Advertisement

Climate Dynamics

, Volume 44, Issue 1–2, pp 359–369 | Cite as

Observed and SST-forced multidecadal variability in global land surface air temperature

  • L. H. Gao
  • Z. W. YanEmail author
  • X. W. Quan
Article

Abstract

The characteristics of multidecadal variability (MDV) in global land surface air temperature (SAT) are analyzed based on observations. The role of sea surface temperature (SST) variations in generating MDV in land SAT is assessed using atmospheric general circulation model simulations forced by observed SST. MDV in land SAT exhibits regional differences, with amplitude larger than 0.3 °C mainly over North America, East Asia, Northern Eurasia, Northern Africa and Greenland for the study period of 1902–2004. MDV can account for more than 30 % of long-term temperature variation during the last century in most regions, especially more than 50 % in parts of the above-mentioned regions. The SST-forced simulations reproduce the observed feature of zonal mean MDV in land SAT, though with weaker amplitude especially at the northern high-latitudes. Two types of MDV in land SAT, one of 60-year-timescale, mainly observed in the northern mid-high-latitude lands, and another of 20–30-year-timescale, mainly observed in the low-latitude lands, are also well reproduced. The SST-forced MDV accounts for more than 40 % amplitude of observed MDV in most regions. Except for some sporadically distributed regions in central Eurasia, South America and Western Australia, the SST-forced multidecadal variations are well in-phase with observations. The Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation signals are found dominant in MDV of both the observed and SST-forced land SAT, suggesting important roles of these oceanic oscillations in generating MDV in global land SAT.

Keywords

Multidecadal variability Ensemble empirical mode decomposition Atmospheric general circulation model Sea surface temperature 

Notes

Acknowledgments

The authors thank Philip Pegion, Taiyi Xu, and Tao Zhang at NOAA/ESRL/PSD for helps in preparing the data. Thanks are also due to two anonymous reviewers for their constructive comments. This work was supported by grants CAS-SPRP XDA05090000 and MOST-NBRPC 2012CB956200.

References

  1. Compo GP, Sardeshmukh PD (2009) Oceanic influences on recent continental warming. Clim Dyn 32:333–342. doi: 10.1007/s00382-008-0448-9 CrossRefGoogle Scholar
  2. Delworth TL, Broccoli AJ, Rosati A et al (2006) GFDL’s CM2 global coupled climate models. Part I: formulation and simulation characteristics. J Clim 19:643–674. doi: 10.1175/jcli3629.1 CrossRefGoogle Scholar
  3. Dommenget D (2009) The ocean’s role in continental climate variability and change. J Clim 22:4939–4952. doi: 10.1175/2009jcli2778.1 CrossRefGoogle Scholar
  4. Enfield DB, Mestas-Nunez AM, Trimble PJ (2001) The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental US. Geophys Res Lett 28:2077–2080. doi: 10.1029/2000gl012745 CrossRefGoogle Scholar
  5. Henriksson SV, Raisanen P, Silen J, Laaksonen A (2012) Quasiperiodic climate variability with a period of 50–80 years: Fourier analysis of measurements and earth system model simulations. Clim Dyn 39:1999–2011. doi: 10.1007/s00382-012-1341-0 CrossRefGoogle Scholar
  6. Hoerling M, Kumar A, Eischeid J, Jha B (2008) What is causing the variability in global mean land temperature? Geophys Res Lett 35 (23) doi: 10.1029/2008gl035984
  7. Hoerling M, Hurrell J, Kumar A, Terray L, Eischeid J, Pegion P, Zhang T, Quan XW, Xu TY (2011) On North American decadal climate for 2011–20. J Clim 24:4519–4528. doi: 10.1175/2011jcli4137.1 CrossRefGoogle Scholar
  8. Huang NE, Wu ZH (2008) A review on Hilbert-Huang transform: method and its applications to geophysical studies. Rev Geophys 46: RG2006. doi: 10.1029/2007rg000228
  9. Jha B, Hu ZZ, Kumar A (2013) SST and ENSO variability and change simulated in historical experiments of CMIP5 models. Clim Dyn. doi: 10.1007/s00382-013-1803-z Google Scholar
  10. Karoly DJ, Wu QG (2005) Detection of regional surface temperature trends. J Clim 18:4337–4343. doi: 10.1175/jcli3565.1 CrossRefGoogle Scholar
  11. Kerr RA (2000) A North Atlantic climate pacemaker for the centuries. Science 288(5473):1984–1986. doi: 10.1126/science.288.5473.1984 CrossRefGoogle Scholar
  12. Kiehl JT, Hack JJ, Bonan GB, Boville BA, Williamson DL, Rasch PJ (1998) The National Center for Atmospheric Research Community Climate Model: CCM3. J Clim 11:1131–1149. doi: 10.1175/1520-0442(1998)011<1131:tncfar>2.0.co;2 CrossRefGoogle Scholar
  13. Knight JR, Folland CK, Scaife AA (2006) Climate impacts of the Atlantic Multidecadal Oscillation. Geophys Res Lett 33 (17) doi: 10.1029/2006gl026242
  14. Kravtsov S, Spannagle C (2008) Multidecadal climate variability in observed and modeled surface temperatures. J Clim 21:1104–1121. doi: 10.1175/2007jcli1874.1 CrossRefGoogle Scholar
  15. Latif M, Keenlyside NS (2011) A perspective on decadal climate variability and predictability. Deep Sea Res Part II Top Stud in Oceanogr 58:1880–1894. doi: 10.1016/j.dsr2.2010.10.066 CrossRefGoogle Scholar
  16. L’Heureux M, Collins D, Hu ZZ (2013) Linear trends in sea surface temperature of the tropical Pacific Ocean and implications for the El Niño-Southern Oscillation. Clim Dyn 40:1223–1236. doi: 10.1007/s00382-012-1331-2 CrossRefGoogle Scholar
  17. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25:693–712. doi: 10.1002/joc.1181 CrossRefGoogle Scholar
  18. Qian C, Fu CB, Wu ZH (2011) Changes in the amplitude of the temperature annual cycle in China and their implication for climate change research. J Clim 24:5292–5302. doi: 10.1175/jcli-d-11-00006.1 CrossRefGoogle Scholar
  19. Schlesinger ME, Ramankutty N (1994) An oscillation in the global climate system of period 65–70 years. Nature 367:723–726. doi: 10.1038/367723a0 CrossRefGoogle Scholar
  20. Schubert SD, Suarez MJ, Pegion PJ, Koster RD, Bacmeister JT (2004) Causes of long-term drought in the US Great Plains. J Clim 17:485–503. doi: 10.1175/1520-0442(2004)017<0485:coldit>2.0.co;2 CrossRefGoogle Scholar
  21. Seager R, Kushnir Y, Herweijer C, Naik N, Velez J (2005) Modeling the tropical forcing of persistent droughts and pluvials over western North America: 1856–2000. J Clim 18:4065–4091. doi: 10.1175/JCLI3522.1 CrossRefGoogle Scholar
  22. Semenov VA, Latif M, Dommenget D, Keenlyside NS, Strehz A, Martin T, Park W (2010) The impact of North Atlantic-Arctic multidecadal variability on northern hemisphere surface air temperature. J Clim 23:5668–5677. doi: 10.1175/2010jcli3347.1 CrossRefGoogle Scholar
  23. Sutton RT, Hodson DLR (2005) Atlantic Ocean forcing of North American and European summer climate. Science 309:115–118. doi: 10.1126/science.1109496 CrossRefGoogle Scholar
  24. Trenberth KE, Shea DJ (2006) Atlantic hurricanes and natural variability in 2005. Geophys Res Lett 33:L12704. doi: 10.1029/2006gl026894 CrossRefGoogle Scholar
  25. Wu ZH, Huang NE (2009) Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv Adapt Data Anal 1:1–41CrossRefGoogle Scholar
  26. Wu ZH, Huang NE, Wallace JM, Smoliak BV, Chen XY (2011) On the time-varying trend in global-mean surface temperature. Clim Dyn 37:759–773. doi: 10.1007/s00382-011-1128-8 CrossRefGoogle Scholar
  27. Xia JJ, Yan ZW, Wu PL (2013) Multidecadal variability in local growing season during 1901–2009. Clim Dyn 41:295–305. doi: 10.1007/s00382-012-1438-5 CrossRefGoogle Scholar
  28. Zhang Y, Wallace JM, Battisti DS (1997) ENSO-like interdecadal variability: 1900–93. J Clim 10:1004–1020. doi: 10.1175/1520-0442(1997)010<1004:eliv>2.0.co;2 CrossRefGoogle Scholar
  29. Zhang R, Delworth TL, Held IM (2007) Can the Atlantic Ocean drive the observed multidecadal variability in Northern Hemisphere mean temperature? Geophys Res Lett 34 (2) doi: 10.1029/2006gl028683

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Cooperative Institute for Research in Environmental SciencesUniversity of ColoradoBoulderUSA
  4. 4.NOAA/Earth System Research LaboratoryBoulderUSA

Personalised recommendations