Climate Dynamics

, Volume 53, Issue 3–4, pp 1637–1651 | Cite as

Potential impacts of Arctic warming on Northern Hemisphere mid-latitude aerosol optical depth

  • Yuyang Chen
  • Chuanfeng ZhaoEmail author
  • Yi Ming


The weather and climate conditions can provide favorable or unfavorable atmospheric background for the maintenance and development of haze events. This study investigates the potential impacts of Arctic warming on the variation of Northern Hemisphere mid-latitude aerosol optical depth (AOD) in winter when haze often occurs. We first analyze the spatio-temporal variability of wintertime AOD in mid-latitudes of Northern Hemisphere from NASA MERRA-2 for the period of 1980–2016 using the empirical orthogonal function analysis and morlet wavelet analysis. It showes increasing trend for AOD in East China and North India and decreasing trend for AOD in Europe and North America during last 37 years while inter-decadal fluctuations exist. In addition to the temporal trends of AOD, two long-term periodic variations with periods of about 7 and 11 years exist, which implies the potential impacts from natural variabilities. Further analysis shows high correlations between the mid-latitude winter AOD (WA) and Arctic summer (May and June) surface temperature (T56). Moreover, the Arctic summer surface temperature demonstrates similar periodic variations with periods of about 7–9 and 11–13 years. Both of these indicate the potential impacts of Arctic summer warming on mid-latitude winter pollution. We then analyze the temporal correlations between Arctic summer temperature and mid-latitude winter AOD in different regions. Arctic T56 correlates negatively with WA in Europe and North America, and positively with that in East Asia, North India and Middle East. Particularly, T56 in western sea of Novaya Zemlya has the most prominent correlation with the WA in mid-latitudes of East Asia, especially in East China. This implies that Arctic T56 in the Arctic circle of Europe could be used for rough estimates of winter AOD in East Asia.


Spatio-temporal variability Aerosol optical depth Near surface air temperature Arctic Mid-latitude Teleconnection 



This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant number XDA19070202), the National Natural Science Foundation of China (Grant 41575143), the ministry of science and technology of China (2017YFC1501403, 2012AA120901), the State Key Laboratory of Earth Surface Processes and Resource Ecology (2017-ZY-02), the China “1000 plan” young scholar program, and the Fundamental Research Funds for the Central Universities (2017EYT18, 312231103). The data are obtained from the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) product (, and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) (


  1. Barnes E (2013) Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes. J Geophys Res Lett 40:4734–4739. CrossRefGoogle Scholar
  2. Barnett TP, Preisendorfer R (1987) Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis. Mon Weather Rev 115:1825–1850.,1825:OALOMA.2.0.CO;2 CrossRefGoogle Scholar
  3. Barnston AG, Ropelewski CF (1992) Prediction of ENSO episodes using canonical correlation analysis. J Clim 5:1316–1345CrossRefGoogle Scholar
  4. Bintanja R, van der Linden EC (2013) The changing seasonal climate in the Arctic. Sci Rep 3:1556CrossRefGoogle Scholar
  5. Brunekreef B, Holgate ST (2002) Air pollution and health. J Lancet 360:1233–1242. CrossRefGoogle Scholar
  6. Cai W, Li K, Liao H, Wang H, Wu L (2017) Weather conditions conducive to Beijing severe haze more frequent under climate change. Nat Clim Change 7:257–262. CrossRefGoogle Scholar
  7. Chen HP, Wang HJ (2015) Haze days in North China and the associated atmospheric circulations based on daily visibility data from 1960 to 2012. J Geophys Res Atmos 120:5895–5909. CrossRefGoogle Scholar
  8. Chin M, Diehl T, Tan Q, Prospero JM, Kahn RA, Remer LA, Yu H, Sayer AM, Bian H, Geogdzhayev IV, Holben BN, Howell SG, Huebert BJ, Hsu NC, Kim D, Kucsera TL, Levy RC, Mishchenko MI, Pan X, Quinn PK, Schuster GL, Streets DG, Strode SA, Torres O, Zhao XP (2014) Multi-decadal aerosol variations from 1980 to 2009: a perspective from observations and a global model. Atmos Chem Phys 14:3657–3690., 2014CrossRefGoogle Scholar
  9. Chung CE, Cha H, Vihma T, Räisänen P, Decremer D (2013) On the possibilities to use atmospheric reanalyses to evaluate the warming structure in the Arctic. Atmos Chem Phys 13:11209–11219. CrossRefGoogle Scholar
  10. Cohen J et al (2014) Recent Arctic amplification and extreme mid-latitude weather. Nat Geosci 7:627–637. CrossRefGoogle Scholar
  11. Deng ZW, You WH, Lin ZS (1997) Application of wavelet transform in global climate on a multiple time scale. J Trans Atmos Sci 20:505–510 (in Chinese) Google Scholar
  12. Deng ZW, Lin ZS, Zhou XL (2005) Analysis of climate change on a multiple time scale in Xi’an over the past 50 years. J Plateau Meteorol 16:81–93 (in Chinese) Google Scholar
  13. Francis JA, Hunter E (2006) New insight into the disappearing Arctic sea ice. Trans Am Geophys Union 87(46):509–511. CrossRefGoogle Scholar
  14. Francis JA, Vavrus SJ (2012) Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophys Res Lett. Google Scholar
  15. Garrett TJ, Zhao C (2006) Increased Arctic cloud longwave emissivity associated with pollution from mid-latitudes. Nature 440:787–789. CrossRefGoogle Scholar
  16. Garrett TJ, Zhao C, Noel PC (2010) Assessing the relative contributions of transport efficiency and scavenging to seasonal variability in Arctic aerosol. Tellus B 62:190–196CrossRefGoogle Scholar
  17. Gerlach TM, Westrich HR, Symonds RB (1996) Preeruption vapor in magma of the climactic Mount Pinatubo eruption: source of the giant stratospheric sulfur dioxide cloud. In: Newhall CG, Punongbayan RS (eds) Fire and mud eruptions and lahars of Mount Pinatubo, Philippines. University of Washington Press, Seattle, pp 415–434Google Scholar
  18. Gillett NP, Stone DA, Stott PA, Nozawa T, Karpechko AY, Heger GC, Wehner MF, Jones PD (2008) Attribution of polar warming to human influence. Nat Geosci 1:750–754. CrossRefGoogle Scholar
  19. Graversen RG, Wang M (2009) Polar amplification in a coupled climate model with locked albedo. Clim Dyn 33:629–643. CrossRefGoogle Scholar
  20. Graversen RG, Mauritsen T, Tjernström M, Källén E, Svensson G (2008) Vertical structure of recent Arctic warming. Nature 451:53–56. CrossRefGoogle Scholar
  21. Guo S, Hu M, Guo Q, Zhang X, Zheng M, Zheng J, Chang CC, Schauer JJ, Zhang R (2012) Primary sources and secondary formation of organic aerosols in Beijing, China. Environ Sci Technol 46:9846–9853. CrossRefGoogle Scholar
  22. Guo S, Hu M, Zamora ML, Peng J, Shang D, Zheng J, Du Z, Wu Z, Shao M, Zeng L, Molina MJ, Zhang R (2014) Elucidating severe urban haze formation in China. Proc Natl Acad Sci USA 111:17373–17378. CrossRefGoogle Scholar
  23. Hu T, Sun Z, Zhang H (2008) Spatial/temporal variations and trends of aerosol optical depth at 380 nm wavelength in China during 1980–2001. J Appl Meteorol Sci 19:513–521 (in Chinese) Google Scholar
  24. Huang RJ, Zhang Y, Bozzetti C, Ho KF, Cao JJ, Han Y, Prévôt AS (2014) High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514:218–222. CrossRefGoogle Scholar
  25. Inoue J, Hori ME, Takaya K (2012) The role of barents sea ice in the wintertime cyclone track and emergence of a warm-arctic cold-siberian anomaly. J Clim 25(7):2561–2568CrossRefGoogle Scholar
  26. Kaufman YJ, Tanré D, Boucher O (2002) A satellite view of aerosols in the climate system. Nature 419:215–223. CrossRefGoogle Scholar
  27. Li Z, Zhao X, Kahn R, Mishchenko M, Remer L, Lee K-H, Wang M, Laszlo I, Nakajima T, Maring H (2009) Uncertainties in satellite remote sensing of aerosols and impact on monitoring its long-term trend: a review and perspective. Ann Geophys 27:2755–2770. CrossRefGoogle Scholar
  28. Li J, Carlson BE, Lacis AA (2013) Application of spectral analysis techniques in the intercomparison of aerosol data: 1. An EOF approach to analyze the spatial-temporal variability of aerosol optical depth using multiple remote sensing data sets. J Geophys Res Atmos 118:8640–8648. CrossRefGoogle Scholar
  29. Luo YF, Lu D, Zhou XJ, Li WL (2001) Characteristics of the spatial distribution and yearly variation of aerosol optical depth over China in last 30 years. J Geophys Res 106(D13):14501–14513. CrossRefGoogle Scholar
  30. Ma PK, Zhao Y, Robinson AL, Worton DR, Goldstein AH, Ortega AM, Jimenez JL, Zotter P, Prévôt ASH, Szidat S, Hayes PL (2017) Evaluating the impact of new observational constraints on P-S/IVOC emissions, multigeneration oxidation, and chamber wall losses on SOA modeling for Los Angeles, CA. Atmos Chem Phys 17:9237–9259. CrossRefGoogle Scholar
  31. Navarro JA, Varma V, Riipinen I, Seland Ø, Kirkevåg A, Struthers H, Iversen T, Hansson HC, Ekman AM (2016) Amplification of Arctic warming by past air pollution reductions in Europe. Nat Geosci 9(4):277–281. CrossRefGoogle Scholar
  32. Nel A (2005) Air pollution-related illness: effects of particles. Science 309:1326. Google Scholar
  33. Nicholls N (1987) The use of canonical correlation to study teleconnections. Mon Weather Rev 115:393–399.,0393:TUOCCT.2.0.CO;2 CrossRefGoogle Scholar
  34. Niu F, Li ZQ, Li C, Lee K-H, Wang MY (2010) Increase of wintertime fog in China: potential impacts of weakening of the Eastern Asian monsoon circulation and increasing aerosol loading. J Geophys Res 115:D00K20. CrossRefGoogle Scholar
  35. Petoukhov V, Semenov VA (2010) A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents. J Geophys Res. Google Scholar
  36. Petoukhov V, Rahmstorf S, Petri S, Schellnhuber HJ (2013) Quasiresonant amplification of planetary waves and recent Northern Hemisphere weather extremes. Proc Natl Acad Sci USA 110:5336–5341. CrossRefGoogle Scholar
  37. Preisendorfer RW, Mobley CD (1988) Principal component analysis in meteorology and oceanography. Elsevier, AmsterdamGoogle Scholar
  38. Qian B, De Jong R, Gameda S (2009) Multivariate analysis of water-related agroclimatic factors limiting spring wheat yields on the Canadian prairies. Eur J Agron 30(2):140–150CrossRefGoogle Scholar
  39. Qiu Y, Zhao C, Guo J, Li J (2017) 8-Year ground-based observational analysis about the seasonal variation of the aerosol-cloud droplet effective radius relationship at SGP site. Atmos Environ 164:139–146CrossRefGoogle Scholar
  40. Randles CA, da Silva AM, Buchard V, Colarco PR, Darmenov A, Govindaraju R et al (2017) The MERRA-2 aerosol reanalysis, 1980 onward. Part I: system description and data assimilation evaluation. J Clim 30:6823–6850CrossRefGoogle Scholar
  41. Rimbu N, Lohmann G, Ionita M (2014) Interannual to multidecadal Euro-Atlantic blocking variability during winter and its relationship with extreme low temperatures in Europe. J Geophys Res Atmos 119(24):13621–13636. CrossRefGoogle Scholar
  42. Screen JA, Simmonds I (2014) Amplified mid-latitude planetary waves favour particular regional weather extremes. Nat Clim Change. Google Scholar
  43. Screen JA, Deser C, Simmonds I (2012) Local and remote controls on observed Arctic warming. Geophys Res Lett 39:L10709. CrossRefGoogle Scholar
  44. Serreze MC, Barry RG (2011) Processes and impacts of Arctic amplification: a research synthesis. Glob Planet Change 77:85–96. CrossRefGoogle Scholar
  45. Serreze MC, Barrett AP, Slater AG, Steele M, Zhang J, Trenberth KE (2007) The large-scale energy budget of the Arctic. J Geophys Res 112:D11122. CrossRefGoogle Scholar
  46. Shindell D, Faluvegi G (2009) Climate response to regional radiative forcing during the twentieth century. Nat Geosci 2:294–300. CrossRefGoogle Scholar
  47. Shrestha P, Barros AP (2010) Joint spatial variability of aerosol, clouds and rainfall in the Himalayas from satellite data. Atmos Chem Phys 10:8305–8317. CrossRefGoogle Scholar
  48. Stroeve JC, Serreze MC, Holland MM, Kay JE, Malanik J, Barrett AP (2012) The Arctic’s rapidly shrinking sea ice cover: a research synthesis. Clim Change 110:1005–1027. CrossRefGoogle Scholar
  49. Sun K, Tao L, Miller DJ, Zondlo MA, Shonkwiler KB, Nash C, Ham JM (2015) Open-path eddy covariance measurements of ammonia fluxes from a beef cattle feedlot. Agric For Meteorol 213:193–202. CrossRefGoogle Scholar
  50. Tang Q, Zhang X, Yang X, Francis J (2013) Cold winter extremes in northern continents linked to Arctic sea ice loss. Environ Res Lett 8:014036. CrossRefGoogle Scholar
  51. Tao M, Chen L, Su L, Tao J (2012) Satellite observation of regional haze pollution over the North China Plain. J Geophys Res Atmos 117:D12203. Google Scholar
  52. Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79(1):61–78CrossRefGoogle Scholar
  53. Wang Y, Zhang RY, Saravanan R (2014a) Asian pollution climatically modulates mid-latitude cyclones following hierarchical modeling and observational analysis. Nat Commun. Google Scholar
  54. Wang YS, Yao L, Wang LL, Liu ZR, Ji DS, Tang GQ, Zhang JK, Sun Y, Hu B, Xin JY (2014b) Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China. Sci China Earth Sci 57:14–25. CrossRefGoogle Scholar
  55. Wang HJ, Chen HP, Liu JP (2015a) Arctic sea ice decline intensified haze pollution in eastern China. Atmos Ocean Sci Lett 8:1–9. Google Scholar
  56. Wang Y, Jiang J, Su H (2015b) Atmospheric responses to the redistribution of anthropogenic aerosols. J Geophys Res Atmos 120(18):9625–9641. CrossRefGoogle Scholar
  57. Wang Y, Jiang J, Su H, Choi S, Huang L, Guo J, Yung Y (2018) Elucidating the role of anthropogenic aerosols in Arctic Sea ice variations. J Clim 31(1):99–114CrossRefGoogle Scholar
  58. Wilks DS (2006) Statistical methods in the atmospheric sciences. vol 14, The second edition. Academic PressGoogle Scholar
  59. Winton M (2006) Amplified Arctic climate change: what does surface albedo feedback have to do with it? Geophys Res Lett 33:L03701. Google Scholar
  60. Wu BY, Huang RH (1999) The effects of the variation of the sea-ice areas in the North Pole, Kara Sea, and Barents Sea on the winter monsoon in east Asia. Chin J Atmos Sci 23:268–275Google Scholar
  61. Wu ZJ, Hu M, Liu S, Wehner B, Bauer S, Ma ßling A, Wiedensohler A, Petaja T, Dal Maso M, Kulmala M (2007) New particle formation in Beijing: China Statistical analysis of a 1-year data set. J Geophys Res 112:D09209. Google Scholar
  62. Wu J, Luo JG, Zhang LY, Xia L, Zhao DM, Tang JP (2014) Improvement of aerosol optical depth retrieval using visibility data in China during the past 50 years. J Geophys Res Atmos 119:13370–13387. CrossRefGoogle Scholar
  63. Yang X, Zhao C, Guo J, Wang Y (2016) Intensification of aerosol pollution associated with its feedback with surface solar radiation and winds in Beijing. J Geophys Res Atmos 121:4093–4099. CrossRefGoogle Scholar
  64. Zhai T, Zhao Q, Gao W, Shi R, Xiang W, Huang HLA, Zhang C (2015) Analysis of spatio-temporal variability of aerosol optical depth with empirical orthogonal functions in the Changjiang River Delta, China. Front Earth Sci 9(1):1–12CrossRefGoogle Scholar
  65. Zhang R, Jing J, Tao J, Hsu S-C, Wang G, Cao J, Lee CSL, Zhu L, Chen Z, Zhao Y, Shen Z (2013) Chemical characterization and source apportionment of PM2.5 in Beijing: seasonal perspective. Atmos Chem Phys 13:7053–7074. CrossRefGoogle Scholar
  66. Zhao C, Garrett TJ (2015) Effects of Arctic haze on surface cloud radiative forcing. Geophys Res Lett 42:557–564. CrossRefGoogle Scholar
  67. Zhao P, Zhang X, Zhou X, Ikeda M, Yin Y (2004) The sea ice extent anomaly in the North Pacific and its impact on the East Asia summer monsoon rainfall. J Clim 17:3434–3447CrossRefGoogle Scholar
  68. Zhao XJ, Zhao PS, Xu J, Meng W, Pu WW, Dong F, He D, Shi QF (2013) Analysis of a winter regional haze event and its formation mechanism in the North China Plain. Atmos Chem Phys 13:5685–5696. CrossRefGoogle Scholar
  69. Zhao C, Qiu Y, Dong X, Wang Z, Peng Y, Li B, Wu Z, Wang Y (2018a) Negative aerosol-cloud re relationship from aircraft observations over Hebei, China. Earth Space Sci 5:19–29. CrossRefGoogle Scholar
  70. Zhao C, Lin Y, Wu F, Wang Y, Li Z, Rosenfeld D, Wang Y (2018b) Enlarging rainfall area of tropical cyclones by atmospheric aerosols. Geophys Res Lett. Google Scholar
  71. Zhao C, Li YN, Zhang F, Sun YL, Wang PC (2018c) Growth rates of fine aerosol particles at a site near Beijing in June 2013. Adv Atmos Sci 35(2):209–217. CrossRefGoogle Scholar
  72. Zhao B, Jiang JH, Diner DJ, Su H, Gu Y, Liou KN, Jiang Z, Huang L, Takano Y, Fan XH, Omer AH (2018d) Intra-annual variations of regional aerosol optical depth, vertical distribution, and particle types from multiple satellite and ground-based observational datasets. Atmos Chem Phys 18:11247–11260. CrossRefGoogle Scholar
  73. Zheng Y, Rosenfeld D, Li Z (2015) Satellite inference of thermals and cloud-base updraft speeds based on retrieved surface and cloud-base temperatures. J Atmos Sci 72:2411–2428. CrossRefGoogle Scholar
  74. Zhu QK, Lin J, Shou SW, Tang DS (2007) Principles and methods of meteorology M. Meteorol Press 4:267–268 (in Chinese) Google Scholar
  75. Zou Y, Wang Y, Zhang Y, Koo J-H (2017) Arctic sea ice, Eurasia snow, and extreme winter haze in China. Sci Adv 3:e1602751. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina
  2. 2.Atmospheric Physics and Climate GroupPrinceton UniversityPrincetonUSA

Personalised recommendations