Abstract
The winter Arctic Oscillation (WAO), as a primary atmospheric variability mode in the Northern Hemisphere, plays a key role in influencing mid-high-latitude climate variations. However, current dynamical seasonal forecasting systems have limited skills in predicting WAO with lead time longer than two months. In this study, we design a linear empirical model using two effective precursors from anomalies of the Arctic sea ice concentration (SIC) and the tropical sea surface temperature (SST) initiated in preceding late summer (August) which are both significantly correlated with WAO in recent four decades. This model can provide a skillful prediction of WAO at about half-year lead started from previous summer and perform much better than the dynamical models. Such a significantly prolonged lead time is owed to the stable precursor signals extracted from the SIC and SST anomalies over specific areas, which can persist from previous August and be further enhanced through autumn months. Validation results show that this model can produce a 20-year independent-validated prediction skill of 0.45 for 1999–2018 and a 39-year cross-validated skill of 0.67 for 1980–2018, providing a potentially effective tool for earlier predictions of winter climate variations at mid-high latitudes.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Adler R F, Huffman G J, Chang A, Ferraro R, Xie P P, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D, Gruber A, Susskind J, Arkin P, Nelkin E. 2003. The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present). J Hydrometeorol, 4: 1147–1167
Ambaum M H P, Hoskins B J, Stephenson D B. 2001. Arctic Oscillation or North Atlantic Oscillation? J Clim, 14: 3495–3507
Barnes E A, Screen J A. 2015. The impact of arctic warming on the midlatitude jet-stream: Can it? Has it? Will it? WIREs Clim Change, 6: 277–286
Butler A H, Polvani L M, Deser C. 2014. Separating the stratospheric and tropospheric pathways of El Niño-Southern Oscillation teleconnections. Environ Res Lett, 9: 024014
Cavalieri D J, Parkinson C L, Gloersen P, Zwally H J. 1996. Updated yearly. Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: 10.5067/8GQ8LZQ
Cohen J, Salstein D, Saito K. 2002. A dynamical framework to understand and predict the major Northern Hemisphere mode. Geophys Res Lett, 29: 51–1–51–4
Cohen J, Jones J, Furtado J, Tziperman E. 2013. Warm arctic, cold continents: A common pattern related to arctic sea ice melt, snow advance, and extreme winter weather. Oceanography, 26: 150–160
Cohen J, Screen J A, Furtado J C, Barlow M, Whittleston D, Coumou D, Francis J, Dethloff K, Entekhabi D, Overland J, Jones J. 2014. Recent Arctic amplification and extreme mid-latitude weather. Nat Geosci, 7: 627–637
Dai P, Tan B. 2017. The nature of the Arctic Oscillation and diversity of the extreme surface weather anomalies it generates. J Clim, 30: 5563–5584
Dai A, Luo D, Song M, Liu J. 2019. Arctic amplification is caused by seaice loss under increasing CO2. Nat Commun, 10: 121
Dee D P, Uppala S M, Simmons A J, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda M A, Balsamo G, Bauer P, Bechtold P, Beljaars A C M, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer A J, Haimberger L, Healy S B, Hersbach H, Hólm E V, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally A P, Monge-Sanz B M, Morcrette J J, Park B K, Peubey C, de Rosnay P, Tavolato C, Thépaut J N, Vitart F. 2011. The ERA-interim reanalysis: Configuration and performance of the data assimilation system. Q J R Meteorol Soc, 137: 553–597
Derome J, Lin H, Brunet G. 2005. Seasonal forecasting with a simple general circulation model: Predictive skill in the AO and PNA. J Clim, 18: 597–609
Dunstone N, Smith D, Scaife A, Hermanson L, Eade R, Robinson N, Andrews M, Knight J. 2016. Skilful predictions of the winter North Atlantic Oscillation one year ahead. Nat Geosci, 9: 809–814
Feldstein S B. 2000. The timescale, power spectra, and climate noise properties of teleconnection patterns. J Clim, 13: 4430–4440
García-Serrano J, Frankignoul C. 2014. High predictability of the winter Euro–Atlantic climate from cryospheric variability. Nat Geosci, 7: E1
Greatbatch R J, Lin H, Lu J, Peterson K A, Derome J. 2003. Tropical/extratropical forcing of the AO/NAO: A corrigendum. Geophys Res Lett, 30: 1738
Huang B, Thorne P W, Banzon V F, Boyer T, Chepurin G, Lawrimore J H, Menne M J, Smith T M, Vose R S, Zhang H M. 2017. Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J Clim, 30: 8179–8205
Kang D, Lee M I. 2017. Increase in the potential predictability of the Arctic Oscillation via intensified teleconnection with ENSO after the mid- 1990s. Clim Dyn, 49: 2147–2160
Kang D, Lee M I, Im J, Kim D, Kim H M, Kang H S, Schubert S D, Arribas A, MacLachlan C. 2014. Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems. Geophys Res Lett, 41: 3577–3585
Kim H J, Ahn J B. 2015. Improvement in prediction of the Arctic Oscillation with a realistic ocean initial condition in a CGCM. J Clim, 28: 8951–8967
L’Heureux M L, Tippett M K, Kumar A, Butler A H, Ciasto L M, Ding Q, Harnos K J, Johnson N C. 2017. Strong relations between ENSO and the Arctic Oscillation in the North American multimodel ensemble. Geophys Res Lett, 44: 11,654
Lorenz D J, Hartmann D L. 2003. Eddy-zonal flow feedback in the Northern hemisphere winter. J Clim, 16: 1212–1227
Miller R L, Schmidt G A, Shindell D T. 2006. Forced annular variations in the 20th century Intergovernmental Panel on Climate Change Fourth Assessment Report models. J Geophys Res, 111: D18101
MacLachlan C, Arribas A, Peterson K A, Maidens A, Fereday D, Scaife A A, Gordon M, Vellinga M, Williams A, Comer R E, Camp J, Xavier P, Madec G. 2015. Global Seasonal forecast system version 5 (GloSea5): A high-resolution seasonal forecast system. Q J R Meteorol Soc, 141: 1072–1084
Riddle E E, Butler A H, Furtado J C, Cohen J L, Kumar A. 2013. CFSv2 ensemble prediction of the wintertime Arctic Oscillation. Clim Dyn, 41: 1099–1116
Ren H L, Jin F F, Song L, Lu B, Tian B, Zuo J, Liu Y, Wu J, Zhao C, Nie Y, Zhang P, Ba J, Wu Y, Wan J, Yan Y, Zhou F. 2017. Prediction of primary climate variability modes at the Beijing Climate Center. J Meteorol Res, 31: 204–223
Ren H L, Zuo J, Deng Y. 2019. Statistical predictability of Niño indices for two types of ENSO. Clim Dyn, 52: 5361–5382
Robinson W A. 2000. A baroclinic mechanism for the eddy feedback on the zonal index. J Atmos Sci, 57: 415–422
Scaife A A, Comer R E, Dunstone N J, Knight J R, Smith D M, MacLachlan C, Martin N, Peterson K A, Rowlands D, Carroll E B, Belcher S, Slingo J. 2017. Tropical rainfall, Rossby waves and regional winter climate predictions. Q J R Meteorol Soc, 143: 1–11
Sun J, Ahn J B. 2015. Dynamical seasonal predictability of the Arctic Oscillation using a CGCM. Int J Climatol, 35: 1342–1353
Thompson D W J, Wallace J M. 1998. The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys Res Lett, 25: 1297–1300
Thompson D W J, Wallace J M. 2000. Annular modes in the extratropical circulation. Part I: Month-to-month variability. J Clim, 13: 1000–1016
Thompson D W J, Wallace J M. 2001. Regional climate impacts of the Northern Hemisphere annular mode. Science, 293: 85–89
Walker G T, Bliss E W. 1932. World weather V.Mem Roy Meteor Soc, 4: 53–84
Wallace J M. 2000. North atlantic oscillatiodannular mode: Two paradigms- one phenomenon. Q J R Meteorol Soc, 126: 791–805
Wang B, Xiang B, Li J, Webster P J, Rajeevan M N, Liu J, Ha K J. 2015. Rethinking Indian monsoon rainfall prediction in the context of recent global warming. Nat Commun, 6: 7154
Wang L, Ting M, Kushner P J. 2017. A robust empirical seasonal prediction of winter NAO and surface climate. Sci Rep, 7: 279
Wu Y, Smith K L. 2016. Response of Northern hemisphere midlatitude circulation to Arctic amplification in a simple atmospheric general circulation model. J Clim, 29: 2041–2058
Yang X Y, Yuan X, Ting M. 2016. Dynamical link between the Barents–Kara Sea Ice and the Arctic Oscillation. J Clim, 29: 5103–5122
Yu B, Lin H. 2016. Tropical atmospheric forcing of the wintertime North Atlantic oscillation. J Clim, 29: 1755–1772
Zhang Y, Yang X Q, Nie Y, Chen G. 2012. Annular mode-like variation in a multilayer quasigeostrophic model. J Atmos Sci, 69: 2940–2958
Zuo J Q, Li W J, Ren H L. 2013. Representation of the Arctic Oscillation in the CMIP5 models. Adv Clim Change Res, 4: 242–249
Zuo J, Ren H L, Li W. 2015. Contrasting impacts of the Arctic Oscillation on surface air temperature anomalies in Southern China between early and middle-to-late winter. J Clim, 28: 4015–4026
Zuo J, Ren H L, Wu J, Nie Y, Li Q. 2016. Subseasonal variability and predictability of the Arctic Oscillation/North Atlantic Oscillation in BCC_AGCM2.2. Dyn Atmos Oceans, 75: 33–45
Acknowledgements
The authors thank the three anonymous reviewers for their constructive suggestions, which help improve the quality of the manuscript. This work was supported by the China National Key Research and Development Program on Monitoring, Early Warning and Prevention of Major Natural Disaster (Grant No. 2018YFC1506005), and the National Natural Science Foundation of China (Grant Nos. 41705043, 41775066 & 41375062).
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Ren, HL., Nie, Y. Skillful prediction of winter Arctic Oscillation from previous summer in a linear empirical model. Sci. China Earth Sci. 64, 27–36 (2021). https://doi.org/10.1007/s11430-020-9665-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11430-020-9665-3