Abstract
The rate of warming of the Arctic surface temperature has exceeded that of the global surface temperature in recent decades. However, the underlying process and causes of the long-term warming remain uncertain. In this paper, we explored the factors underlying variation in Arctic mean surface temperature anomalies (AMTA) using a piecewise linear model for 1920–2018. This analysis indicated that the change in AMTA during the study period could be divided into three segments, with AMTA increasing from 1920 to 1938, declining from 1939 to 1976, and finally increasing rapidly after 1977. By a newly developed rigorous formalism of information flow, we found a one-way causality from the driving forces to AMTA. Moreover, the AMTA evolution could mainly be attributed to a combined effect of anthropogenic and natural factors (e.g., CO2, aerosol, and PDO). During the first warming stage (1920–1938), the PDO and aerosols are the main factors determining the change in AMTA. During the second warming stage (1977–2018), greenhouse gases, dominated by CO2, are the major factors accounting for the Arctic warming. In 1939–1976, the observed cooling may be associated with aerosols, clouds, and land use. A better understanding of the driving mechanism underlying AMTA evolution provides insight into the historical Arctic climate change, and can improve the prediction of future changes in AMTA.
Similar content being viewed by others
References
ACIA (2005) Arctic climate impact assessment. Cambridge University Press, Cambridge. https://doi.org/10.1007/978-3-319-25582-8_10037
Blackport R, Screen JA, van der Wiel K, Bintanja R (2019) Minimal influence of reduced Arctic sea ice on coincident cold winters in mid-latitudes. Nat Clim Change 9:697–704. https://doi.org/10.1038/s41558-019-0551-4
Chylek P, Folland CK, Lesins G, Dubey MK, Wang M (2009) Arctic air temperature change amplification and the Atlantic Multidecadal Oscillation. Geophys Res Lett 36:61–65. https://doi.org/10.1029/2009GL038777
Cowtan K, Way RG (2014) Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Q J R Meteorol Soc 140:1935–1944. https://doi.org/10.1002/qj.2297
Crespin E, Goosse H, Fichefet T, Mairesse A, Sallaz-Damaz Y (2013) Arctic climate over the past millennium: annual and seasonal responses to external forcings. Holocene 23:321–329. https://doi.org/10.1177/0959683612463095
Crowley TJ, Baum SK, Kim K-Y et al (2003) Modeling ocean heat content changes during the last millennium. Geophys Res Lett 30:1932. https://doi.org/10.1029/2003gl017801
Ding QH, Schweiger A, L'Heureux M et al (2019) Fingerprints of internal drivers of Arctic sea ice loss in observations and model simulations. Nat Geosci 12:28–33. https://doi.org/10.1038/s41561-018-0256-8
Dodd E, Merchant CJ, Rayner NA, Morice CP (2015) An investigation into the impact of using various techniques to estimate Arctic surface air temperature anomalies. J Clim 28:1743–1763. https://doi.org/10.1175/jcli-d-14-00250.1
Dudok de Wit T, Kopp G, Fröhlich C et al (2017) Methodology to create a new total solar irradiance record: making a composite out of multiple data records. Geophys Res Lett 44:1196–1203. https://doi.org/10.1002/2016GL071866
Egorova T, Schmutz W, Rozanov E et al (2018) Revised historical solar irradiance forcing. Astron Astrophys 615:A85. https://doi.org/10.1051/0004-6361/201731199
Flanner MG (2013) Arctic climate sensitivity to local black carbon. J Geophys Res Atmos 118:1840–1851. https://doi.org/10.1002/jgrd.50176
Fyfe JC, Salzen KV, Gillett NP, Arora VK, Flato GM, Mcconnell JR (2013) One hundred years of Arctic surface temperature variation due to anthropogenic influence. Sci Rep 3:2645. https://doi.org/10.1038/srep02645
Gillett NP, Stone DA, Stott PA et al (2008) Attribution of polar warming to human influence. J Geophys Res Atmos 1:750–754. https://doi.org/10.1038/ngeo338
Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37:424–438
Hansen J, Ruedy R, Sato M, Lo K (2010) Global surface temperature change. Rev Geophys 48:1–29. https://doi.org/10.1029/2010RG000345
Hristopulos D, Babul A, Babul SA, Brucar LR, Virji-Babul N (2019) Disrupted information flow in resting-state in adolescents with sports related concussion. Front Hum Neurosci 13:419. https://doi.org/10.1101/671685
Huang JB, Zhang XD, Zhang QY et al (2017) Recently amplified arctic warming has contributed to a continual global warming trend. Nat Clim Change 7:875. https://doi.org/10.1038/s41558-017-0009-5
Hubberten HW, Boike J, Lantuit H (2013) Arctic warming and its con-sequences for Permafrost. Paper presented at the ISAR-3 (Third International Symposium on the Arctic Research), Tokyo, Japan
IPCC (2013) Climate change 2013: the physical science basis. In: Stocker TF et al (eds) Working Group I contribution to the Fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge
IPCC (2014) Climate Change 2014: Synthesis Report. In: Core Writing Team, Pachauri RK, Meyer LA (eds) Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva
Jahn A (2019) Reduced probability of ice-free summers for 1.5 degrees C compared to 2 degrees C warming. Nat Clim Change 9:726–726. https://doi.org/10.1038/s41558-019-0569-7
Johannessen OM, Kuzmina SI, Bobylev LP et al (2016) Surface air temperature variability and trends in the Arctic: new amplification assessment and regionalisation. Tellus A 68:28234. https://doi.org/10.3402/tellusa.v68.28234
Jones GS, Stott PA, Christidis N (2013) Attribution of observed historical near-surface temperature variations to anthropogenic and natural causes using CMIP5 simulations. J Geophys Res Atmos 118:4001–4024. https://doi.org/10.1002/jgrd.50239
Kargel J, Bush A, Leonard G (2013) Arctic warming and sea ice dimi-nution herald changing glacier and cryospheric hazard regimes. In: EGU general assembly conference abstracts, vol 15, p 14188
Kim JS, Kug JS, Jeong SJ et al (2017) Reduced North American terrestrial primary productivity linked to anomalous Arctic warming. Nat Geosci 10:572–576. https://doi.org/10.1038/NGEO2986
Lean J (2000) Evolution of the Sun's spectral irradiance since the Maunder Minimu. Geophys Res Lett 27:2425–2428. https://doi.org/10.1029/2000GL000043
Lean JL, Rind DH (2008) How natural and anthropogenic influences alter global and regional surface temperatures: 1889 to 2006. Geophys Res Lett 35:L18701. https://doi.org/10.1029/2008GL034864
Liang XS (2008) Information flow within stochastic dynamical systems. Phys Rev E Stat Nonlinear Soft Matter Phys 78:031113. https://doi.org/10.1103/PhysRevE.78.031113
Liang XS (2014) Unraveling the cause-effect relation between time series. Phys Rev E Stat Nonlinear Soft Matter Phys 90:052150. https://doi.org/10.1103/PhysRevE.90.052150
Liang XS (2016) Information flow and causality as rigorous notions ab initio. Phys Rev E 94:052201. https://doi.org/10.1103/PhysRevE.94.052201
Liang XS (2018) Causation and information flow with respect to relative entropy. Chaos 28:075311. https://doi.org/10.1063/1.5010253
Liu RQ, Jacobi C, Hoffmann P, Stober G, Merzlyakov EG (2010) A piecewise linear model for detecting climatic trends and their structural changes with application to mesosphere/lower thermosphere winds over Collm, Germany. J Geophys Res Atmos 115:D22105. https://doi.org/10.1029/2010JD014080
Meinshausen M, Smith SJ, Calvin K et al (2011) The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim Change 109:213–241. https://doi.org/10.1007/s10584-011-0156-z
Miao LJ, Zhu F, Sun ZL, Moore JC, Cui XF (2016) China’s land-use changes during the past 300 years: a historical perspective. Int J Environ Res Public Health 13:847. https://doi.org/10.3390/ijerph13090847
Morice CP, Kennedy JJ, Rayner NA et al (2012) Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: the HadCRUT4 data set. J Geophys Res: Atmos 117:D08101. https://doi.org/10.1029/2011JD017187
Najafi MR, Zwiers FW, Gillett NP (2015) Attribution of Arctic temperature change to greenhouse-gas and aerosol influences. Nat Clim Change 5:246–249. https://doi.org/10.1038/NCLIMATE2524
Ng S, Perron P (2005) A note on the selection of time series models. Oxf B Econ Stat 67:115–134. https://doi.org/10.1111/j.1468-0084.2005.00113.x
Portnyagin YI, Merzlyakov EG, Solovjova TV et al (2006) Long-term trends and year-to-year variability of mid-latitude mesosphere/lower thermosphere winds. J Atmos Sol Terr Phys 68:1890–1901. https://doi.org/10.1016/j.jastp.2006.04.004
Przybylak R, Wyszyński P (2020) Air temperature changes in the Arctic in the period 1951–2015 in the light of observational and reanalysis data. Theor Appl Climatol 139:75–94. https://doi.org/10.1007/s00704-019-02952-3
Ribes A, Planton S, Terray L (2013) Application of regularised optimal fingerprinting to attribution. Part I: method, properties and idealised analysis. Clim Dyn 41:2817–2836. https://doi.org/10.1007/s00382-013-1735-7
Screen JA, Francis JA (2016) Contribution of sea-ice loss to Arctic amplification is regulated by Pacific Ocean decadal variability. Nat Clim Change 6:856–860. https://doi.org/10.1038/NCLIMATE3011
Shepherd A, Ivins ER, Geruo A et al (2012) A reconciled estimate of ice-sheet mass balance. Science 338:1183–1189. https://doi.org/10.1126/science.1228102
Shimizu S, Hoyer PO, Hyvärinen A, Kerminen A (2006) A linear non-Gaussian acyclic model for causal discovery. J Mach Learn Res 7:2003–2030. https://doi.org/10.1007/s10883-006-0005-y
Shindell D, Faluvegi G (2009) Climate response to regional radiative forcing during the twentieth century. Nat Geosci 2:294–300. https://doi.org/10.1038/NGEO473
Sies H (1988) A new parameter for sex education. Nature 332:495–495
Smith DM, Screen JA, Deser C et al (2019) The Polar Amplification Model Intercomparison Project (PAMIP) contribution to CMIP6: investigating the causes and consequences of polar amplification. Geosci Model Dev 12:1139–1164. https://doi.org/10.5194/gmd-12-1139-2019
Stern DI, Kaufmann RK (2014) Anthropogenic and natural causes of climate change. Clim Change 122:257–269. https://doi.org/10.1007/s10584-013-1007-x
Stips A, Macias D, Coughlan C, Garcia-Gorriz E, Liang XS (2016) On the causal structure between CO2 and global temperature. Sci Rep 6:21691. https://doi.org/10.1038/srep21691
Stroeve J, Notz D (2018) Changing state of Arctic sea ice across all seasons. Environ Res Lett 13:103001. https://doi.org/10.1088/1748-9326/aade56
Suo L, Otterå OH, Bentsen M, Gao Y, Johannessen OM (2013) External forcing of the early 20th century Arctic warming. Tellus A 65:187–190. https://doi.org/10.3402/tellusa.v65i0.20578
Svendsen L, Keenlyside N, Bethke I, Gao Y, Omrani NE (2018) Pacific contribution to the early twentieth-century warming in the Arctic. Nat Clim Change 8:793–797. https://doi.org/10.1038/s41558-018-0247-1
Tomé A, Miranda P (2005) Continuous partial trends and low-frequency oscillations of time series. Nonlinear Proc Geophys 12:451–460. https://doi.org/10.5194/npg-12-451-2005
Triacca U, Attanasio A, Pasini A (2013) Anthropogenic global warming hypothesis: testing its robustness by Granger causality analysis. Environmetrics 24:260–268. https://doi.org/10.1002/env.2210
Vannitsem S, Dalaiden Q, Goosse H (2019) Testing for dynamical dependence—application to the surface mass balance over Antarctica. Geophys Res Lett 46:12125–12135. https://doi.org/10.1029/2019GL084329
Vose RS, Arndt D, Banzon VF et al (2012) NOAA's merged land-ocean surface temperature analysis. B Am Meteorol Soc 93:1677–1685. https://doi.org/10.1175/BAMS-D-11-00241.1
Wu CJ, Krivova NA, Solanki SK et al (2018) Solar total and spectral irradiance reconstruction over the last 9000 years. Astron Astrophys 620:A120. https://doi.org/10.1051/0004-6361/201832956
Yang P, Wang G, Zhang F, Zhou X (2016) Causality of global warming seen from observations: a scale analysis of driving force of the surface air temperature time series in the Northern Hemisphere. Clim Dyn 46:3197–3204. https://doi.org/10.1007/s00382-015-2761-4
Acknowledgements
The authors thank the National Oceanographic and Atmospheric Administration (NOAA) for providing the AMO and PDO data, and the Potsdam Institute for Climate Impact Research, Germany, for providing the driving forces dataset. Special thanks also go to Huang et al. for proving the Arctic temperature. The authors also would like to thank the anonymous reviewers and editors for their insightful comments and suggestions, which have significantly improved this paper. This study was financially supported by the National Natural Science Foundation of China (41675003, 41775008, and 41575040).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Xiao, H., Zhang, F., Miao, L. et al. Long-term trends in Arctic surface temperature and potential causality over the last 100 years. Clim Dyn 55, 1443–1456 (2020). https://doi.org/10.1007/s00382-020-05330-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-020-05330-2