Quantifying the importance of interannual, interdecadal and multidecadal climate natural variabilities in the modulation of global warming rates
Despite the monotonically rising greenhouse gas emission, global warming rate changes again and again, especially the slowdown during 1998–2013, challenging the current global temperature change mechanisms. Recently, different-scale natural climate variabilities have been individually recognized as the potential causes of global warming rate change, particularly the recent warming slowdown, but disagreements still exist on their relative importance. Here we quantify the contribution of interannual, interdecadal and multidecadal variabilities (IAV, IDV and MDV) in modulating the global warming rate during the period 1850–2017 via decomposing the global mean temperature timeseries derived from 12 datasets into several quasi-periodic fluctuations and a monotonical secular trend (ST) using the ensemble empirical mode decomposition method. Our results show that the IAV, IDV and MDV dominate the global warming rate change together, rather than one-scale variability alone. For example, during 1998–2013 both the IAV and IDV present obvious negative trends and combine to cut 59 ± 22% of global mean surface temperature (GMST) and 65 ± 38% of sea surface temperature (SST) positive trends which are caused by the steadily warming ST and the warming phase of MDV, thus causing an apparent warming slowdown during this period. Furthermore, we illustrate that the IAV, IDV and MDV mainly originate from the El Niño-Southern oscillation (ENSO), Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO), respectively. Our work partly reconciles the controversy over the importance of different-scale natural variabilities, and provides some insights for climate change attribution and prediction research.
KeywordsGlobal warming slowdown Hiatus Natural climate variability ENSO PDO AMO
We thank all the data providers. M Wei is supported by National Natural Science Foundation of China (NSFC) (No. 41806043) and the Basic Scientific Fund for National Public Research Institutes of China (No. GY0219Q08). F Qiao is jointly supported by the NSFC (No. 41821004), the NSFC-Shandong Joint Fund for Marine Science Research Centers (No. U1606405) and the International cooperation project of Indo-Pacific ocean environment variation and air-sea interaction (No. GASI-IPOVAI-05). Z Song is supported by International cooperation project on the China-Australia Research Centre for Maritime Engineering of Ministry of Science and Technology, P. R. China (No. 2016YFE0101400) and AoShan Talents Cultivation Excellent Scholar Program Supported by Qingdao National Laboratory for Marine Science and Technology (No. 2017ASTCP-ES04). Q Shu is supported by the Basic Scientic Fund for National Public Research Institute of China (ShuXingbei Young Talent Program 2019S06).
- Cai W, Wu L, Lengaigne M, Li T, McGregor S, Kug J, Yu J, Stuecker MF, Santoso A, Li X, Ham Y, Chikamoto Y, Ng B, McPhaden MJ, Du Y, Dommenget D, Jia F, Kajtar JB, Keenlyside N, Lin X, Luo J, Martín-Rey M, Ruprich-Robert Y, Wang G, Xie S, Yang Y, Kang SM, Choi J, Gan B, Kim G, Kim C, Kim S, Kim J, Chang P (2019) Pantropical climate interactions. Science 363:v4236. https://doi.org/10.1126/science.aav4236 CrossRefGoogle Scholar
- Freeman E, Woodruff SD, Worley SJ, Lubker SJ, Kent EC, Angel WE, Berry DI, Brohan P, Eastman R, Gates L, Gloeden W, Ji Z, Lawrimore J, Rayner NA, Rosenhagen G, Smith SR (2017) ICOADS Release 3.0: a major update to the historical marine climate record. Int J Climatol 37:2211–2232. https://doi.org/10.1002/joc.4775 CrossRefGoogle Scholar
- Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen N, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond Ser A Math Phys Eng Sci 454:903–995. https://doi.org/10.1098/rspa.1998.0193 CrossRefGoogle Scholar
- Huang B, Thorne PW, Banzon VF, Boyer T, Chepurin G, Lawrimore JH, Menne MJ, Smith TM, Vose RS, Zhang H (2017) Extended reconstructed sea surface temperature, version 5 (ERSSTv5): upgrades, validations, and intercomparisons. J Clim 30:8179–8205. https://doi.org/10.1175/JCLI-D-16-0836.1 CrossRefGoogle Scholar
- Kennedy JJ, Rayner NA, Smith RO, Parker DE, Saunby M (2011a) Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 1. Measurement and sampling uncertainties. J Geophys Res Atmos 116:D14103. https://doi.org/10.1029/2010jd015218 CrossRefGoogle Scholar
- Knight JR, Kennedy JJ, Folland C, Harris G, Jones GS, Palmer M, Parker D, Scaife A, Stott P (2009) Do global temperature trends over the last decade falsify climate predictions? [In “State of the Climate in 2008”]. Bull Am Meteor Soc 90:S22–S23. https://doi.org/10.1175/BAMS-90-8-StateoftheClimate CrossRefGoogle Scholar
- Mantua NJ, Hare SR, Zhang Y, Wallace JM, Francis RC (1997) A Pacific interdecadal climate oscillation with impacts on salmon production. Bull Am Meteor Soc 78:1069–1079. https://doi.org/10.1175/1520-0477(1997)078%3c1069:APICOW%3e2.0.CO;2 CrossRefGoogle Scholar
- Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res Atmos 108:4407. https://doi.org/10.1029/2002JD002670 CrossRefGoogle Scholar
- Stocker TF, Qin D, Plattner GK, Tignor MMB, Allen SK, Boschung J, Xia Y, Bex V, Midgley PM, Nauels A (2013) Climate Change 2013: The Physical Science Basis. In: Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Report No. 1535 pp, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA,Google Scholar
- Trenberth KE (1997) The definition of El Niño. Bull Am Meteor Soc 78:2771–2778. https://doi.org/10.1175/1520-0477(1997)078%3c2771:TDOENO%3e2.0.CO;2 CrossRefGoogle Scholar
- Vose RS, Arndt D, Banzon VF, Easterling DR, Gleason B, Huang B, Kearns E, Lawrimore JH, Menne MJ, Peterson TC, Reynolds RW, Smith TM, Williams CN, Wuertz DB (2012) NOAA’s merged land-ocean surface temperature analysis. Bull Am Meteor Soc 93:1677–1685. https://doi.org/10.1175/BAMS-D-11-00241.1 CrossRefGoogle Scholar