Abstract
We investigate the interannual variability of surface air temperature in the twenty-first century using the Coupled Model Intercomparison Project Phase 6 (CMIP6) model data under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Relative to 1961−2014, the interannual variability of annual temperature is projected to increase by 6%, 6%, and 12% globally in the 2051–2100 period under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively, with an average increase of 10–22% in low latitudes and decrease of 3–28% in high-latitude oceans. The spatial pattern of wintertime variability changes is mainly determined by variations in the meridional temperature gradient. Sea ice losses and variations in snow extent in the mid to high latitudes are both related with large variability decreases according to analysis of the underlying surface. In South America and South Africa, the variability enhancement is related to the adjustment of the wet–dry status, while that in South Asia and central Africa depends more on the positive longwave radiative effect due to the increase in clouds. In tropical oceans, the increases in sea surface temperature variabilities and air–sea interactions dominate the enhanced surface air temperature variability.
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Data availability
All datasets used in this research can be accessed via the following websites: CMIP6 model outputs at https://esgf-node.llnl.gov/search/cmip6/, and BEST near-surface air temperature data (Rohde et al. 2013a, b) at http://berkeleyearth.org/data/.
References
Alexander L (2011) Extreme heat rooted in dry soils. Nat Geosci 4(1):12–13. https://doi.org/10.1038/ngeo1045
Almazroui M, Saeed S, Saeed F, Ismail M (2020) Projections of precipitation and temperature over the South Asian countries in CMIP6. Earth Syst Environ 4(2):297–320. https://doi.org/10.1007/s41748-020-00157-7
Attada R, Dasari HP, Chowdary JS, Yadav RK, Knio O, Hoteit I (2019) Surface air temperature variability over the Arabian Peninsula and its links to circulation patterns. Int J Climatol 39(1):445–464. https://doi.org/10.1002/joc.5821
Bannister D, Herzog M, Graf H-F, Hosking JS, Short CA (2017) An assessment of recent and future temperature change over the Sichuan Basin, China, using CMIP5 climate models. J Clim 30(17):6701–6722. https://doi.org/10.1175/JCLI-D-16-0536.1
Barnett T, Dümenil L, Schlese U, Roeckner E, Latif M (1989) The effect of Eurasian snow cover on regional and global climate variations. J Atmos Sci 46(5):661–686. https://doi.org/10.1175/1520-0469(1989)046%3c0661:TEOESC%3e2.0.CO;2
Barriopedro D, Fischer EM, Luterbacher J, Trigo RM, García-Herrera R (2011) The hot summer of 2010: redrawing the temperature record map of Europe. Science 332(6026):220–224. https://doi.org/10.1126/science.1201224
Bartusek S, Kornhuber K, Ting M (2022) 2021 North American heatwave amplified by climate change-driven nonlinear interactions. Nat Clim Change 12(12):1143–1150. https://doi.org/10.1038/s41558-022-01520-4
Bathiany S, Dakos V, Scheffer M, Lenton TM (2018) Climate models predict increasing temperature variability in poor countries. Sci Adv 4(5):eaar5809. https://doi.org/10.1126/sciadv.aar5809
Bjerknes J (1964) Atlantic air–sea interaction. Adv Geophys 10:1–82. https://doi.org/10.1016/S0065-2687(08)60005-9
Black E, Blackburn M, Harrison G, Hoskins B, Methven J (2004) Factors contributing to the summer 2003 European heat wave. Weather 59(8):217–223. https://doi.org/10.1256/wea.74.04
Blackport R, Kushner PJ (2016) The transient and equilibrium climate response to rapid summertime sea ice loss in CCSM4. J Clim 29(2):401–417. https://doi.org/10.1175/jcli-d-15-0284.1
Bowen IS (1926) The ratio of heat loss by conduction and by evaporation from any water surface. Phys Rev 27(6):779–787. https://doi.org/10.1103/PhysRev.27.779
Brando PM, Soares-Filho B, Rodrigues L, Assunção A, Morton D, Tuchschneider D, Fernandes ECM, Macedo MN, Oliveira U, Coe MT (2020) The gathering firestorm in southern Amazonia. Sci Adv 6(2):eaay1632. https://doi.org/10.1126/sciadv.aay1632
Brown PT, Yi M, Li W, Hill SA (2017) Change in the magnitude and mechanisms of global temperature variability with warming. Nat Clim Chang 7(10):743–748. https://doi.org/10.1038/nclimate3381
Cai W, Borlace S, Lengaigne M, van Rensch P, Collins M, Vecchi G, Timmermann A, Santoso A, McPhaden MJ, Wu L, England MH, Wang G, Guilyardi E, Jin F-F (2014) Increasing frequency of extreme El Niño events due to greenhouse warming. Nat Clim Change 4(2):111–116. https://doi.org/10.1038/nclimate2100
Cai W, Ng B, Wang G, Santoso A, Wu L, Yang K (2022) Increased ENSO sea surface temperature variability under four IPCC emission scenarios. Nat Clim Change 12(3):228–231. https://doi.org/10.1038/s41558-022-01282-z
Caloiero T (2017) Trend of monthly temperature and daily extreme temperature during 1951–2012 in New Zealand. Theor Appl Climatol 129(1–2):111–127. https://doi.org/10.1007/s00704-016-1764-3
Chen W, Lu R (2014) The interannual variation in monthly temperature over Northeast China during summer. Adv Atmos Sci 31(3):515–524. https://doi.org/10.1007/s00376-013-3102-3
Chen S, Wu R, Liu Y (2016) Dominant modes of interannual variability in Eurasian surface air temperature during boreal spring. J Clim 29(3):1109–1125. https://doi.org/10.1175/JCLI-D-15-0524.1
Christensen JH, Krishna Kumar K, Aldrian E, An S-I, Cavalcanti IFA, de Castro M, Dong W, Goswami P, Hall A, Kanyanga JK, Kitoh A, Kossin J, Lau N-C, Renwick J, Stephenson DB, Xie S-P, Zhou T (2013) Climate phenomena and their relevance for future regional 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) Climate Change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 1217–1308. https://doi.org/10.1017/CBO9781107415324.028
Collow TW, Wang W, Kumar A (2019) Reduction in northern midlatitude 2-m temperature variability due to Arctic sea ice loss. J Clim 32(16):5021–5035. https://doi.org/10.1175/JCLI-D-18-0692.1
Cubasch U, Wuebbles D, Chen D, Facchini MC, Frame D, Mahowald N, Winther J-G (2013) Introduction. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate Change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 119–158. https://doi.org/10.1017/cbo9781107415324.007
d’Annunzio R, Sandker M, Finegold Y, Min Z (2015) Projecting global forest area towards 2030. Forest Ecol Manag 352(7):124–133. https://doi.org/10.1016/j.foreco.2015.03.014
Dell M, Jones BF, Olken BA (2012) Temperature shocks and economic growth: evidence from the last half century. Am Econ J Macroecon 4(3):66–95. https://doi.org/10.1257/mac.4.3.66
Dell M, Jones BF, Olken BA (2014) What do we learn from the weather? The new climate-economy literature. J Econ Lit 52(3):740–798. https://doi.org/10.1257/jel.52.3.740
Deser C, Blackmon ML (1993) Surface climate variations over the North Atlantic Ocean during winter: 1900–1989. J Clim 6(9):1743–1753. https://doi.org/10.1175/1520-0442(1993)006%3c1743:SCVOTN%3e2.0.CO;2
Deser C, Phillips A, Bourdette V, Teng H (2012) Uncertainty in climate change projections: the role of internal variability. Clim Dyn 38(3–4):527–546. https://doi.org/10.1007/s00382-010-0977-x
Diaz HF, Hoerling MP, Eischeid JK (2001) ENSO variability, teleconnections and climate change. Int J Climatol 21(15):1845–1862. https://doi.org/10.1002/joc.631
DiNezio PN, Puy M, Thirumalai K, Jin F, Tierney JE (2020) Emergence of an equatorial mode of climate variability in the Indian Ocean. Sci Adv 6(19):eaay7684. https://doi.org/10.1126/sciadv.aay7684
Duchon CE (1979) Lanczos filtering in one and two dimensions. J Appl Meteorol Clim 18(8):1016–1022. https://doi.org/10.1175/1520-0450(1979)018%3c1016:LFIOAT%3e2.0.CO;2
Emmanuel I (2022) Linkages between El Niño-Southern Oscillation (ENSO) and precipitation in West Africa regions. Arab J Geosci 15(7):675. https://doi.org/10.1007/s12517-022-09942-2
Erfanian A, Wang G, Yu M, Anyah R (2016) Multimodel ensemble simulations of present and future climates over West Africa: Impacts of vegetation dynamics. J Adv Model Earth Syst 8(3):1411–1431. https://doi.org/10.1002/2016MS000660
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
Eyring V, Cox PM, Flato GM, Gleckler PJ, Abramowitz G, Caldwell P, Collins WD, Gier BK, Hall AD, Hoffman FM, Hurtt GC, Jahn A, Jones CD, Klein SA, Krasting JP, Kwiatkowski L, Lorenz R, Maloney E, Meehl GA, Pendergrass AG, Pincus R, Ruane AC, Russell JL, Sanderson BM, Santer BD, Sherwood SC, Simpson IR, Stouffer RJ, Williamson M (2019) Taking climate model evaluation to the next level. Nat Clim Change 9(2):102–110. https://doi.org/10.1038/s41558-018-0355-y
Fan Q, Zhou B (2022) Upper-tropospheric temperature pattern over the Asian-Pacific region in CMIP6 simulations: climatology and interannual variability. Front Earth Sci 10:917660. https://doi.org/10.3389/feart.2022.917660
Ferguson IM, Dracup JA, Duffy PB, Pegion P, Schubert S (2010) Influence of SST forcing on stochastic characteristics of simulated precipitation and drought. J Hydrometeorol 11(3):754–769. https://doi.org/10.1175/2009jhm1132.1
Feudale L, Shukla J (2010) Influence of sea surface temperature on the European heat wave of 2003 summer. Part I: an observational study. Clim Dyn 36(9–10):1691–1703. https://doi.org/10.1007/s00382-010-0788-0
Fischer EM, Seneviratne SI, Lüthi D, Schär C (2007) Contribution of land–atmosphere coupling to recent European summer heat waves. Geophys Res Lett 34(6):L06707. https://doi.org/10.1029/2006GL029068
Fischer EM, Rajczak J, Schär C (2012) Changes in European summer temperature variability revisited. Geophys Res Lett 39(19):L19702. https://doi.org/10.1029/2012GL052730
Forzieri G, Miralles DG, Ciais P, Alkama R, Ryu Y, Duveiller G, Zhang K, Robertson E, Kautz M, Martens B, Jiang C, Arneth A, Georgievski G, Li W, Ceccherini G, Anthoni P, Lawrence P, Wiltshire A, Pongratz J, Piao S, Sitch S, Goll DS, Arora VK, Lienert S, Lombardozzi D, Kato E, Nabel JEMS, Tian H, Friedlingstein P, Cescatti A (2020) Increased control of vegetation on global terrestrial energy fluxes. Nat Clim Change 10(4):356–362. https://doi.org/10.1038/s41558-020-0717-0
Fricko O, Havlik P, Rogelj J, Klimont Z, Gusti M, Johnson N, Kolp P, Strubegger M, Valin H, Amann M, Ermolieva T, Forsell N, Herrero M, Heyes C, Kindermann G, Krey V, McCollum DL, Obersteiner M, Pachauri S, Rao S, Schmid E, Schoepp W, Riahi K (2017) The marker quantification of the shared socioeconomic pathway 2: a middle-of-the-road scenario for the 21st century. Glob Environ Change 42:251–267. https://doi.org/10.1016/j.gloenvcha.2016.06.004
Grose MR, Narsey S, Delage FP, Dowdy AJ, Bador M, Boschat G, Chung C, Kajtar JB, Rauniyar S, Freund MB, Lyu K, Rashid H, Zhang X, Wales S, Trenham C, Holbrook NJ, Cowan T, Alexander L, Arblaster JM, Power S (2020) Insights from CMIP6 for Australia’s future climate. Earth’s Future 8(5):e2019EF001469. https://doi.org/10.1029/2019EF001469
Hansen J, Sato M, Ruedy R (2012) Perception of climate change. Proc Natl Acad Sci USA 109(37):E2415–E2423. https://doi.org/10.1073/pnas.1205276109
Hasselmann K (1976) Stochastic climate models. Part I. Theory. Tellus 28(6):473–485. https://doi.org/10.3402/tellusa.v28i6.11316
Hoerling M, Kumar A, Eischeid J, Jha B (2008) What is causing the variability in global mean land temperature? Geophys Res Lett 35(23):L23712. https://doi.org/10.1029/2008GL035984
Holmes CR, Woollings T, Hawkins E, de Vries H (2016) Robust future changes in temperature variability under greenhouse gas forcing and the relationship with thermal advection. J Clim 29(6):2221–2236. https://doi.org/10.1175/jcli-d-14-00735.1
Hsiang SM, Burke M, Miguel E (2013) Quantifying the influence of climate on human conflict. Science 341(6151):1235367. https://doi.org/10.1126/science.1235367
Huntingford C, Jones PD, Livina VN, Lenton TM, Cox PM (2013) No increase in global temperature variability despite changing regional patterns. Nature 500(7462):327–330. https://doi.org/10.1038/nature12310
Jin F-F (1996) Tropical ocean–atmosphere interaction, the Pacific cold tongue, and the El Niño-Southern Oscillation. Science 274(5284):76–78. https://doi.org/10.1126/science.274.5284.76
Kriegler E, Bauer N, Popp A, Humpenöder F, Leimbach M, Strefler J, Baumstark L, Bodirsky BL, Hilaire J, Klein D, Mouratiadou I, Weindl I, Bertram C, Dietrich J-P, Luderer G, Pehl M, Pietzcker R, Piontek F, Lotze-Campen H, Biewald A, Bonsch M, Giannousakis A, Kreidenweis U, Müller C, Rolinski S, Schultes A, Schwanitz J, Stevanovic M, Calvin K, Emmerling J, Fujimori S, Edenhofer O (2017) Fossil-fueled development (SSP5): an energy and resource intensive scenario for the 21st century. Glob Environ Change 42:297–315. https://doi.org/10.1016/j.gloenvcha.2016.05.015
Kummu M, Gerten D, Heinke J, Konzmann M, Varis O (2014) Climate-driven interannual variability of water scarcity in food production potential: a global analysis. Hydrol Earth Syst Sci 18(2):447–461. https://doi.org/10.5194/hess-18-447-2014
Kunz T, Laepple T (2021) Frequency-dependent estimation of effective spatial degrees of freedom. J Clim 34(18):7373–7388. https://doi.org/10.1175/JCLI-D-20-0228.1
Kushnir Y (1994) Interdecadal variations in North Atlantic sea surface temperature and associated atmospheric conditions. J Clim 7(1):141–157. https://doi.org/10.1175/1520-0442(1994)007%3c0141:IVINAS%3e2.0.CO;2
Labat D, Goddéris Y, Probst JL, Guyot JL (2004) Evidence for global runoff increase related to climate warming. Adv Water Resour 27(6):631–642. https://doi.org/10.1016/j.advwatres.2004.02.020
Lenton TM, Dakos V, Bathiany S, Scheffer M (2017) Observed trends in the magnitude and persistence of monthly temperature variability. Sci Rep 7:5940. https://doi.org/10.1038/s41598-017-06382-x
Liguori G, McGregor S, Singh M, Arblaster J, Lorenzo ED (2022) Revisiting ENSO and IOD contributions to Australian precipitation. Geophys Res Lett 49(1):e2021GL094295. https://doi.org/10.1029/2021GL094295
Manabe S, Stouffer RJ (1979) A CO2-climate sensitivity study with a mathematical model of the global climate. Nature 282(5738):491–493. https://doi.org/10.1038/282491a0
Matsueda M (2011) Predictability of Euro-Russian blocking in summer of 2010. Geophys Res Lett 38(6):L06801. https://doi.org/10.1029/2010GL046557
Matthes K, Funke B, Andersson ME, Barnard L, Beer J, Charbonneau P, Clilverd MA, Dudok de Wit T, Haberreiter M, Hendry A, Jackman CH, Kretzschmar M, Kruschke T, Kunze M, Langematz U, Marsh DR, Maycock AC, Misios S, Rodger CJ, Scaife AA, Seppälä A, Shangguan M, Sinnhuber M, Tourpali K, Usoskin I, van de Kamp M, Verronen PT, Versick S (2017) Solar forcing for CMIP6 (v3.2). Geosci Model Dev 10(6):2247–2302. https://doi.org/10.5194/gmd-10-2247-2017
Mearns LO, Rosenzweig C, Goldberg R (1992) Effect of changes in interannual climatic variability on CERES-wheat yields: sensitivity and 2 × CO2 general circulation model studies. Agric for Meteorol 62(3–4):159–189. https://doi.org/10.1016/0168-1923(92)90013-T
Mie Sein ZM, Ullah I, Syed S, Zhi X, Azam K, Rasool G (2021) Interannual variability of air temperature over Myanmar: the influence of ENSO and IOD. Climate 9(2):35. https://doi.org/10.3390/cli9020035
Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463(7282):747–756. https://doi.org/10.1038/nature08823
Neelin JD, Münnich M, Su H, Meyerson JE, Holloway CE (2006) Tropical drying trends in global warming models and observations. Proc Natl Acad Sci USA 103(16):6110–6115. https://doi.org/10.1073/pnas.0601798103
O’Neill BC, Tebaldi C, van Vuuren DP, Eyring V, Friedlingstein P, Hurtt G, Knutti R, Kriegler E, Lamarque J-F, Lowe J, Meehl GA, Moss R, Riahi K, Sanderson BM (2016) The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci Model Dev 9(9):3461–3482. https://doi.org/10.5194/gmd-9-3461-2016
Olonscheck D, Notz D (2017) Consistently estimating internal climate variability from climate model simulations. J Clim 30(2):9555–9573. https://doi.org/10.1175/JCLI-D-16-0428.1
Olonscheck D, Mauritsen T, Notz D (2019) Arctic sea-ice variability is primarily driven by atmospheric temperature fluctuations. Nat Geosci 12(6):430–434. https://doi.org/10.1038/s41561-019-0363-1
Olonscheck D, Schurer AP, Lücke L, Hegerl GC (2021) Large-scale emergence of regional changes in year-to-year temperature variability by the end of the 21st century. Nat Commun 12(1):7237. https://doi.org/10.1038/s41467-021-27515-x
Otomi Y, Tachibana Y, Nakamura T (2013) A possible cause of the AO polarity reversal from winter to summer in 2010 and its relationship to hemispheric extreme summer weather. Clim Dyn 40(7–8):1939–1947. https://doi.org/10.1007/s00382-012-1386-0
Perkins SE, Argüeso D, White CJ (2015) Relationships between climate variability, soil moisture, and Australian heatwaves. J Geophys Res Atmos 120(16):8144–8164. https://doi.org/10.1002/2015JD023592
Räisänen J (2019) Energetics of interannual temperature variability. Clim Dyn 52(5–6):3139–3156. https://doi.org/10.1007/s00382-018-4306-0
Rashid IU, Abid MA, Almazroui M, Kucharski F, Hanif M, Ali S, Ismail M (2022) Early summer surface air temperature variability over Pakistan and the role of El Niño-Southern Oscillation teleconnections. Int J Climatol 42(11):5768–5784. https://doi.org/10.1002/joc.7560
Rehfeld K, Hébert R, Lora JM, Lofverstrom M, Brierley CM (2020) Variability of surface climate in simulations of past and future. Earth Syst Dyn 11(2):447–468. https://doi.org/10.5194/esd-11-447-2020
Ren Y, Zhou B, Song L, Xiao Y (2017) Interannual variability of western North Pacific subtropical high, East Asian jet and East Asian summer precipitation: CMIP5 simulation and projection. Quat Int 440:64–70. https://doi.org/10.1016/j.quaint.2016.08.033
Rohde R, Muller RA, Jacobsen R, Muller E, Perlmutter S, Rosenfeld A, Wurtele J, Groom D, Wickham C (2013a) A new estimate of the average Earth surface land temperature spanning 1753 to 2011. Geoinfor Geostat Overv 1:1000101. https://doi.org/10.4172/2327-4581.1000101
Rohde R, Muller R, Jacobsen R, Perlmutter S, Rosenfeld A, Wurtele J, Curry J, Wickham C, Mosher S (2013b) Berkeley Earth temperature averaging process. Geoinfor Geostat Overv 1:1000103. https://doi.org/10.4172/2327-4581.1000103
Rypdal K, Rypdal M, Fredriksen H-B (2015) Spatiotemporal long-range persistence in Earth’s temperature field: analysis of stochastic–diffusive energy balance models. J Clim 28(21):8379–8395. https://doi.org/10.1175/jcli-d-15-0183.1
Schär C, Vidale PL, Lüthi D, Frei C, Häberli C, Liniger MA, Appenzeller C (2004) The role of increasing temperature variability in European summer heatwaves. Nature 427(6972):332–336. https://doi.org/10.1038/nature02300
Schneider T, Bischoff T, Płotka H (2015) Physics of changes in synoptic midlatitude temperature variability. J Clim 28(6):2312–2331. https://doi.org/10.1175/jcli-d-14-00632.1
Screen JA (2014) Arctic amplification decreases temperature variance in northern mid- to high-latitudes. Nat Clim Chang 4(7):577–582. https://doi.org/10.1038/nclimate2268
Seneviratne S, Pal J, Eltahir E, Schär C (2002) Summer dryness in a warmer climate: a process study with a regional climate model. Clim Dyn 20(1):69–85. https://doi.org/10.1007/s00382-002-0258-4
Serreze MC, Francis JA (2006) The Arctic amplification debate. Clim Change 76(3–4):241–264. https://doi.org/10.1007/s10584-005-9017-y
Sherwood S, Fu Q (2014) A drier future? Science 343(6172):737–739. https://doi.org/10.1126/science.1247620
Staal A, Fetzer I, Wang-Erlandsson L, Bosmans JH, Dekker SC, van Nes EH, Rockström J, Tuinenburg OA (2020) Hysteresis of tropical forests in the 21st century. Nat Commun 11(1):4978. https://doi.org/10.1038/s41467-020-18728-7
Stevenson S, Fox-Kemper B, Jochum M, Neale R, Deser C, Meehl G (2012) Will there be a significant change to El Niño in the twenty-first century? J Clim 25(6):2129–2145. https://doi.org/10.1175/JCLI-D-11-00252.1
Stevenson S, Timmermann A, Chikamoto Y, Langford S, DiNezio P (2015) Stochastically generated North American megadroughts. J Clim 28(5):1865–1880. https://doi.org/10.1175/jcli-d-13-00689.1
Stott PA, Stone DA, Allen MR (2004) Human contribution to the European heatwave of 2003. Nature 432(7017):610–614. https://doi.org/10.1038/nature03089
Su F, Duan X, Chen D, Hao Z, Cuo L (2013) Evaluation of the global climate models in the CMIP5 over the Tibetan Plateau. J Clim 26(10):3187–3208. https://doi.org/10.1175/JCLI-D-12-00321.1
Sun L, Perlwitz J, Hoerling M (2016) What caused the recent “Warm Arctic, Cold Continents” trend pattern in winter temperatures? Geophys Res Lett 43(10):5345–5352. https://doi.org/10.1002/2016GL069024
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos 106(D7):7183–7192. https://doi.org/10.1029/2000JD900719
Thompson DW, Barnes EA, Deser C, Foust WE, Phillips AS (2015) Quantifying the role of internal climate variability in future climate trends. J Clim 28(16):6443–6456. https://doi.org/10.1175/JCLI-D-14-00830.1
van Oldenborgh GJ, Krikken F, Lewis S, Leach NJ, Lehner F, Saunders KR, van Weele M, Haustein K, Li S, Wallom D, Sparrow S, Arrighi J, Singh RK, van Aalst MK, Philip SY, Vautard R, Otto FEL (2021) Attribution of the Australian bushfire risk to anthropogenic climate change. Nat Hazards Earth Syst Sci 21(3):941–960. https://doi.org/10.5194/nhess-21-941-2021
van Vuuren DP, Stehfest E, Gernaat DE, Doelman JC, van den Berg M, Harmsen M, Sytze de Boer H, Bouwman LF, Daioglou V, Edelenbosch OY, Girod B, Kram T, Lassaletta L, Lucas PL, van Meijl H, Müller C, van Ruijven BJ, van der Sluis S, Tabeau A (2017) Energy, land-use and greenhouse gas emissions trajectories under a green growth paradigm. Glob Environ Change 42:237–250. https://doi.org/10.1016/j.gloenvcha.2016.05.008
Vasseur DA, DeLong JP, Gilbert B, Greig HS, Harley CD, McCann KS, Savage V, Tunney TD, O’Connor MI (2014) Increased temperature variation poses a greater risk to species than climate warming. Proc R Soc B 281(1779):20132612. https://doi.org/10.1098/rspb.2013.2612
Wallace JM, Rasmusson EM, Mitchell TP, Kousky VE, Sarachik ES, von Storch H (1998) On the structure and evolution of ENSO-related climate variability in the tropical Pacific: lessons from TOGA. J Geophys Res 103(C7):14241–14259. https://doi.org/10.1029/97JC02905
Wallace JM, Deser C, Smoliak BV, Phillips AS (2016) Attribution of climate change in the presence of internal variability. In: Chang C-P, Ghil M, Latif M, Wallance JM (eds) Climate change: multidecadal and beyond. World Scientific, Singapore, pp 1–29
Wang B, Luo X, Liu J (2020) How robust is the Asian precipitation–ENSO relationship during the industrial warming period (1901–2017)? J Clim 33(7):2779–2792. https://doi.org/10.1175/jcli-d-19-0630.1
Xie SP, Deser C, Vecchi GA, Collins M, Delworth TL, Hall A, Hawkins E, Johnson NC, Cassou C, Giannini A, Watanabe M (2015) Towards predictive understanding of regional climate change. Nat Clim Change 5(10):921–930. https://doi.org/10.1038/nclimate2689
Yang X, DelSole T (2012) Systematic comparison of ENSO teleconnection patterns between models and observations. J Clim 25(2):425–446. https://doi.org/10.1175/JCLI-D-11-00175.1
Yang X, Zhou B, Xu Y, Han Z (2021) CMIP6 evaluation and projection of temperature and precipitation over China. Adv Atmos Sci 38(5):817–830. https://doi.org/10.1007/s00376-021-0351-4
Yasunari T, Kitoh A, Tokioka T (1991) Local and remote responses to excessive snow mass over Eurasia appearing in the northern spring and summer climate—a study with the MRI GCM. J Meteorol Soc Jpn 69(4):473–487. https://doi.org/10.2151/jmsj1965.69.4_473
Ye L, Yang G, van Ranst E, Tang H (2013) Time-series modeling and prediction of global monthly absolute temperature for environmental decision making. Adv Atmos Sci 30(2):382–396. https://doi.org/10.1007/s00376-012-1252-3
Ye K, Wu R, Liu Y (2015) Interdecadal change of Eurasian snow, surface temperature, and atmospheric circulation in the late 1980s. J Geophys Res Atmos 120(7):2738–2753. https://doi.org/10.1002/2015JD023148
Zhou B, Xu Y (2017) CMIP5 analysis of the interannual variability of the Pacific SST and its association with the Asian-Pacific oscillation. Atmos Oceanic Sci Lett 10(2):138–145. https://doi.org/10.1080/16742834.2017.1260427
Zwiers FW, Kharin VV (1998) Intercomparison of interannual variability and potential predictability: an AMIP diagnostic subproject. Clim Dyn 14(7–8):517–528. https://doi.org/10.1007/s003820050238
Acknowledgements
We would like to thank the two anonymous reviewers for their insightful comments and suggestions to improve this manuscript. We also acknowledge the climate modeling groups provided in Table S1 to produce and share the CMIP6 model outputs.
Funding
This work is funded by the National Natural Science Foundation of China (42221004, 42075048) and the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (EarthLab).
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DJ contributed to the study conception and design. Material preparation, data collection and analysis were performed by JS. The first draft of the manuscript was written by JS and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Shi, J., Tian, Z., Lang, X. et al. Projected changes in the interannual variability of surface air temperature using CMIP6 simulations. Clim Dyn 62, 431–446 (2024). https://doi.org/10.1007/s00382-023-06923-3
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DOI: https://doi.org/10.1007/s00382-023-06923-3