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Projections of cold air outbreaks in CMIP6 earth system models

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Abstract

Historical and future simulated temperature data from five climate models in the Coupled Model Intercomparing Project Phase 6 (CMIP6) are used to understand how climate change might alter cold air outbreaks (CAOs) in the future. Three different shared socioeconomic pathways (SSPs), SSP126, SSP245, and SSP585, are examined to identify potential fluctuations in CAOs across the globe between 2015 and 2054. Though CAOs may remain persistent or even increase in some regions through 2040, all five climate models show CAOs disappearing by 2054 based on current climate percentiles. Climate models were able to accurately simulate the spatial distribution and trends of historical CAOs, but there were large errors in the simulated interannual frequency of CAOs in the North Atlantic and North Pacific. Fluctuations in complex processes, such as Atlantic Meridional Overturning Circulation, may be contributing to each model’s inability to simulate historical CAOs in these regions.

Plain language summary

Cold air outbreaks (CAOs) are extreme events that can have large, negative impacts on society. Because of these impacts, it is important to understand how climate change might alter CAOs in the future. Three future scenarios from five different climate models are examined to see where CAOs might change the most between 2015 and 2054. While changes in CAOs may be small for some regions through 2040, all the climate models show CAOs disappearing, relative to the historically defined criteria, by 2054. Where the climate models did a good job simulating historical CAOs, like in North America, we have confidence that future projections are relatively accurate. Where the models did poorly at simulating historical CAOs, like the North Atlantic and North Pacific, we have less confidence in future projections. More work needs to be done to understand the complex processes that lead to these errors.

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Data availability

All data used in this study is publicly available. The data that supports these findings are available at the Mendeley Data repository (Smith, Erik (2020), “Cold Air Outbreaks”, Mendeley Data, v1. https://doi.org/10.17632/mtwfvcvy5z.1). This repository contains a dataset with the dates of the individual CAOs as an .xlsx file. A larger dataset is also available as a .mat file and requires a MATLAB license to access. These datasets were created using ERA5 and CMIP6 climate model output near-surface temperature data. ERA5 near-surface temperature data is available from the European Center for Medium-Range Weather Forecasts (ECMWF) via the Copernicus Climate Change Service at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels. Climate model output from the CMIP6 archive is publicly available from the Earth System Grid Federation (ESGF; https://esgf-node.llnl.gov/search/cmip6/). Climate model data was accessed via the Earth System Grid Federation (CMIP6-DKRZ Data Search | CMIP6-DKRZ | ESGF-CoG).

Materials availability

See “Data availability” statement

Code availability

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References

  • Almazroui M, Saeed F, Saeed S, Nazrul Islam M, Ismail M, Klutse NAB, Siddiqui MH (2020) Projected change in temperature and precipitation over Africa from CMIP6. Earth Syst Environ 4(3):455–475. https://doi.org/10.1007/s41748-020-00161-x

    Article  Google Scholar 

  • Ayarzagüena B, Screen JA (2016) Future Arctic sea ice loss reduces severity of cold air outbreaks in midlatitudes: sea Ice Loss and Midlatitude CAOs. Geophys Res Lett 43(6):2801–2809. https://doi.org/10.1002/2016GL068092

    Article  Google Scholar 

  • Bauer, N., Calvin, K., Emmerling, J., Fricko, O., Fujimori, S., Hilaire, J., Eom, J., Krey, V., Kriegler, E., Mouratiadou, I., Sytze de Boer, H., van den Berg, M., Carrara, S., Daioglou, V., Drouet, L., Edmonds, J. E., Gernaat, D., Havlik, P., Johnson, N., … van Vuuren, D. P. (2017). Shared socio-economic pathways of the energy sector – quantifying the narratives. Global Environ Change, 42, 316–330. https://doi.org/10.1016/j.gloenvcha.2016.07.006

  • Bell JE, Brown CL, Conlon K, Herring S, Kunkel KE, Lawrimore J, Luber G, Schreck C, Smith A, Uejio C (2018) Changes in extreme events and the potential impacts on human health. J Air Waste Manage Assoc 68(4):265–287. https://doi.org/10.1080/10962247.2017.1401017

    Article  Google Scholar 

  • Cohen JL, Furtado JC, Barlow MA, Alexeev VA, Cherry JE (2012) Arctic warming, increasing snow cover and widespread boreal winter cooling. Environ Res Lett 7(1):014007. https://doi.org/10.1088/1748-9326/7/1/014007

    Article  Google Scholar 

  • Cohen J, Pfeiffer K, Francis JA (2018) Warm Arctic episodes linked with increased frequency of extreme winter weather in the United States. Nat Commun 9(1):869. https://doi.org/10.1038/s41467-018-02992-9

    Article  Google Scholar 

  • Collins SN, James RS, Ray P, Chen K, Lassman A, Brownlee J (2013) Grids in numerical weather and climate models. Clim Change Reg/Local Responses. https://doi.org/10.5772/55922

  • Danabasoglu G, Lamarque J-F, Bacmeister J, Bailey DA, DuVivier AK, Edwards J, Emmons LK, Fasullo J, Garcia R, Gettelman A, Hannay C, Holland MM, Large WG, Lauritzen PH, Lawrence DM, Lenaerts JTM, Lindsay K, Lipscomb WH, Mills MJ, … Strand WG (2020). the community earth system model version 2 (CESM2). J Adv Model Earth Syst 12(2), e2019MS001916. https://doi.org/10.1029/2019MS001916

  • Davis SJ, Lewis NS, Shaner M, Aggarwal S, Arent D, Azevedo IL, Benson SM, Bradley T, Brouwer J, Chiang Y-M, Clack CTM, Cohen A, Doig S, Edmonds J, Fennell P, Field CB, Hannegan B, Hodge B-M, Hoffert MI, … Caldeira K (2018). Net-zero emissions energy systems. Science, 360(6396). https://doi.org/10.1126/science.aas9793

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars, ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, … Vitart F (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656), 553–597. https://doi.org/10.1002/qj.828

  • Edwards PN (2011) History of climate modeling. WIREs Clim Change 2(1):128–139. https://doi.org/10.1002/wcc.95

    Article  Google Scholar 

  • Ehret U, Zehe E, Wulfmeyer V, Warrach-Sagi K, Liebert J (2012) HESS opinions. Hydrol Earth Syst Sci Discuss 9:5355–5387. https://doi.org/10.5194/hessd-9-5355-2012

    Article  Google Scholar 

  • Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016) Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9(5):1937–1958. https://doi.org/10.5194/gmd-9-1937-2016

    Article  Google Scholar 

  • Flato GM (2011) Earth system models: an overview. WIREs Clim Change 2(6):783–800. https://doi.org/10.1002/wcc.148

    Article  Google Scholar 

  • Friedrich T, Timmermann A, Tigchelaar M, Elison Timm O, Ganopolski A (2016) Nonlinear climate sensitivity and its implications for future greenhouse warming. Sci Adv 2(11):e1501923. https://doi.org/10.1126/sciadv.1501923

    Article  Google Scholar 

  • Gent PR (2018) A commentary on the Atlantic meridional overturning circulation stability in climate models. Ocean Model 122:57–66. https://doi.org/10.1016/j.ocemod.2017.12.006

    Article  Google Scholar 

  • Gutjahr O, Putrasahan D, Lohmann K, Jungclaus JH, von Storch J-S, Brüggemann N, Haak H, Stössel A (2019) Max planck institute earth system model (MPI-ESM1.2) for the high-resolution model intercomparison project (HighResMIP). Geosci Model Dev 12(7):3241–3281. https://doi.org/10.5194/gmd-12-3241-2019

    Article  Google Scholar 

  • Hu A, Meehl GA, Han W, Yin J, Wu B, Kimoto M (2013) Influence of continental ice retreat on future global climate. J Clim 26(10):3087–3111. https://doi.org/10.1175/JCLI-D-12-00102.1

    Article  Google Scholar 

  • IPCC (2013) Climate Change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds.). Cambridge University Press, Cambridge and New York, p 1535. https://doi.org/10.1017/CBO9781107415324

  • Jeuken ABM, Siegmund PC, Heijboer LC, Feichter J, Bengtsson L (1996) On the potential of assimilating meteorological analyses in a global climate model for the purpose of model validation. J Geophys Res-Atmos 101(D12):16939–16950. https://doi.org/10.1029/96JD01218

    Article  Google Scholar 

  • 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(10):4001–4024. https://doi.org/10.1002/jgrd.50239

    Article  Google Scholar 

  • Kalnay E (2003) Atmospheric modeling, data assimilation and predictability. Cambridge University Press, Cambridge

    Google Scholar 

  • Kim Y, Lee S (2019) Trends of extreme cold events in the central regions of Korea and their influence on the heating energy demand. Weather Clim Extremes 24:100199. https://doi.org/10.1016/j.wace.2019.100199

    Article  Google Scholar 

  • Kim WM, Yeager S, Chang P, Danabasoglu G (2018) Low-frequency North Atlantic climate variability in the community earth system model large ensemble. J Clim 31(2):787–813. https://doi.org/10.1175/JCLI-D-17-0193.1

    Article  Google Scholar 

  • Klinger C, Landeg O, Murray V (2014) Power outages, extreme events and health: a systematic review of the literature from 2011-2012. PLoS Curr 6:ecurrents.dis.04eb1dc5e73dd1377e05a10e9edde673. https://doi.org/10.1371/currents.dis.04eb1dc5e73dd1377e05a10e9edde673

    Article  Google Scholar 

  • Kolstad EW, Bracegirdle TJ (2008) Marine cold-air outbreaks in the future: an assessment of IPCC AR4 model results for the Northern Hemisphere. Clim Dyn 30(7):871–885. https://doi.org/10.1007/s00382-007-0331-0

    Article  Google Scholar 

  • Kumar S, Merwade V, Kinter JL, Niyogi D (2013) Evaluation of temperature and precipitation trends and long-term persistence in CMIP5 twentieth-century climate simulations. J Clim 26(12):4168–4185. https://doi.org/10.1175/JCLI-D-12-00259.1

    Article  Google Scholar 

  • Labe Z, Peings Y, Magnusdottir G (2020) Warm Arctic, cold siberia pattern: role of full arctic amplification versus sea ice loss alone. Geophys Res Lett 47(17):e2020GL088583. https://doi.org/10.1029/2020GL088583

    Article  Google Scholar 

  • Lesk C, Rowhani P, Ramankutty N (2016) Influence of extreme weather disasters on global crop production. Nature 529(7584):84–87. https://doi.org/10.1038/nature16467

    Article  Google Scholar 

  • Liu H-L, Foster BT, Hagan ME, McInerney JM, Maute A, Qian L, Richmond AD, Roble RG, Solomon SC, Garcia RR, Kinnison D, Marsh DR, Smith AK, Richter J, Sassi F, Oberheide J (2010) Thermosphere extension of the Whole Atmosphere Community Climate Model. J Geophys Res Space Physics 115(A12):A12302. https://doi.org/10.1029/2010JA015586

    Article  Google Scholar 

  • Liu H-L, Bardeen CG, Foster BT, Lauritzen P, Liu J, Lu G, Marsh DR, Maute A, McInerney JM, Pedatella NM, Qian L, Richmond AD, Roble RG, Solomon SC, Vitt FM, Wang W (2018) Development and validation of the whole atmosphere community climate model with thermosphere and ionosphere extension (WACCM-X 2.0). J Adv Model Earth Syst 10(2):381–402. https://doi.org/10.1002/2017MS001232

    Article  Google Scholar 

  • Liu X, Shen B, Price L, Hasanbeigi A, Lu H, Yu C, Fu G (2019) A review of international practices for energy efficiency and carbon emissions reduction and lessons learned for China. WIREs Energ Environ 8(5):e342. https://doi.org/10.1002/wene.342

    Article  Google Scholar 

  • Luca AD, Pitman AJ, de Elía R (2020) Decomposing temperature extremes errors in CMIP5 and CMIP6 models. Geophys Res Lett 47(14):e2020GL088031. https://doi.org/10.1029/2020GL088031

    Article  Google Scholar 

  • Maraun D (2016) Bias correcting climate change simulations—a critical review. Curr Clim Change Rep 2(4):211–220. https://doi.org/10.1007/s40641-016-0050-x

    Article  Google Scholar 

  • Meehl GA, Arblaster JM, Bates S, Richter JH, Tebaldi C, Gettelman A, Medeiros B, Bacmeister J, DeRepentigny P, Rosenbloom N, Shields C, Hu A, Teng H, Mills MJ, Strand G (2020) Characteristics of future warmer base states in CESM2. Earth Space Sci 7(9):e2020EA001296. https://doi.org/10.1029/2020EA001296

    Article  Google Scholar 

  • O’Neill BC, Kriegler E, Riahi K, Ebi KL, Hallegatte S, Carter TR, Mathur R, van Vuuren DP (2014) A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim Chang 122(3):387–400. https://doi.org/10.1007/s10584-013-0905-2

    Article  Google Scholar 

  • O’Neill BC, Tebaldi C, Van Vuuren DP, Eyring V, Friedlingstein P, Hurtt G, Knutti R, Kriegler E, Lamarque JF, Lowe J, Meehl GA, Moss R, Riahi K, Sanderson BM (2016) The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci Model Dev 9:3461–3482. https://doi.org/10.5194/gmd-9-3461-2016

    Article  Google Scholar 

  • Polkova I, Köhl A, Stammer D (2019) Climate-mode initialization for decadal climate predictions. Clim Dyn 53(11):7097–7111. https://doi.org/10.1007/s00382-019-04975-y

    Article  Google Scholar 

  • Raäisaänen J (2007) How reliable are climate models? Tellus A: Dyn Meteorol Oceanogr 59(1):2–29. https://doi.org/10.1111/j.1600-0870.2006.00211.x

    Article  Google Scholar 

  • Randall DA, Wood RA, Bony S, Colman R, Fichefet T, Fyfe J, Kattsov V, Pitman A, Shukla J, Srinivasan J, Stouffer RJ, Sumi A, Taylor KE, AchutaRao K, Allan R, Berger A, Blatter H, Bonfils C, Boone A, … McAvaney B (2007) Climate models and their evaluation. In Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC (FAR). Cambridge University Press, pp 589–662

  • Rathore S, Bindoff NL, Phillips HE, Feng M (2020) Recent hemispheric asymmetry in global ocean warming induced by climate change and internal variability. Nat Commun 11(1):2008. https://doi.org/10.1038/s41467-020-15754-3

    Article  Google Scholar 

  • Richardson LF (2007) Weather prediction by numerical process. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Schewe J, Gosling SN, Reyer C, Zhao F, Ciais P, Elliott J, Francois L, Huber V, Lotze HK, Seneviratne SI, van Vliet MTH, Vautard R, Wada Y, Breuer L, Büchner M, Carozza DA, Chang J, Coll M, Deryng D, … Warszawski L (2019). State-of-the-art global models underestimate impacts from climate extremes. Nat Commun 10(1), 1005. https://doi.org/10.1038/s41467-019-08745-6

  • Sheridan SC, Lee CC, Allen MJ (2019) The mortality response to absolute and relative temperature extremes. Int J Environ Res Public Health 16(9):1493. https://doi.org/10.3390/ijerph16091493

    Article  Google Scholar 

  • Smith E (2020) “Cold Air Outbreaks”, Mendeley Data, V1. https://doi.org/10.17632/mtwfvcvy5z.1

  • Smith ET, Sheridan SC (2019) The influence of extreme cold events on mortality in the United States. Sci Total Environ 647:342–351. https://doi.org/10.1016/j.scitotenv.2018.07.466

    Article  Google Scholar 

  • Smith ET, Sheridan SC (2020) Where do cold air outbreaks occur, and how have they changed over time. Geophys Res Lett 47(13):e2020GL086983. https://doi.org/10.1029/2020GL086983

    Article  Google Scholar 

  • Smith DM, Scaife AA, Eade R, Athanasiadis P, Bellucci A, Bethke I, Bilbao R, Borchert LF, Caron L-P, Counillon F, Danabasoglu G, Delworth T, Doblas-Reyes FJ, Dunstone NJ, Estella-Perez V, Flavoni S, Hermanson L, Keenlyside N, Kharin V et al (2020) North Atlantic climate far more predictable than models imply. Nature 583(7818):796–800. https://doi.org/10.1038/s41586-020-2525-0

    Article  Google Scholar 

  • Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., … Winter, B. (2019). The Canadian earth system model version 5 (CanESM5.0.3). Geoscie Model Dev 12(11), 4823–4873. https://doi.org/10.5194/gmd-12-4823-2019

  • Tebaldi C, Debeire K, Eyring V, Fischer E, Fyfe J, Friedlingstein P, Knutti R, Lowe J, O’Neill B, Sanderson B, van Vuuren D, Riahi K, Meinshausen M, Nicholls Z, Hurtt G, Kriegler E, Lamarque J-F, Meehl G, Moss R, … Ziehn T (2021) Climate model projections from the scenario model intercomparison project (ScenarioMIP) of CMIP6. Earth Syst Dyn 12(1):253–293

  • Tokarska KB, Stolpe MB, Sippel S, Fischer EM, Smith CJ, Lehner F, Knutti R (2020) Past warming trend constrains future warming in CMIP6 models. Sci Adv 6(12):eaaz9549. https://doi.org/10.1126/sciadv.aaz9549

    Article  Google Scholar 

  • Vavrus S, Walsh JE, Chapman WL, Portis D (2006) The behavior of extreme cold air outbreaks under greenhouse warming. Int J Climatol 26(9):1133–1147. https://doi.org/10.1002/joc.1301

    Article  Google Scholar 

  • Wang T, Hamann A, Spittlehouse D, Carroll C (2016) Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America. PLoS One 11(6):e0156720. https://doi.org/10.1371/journal.pone.0156720

    Article  Google Scholar 

  • Wilks DS (2016) “The stippling shows statistically significant grid points”: how research results are routinely overstated and overinterpreted, and what to do about it. Bull Am Meteorol Soc 97(12):2263–2273. https://doi.org/10.1175/BAMS-D-15-00267.1

    Article  Google Scholar 

  • Yukimoto S, Kawai H, Koshiro T, Oshima N, Yoshida K, Urakawa S, Tsujino H, Deushi M, Tanaka T, Hosaka M, Yabu S, Yoshimura H, Shindo E, Mizuta R, Obata A, Adachi Y, Ishii M (2019) The meteorological research institute earth system model version 2.0, MRI-ESM2.0: description and basic evaluation of the physical component. Journal of the Meteorological Society of Japan. Ser. II 97(5):931–965. https://doi.org/10.2151/jmsj.2019-051

    Article  Google Scholar 

  • Yun W-T, Stefanova L, Krishnamurti T (2003) Improvement of the multimodel superensemble technique for seasonal forecasts. J Clim 16:3834–3840.

  • Zahn M, von Storch H (2010) Decreased frequency of North Atlantic polar lows associated with future climate warming. Nature 467(7313):309–312. https://doi.org/10.1038/nature09388

    Article  Google Scholar 

  • Zhang R, Sutton R, Danabasoglu G, Kwon Y-O, Marsh R, Yeager SG, Amrhein DE, Little CM (2019) A review of the role of the Atlantic meridional overturning circulation in Atlantic multidecadal variability and associated climate impacts. Rev Geophys 57(2):316–375. https://doi.org/10.1029/2019RG000644

    Article  Google Scholar 

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  1. Department of Geography, Kent State University, Kent, OH, USA

    Erik T. Smith & Scott C. Sheridan

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  1. Erik T. Smith
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  2. Scott C. Sheridan
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Erik Smith: Lead author and researcher

Scott Sheridan: Advisor

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Correspondence to Erik T. Smith.

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Appendix

Appendix

Table 2 Information for the CMIP6 models used in this study.
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Fig. 5
figure 5

Annual number of CAO days (y-axis) simulated by each climate model (solid lines), observed with ERA5 (red dashed line), and the climate model mean (black dashed line) from 1979 to 2015 (x-axis). Regions are denoted by the numbers in the top right corner. Lines are smoothed using a 5-year centered moving average.

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Fig. 6
figure 6

Simulated annual CAO days from 2015 to 2054 for three future scenarios: SSP126, SSP245, and SSP585 for each of the five climate models.

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Smith, E.T., Sheridan, S.C. Projections of cold air outbreaks in CMIP6 earth system models. Climatic Change 169, 14 (2021). https://doi.org/10.1007/s10584-021-03259-x

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