Climate Dynamics

, Volume 50, Issue 7–8, pp 2513–2536 | Cite as

A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900

  • Wenhui Xu
  • Qingxiang LiEmail author
  • Phil Jones
  • Xiaolan L. Wang
  • Blair Trewin
  • Su Yang
  • Chen Zhu
  • Panmao Zhai
  • Jinfeng Wang
  • Lucie Vincent
  • Aiguo Dai
  • Yun Gao
  • Yihui Ding


A new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 [China Meteorological Administration global Land Surface Air Temperature (CMA-LSAT)] is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal t test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900–2014, 1979–2014 and 1998–2014. The best estimates of warming trends and there 95% confidence ranges for 1900–2014 are approximately 0.102 ± 0.006 °C/decade for the whole year, and 0.104 ± 0.009, 0.112 ± 0.007, 0.090 ± 0.006, and 0.092 ± 0.007 °C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900–2014 and 1979–2014. For an even shorter and more recent period (1998–2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes.


CMA-LSAT dataset Surface air temperature Homogenized Climate change 



This study was supported by the National Special Public Welfare Research Fund (Nos. GYHY201406016 and GYHY201206012), China Meteorological Administration Special Foundation for Climate Change (CCSF201438), and the Natural Science Foundation of China (Nos. 91546117 and 71373131). We thank the many contributors of data, which made establishment of the dataset possible.

Supplementary material

382_2017_3755_MOESM1_ESM.doc (2 mb)
Supplementary material 1 (DOC 2019 KB)


  1. Alexander LV et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D18116. doi: 10.1029/2005JD006290 Google Scholar
  2. Auer I et al (2007) HISTALP—Historical instrumental climatological surface time series of the greater Alpine region 1760–2003. Int J Climatol 27:17–46CrossRefGoogle Scholar
  3. Brohan P, Kennedy J, Harris I, Tett SFB, Jones PD (2006) Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850. J Geophys Res 111:D12106. doi: 10.1029/2005JD006548 CrossRefGoogle Scholar
  4. Cao LJ, Zhao P, Yan ZW et al (2013) Instrumental temperature series in eastern and central China back to the 19th century. J Geophys Res Atmos 118(15):8197–8207CrossRefGoogle Scholar
  5. Cowtan K, Way RG (2014) Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Q J R Meteorol Soc 140(683):1935–1944. doi: 10.1002/qj.2297 CrossRefGoogle Scholar
  6. Dai A, Wang J, Thorne PW, Parker DE, Haimberger L, Wang XL (2011) A new approach to homogenize daily radiosonde humidity data. J Clim 24:965–991. doi: 10.1175/2010JCLI3816.1 CrossRefGoogle Scholar
  7. Dai A, Fyfe J, Xie S, Dai X (2015) Decadal modulation of global surface temperature by internal climate variability. Nat Clim Change 5:555–559. doi: 10.1038/nclimate2605 CrossRefGoogle Scholar
  8. Ding Y, Dai X (1994) Temperature variation in China during the Last 100 years. Meteorology 20:19–26Google Scholar
  9. Domonkos P, Venema V, Mestre O (2013) Efficiencies of homogenisation methods: our present knowledge and its limitation. In: Proceedings of the Seventh seminar for homogenization and quality control in climatological databases.
  10. Duan A, Xiao Z (2015) Does the climate warming hiatus exist over the Tibetan Plateau? Sci Rep 5:13711. doi: 10.1038/srep13711 CrossRefGoogle Scholar
  11. Durre I, Menne MJ, Vose R (2007) Strategies for evaluation quality assurance procedures. J Appl Meteorol Climatol. doi: 10.1175/2007JAMC1706.1 Google Scholar
  12. Feng S, Hu Q, Qian W (2004) Quality control of daily meteorological data in China, 1951–2000: a new dataset. Int J Climatol 24:853–870CrossRefGoogle Scholar
  13. Folland CK, Karl TR (2001) Recent rates of warming in marine environment meet controversy. Eos Trans Am Geophys Union 82(40):453–461CrossRefGoogle Scholar
  14. Hansen J, Ruedy R, Glascoe J et al (1999) GISS analysis of surface temperature change. J Geophys Res 104:30997–31022CrossRefGoogle Scholar
  15. Hansen J, Sato M, Ruedy R, Lo K, Lea DW, Medina-Elizade M (2006) Global temperature change. Proc Nat Acad Sci 103(39):14288–14293CrossRefGoogle Scholar
  16. Hansen J, Ruedy R, Sato M, Lo K (2010) Global surface temperature change. Rev Geophys 48:RG4004. doi: 10.1029/2010RG000345 CrossRefGoogle Scholar
  17. Harris I, Jones PD, Osborn TJ, Lister DH (2014) Updated high-resolution monthly grids of monthly climatic observations: the CRU TS 3.10 dataset. Int J Climatol 34:623–642. doi: 10.1002/joc.3711 CrossRefGoogle Scholar
  18. Hartmann DL, AMG Klein Tank, Rusticucci M, Alexander LV, Brönnimann S, Charabi Y, Dentener FJ, Dlugokencky EJ, Easterling DR, Kaplan A, Soden BJ, Thorne PW, Wild M, Zhai PM (2013) Observations: atmosphere and surface. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) 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
  19. Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) (2001) Climate change 2001, in the scientific basis. Cambridge University Press, CambridgeGoogle Scholar
  20. IPCC (2007) Climate Change (2007) The Physical Science Basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds.) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  21. Jaccard P (1901) Etude comparative de la distribution florale dans une portion des Alpes et des Jura. Bull de la Soc Vaud des Sci Nat 37:547–579Google Scholar
  22. Jones PD (1994) Hemispheric surface air temperature variations: a reanalysis and an update to 1993. J Clim 7(11):1794–1802CrossRefGoogle Scholar
  23. Jones PD (2016) The reliability of global and hemispheric surface temperature records. Adv Atmos Sci 33(3):269–282. doi: 10.1007/s00376-015-5194-4 CrossRefGoogle Scholar
  24. Jones PD, Moberg A (2003) Hemispheric and large-scale surface air temperature variations: an extensive revision and an update to 2001, J Clim 16:206–223CrossRefGoogle Scholar
  25. Jones PD, Raper SCB, Santer B, Cherry BSB, Goodess C, Kelly PM, Wigley TML, Bradley RS, Diaz HF (1985) A grid point surface air temperature data set for the northern hemisphere, TR022. Department of Energy, WashingtonGoogle Scholar
  26. Jones PD, New M, Parker DE, Martin S, Rigor IG (1999) Surface air temperature and its changes over the past 150 years. Rev Geophys 37(2):173–199CrossRefGoogle Scholar
  27. Jones PD, Lister DH, Li Q (2008) Urbanization effects in large-scale temperature records, with an emphasis on China. J Geophys Res 113:D16122. doi: 10.1029/2008/JD009916 CrossRefGoogle Scholar
  28. Jones PD, Lister DH, Osborn TJ, Harpham C, Salmon M, Morice CP (2012) Hemispheric and large-scale land-surface air temperature variations: an extensive revision and an update to 2010. J Geophys Res 117:D05127. doi: 10.1029/2011JD017139 Google Scholar
  29. Karl TR, Arguez A, Huang B, Lawrimore JH, McMahon JR, Menne MJ, Peterson TC, Vose RS, Zhang H-M (2015) Possible artifacts of data biases in the recent global surface warming hiatus. Science 348:1469–1472. doi: 10.1126/science.aaa5632 CrossRefGoogle Scholar
  30. Klein Tank AMG, Wijngaard JB, Konnen GP et al (2002) Daily dataset of 20th-century surface air temperature and precipitation series for the European climate assessment. Int J Climatol 22:1441–1453CrossRefGoogle Scholar
  31. Kuglitsch FG, Auchmann R, Bleisch R, Broennigmann S, Martius O, Stewart M (2012) Break detection of annual Swiss temperature series. J Geophys Res 117:D13105. doi: 10.1029/2012JD017729 CrossRefGoogle Scholar
  32. Lawrimore JH, Menne MJ, Gleason BE, Williams CN, Wuertz DB, Vose RS, Rennie J (2011) An overview of the Global Historical Climatology Network monthly mean temperature data set, version 3. J Geophys Res 116:D19121. doi: 10.1029/2011jd016187 CrossRefGoogle Scholar
  33. Legates DR, McCabe GJ (1999) Evaluating the use of ‘goodness-of-fit’ measures in hydrologic and hydroclimatic model evaluation. Water Resour Res 35:233–241. doi: 10.1029/1998WR900018 CrossRefGoogle Scholar
  34. Lewandowsky S, Risbey J, Oreskes N (2015) The “Pause” in Global Warming: turning a routine fluctuation into a problem for science. Bull Am Meteorol Soc 97(5):723–733. doi: 10.1175/BAMS-D-14-00106.1 CrossRefGoogle Scholar
  35. Li Q (2013) Development of homogenized data sets in China and the possible contributions to global/regional products, International Workshop on Climate Data Requirements and Applications, March 4–8, NanjingGoogle Scholar
  36. Li Q, Dong WJ (2009) Detection and adjustment of undocumented discontinuities in Chinese temperature series using a composite approach. Adv Atmos Sci 26(1):143–153CrossRefGoogle Scholar
  37. Li Z, Yan ZW (2010) Application of multiple analysis of series for homogenization (MASH) to Beijing daily temperature series 1960–2006. Adv Atmos Sci 27(4):777–787CrossRefGoogle Scholar
  38. Li Q, Liu X, Zhang H et al (2004a) Detecting and adjusting on temporal inhomogeneity in Chinese mean surface air temperature datasets. Adv Atmos Sci 21:260–268CrossRefGoogle Scholar
  39. Li Q, Zhang HZ, Liu XN, Huang J-Y (2004b) Urban heat island effect on annual mean temperature during the last 50 years in China. Theor Appl Climatol 79:165–174CrossRefGoogle Scholar
  40. Li Q, Zhang H, Chen J, Li W, Liu X, Jones P (2009) A mainland China homogenized historical temperature dataset of 1951–2004. Bull Am Meteorol Soc 90:1062–1065. doi: 10.1175/2009BAMS2736.1 CrossRefGoogle Scholar
  41. Li Q, Dong W, Li W, Gao X, Jones P, Kennedy J, Parker D (2010a) Assessment of the uncertainties in temperature change in China during the last century. Chin Sci Bull 55:1974–1982. doi: 10.1007/s11434-010-3209-1 CrossRefGoogle Scholar
  42. Li Q, Li W, Si P et al (2010b) Assessment of surface air warming in northeast China, with emphasis on the impacts of urbanization. Theor Appl Climatol. doi: 10.1007/s00704-009-0155-4 Google Scholar
  43. Li Q, Yang S, Xu WH et al (2015) China experiences recent warming hiatus. Geophys Res Lett. doi: 10.1002/2014GL062773 Google Scholar
  44. Li Q, Zhang L, Xu W et al (2016) Comparisons of time series of annual mean surface air temperature for China since 1900: observations, model simulations and extended reanalysis. Bull Am Meteorol Soc. doi: 10.1175/BAMS-D-16-0092.1 (in press) Google Scholar
  45. Mann ME et al (2016) The likelihood of recent record warmth. Sci Rep 6:19831. doi: 10.1038/srep19831 CrossRefGoogle Scholar
  46. Menne MJ, Williams JR (2009) Homogenization of temperature series via pairwise comparisons. J Clim 22:1700–1717CrossRefGoogle Scholar
  47. Oke TR (2004) Initial Guidance to Obtain Representative Meteorological Observations at Urban Sites, Instruments and Methods of Observation Program, IOM Report No. 81, WMO/TD 1250, World Meteorological Organization, GenevaGoogle Scholar
  48. Parker DE (1994) Effects of changing exposure of thermometers at land stations. Int J Climatol 14:1–31CrossRefGoogle Scholar
  49. Parker DE (2004) Large-scale warming is not urban. Nature 432:290–290CrossRefGoogle Scholar
  50. Parker DE (2006) A demonstration that large-scale warming is not urban. J Clim 19:2882–2895CrossRefGoogle Scholar
  51. Peterson TC (2003) Assessment of urban versus rural in situ surface temperatures in the contiguous United States: no difference found. J Clim 16:2941–2959CrossRefGoogle Scholar
  52. Peterson TC, Easterling DR (1994) Creation of homogeneous composite climatological reference series. Int J Climatol 14:671–679CrossRefGoogle Scholar
  53. Peterson TC, Owen TW (2005) Urban heat island assessment: metadata are important. J Clim 18:2637–2646CrossRefGoogle Scholar
  54. Peterson TC, Vose RS (1997) An overview of the global historical climatology network temperature data base. Bull Am Meteorol Soc 78:2837–2849CrossRefGoogle Scholar
  55. Peterson TC, Easterling DR, Karl TR, Groisman P, Nicholls N et al (1998) Homogeneity adjustments of in situ atmospheric climate data: a review. Int J Climatol 18:1493–1517CrossRefGoogle Scholar
  56. Ren G, Chu Z, Zhou Y et al (2005) Recent progresses in studies of regional temperature changes in China. Clim Environ Res 10(4):701–716Google Scholar
  57. Rennie JJ, Lawrimore JH, Gleason BE, Thorne PW, Morice CP, Menne MJ, Williams CN, Gambi de Almeida W, Christy JR, Flannery M, Ishihara M, Kamiguchi K, Klein-Tank AMG, Mhanda A, Lister DH, Razuvaev V, Renom M, Rusticucci M, Tandy J, Worley SJ, Venema V, Angel W, Brunet M, Dattore B, Diamond H, Lazzara MA, Le Blancq F, Luterbacher J, Mächel H, Revadekar J, Vose RS, Yin X (2014) The international surface temperature initiative global land surface databank: monthly temperature data release description and methods. Geosci Data J 1(2):75–102Google Scholar
  58. Rohde R, Muller RA, Jacobsen R et al (2013) A new estimate of the average earth surface land temperature spanning 1753 to 2011. Geoinform Geostat. doi: 10.4172/gigs.1000101.Google Scholar
  59. Simmons AJ, Berrisford P, Dee DP, Hersbach H, Hirahara S, Thépaut J-N (2017) A reassessment of temperature variations and trends from global reanalyses and monthly surface climatological datasets. Q J R Meteorol Soc 143:101–119. doi: 10.1002/qj.2949 CrossRefGoogle Scholar
  60. Slingo J et al (2013) The recent pause in global warming parts 1–3 Rep., The met office, FitzRoy Road, Exeter, UKGoogle Scholar
  61. Smith TM, Reynolds RW, Lawrimore J (2008) Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). J Clim 21:2283–2296CrossRefGoogle Scholar
  62. Sun Q, Miao C, Duan Q et al (2014) Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China. Environ Res Lett 9(1):015001. doi: 10.1088/1748-9326/9/1/015001 (1–16) CrossRefGoogle Scholar
  63. Trewin BC (2004) Effects of changes in algorithms used for the calculation of Australian mean temperature. Aust Meteorol Mag 53:1–11Google Scholar
  64. Trewin BC (2010) Exposure, instrumentation and observing practice effects on land temperature measurements. Wiley Interdisciplinary reviews. Clim Change 1:409–506. doi: 10.1002/wcc.46 Google Scholar
  65. Trewin BC (2013) A daily homogenized temperature data set for Australia. Int J Climatol 33:1510–1529CrossRefGoogle Scholar
  66. Venema VKC, Mestre O, Aguilar E, Auer I, Guijarro JA, Domonkos P, Vertacnik G, Szentimrey T, Stepanek P, Zahradnicek P, Viarre J, Müller-Westermeier G, Lakatos M, Williams CN, Menne MJ, Lindau R, Rasol D, Rustemeier E, Kolokythas K, Marinova T, Andresen L, Acquaotta F, Fratianni S, Cheval S, Klancar M, Brunetti M, Gruber C, Prohom Duran M, Likso T, Esteban P, Brandsma T (2012) Benchmarking homogenization algorithms for monthly data. Clim Past 8:89–115. doi: 10.5194/cp-8-89-2012 CrossRefGoogle Scholar
  67. Vincent LA, Wang XL, Milewska EJ et al (2012) A second generation of homogenized Canadian monthly surface air temperature for climate trend analysis. J Geophys Res 117:D18110. doi: 10.1029/2012JD017859 Google Scholar
  68. Vincent LA, Zhang X, Brown RD, Feng Y, Mekis E, Milewska EJ, Wan H, Wang XL (2015) Observed trends in Canada’s climate and influence of low-frequency variability modes. J Clim 28:4545–4560 (00697.1) CrossRefGoogle Scholar
  69. Vose RS, Schmoyer RL, Steurer PM, Peterson TC, Heim R, Karl TR, Eischeid J (1992) The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea level pressure, and station pressure data. ORNL/CDIAC-53, NDP-041, 325 pp. [Available from Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831]Google Scholar
  70. Wan H, Wang XL, Swail VR (2010) Homogenization and trend analysis of Canadian near-surface wind speeds. J Clim 23:1209–1225CrossRefGoogle Scholar
  71. Wang XL (2008a) Accounting for autocorrelation in detecting mean-shifts in climate data series using the penalized maximal t or F test. J App Meteor Climatol 47:2423–2444. doi: 10.1175/2008JAMC1741.1 CrossRefGoogle Scholar
  72. Wang XL (2008b) Penalized maximal F test for detecting undocumented mean shift without trend change. J Atmos Ocean Technol 19:368–384CrossRefGoogle Scholar
  73. Wang XL, Feng Y (2010) RHtestsV4 user manual, climate research division, science and technology branch, environment Canada, Toronto, Ontario, Canada.
  74. Wang KC, Zhou CL (2015) Regional contrasts of the warming rate over land significantly depend on the calculation methods of mean air temperature. Sci Rep 5:12324. doi: 10.1038/srep12324 CrossRefGoogle Scholar
  75. Wang XL, Wen QH, Wu Y (2007) Penalized maximal t test for detecting undocumented mean change in climate data series. J Appl Meteorol Climatol 46:916–931CrossRefGoogle Scholar
  76. Wang XL, Chen H, Wu Y, Feng Y, Pu Q (2010) New techniques for detection and adjustment of shifts in daily precipitation data series. J Appl Meteor Climatol 49(12):2416–2436. doi: 10.1175/2010JAMC2376.1.CrossRefGoogle Scholar
  77. Wang XL, Feng Y, Vincent LA (2013) Observed changes in one-in-20 year extremes of Canadian surface air temperatures. Atmos Ocean 52(3):222–231. doi: 10.1080/07055900.2013.818526 CrossRefGoogle Scholar
  78. Wang J, Xu C, Hu M et al (2014) A new estimate of the China temperature anomaly series and uncertainty assessment in 1900–2006. J Geophys Res Atmos. doi: 10.1002/2013JD020542.Google Scholar
  79. Wang F, Ge Q, Wang S, Li Q, Jones P (2015) A new estimation of urbanization contribution to the warming trend in China. J Clim 28:8923–8938. doi: 10.1175/JCLI-D-14-00427.1 CrossRefGoogle Scholar
  80. Wickham C et al (2013) Influence of urban heating on the global temperature land average using rural sites identified from MODIS classifications. Geoinfor Geostat. doi: 10.4172/2327-4581.1000104.Google Scholar
  81. Wijngaard JB, Klein Tank AMG, Konnen GP et al (2003) Homogeneity of 20th century European daily temperature and precipitation series. Int J Climatol 23:679CrossRefGoogle Scholar
  82. Williams CN, Menne MJ, Thorne PW (2012) Benchmarking the performance of pairwise homogenization of surface temperatures in the United States. J Geophys Res 117:D05116. doi: 10.1029/2011JD016761 CrossRefGoogle Scholar
  83. Willmott CJ (1981) On the validation of models. Phys Geogr 2:184–194Google Scholar
  84. Willmott CJ, Ackleson SG, Davis RE, Feddema JJ, Klink KM, Legates DR, O’Donnell J, Rowe CM (1985) Statistics for the evaluation and comparisons of models. J Geophys Res 90:8995–9005. doi: 10.1029/JC090iC05p08995 CrossRefGoogle Scholar
  85. Xu W, Li Q, Wang X et al (2013) Homogenization of Chinese daily surface air temperatures and analysis of trends in the extreme temperature indices. J Geophys Res Atmos 118(17):9708–9720CrossRefGoogle Scholar
  86. Yan Z, Li Z, Li Q et al (2009) Effects of site-change and urbanisation in the Beijing temperature series 1977–2006. Int J Climat. doi: 10.1002/joc.1971 Google Scholar
  87. Yin H, Donat MG, Alexander LV et al (2015) Multi-dataset comparison of gridded observed temperature and precipitation extremes over China. Int J Climatol 35(10):2809–2827. doi: 10.1002/joc.4174 CrossRefGoogle Scholar
  88. You Q, Kang S, Anguilar E et al (2011) Changes in daily climate extremes in China and its connection to the large scale atmospheric circulation during 1961–2003. Clim Dyn 36:2399–2417. doi: 10.1007/s00382-009-0735-0 CrossRefGoogle Scholar
  89. Zhai P, Chao Q, Zou X (2004) Progress in China’s climate change study in the 20th century. J Geogr Sci 14:3–11. doi: 10.1007/BF02841101 Google Scholar
  90. Zhai P, Yu R, Guo Y, Li Q, Ren X, Wang Y, Xu W, Liu Y, Ding Y (2016) The strong El Niño in 2015/2016 and its dominant impacts on global and China’s climate. J Meteorol Res 74(3):309–321. doi: 10.11676/qxxb2016.049 Google Scholar
  91. Zhang X, Hegerl G, Zwiers FW, Kenyon J (2005) Avoiding inhomogeneity in percentile-based indices of temperature extremes. J Clim 18:1641–1651. doi: 10.1175/JCLI3366.1 CrossRefGoogle Scholar
  92. Zhou L, Dickinson RE, Tian Y, Fang J, Li Q, Kaufmann RK (2004) Evidence for a significant urbanization effect on climate in China. Proc Natl Acad Sci USA 101:9540–9544CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Wenhui Xu
    • 1
  • Qingxiang Li
    • 2
    Email author
  • Phil Jones
    • 3
    • 4
  • Xiaolan L. Wang
    • 5
  • Blair Trewin
    • 6
  • Su Yang
    • 1
  • Chen Zhu
    • 1
  • Panmao Zhai
    • 7
  • Jinfeng Wang
    • 8
  • Lucie Vincent
    • 5
  • Aiguo Dai
    • 9
  • Yun Gao
    • 10
  • Yihui Ding
    • 11
  1. 1.China Meteorological AdministrationNational Meteorological Information CenterBeijingChina
  2. 2.School of Atmospheric SciencesSun Yat-sen UniversityGuangzhouChina
  3. 3.Climatic Research Unit, School of Environmental SciencesUniversity of East AngliaNorwichUK
  4. 4.Center of Excellence for Climate Change Research, Department of MeteorologyKing Abdulaziz UniversityJeddahSaudi Arabia
  5. 5.Climate Research Division, Science and Technology BranchEnvironment and Climate Change CanadaTorontoCanada
  6. 6.Australian Bureau of MeteorologyMelbourneAustralia
  7. 7.China Meteorological AdministrationChina Academy of Meteorological SciencesBeijingChina
  8. 8.LREIS, Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  9. 9.Department of Atmospheric and Environmental SciencesUniversity at Albany, SUNYAlbanyUSA
  10. 10.China Meteorological AdministrationBeijingChina
  11. 11.China Meteorological AdministrationNational Climate CenterBeijingChina

Personalised recommendations