Theoretical and Applied Climatology

, Volume 135, Issue 3–4, pp 1609–1627 | Cite as

Assessment of trends and variability in surface air temperature on multiple high-resolution datasets over the Indochina Peninsula

  • Fei GeEmail author
  • Ting Peng
  • Klaus Fraedrich
  • Frank Sielmann
  • Xiuhua Zhu
  • Xiefei Zhi
  • Xiaoran Liu
  • Weiwei Tang
  • Pengguo Zhao
Original Paper


The climatological means and surface air temperature (SAT) trends of the Indochina Peninsula (ICP) are being analyzed on a yearly and seasonal basis using a newly published observation dataset (SA-OBS). The SAT for the period 1981 to 2010 shows a north-south gradient over the ICP, with the highest mean annual temperature in the central plain and the lowest in the northern mountain region. In addition, over the past 30 years, the ICP has been undergoing a significant warming trend of 0.37 °C/decade. The seasonal mean SAT fluctuations are significant in the dry seasons compared to the wet seasons, with a rapid increase in JFM (January to March) and OND (October to December). Further, comparisons are made using SA-OBS and the other observation (CRU, GHCN_CAMS, DEL) or reanalysis (ERA-20C, CERA-20C, ERA-Interim, JRA-55) datasets. The result shows (i) that the SA-OBS dataset can capture the spatial distributions and temporal patterns reasonably well throughout the ICP on annual and seasonal scales. (ii) CERA-20C is very similar to SA-OBS in replicating the annual mean SAT over the ICP, suggesting that the ECMWF’s coupled data assimilation system (CERA) could obviously improve the temperature estimates in that region. (iii) That significant differences, however, still exist between observations and reanalyses in annual and seasonal trends. These discrepancies need to be taken into account to study climate change and variability or to assess regional climate models with focus on the ICP.



This study acknowledges the support of the National Natural Science Foundation of China (91537214, 41575104), the Max Planck Fellow Group, the Scientific Research Foundation of Chengdu University of Information Technology (KYTZ201730), the Open Research Fund Program of Plateau Atmosphere and Environment Key Laboratory of Sichuan Province (PAEKL-2018-Y1), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).


  1. Alexander LV, Zhang X, Peterson TC et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. Google Scholar
  2. Alexander LV, Uotila P, Nicholls N (2009) Influence of sea surface temperature variability on global temperature and precipitation extremes. J Geophys Res 114:D18116. CrossRefGoogle Scholar
  3. Berrisford P, Dee DP, Fielding K, Fuentes M, Kållberg P, Kobayashi S, Uppala SM (2009) ‘The ERA-Interim Archive’. ERA Report Series, No.1. ECMWF, ReadingGoogle Scholar
  4. Caesar J, Alexander LV, Trewin B (2011) Changes in temperature and precipitation extremes over the indo-Pacific region from 1971 to 2005. Int J Climatol 31:791–801CrossRefGoogle Scholar
  5. Cai DL, You QL, Fraedrich K, Guan YN (2017) Spatiotemporal temperature variability over the Tibetan plateau: altitudinal dependence associated with the global warming hiatus. J Clim 30:969–983CrossRefGoogle Scholar
  6. Chen TC, Yoon JH (2000) Interannual variation in Indochina summer monsoon rainfall: possible mechanism. J Clim 13:1979–1986CrossRefGoogle Scholar
  7. Chou C, Neelin JD, Chen CA, Tu JY (2009) Evaluating the “rich-get-richer” mechanism in tropical precipitation change under global warming. J Clim 22(8):1982–2005CrossRefGoogle Scholar
  8. Cornes RC, Jones PD (2013) How well does the ERA-interim reanalysis replicate trends in extremes of surface temperature across Europe? J Geophys Res 118:10262–10272. Google Scholar
  9. Cressman GP (1959) An operational objective analysis system. Mon Weather Rev 87(10):367–374CrossRefGoogle Scholar
  10. Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thépaut JN, Vitart F (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597CrossRefGoogle Scholar
  11. Dee DP, Balmaseda M, Balsamo G, Engelen R, Simmons A, Thépaut J-N (2014) Toward a consistent reanalysis of the climate system. Bull Am Meteorol Soc 95(8):1235–1248CrossRefGoogle Scholar
  12. Easterling DR, Wehner MF (2009) Is the climate warming or cooling? Geophys Res Lett 36:L08706CrossRefGoogle Scholar
  13. Easterling DR, Evans JL, Groisman PY, Karl TR, Kunkel KE, Ambenje P (2000) Observed variability and trends in extreme climate events: a brief review. Bull Am Meteorol Soc 81:417–425CrossRefGoogle Scholar
  14. Fan Y, van den Dool H (2008) A global monthly land surface air temperature analysis for 1948-present. J Geophys Res 113:D01103. CrossRefGoogle Scholar
  15. Ge F, Zhi XF, Babar ZA, Tang WW, Chen P (2017) Interannual variability of summer monsoon precipitation over the Indochina Peninsula in association with ENSO. Theor Appl Climatol 128(3–4):523–531CrossRefGoogle Scholar
  16. Griffiths GM, Chambers LE, Haylock MR (2005) Change in mean temperature as a predictor of extreme temperature change in the Asia-Pacific region. Int J Climatol 25:1301–1330CrossRefGoogle Scholar
  17. Harada Y, Kamahori H, Kobayashi C et al (2016) The JRA-55 reanalysis: representation of atmospheric circulation and climate variability. J Meteor Soc Jpn 94:269–302CrossRefGoogle Scholar
  18. Harris I, Jones PD, Osborn TJ, Lister DH (2014) Updated high-resolution grids of monthly climatic observations–the CRU TS3. 10 dataset. Int J Climatol 34(3):623–642CrossRefGoogle Scholar
  19. Haylock M, Hofstra N, Klein Tank A et al (2008) A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006. J Geophys Res 113:D20119. CrossRefGoogle Scholar
  20. Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. J Clim 19:5686–5699CrossRefGoogle Scholar
  21. Hersbach H, Peubey C, Simmons A, Berrisford P, Poli P, Dee D (2015) ERA-20CM: a twentieth-century atmospheric model ensemble. Q J R Meteorol Soc 141(691):2350–2375CrossRefGoogle Scholar
  22. Hersbach H, Brönnimann S, Haimberger L, Mayer M, Villiger L, Comeaux J, Simmons A, Dee D, Jourdain S, Peubey C, Poli P, Rayner N, Sterin AM, Stickler A, Valente MA, Worley SJ (2017) The potential value of early (1939-1967) upper-air data in atmospheric climate reanalysis. Q J R Meteorol Soc 143(704):1197–1210CrossRefGoogle Scholar
  23. Hsu HH, Zhou T, Matsumoto J (2014) East Asian, Indochina and western North Pacific summer monsoon-an update. Asia-Pac J Atmos Sci 50(1):45–68CrossRefGoogle Scholar
  24. IPCC (2013) Summary for policymakers of 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, CambridgeGoogle Scholar
  25. Ji F, Wu ZH, Huang JP, Chassignet EP (2014) Evolution of land surface air temperature trend. Nat Clim Chang 4(6):462–466CrossRefGoogle Scholar
  26. Jones PD, Lister DH, Osborn TJ et al (2012) Hemispheric and large-scale land-surface air temperature variations: an extensive revision and an update to 2010. J Geophys Res 117:D05127. Google Scholar
  27. Kendall MG (1975) Rank correlation methods. Griffin, LondonGoogle Scholar
  28. Kobayashi S, Ota Y, Harada Y et al (2015) The JRA-55 reanalysis: general specifications and basic characteristics. J Meteor Soc Jpn 93:5–48CrossRefGoogle Scholar
  29. Laloyaux P, Balmaseda M, Dee D, Mogensen K, Janssen P (2016) A coupled data assimilation system for climate reanalysis. Q J R Meteorol Soc 142(694):65–78CrossRefGoogle Scholar
  30. Lau KM, Yang S (1997) Climatology and interannual variability of the Southeast Asian summer monsoon. Adv Atmos Sci 14:141–161CrossRefGoogle Scholar
  31. Legates DR, Willmott CJ (1990) Mean seasonal and spatial variability in global surface air temperature. Theor Appl Climatol 41:11–21CrossRefGoogle Scholar
  32. Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259CrossRefGoogle Scholar
  33. Manton MJ, Della-Marta PM, Haylock MR, Hennessy KJ, Nicholls N, Chambers LE, Collins DA, Daw G, Finet A, Gunawan D, Inape K, Isobe H, Kestin TS, Lefale P, Leyu CH, Lwin T, Maitrepierre L, Ouprasitwong N, Page CM, Pahalad J, Plummer N, Salinger MJ, Suppiah R, Tran VL, Trewin B, Tibig I, Yee D (2001) Trends in extreme daily rainfall and temperature in Southeast Asia and the south pacific: 1961–1998. Int J Climatol 21:269–284CrossRefGoogle Scholar
  34. Marjuki, van der Schrier G, Klein Tank AMG et al (2016) Observed trends and variability in climate indices relevant for crop yields in Southeast Asia. J Clim 29:2651–2669. CrossRefGoogle Scholar
  35. Meehl GA (1987) The annual cycle and interannual variability in the tropical Pacific and Indian Ocean regions. Mon Weather Rev 115(1):27–50CrossRefGoogle Scholar
  36. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high resolution grids. Int J Climatol 25:693–712CrossRefGoogle Scholar
  37. Modarres R, Silva VPR (2007) Rainfall trends in arid and semi-arid regions of Iran. J Arid Environ 70:344–355CrossRefGoogle Scholar
  38. Naylor RL, Falcon WP, Rochberg D, Wada N (2001) Using El Nino/Southern Oscillation climate data to predict rice production in Indonesia. Clim Chang 50(3):255–265CrossRefGoogle Scholar
  39. Naylor RL, Battisti DS, Vimont DJ, Falcon WP, Burke MB (2007) Assessing risks of climate variability and climate change for Indonesian rice agriculture. Proc Natl Acad Sci 104:7752–7757CrossRefGoogle Scholar
  40. Nguyen DQ, Renwick J, McGregor J (2014) Variations of surface temperature and rainfall in Vietnam from 1971 to 2010. Int J Climatol 34(1):249–264CrossRefGoogle Scholar
  41. Pepin NC, Lundquist JD (2008) Temperature trends at high elevations: patterns across the globe. Geophys Res Lett 35:L14701. CrossRefGoogle Scholar
  42. Peterson TC, Karl TR, Jamason PF, Knight R, Easterling DR (1998) First difference method: maximizing station density for the calculation of long-term global temperature change. J Geophys Res 103(D20):25967–25974CrossRefGoogle Scholar
  43. Poli P, Hersbach H, Dee DP, Berrisford P, Simmons AJ, Vitart F, Laloyaux P, Tan DGH, Peubey C, Thépaut JN, Trémolet Y, Hólm EV, Bonavita M, Isaksen L, Fisher M (2016) ERA-20C: an atmospheric reanalysis of the twentieth century. J Clim 29(11):4083–4097CrossRefGoogle Scholar
  44. Rangwala I, Miller JR (2012) Climate change in mountains: a review of elevation-dependent warming and its possible causes. Clim Chang 114:527–547CrossRefGoogle Scholar
  45. Sen PK (1968) Estimates of regression coefficient based on Kendall’s tau. J Am Stat Assoc 63:1379–1389CrossRefGoogle Scholar
  46. Simmons AJ, Willett KM, Jones PD et al (2010) Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: inferences from reanalyses and monthly gridded observational data sets. J Geophys Res 115:D01110. Google Scholar
  47. Tabari H, Talaee PH (2011) Temporal variability of precipitation over Iran:1966-2005. J Hydrol 396(3):313–320CrossRefGoogle Scholar
  48. Takahashi HG, Yasunari T (2006) A climatological monsoon break in rainfall over Indochina—a singularity in the seasonal march of the Asian summer monsoon. J Clim 19(8):1545–1556CrossRefGoogle Scholar
  49. Takahashi HG, Fujinami H, Yasunari T, Matsumoto J, Baimoung S (2015) Role of tropical cyclones along the monsoon trough in the 2011 Thai flood and interannual variability. J Clim 28:1465–1476CrossRefGoogle Scholar
  50. Tanarhte M, Hadjinicolaou P, Lelieveld J (2012) Intercomparison of temperature and precipitation data sets based on observations in the Mediterranean and the Middle East. J Geophys Res 117:D12102. CrossRefGoogle Scholar
  51. Tao H, Gemmer M, Bai Y, Su B, Mao W (2011) Trends of stream flow in the Tarim River basin during the past 50 years: human impact or climate change? J Hydrol 400:1): 1–1): 9CrossRefGoogle Scholar
  52. van den Besselaar EJM, van der Schrier G, Cornes RC, Iqbal AS, Klein Tank AMG (2017) SA-OBS: a daily gridded surface temperature and precipitation dataset for Southeast Asia. J Clim 30(14):5151–5165CrossRefGoogle Scholar
  53. Vecchi GA, Soden BJ, Wittenberg AT, Held IM, Leetmaa A, Harrison MJ (2006) Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing. Nature 441(7089):73–76CrossRefGoogle Scholar
  54. Villafuerte MQ, Matsumoto J (2015) Significant influences of global mean temperature and ENSO on extreme rainfall in Southeast Asia. J Clim 28(5):1905–1919CrossRefGoogle Scholar
  55. Wang B, Fan Z (1999) Choice of South Asian summer monsoon indices. Bull Am Meteorol Soc 80(4):629–638CrossRefGoogle Scholar
  56. Williamson F, Allan R, Switzer AD, Chan JCL, Wasson RJ, D’Arrigo R, Gartner R (2015) New directions in hydro-climatic histories: observational data recovery, proxy records and the atmospheric circulation reconstructions over the earth (ACRE) initiative in Southeast Asia. Geosci Lett 2, 2Google Scholar
  57. Willmott CJ (1984) On the evaluation of model performance in physical geography. In: Gaile GL, Willmott CJ (eds) Spatial statistics and models. Springer, Dordrecht ISBN: 978-90-481-8385-2Google Scholar
  58. Willmott CJ, Matsuura K (1995) Smart interpolation of annually averaged air temperature in the United States. J Appl Meteorol 34:2577–2586CrossRefGoogle Scholar
  59. Willmott CJ, Robeson SM (1995) Climatologically aided interpolation (CAI) of terrestrial air temperature. Int J Climatol 15(2):221–229CrossRefGoogle Scholar
  60. Willmott CJ, Rowe CM, Philpot WD (1985) Small-scale climate maps: a sensitivity analysis of some common assumptions associated with grid-point interpolation and contouring. Am Cartogr 12:5–16CrossRefGoogle Scholar
  61. Wu RG, Wang B (2000) Interannual variability of summer monsoon onset over the western North Pacific and the underlying processes. J Clim 13(14):2483–2501CrossRefGoogle Scholar
  62. Wu ZH, Huang NE, Long SR, Peng C-K (2007) On the trend, detrending and variability of nonlinear and non-stationary time series. Proc Natl Acad Sci U S A 104:14889–14894CrossRefGoogle Scholar
  63. Wu ZH, Huang NE, Wallace JM, Smoliak BV, Chen XY (2011) On the time-varying trend in global-mean surface temperature. Clim Dyn 37(3):759–773CrossRefGoogle Scholar
  64. You QL, Fraedrich K, Ren GY, Pepin N, Kang SC (2013) Variability of temperature in the Tibetan plateau based on homogenized surface stations and reanalysis data. Int J Climatol 33(6):1337–1347CrossRefGoogle Scholar
  65. You QL, Min JZ, Zhang W, Pepin N, Kang SC (2015) Comparison of multiple datasets with gridded precipitation observations over the Tibetan plateau. Clim Dyn 45(3):791–806CrossRefGoogle Scholar
  66. Yue S, Hashino M (2003) Temperature trends in Japan: 1900-1996. Theor Appl Climatol 75(1):15–27Google Scholar
  67. Zhu X, Bye J, Fraedrich K, Bordi I (2016) Statistical structure of intrinsic climate variability under global warming. J Clim 29:5935–5947CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  • Fei Ge
    • 1
    Email author
  • Ting Peng
    • 2
  • Klaus Fraedrich
    • 3
  • Frank Sielmann
    • 4
  • Xiuhua Zhu
    • 5
  • Xiefei Zhi
    • 2
  • Xiaoran Liu
    • 6
  • Weiwei Tang
    • 7
  • Pengguo Zhao
    • 1
  1. 1.Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric SciencesChengdu University of Information TechnologyChengduChina
  2. 2.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, KLMENanjing University of Information Science and TechnologyNanjingChina
  3. 3.Max Planck Institute for MeteorologyHamburgGermany
  4. 4.Meteorological InstituteHamburg UniversityHamburgGermany
  5. 5.Klima CampusHamburg UniversityHamburgGermany
  6. 6.Chongqing Climate CenterChongqingChina
  7. 7.College of Communication EngineeringChengdu University of Information TechnologyChengduChina

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