Interdecadal Variations of the Scandinavian Pattern

Bo Pang aState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Adam A. Scaife bMet Office Hadley Centre, Met Office, Exeter, United Kingdom
cCollege of Engineering, Mathematics and Physical Sciences, Exeter University, Exeter, United Kingdom

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Riyu Lu aState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
dCollege of Earth and Planetary Sciences, University of the Chinese Academy of Sciences, Beijing, China

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Rongcai Ren aState Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
eKey Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China

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Xiaoxuan Zhao fNansen-Zhu International Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Abstract

This study investigates the interdecadal variation of the Scandinavian (SCA) pattern and corresponding drivers during the boreal winter. It is found that the SCA pattern experiences a prominent regime shift from its negative to positive phase in the early 2000s based on several reanalyses. This interdecadal change contributes to an extensive cooling over Siberia after the early 2000s, revealing its importance for recent variations of climate over Eurasia. The outputs from 35 coupled models within phase 6 of the Coupled Model Intercomparison Project (CMIP6) are also analyzed. The results show that the interdecadal change of the SCA is weak in response to external forcings but can be largely explained by internal variability associated with a change of precipitation over the tropical Atlantic. Further analysis indicates that the enhanced tropical convection induces poleward propagation of Rossby waves and further results in an intensification of geopotential height over the Scandinavian Peninsula during the transition to positive SCA phases. These findings imply a contribution of tropical forcing to the observed interdecadal strengthening of the SCA around the early 2000s and offer an insight into the understanding of future climate change over the Eurasian continent.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Bo Pang, pangbo@mail.iap.ac.cn

Abstract

This study investigates the interdecadal variation of the Scandinavian (SCA) pattern and corresponding drivers during the boreal winter. It is found that the SCA pattern experiences a prominent regime shift from its negative to positive phase in the early 2000s based on several reanalyses. This interdecadal change contributes to an extensive cooling over Siberia after the early 2000s, revealing its importance for recent variations of climate over Eurasia. The outputs from 35 coupled models within phase 6 of the Coupled Model Intercomparison Project (CMIP6) are also analyzed. The results show that the interdecadal change of the SCA is weak in response to external forcings but can be largely explained by internal variability associated with a change of precipitation over the tropical Atlantic. Further analysis indicates that the enhanced tropical convection induces poleward propagation of Rossby waves and further results in an intensification of geopotential height over the Scandinavian Peninsula during the transition to positive SCA phases. These findings imply a contribution of tropical forcing to the observed interdecadal strengthening of the SCA around the early 2000s and offer an insight into the understanding of future climate change over the Eurasian continent.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Bo Pang, pangbo@mail.iap.ac.cn

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  • Barnston, A. G., and R. E. Livezey, 1987: Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon. Wea. Rev., 115, 10831126, https://doi.org/10.1175/1520-0493(1987)115<1083:CSAPOL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bell, B., and Coauthors, 2021: The ERA5 global reanalysis: Preliminary extension to 1950. Quart. J. Roy. Meteor. Soc., 147, 41864227, https://doi.org/10.1002/qj.4174.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., M. Widmann, V. P. Dymnikov, J. M. Wallace, and I. Bladé, 1999: The effective number of spatial degrees of freedom of a time-varying field. J. Climate, 12, 19902009, https://doi.org/10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bueh, C., and H. Nakamura, 2007: Scandinavian pattern and its climatic impact. Quart. J. Roy. Meteor. Soc., 133, 21172131, https://doi.org/10.1002/qj.173.

    • Search Google Scholar
    • Export Citation
  • Bueh, C., N. Shi, and Z. Xie, 2011: Large-scale circulation anomalies associated with persistent low temperature over southern China in January 2008. Atmos. Sci. Lett., 12, 273280, https://doi.org/10.1002/asl.333.

    • Search Google Scholar
    • Export Citation
  • Casanueva, A., C. Rodríguez-Puebla, M. D. Frías, and N. González-Reviriego, 2014: Variability of extreme precipitation over Europe and its relationships with teleconnection patterns. Hydrol. Earth Syst. Sci., 18, 709725, https://doi.org/10.5194/hess-18-709-2014.

    • Search Google Scholar
    • Export Citation
  • Chu, J.-E., K.-J. Ha, J.-Y. Lee, B. Wang, B.-H. Kim, and C. E. Chung, 2014: Future change of the Indian Ocean basin-wide and dipole modes in the CMIP5. Climate Dyn., 43, 535551, https://doi.org/10.1007/s00382-013-2002-7.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and Coauthors, 2014: Recent Arctic amplification and extreme mid-latitude weather. Nat. Geosci., 7, 627637, https://doi.org/10.1038/ngeo2234.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and Coauthors, 2020: Divergent consensuses on Arctic amplification influence on midlatitude severe winter weather. Nat. Climate Change, 10, 2029, https://doi.org/10.1038/s41558-019-0662-y.

    • Search Google Scholar
    • Export Citation
  • Cook, B. I., K. J. Anchukaitis, R. Touchan, D. M. Meko, and E. R. Cook, 2016: Spatiotemporal drought variability in the Mediterranean over the last 900 years. J. Geophys. Res. Atmos., 121, 20602074, https://doi.org/10.1002/2015JD023929.

    • Search Google Scholar
    • Export Citation
  • Crasemann, B., D. Handorf, R. Jaiser, K. Dethloff, T. Nakamura, J. Ukita, and K. Yamazaki, 2017: Can preferred atmospheric circulation patterns over the North-Atlantic-Eurasian region be associated with Arctic sea ice loss? Polar Sci., 14, 920, https://doi.org/10.1016/j.polar.2017.09.002.

    • Search Google Scholar
    • Export Citation
  • Cusinato, E., A. Rubino, and D. Zanchettin, 2021: Winter Euro-Atlantic climate modes: Future scenarios from a CMIP6 multi-model ensemble. Geophys. Res. Lett., 48, e2021GL094532, https://doi.org/10.1029/2021GL094532.

    • Search Google Scholar
    • Export Citation
  • Dunstone, N., and Coauthors, 2018: Predictability of European winter 2016/2017. Atmos. Sci. Lett., 19, e868, https://doi.org/10.1002/asl.868.

    • Search Google Scholar
    • Export Citation
  • Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 19371958, https://doi.org/10.5194/gmd-9-1937-2016.

    • Search Google Scholar
    • Export Citation
  • Frankcombe, L. M., M. H. England, M. E. Mann, and B. A. Steinman, 2015: Separating internal variability from the externally forced climate response. J. Climate, 28, 81848202, https://doi.org/10.1175/JCLI-D-15-0069.1.

    • Search Google Scholar
    • Export Citation
  • Frankcombe, L. M., M. H. England, J. B. Kajtar, M. E. Mann, and B. A. Steinman, 2018: On the choice of ensemble mean for estimating the forced signal in the presence of internal variability. J. Climate, 31, 56815693, https://doi.org/10.1175/JCLI-D-17-0662.1.

    • Search Google Scholar
    • Export Citation
  • Harris, I., T. J. Osborn, P. Jones, and D. Lister, 2020: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data, 7, 109, https://doi.org/10.1038/s41597-020-0453-3.

    • Search Google Scholar
    • Export Citation
  • Hernández, A., and Coauthors, 2015: Sensitivity of two Iberian lakes to North Atlantic atmospheric circulation modes. Climate Dyn., 45, 34033417, https://doi.org/10.1007/s00382-015-2547-8.

    • Search Google Scholar
    • Export Citation
  • Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 19992049, https://doi.org/10.1002/qj.3803.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., and D. J. Karoly, 1981: The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci., 38, 11791196, https://doi.org/10.1175/1520-0469(1981)038<1179:TSLROA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Jung, O., M.-K. Sung, K. Sato, Y.-K. Lim, S.-J. Kim, E.-H. Baek, J.-H. Jeong, and B.-M. Kim, 2017: How does the SST variability over the western North Atlantic Ocean control Arctic warming over the Barents–Kara Seas? Environ. Res. Lett., 12, 034021, https://doi.org/10.1088/1748-9326/aa5f3b.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kim, M., C. Yoo, M.-K. Sung, and S. Lee, 2021: Classification of wintertime atmospheric teleconnection patterns in the Northern Hemisphere. J. Climate, 34, 18471861, https://doi.org/10.1175/JCLI-D-20-0339.1.

    • Search Google Scholar
    • Export Citation
  • Kobayashi, S., and Coauthors, 2015: The JRA-55 reanalysis: General specifications and basic characteristics. J. Meteor. Soc. Japan, 93, 548, https://doi.org/10.2151/jmsj.2015-001.

    • Search Google Scholar
    • Export Citation
  • Kravtsov, S., and D. Callicutt, 2017: On semi-empirical decomposition of multidecadal climate variability into forced and internally generated components. Int. J. Climatol., 37, 44174433, https://doi.org/10.1002/joc.5096.

    • Search Google Scholar
    • Export Citation
  • Li, R. K. K., T. Woollings, C. O’Reilly, and A. A. Scaife, 2020: Tropical atmospheric drivers of wintertime European precipitation events. Quart. J. Roy. Meteor. Soc., 146, 780794, https://doi.org/10.1002/qj.3708.

    • Search Google Scholar
    • Export Citation
  • Li, X., S.-P. Xie, S. T. Gille, and C. Yoo, 2016: Atlantic-induced pan-tropical climate change over the past three decades. Nat. Climate Change, 6, 275279, https://doi.org/10.1038/nclimate2840.

    • Search Google Scholar
    • Export Citation
  • Liu, Y., L. Wang, W. Zhou, and W. Chen, 2014: Three Eurasian teleconnection patterns: Spatial structures, temporal variability, and associated winter climate anomalies. Climate Dyn., 42, 28172839, https://doi.org/10.1007/s00382-014-2163-z.

    • Search Google Scholar
    • Export Citation
  • Łupikasza, E. B., and K. Cielecka-Nowak, 2020: Changing probabilities of days with snow and rain in the Atlantic sector of the Arctic under the current warming trend. J. Climate, 33, 25092532, https://doi.org/10.1175/JCLI-D-19-0384.1.

    • Search Google Scholar
    • Export Citation
  • Maidens, A., J. R. Knight, and A. A. Scaife, 2021: Tropical and stratospheric influences on winter atmospheric circulation patterns in the North Atlantic sector. Environ. Res. Lett., 16, 024035, https://doi.org/10.1088/1748-9326/abd8aa.

    • Search Google Scholar
    • Export Citation
  • Manola, I., R. J. Haarsma, and W. Hazeleger, 2013: Drivers of North Atlantic Oscillation events. Tellus, 65A, 19741, https://doi.org/10.3402/tellusa.v65i0.19741.

    • Search Google Scholar
    • Export Citation
  • Mori, M., M. Watanabe, H. Shiogama, J. Inoue, and M. Kimoto, 2014: Robust Arctic sea-ice influence on the frequent Eurasian cold winters in past decades. Nat. Geosci., 7, 869873, https://doi.org/10.1038/ngeo2277.

    • Search Google Scholar
    • Export Citation
  • Okumura, Y., S.-P. Xie, A. Numaguti, and Y. Tanimoto, 2001: Tropical Atlantic air-sea interaction and its influence on the NAO. Geophys. Res. Lett., 28, 15071510, https://doi.org/10.1029/2000GL012565.

    • Search Google Scholar
    • Export Citation
  • Pang, B., R. Lu, and R. Ren, 2022: Impact of the Scandinavian pattern on long-lived cold surges over the South China Sea. J. Climate, 35, 17731785, https://doi.org/10.1175/JCLI-D-21-0607.1.

    • Search Google Scholar
    • Export Citation
  • Sardeshmukh, P. D., and B. J. Hoskins, 1988: The generation of global rotational flow by steady idealized tropical divergence. J. Atmos. Sci., 45, 12281251, https://doi.org/10.1175/1520-0469(1988)045<1228:TGOGRF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Scaife, A. A., and D. Smith, 2018: A signal-to-noise paradox in climate science. npj Climate Atmos. Sci., 1, 28, https://doi.org/10.1038/s41612-018-0038-4.

    • Search Google Scholar
    • Export Citation
  • Scaife, A. A., and Coauthors, 2017: Tropical rainfall, Rossby waves and regional winter climate predictions. Quart. J. Roy. Meteor. Soc., 143 (702), 111, https://doi.org/10.1002/qj.2910.

    • Search Google Scholar
    • Export Citation
  • Servain, J., G. Caniaux, Y. K. Kouadio, M. J. McPhaden, and M. Araujo, 2014: Recent climatic trends in the tropical Atlantic. Climate Dyn., 43, 30713089, https://doi.org/10.1007/s00382-014-2168-7.

    • Search Google Scholar
    • Export Citation
  • Shi, N., D. Zhang, Y. Wang, and S. Tajie, 2019: Subseasonal influences of teleconnection patterns on the boreal wintertime surface air temperature over southern China as revealed from three reanalysis datasets. Atmosphere, 10, 514, https://doi.org/10.3390/atmos10090514.

    • Search Google Scholar
    • Export Citation
  • Smith, D. M., and Coauthors, 2020: North Atlantic climate far more predictable than models imply. Nature, 583, 796800, https://doi.org/10.1038/s41586-020-2525-0.

    • Search Google Scholar
    • Export Citation
  • Smith, D. M., and Coauthors, 2022: Robust but weak winter atmospheric circulation response to future Arctic sea ice loss. Nat. Commun., 13, 727, https://doi.org/10.1038/s41467-022-28283-y.

    • Search Google Scholar
    • Export Citation
  • Sohn, S.-J., C.-Y. Tam, and C.-K. Park, 2011: Leading modes of East Asian winter climate variability and their predictability: An assessment of the APCC multi-model ensemble. J. Meteor. Soc. Japan, 89, 455474, https://doi.org/10.2151/jmsj.2011-504.

    • Search Google Scholar
    • Export Citation
  • Sui, C., L. Yu, and T. Vihma, 2020: Occurrence and drivers of wintertime temperature extremes in northern Europe during 1979–2016. Tellus, 72A, 119, https://doi.org/10.1080/16000870.2020.1788368.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., 2001: Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res., 106, 71837192, https://doi.org/10.1029/2000JD900719.

    • Search Google Scholar
    • Export Citation
  • Tokinaga, H., and S.-P. Xie, 2011: Weakening of the equatorial Atlantic cold tongue over the past six decades. Nat. Geosci., 4, 222226, https://doi.org/10.1038/ngeo1078.

    • Search Google Scholar
    • Export Citation
  • Wang, M., and B. Tan, 2020: Two types of the Scandinavian pattern: Their formation mechanisms and climate impacts. J. Climate, 33, 26452661, https://doi.org/10.1175/JCLI-D-19-0447.1.

    • Search Google Scholar
    • Export Citation
  • Warner, J. L., J. A. Screen, and A. A. Scaife, 2020: Links between Barents-Kara sea ice and the extratropical atmospheric circulation explained by internal variability and tropical forcing. Geophys. Res. Lett., 47, e2019GL085679, https://doi.org/10.1029/2019GL085679.

    • Search Google Scholar
    • Export Citation
  • Yu, L., C. Sui, D. H. Lenschow, and M. Zhou, 2017: The relationship between wintertime extreme temperature events north of 60°N and large-scale atmospheric circulations. Int. J. Climatol., 37, 597611, https://doi.org/10.1002/joc.5024.

    • Search Google Scholar
    • Export Citation
  • Yuan, C., and W. Li, 2019: Variations in the frequency of winter extreme cold days in northern China and possible causalities. J. Climate, 32, 81278141, https://doi.org/10.1175/JCLI-D-18-0771.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, D., N. Shi, and S. Tajie, 2022: Mechanisms of the subseasonal influences of Scandinavian events on winter surface air temperature over eastern China. Atmos. Res., 268, 105994, https://doi.org/10.1016/j.atmosres.2021.105994.

    • Search Google Scholar
    • Export Citation
  • Zhou, W., J. C. L. Chan, W. Chen, J. Ling, J. G. Pinto, and Y. Shao, 2009: Synoptic-scale controls of persistent low temperature and icy weather over southern China in January 2008. Mon. Wea. Rev., 137, 39783991, https://doi.org/10.1175/2009MWR2952.1.

    • Search Google Scholar
    • Export Citation
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