nanni T (2011) Evolution of extreme temperatures in a warming climate. Geophys Res Lett 38:L16701. doi:10.1029/2011GL048437

    Article  Google Scholar 

  • Sonali P, Kumar N (2013) Review of trend detection methods and their application to detect temperature changes in India. J Hydrol 476:212–227

    Article  Google Scholar 

  • Sterl A, Severijns C, Dijkstra H, Hazeleger W, van Oldenborgh GJ, van den Broeke M, Burgers G (2008) When can we expect extremely high surface temperatures? Geophys Res Lett 35:L14703. doi:10.1029/2008GL034071

    Article  Google Scholar 

  • Wang A-H, Jian-Jian FU (2013) Changes in daily climate extremes of observed temperature and precipitation in China. ATMOSPHERIC AND OCEANIC SCIENCE LETTERS 6(5):312–319

    Article  Google Scholar 

  • Wang L, Wu Z, Wang F, Haibo D, Zong S (2015) Comparative analysis of the extreme temperature event change over Northeast China and Hokkaido, Japan from 1951 to 2011. Theor Appl Climatol. doi:10.1007/s00704-015-1425-y

    Google Scholar 

  • Wei FY (1999) The technologies of statistics diagnosis and forecast in modem climate (in Chinese). China Meteorological Press, Beijing

    Google Scholar 

  • Weisheimer A, Palmer TN (2005) Changing frequency of occurrence of extreme seasonal temperatures under global warming. Geophys Res Lett 32:L20721. doi:10.1029/2005GL023365

    Article  Google Scholar 

  • Wen H Q, Zhang X, Xu Y, and Wang B (2013) Detecting human influence on extreme temperatures in China Geophys. Res. Lett. 0171–1176 doi:10.1002/grl.50285

  • Yang JH, Ren CY, Jiang ZH (2008) Characteristics of extreme temperature event and its response to regional warming in northwest. China in past 45 years Chinese Geographical Science 18(1):70–76. doi:10.1007/s11769-008-0070-0

    Article  Google Scholar 

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Acknowledgments

This study was made possible by funding from National Natural Science Foundation of China (No.41401511); grants from the open funding from the State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (OFSLRSS201410); funding from the National Science and Technology Major Project under Grant 14CNIC-032079-32-02; funding from the foundation of the director of Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, the Hundred Talents Program of the Chinese Academy of Sciences (Y34004101A); and funding from the National Natural Science Foundation of Major International (regional) Collaborative Research Project and the National Natural Science Foundation Project (41101342).

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Authors and Affiliations

  1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China

    Bin Li & Fang Chen

  2. National Disaster Reduction Center/Satellite Application Center for Disaster Reduction of the Ministry of Civil Affairs, Beijing, 100124, China

    Feng Xu

  3. South China Sea Branch State Oceanic Administration, Beijing, China

    Xinrui Wang

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  1. Bin Li
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  2. Fang Chen
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  3. Feng Xu
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  4. Xinrui Wang
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Correspondence to Fang Chen.

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Li, B., Chen, F., Xu, F. et al. Changes of the time-varying percentiles of daily extreme temperature in China. Theor Appl Climatol 130, 1035–1041 (2017). https://doi.org/10.1007/s00704-016-1938-z

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  • DOI: https://doi.org/10.1007/s00704-016-1938-z

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