Comprehensive Representation of Tropical–Extratropical Teleconnections Obstructed by Tropical Pacific Convection Biases in CMIP6

Xiaofang Feng aDepartment of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences, Fudan University, Shanghai, China
bDepartment of Geography, and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, California
cKey Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

Search for other papers by Xiaofang Feng in
Current site
Google Scholar
PubMed
Close
,
Qinghua Ding bDepartment of Geography, and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, California

Search for other papers by Qinghua Ding in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0003-3634-0181
,
Liguang Wu aDepartment of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences, Fudan University, Shanghai, China

Search for other papers by Liguang Wu in
Current site
Google Scholar
PubMed
Close
,
Charles Jones bDepartment of Geography, and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, California

Search for other papers by Charles Jones in
Current site
Google Scholar
PubMed
Close
,
Huijun Wang cKey Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China
dCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

Search for other papers by Huijun Wang in
Current site
Google Scholar
PubMed
Close
,
Mitchell Bushuk eGeophysical Fluid Dynamics Laboratory, Princeton, New Jersey

Search for other papers by Mitchell Bushuk in
Current site
Google Scholar
PubMed
Close
, and
Dániel Topál bDepartment of Geography, and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, California
fInstitute for Geological and Geochemical Research, Research Centre for Astronomy and Earth Sciences, MTA-Centre of Excellence, ELKH, Budapest, Hungary
gUniversité Catholique de Louvain, Louvain-la-Neuve, Belgium

Search for other papers by Dániel Topál in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The central role of tropical sea surface temperature (SST) variability in modulating Northern Hemisphere (NH) extratropical climate has long been known. However, the prevailing pathways of teleconnections in observations and the ability of climate models to replicate these observed linkages remain elusive. Here, we apply maximum covariance analysis between atmospheric circulation and tropical SST to reveal two coexisting tropical–extratropical teleconnections albeit with distinctive spatiotemporal characteristics. The first mode, resembling the Pacific–North American (PNA) pattern, favors a tropical–Arctic in-phase (warm Pacific–warm Arctic) teleconnection in boreal spring and winter. However, the second mode, with a slight seasonal preference of summer, is manifested as an elongated Rossby wave train emanating from the tropical eastern Pacific that features an out-of-phase relationship (cold Pacific–warm Arctic) between tropical central Pacific SSTs and temperature variability over the Arctic (referred to as the PARC mode). While climate models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) appear to successfully simulate the PNA mode and its temporal characteristics, the majority of models’ skill in reproducing the PARC mode is obstructed to some extent by biases in simulating low-frequency SST and rainfall variability over the tropical eastern Pacific and the climatological mean flow over the North Pacific during boreal summer. Considering the contribution of the PARC mode in shaping low-frequency climate variations over the past 42 years from the tropics to the Arctic, improving models’ capability to capture the PARC mode is essential to reduce uncertainties associated with decadal prediction and climate change projection over the NH.

Significance Statement

This study focuses on the skill of models in phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating two leading observed Northern Hemisphere (NH) teleconnections that show distinctive spatial and temporal characteristics. The first one, the Pacific–North American (PNA) mode, exhibits a warm Pacific–warm Arctic pattern in boreal spring and winter, and the second one, the Pacific–Arctic (PARC) mode, features a cold Pacific–warm Arctic out-of-phase relationship. We find that models are skillful in simulating the PNA mode but not the PARC mode. This limitation may be rooted in unrealistic simulations of the mean state of winds and the low-frequency sea surface temperature variability in the tropical eastern Pacific. These biases call for caution when interpreting current models’ projections of extratropical circulations on multidecadal time scales.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is included in the Process-oriented Diagnostics in CMIP6 and Beyond Special Collection.

Corresponding author: Qinghua Ding, qinghua@ucsb.edu

Abstract

The central role of tropical sea surface temperature (SST) variability in modulating Northern Hemisphere (NH) extratropical climate has long been known. However, the prevailing pathways of teleconnections in observations and the ability of climate models to replicate these observed linkages remain elusive. Here, we apply maximum covariance analysis between atmospheric circulation and tropical SST to reveal two coexisting tropical–extratropical teleconnections albeit with distinctive spatiotemporal characteristics. The first mode, resembling the Pacific–North American (PNA) pattern, favors a tropical–Arctic in-phase (warm Pacific–warm Arctic) teleconnection in boreal spring and winter. However, the second mode, with a slight seasonal preference of summer, is manifested as an elongated Rossby wave train emanating from the tropical eastern Pacific that features an out-of-phase relationship (cold Pacific–warm Arctic) between tropical central Pacific SSTs and temperature variability over the Arctic (referred to as the PARC mode). While climate models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) appear to successfully simulate the PNA mode and its temporal characteristics, the majority of models’ skill in reproducing the PARC mode is obstructed to some extent by biases in simulating low-frequency SST and rainfall variability over the tropical eastern Pacific and the climatological mean flow over the North Pacific during boreal summer. Considering the contribution of the PARC mode in shaping low-frequency climate variations over the past 42 years from the tropics to the Arctic, improving models’ capability to capture the PARC mode is essential to reduce uncertainties associated with decadal prediction and climate change projection over the NH.

Significance Statement

This study focuses on the skill of models in phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating two leading observed Northern Hemisphere (NH) teleconnections that show distinctive spatial and temporal characteristics. The first one, the Pacific–North American (PNA) mode, exhibits a warm Pacific–warm Arctic pattern in boreal spring and winter, and the second one, the Pacific–Arctic (PARC) mode, features a cold Pacific–warm Arctic out-of-phase relationship. We find that models are skillful in simulating the PNA mode but not the PARC mode. This limitation may be rooted in unrealistic simulations of the mean state of winds and the low-frequency sea surface temperature variability in the tropical eastern Pacific. These biases call for caution when interpreting current models’ projections of extratropical circulations on multidecadal time scales.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is included in the Process-oriented Diagnostics in CMIP6 and Beyond Special Collection.

Corresponding author: Qinghua Ding, qinghua@ucsb.edu

Supplementary Materials

    • Supplemental Materials (PDF 0.6235 MB)
Save
  • Adler, R. F., and Coauthors, 2003: The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Baggett, C., and S. Lee, 2015: Arctic warming induced by tropically forced tapping of available potential energy and the role of the planetary-scale waves. J. Atmos. Sci., 72, 15621568, https://doi.org/10.1175/JAS-D-14-0334.1.

    • Search Google Scholar
    • Export Citation
  • 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
  • Batehup, R., S. McGregor, and A. J. E. Gallant, 2015: The influence of non-stationary teleconnections on palaeoclimate reconstructions of ENSO variance using a pseudoproxy framework. Climate Past, 11, 17331749, https://doi.org/10.5194/cp-11-1733-2015.

    • Search Google Scholar
    • Export Citation
  • Baxter, I., and Coauthors, 2019: How tropical Pacific surface cooling contributed to accelerated sea ice melt from 2007 to 2012 as ice is thinned by anthropogenic forcing. J. Climate, 32, 85838602, https://doi.org/10.1175/JCLI-D-18-0783.1.

    • Search Google Scholar
    • Export Citation
  • Bonan, D. B., and E. Blanchard-Wrigglesworth, 2020: Nonstationary teleconnection between the Pacific Ocean and Arctic sea ice. Geophys. Res. Lett., 47, e2019GL085666, https://doi.org/10.1029/2019GL085666.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An intercomparison of methods for finding coupled patterns in climate data. J. Climate, 5, 541560, https://doi.org/10.1175/1520-0442(1992)005<0541:AIOMFF>2.0.CO;2.

    • 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
  • Cavalieri, D. J., C. L. Parkinson, P. Gloersen, and H. J. Zwally, 1996: Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS passive microwave data, version 1. NASA National Snow and Ice Data Center Distributed Active Archive Center, accessed 7 December 2023, https://doi.org/10.5067/8GQ8LZQVL0VL.

  • Chen, Z., B. Gan, L. Wu, and F. Jia, 2018: Pacific–North American teleconnection and North Pacific Oscillation: Historical simulation and future projection in CMIP5 models. Climate Dyn., 50, 43794403, https://doi.org/10.1007/s00382-017-3881-9.

    • Search Google Scholar
    • Export Citation
  • Chiang, J. C. H., and D. J. Vimont, 2004: Analogous Pacific and Atlantic meridional modes of tropical atmosphere–ocean variability. J. Climate, 17, 41434158, https://doi.org/10.1175/JCLI4953.1.

    • Search Google Scholar
    • Export Citation
  • Choi, K.-S., C.-C. Wu, and E.-J. Cha, 2010: Change of tropical cyclone activity by Pacific-Japan teleconnection pattern in the western North Pacific. J. Geophys. Res., 115, D19114, https://doi.org/10.1029/2010JD013866.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., 2016: An observational analysis: Tropical relative to Arctic influence on midlatitude weather in the era of Arctic amplification. Geophys. Res. Lett., 43, 52875294, https://doi.org/10.1002/2016GL069102.

    • Search Google Scholar
    • Export Citation
  • Deser, C., A. Phillips, V. Bourdette, and H. Teng, 2012a: Uncertainty in climate change projections: The role of internal variability. Climate Dyn., 38, 527546, https://doi.org/10.1007/s00382-010-0977-x.

    • Search Google Scholar
    • Export Citation
  • Deser, C., and Coauthors, 2012b: ENSO and Pacific decadal variability in the Community Climate System Model version 4. J. Climate, 25, 26222651, https://doi.org/10.1175/JCLI-D-11-00301.1.

    • Search Google Scholar
    • Export Citation
  • Deser, C., R. Guo, and F. Lehner, 2017a: The relative contributions of tropical Pacific sea surface temperatures and atmospheric internal variability to the recent global warming hiatus. Geophys. Res. Lett., 44, 79457954, https://doi.org/10.1002/2017GL074273.

    • Search Google Scholar
    • Export Citation
  • Deser, C., I. R. Simpson, K. A. McKinnon, and A. S. Phillips, 2017b: The Northern Hemisphere extratropical atmospheric circulation response to ENSO: How well do we know it and how do we evaluate models accordingly? J. Climate, 30, 50595082, https://doi.org/10.1175/JCLI-D-16-0844.1.

    • Search Google Scholar
    • Export Citation
  • Ding, Q., and B. Wang, 2005: Circumglobal teleconnection in the Northern Hemisphere summer. J. Climate, 18, 34833505, https://doi.org/10.1175/JCLI3473.1.

    • Search Google Scholar
    • Export Citation
  • Ding, Q., E. J. Steig, D. S. Battisti, and M. Küttel, 2011: Winter warming in West Antarctica caused by central tropical Pacific warming. Nat. Geosci., 4, 398403, https://doi.org/10.1038/ngeo1129.

    • Search Google Scholar
    • Export Citation
  • Ding, Q., J. M. Wallace, D. S. Battisti, E. J. Steig, A. J. E. Gallant, H. J. Kim, and L. Geng, 2014: Tropical forcing of the recent rapid Arctic warming in northeastern Canada and Greenland. Nature, 509, 209212, https://doi.org/10.1038/nature13260.

    • Search Google Scholar
    • Export Citation
  • Dunn-Sigouin, E., C. Li, and P. J. Kushner, 2021: Limited influence of localized tropical sea-surface temperatures on moisture transport into the Arctic. Geophys. Res. Lett., 48, e2020GL091540, https://doi.org/10.1029/2020GL091540.

    • 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
  • Fasullo, J. T., A. S. Phillips, and C. Deser, 2020: Evaluation of leading modes of climate variability in the CMIP archives. J. Climate, 33, 55275545, https://doi.org/10.1175/JCLI-D-19-1024.1.

    • Search Google Scholar
    • Export Citation
  • Feng, X., and Coauthors, 2021: A multidecadal-scale tropically driven global teleconnection over the past millennium and its recent strengthening. J. Climate, 34, 25492565, https://doi.org/10.1175/JCLI-D-20-0216.1.

    • Search Google Scholar
    • Export Citation
  • Fetterer, F., and K. Knowles, 2004: Sea ice index monitors polar ice extent. Eos, Trans. Amer. Geophys. Union, 85, 163, https://doi.org/10.1029/2004EO160007.

    • Search Google Scholar
    • Export Citation
  • Gibson, P. B., S. E. Perkins-Kirkpatrick, P. Uotila, A. S. Pepler, and L. V. Alexander, 2017: On the use of self-organizing maps for studying climate extremes. J. Geophys. Res. Atmos., 122, 38913903, https://doi.org/10.1002/2016JD026256.

    • Search Google Scholar
    • Export Citation
  • Hall, R. J., E. Hanna, and L. Chen, 2021: Winter Arctic amplification at the synoptic timescale, 1979–2018, its regional variation and response to tropical and extratropical variability. Climate Dyn., 56, 457473, https://doi.org/10.1007/s00382-020-05485-y.

    • Search Google Scholar
    • Export Citation
  • Hanna, E., T. E. Cropper, R. J. Hall, and J. Cappelen, 2016: Greenland blocking index 1851–2015: A regional climate change signal. Int. J. Climatol., 36, 48474861, https://doi.org/10.1002/joc.4673.

    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., 2007: The atmospheric general circulation and its variability. J. Meteor. Soc. Japan, 85B, 123143, https://doi.org/10.2151/jmsj.85B.123.

    • Search Google Scholar
    • Export Citation
  • Henderson, G. R., B. S. Barrett, L. J. Wachowicz, K. S. Mattingly, J. R. Preece, and T. L. Mote, 2021: Local and remote atmospheric circulation drivers of Arctic change: A review. Front. Earth Sci., 9, 709896, https://doi.org/10.3389/feart.2021.709896.

    • Search Google Scholar
    • Export Citation
  • Herbst, M., H. V. Gupta, and M. C. Casper, 2009: Mapping model behaviour using self-organizing maps. Hydrol. Earth Syst. Sci., 13, 395409, https://doi.org/10.5194/hess-13-395-2009.

    • 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
  • Horel, J. D., and J. M. Wallace, 1981: Planetary-scale atmospheric phenomena associated with the Southern Oscillation. Mon. Wea. Rev., 109, 813829, https://doi.org/10.1175/1520-0493(1981)109<0813:PSAPAW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., and T. Ambrizzi, 1993: Rossby wave propagation on a realistic longitudinally varying flow. J. Atmos. Sci., 50, 16611671, https://doi.org/10.1175/1520-0469(1993)050<1661:RWPOAR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., and T. Woollings, 2015: Persistent extratropical regimes and climate extremes. Curr. Climate Change Rep., 1, 115124, https://doi.org/10.1007/s40641-015-0020-8.

    • Search Google Scholar
    • Export Citation
  • Hu, C., S. Yang, Q. Wu, Z. Li, J. Chen, K. Deng, T. Zhang, and C. Zhang, 2016: Shifting El Niño inhibits summer Arctic warming and Arctic sea-ice melting over the Canada Basin. Nat. Commun., 7, 11721, https://doi.org/10.1038/ncomms11721.

    • Search Google Scholar
    • Export Citation
  • Huang, B., and Coauthors, 2017: Extended reconstructed sea surface temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 81798205, https://doi.org/10.1175/JCLI-D-16-0836.1.

    • Search Google Scholar
    • Export Citation
  • Jeong, H., H.-S. Park, M. F. Stuecker, and S.-W. Yeh, 2022: Record low Arctic sea ice extent in 2012 linked to two-year La Niña-driven sea surface temperature pattern. Geophys. Res. Lett., 49, e2022GL098385, https://doi.org/10.1029/2022GL098385.

    • Search Google Scholar
    • Export Citation
  • Joseph, P. V., and J. Srinivasan, 1999: Rossby waves in May and the Indian summer monsoon rainfall. Tellus, 51A, 854864, https://doi.org/10.3402/tellusa.v51i5.14497.

    • Search Google Scholar
    • Export Citation
  • Karnauskas, K. B., J. E. Smerdon, R. Seager, and J. F. González-Rouco, 2012: A Pacific centennial oscillation predicted by coupled GCMs. J. Climate, 25, 59435961, https://doi.org/10.1175/JCLI-D-11-00421.1.

    • Search Google Scholar
    • Export Citation
  • Kay, J. E., and Coauthors, 2015: The Community Earth System Model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability. Bull. Amer. Meteor. Soc., 96, 13331349, https://doi.org/10.1175/BAMS-D-13-00255.1.

    • Search Google Scholar
    • Export Citation
  • Kohonen, T., 1990: The self-organizing map. Proc. IEEE, 78, 14641480, https://doi.org/10.1109/5.58325.

  • Kosaka, Y., and H. Nakamura, 2010: Mechanisms of meridional teleconnection observed between a summer monsoon system and a subtropical anticyclone. Part I: The Pacific–Japan pattern. J. Climate, 23, 50855108, https://doi.org/10.1175/2010JCLI3413.1.

    • Search Google Scholar
    • Export Citation
  • Kosaka, Y., H. Nakamura, M. Watanabe, and M. Kimoto, 2009: Analysis on the dynamics of a wave-like teleconnection pattern along the summertime Asian jet based on a reanalysis dataset and climate model simulations. J. Meteor. Soc. Japan, 87, 561580, https://doi.org/10.2151/jmsj.87.561.

    • Search Google Scholar
    • Export Citation
  • Larson, S. M., D. J. Vimont, A. C. Clement, and B. P. Kirtman, 2018: How momentum coupling affects SST variance and large-scale Pacific climate variability in CESM. J. Climate, 31, 29272944, https://doi.org/10.1175/JCLI-D-17-0645.1.

    • Search Google Scholar
    • Export Citation
  • Lewis, S. C., and A. N. LeGrande, 2015: Stability of ENSO and its tropical Pacific teleconnections over the last millennium. Climate Past, 11, 13471360, https://doi.org/10.5194/cp-11-1347-2015.

    • Search Google Scholar
    • Export Citation
  • L’Heureux, M. L., M. K. Tippett, A. Kumar, A. H. Butler, L. M. Ciasto, Q. Ding, K. J. Harnos, and N. C. Johnson, 2017: Strong relations between ENSO and the Arctic Oscillation in the North American Multimodel Ensemble. Geophys. Res. Lett., 44, 11 65411 662, https://doi.org/10.1002/2017GL074854.

    • Search Google Scholar
    • Export Citation
  • Lin, H., G. Brunet, and J. Derome, 2009: An observed connection between the North Atlantic Oscillation and the Madden–Julian oscillation. J. Climate, 22, 364380, https://doi.org/10.1175/2008JCLI2515.1.

    • Search Google Scholar
    • Export Citation
  • Liu, Z., 2012: Dynamics of interdecadal climate variability: A historical perspective. J. Climate, 25, 19631995, https://doi.org/10.1175/2011JCLI3980.1.

    • Search Google Scholar
    • Export Citation
  • Liu, Z., Y. Tang, Z. Jian, C. J. Poulsen, J. M. Welker, and G. J. Bowen, 2017: Pacific North American circulation pattern links external forcing and North American hydroclimatic change over the past millennium. Proc. Natl. Acad. Sci. USA, 114, 33403345, https://doi.org/10.1073/pnas.1618201114.

    • Search Google Scholar
    • Export Citation
  • Lu, R.-Y., J.-H. Oh, and B.-J. Kim, 2002: A teleconnection pattern in upper-level meridional wind over the North African and Eurasian continent in summer. Tellus, 54A, 4455, https://doi.org/10.3402/tellusa.v54i1.12122.

    • Search Google Scholar
    • Export Citation
  • Matsumura, S., and Y. Kosaka, 2019: Arctic-Eurasian climate linkage induced by tropical ocean variability. Nat. Commun., 10, 3441, https://doi.org/10.1038/s41467-019-11359-7.

    • Search Google Scholar
    • Export Citation
  • McCrystall, M. R., and J. A. Screen, 2021: Arctic winter temperature variations correlated with ENSO are dependent on coincidental sea ice changes. Geophys. Res. Lett., 48, e2020GL091519, https://doi.org/10.1029/2020GL091519.

    • Search Google Scholar
    • Export Citation
  • McCrystall, M. R., J. S. Hosking, I. P. White, and A. C. Maycock, 2020: The impact of changes in tropical sea surface temperatures over 1979–2012 on Northern Hemisphere high-latitude climate. J. Climate, 33, 51035121, https://doi.org/10.1175/JCLI-D-19-0456.1.

    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., and Coauthors, 2009: Decadal prediction. Bull. Amer. Meteor. Soc., 90, 14671486, https://doi.org/10.1175/2009BAMS2778.1.

    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., and Coauthors, 2014: Decadal climate prediction: An update from the trenches. Bull. Amer. Meteor. Soc., 95, 243267, https://doi.org/10.1175/BAMS-D-12-00241.1.

    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., C. T. Y. Chung, J. M. Arblaster, M. M. Holland, and C. M. Bitz, 2018: Tropical decadal variability and the rate of Arctic sea ice decrease. Geophys. Res. Lett., 45, 11 32611 333, https://doi.org/10.1029/2018GL079989.

    • 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
  • Neelin, J. D., and Coauthors, 1992: Tropical air-sea interaction in general circulation models. Climate Dyn., 7, 73104, https://doi.org/10.1007/BF00209610.

    • Search Google Scholar
    • Export Citation
  • Orbe, C., and Coauthors, 2020: Representation of modes of variability in six U.S. climate models. J. Climate, 33, 75917617, https://doi.org/10.1175/JCLI-D-19-0956.1.

    • Search Google Scholar
    • Export Citation
  • Perlwitz, J., M. Hoerling, and R. Dole, 2015: Arctic tropospheric warming: Causes and linkages to lower latitudes. J. Climate, 28, 21542167, https://doi.org/10.1175/JCLI-D-14-00095.1.

    • Search Google Scholar
    • Export Citation
  • Plumb, R. A., 1985: On the three-dimensional propagation of stationary waves. J. Atmos. Sci., 42, 217229, https://doi.org/10.1175/1520-0469(1985)042<0217:OTTDPO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Reusser, D. E., T. Blume, B. Schaefli, and E. Zehe, 2009: Analysing the temporal dynamics of model performance for hydrological models. Hydrol. Earth Syst. Sci., 13, 9991018, https://doi.org/10.5194/hess-13-999-2009.

    • 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
  • Seo, K.-H., and S.-W. Son, 2012: The global atmospheric circulation response to tropical diabatic heating associated with the Madden–Julian oscillation during northern winter. J. Atmos. Sci., 69, 7996, https://doi.org/10.1175/2011JAS3686.1.

    • Search Google Scholar
    • Export Citation
  • Shen, Z., Y. Ming, and I. M. Held, 2020: Using the fast impact of anthropogenic aerosols on regional land temperature to constrain aerosol forcing. Sci. Adv., 6, eabb5297, https://doi.org/10.1126/sciadv.abb5297.

    • Search Google Scholar
    • Export Citation
  • Sigmond, M., and J. C. Fyfe, 2016: Tropical Pacific impacts on cooling North American winters. Nat. Climate Change, 6, 970974, https://doi.org/10.1038/nclimate3069.

    • Search Google Scholar
    • Export Citation
  • Stan, C., D. M. Straus, J. S. Frederiksen, H. Lin, E. D. Maloney, and C. Schumacher, 2017: Review of tropical-extratropical teleconnections on intraseasonal time scales. Rev. Geophys., 55, 902937, https://doi.org/10.1002/2016RG000538.

    • Search Google Scholar
    • Export Citation
  • Stickler, A., and Coauthors, 2014: ERA-CLIM: Historical surface and upper-air data for future reanalyses. Bull. Amer. Meteor. Soc., 95, 14191430, https://doi.org/10.1175/BAMS-D-13-00147.1.

    • Search Google Scholar
    • Export Citation
  • Stoner, A. M. K., K. Hayhoe, and D. J. Wuebbles, 2009: Assessing general circulation model simulations of atmospheric teleconnection patterns. J. Climate, 22, 43484372, https://doi.org/10.1175/2009JCLI2577.1.

    • Search Google Scholar
    • Export Citation
  • Sun, D.-Z., T. Zhang, Y. Sun, and Y. Yu, 2014: Rectification of El Niño–Southern Oscillation into climate anomalies of decadal and longer time scales: Results from forced ocean GCM experiments. J. Climate, 27, 25452561, https://doi.org/10.1175/JCLI-D-13-00390.1.

    • Search Google Scholar
    • Export Citation
  • Swart, N., 2017: Natural causes of Arctic sea-ice loss. Nat. Climate Change, 7, 239241, https://doi.org/10.1038/nclimate3254.

  • Topál, D., Q. Ding, J. Mitchell, I. Baxter, M. Herein, T. Haszpra, R. Luo, and Q. Li, 2020: An internal atmospheric process determining summertime Arctic sea ice melting in the next three decades: Lessons learned from five large ensembles and multiple CMIP5 climate simulations. J. Climate, 33, 74317454, https://doi.org/10.1175/JCLI-D-19-0803.1.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., G. W. Branstator, D. Karoly, A. Kumar, N.-C. Lau, and C. Ropelewski, 1998: Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res., 103, 14 29114 324, https://doi.org/10.1029/97JC01444.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., J. T. Fasullo, G. Branstator, and A. S. Phillips, 2014: Seasonal aspects of the recent pause in surface warming. Nat. Climate Change, 4, 911916, https://doi.org/10.1038/nclimate2341.

    • Search Google Scholar
    • Export Citation
  • Vavrus, S. J., 2018: The influence of Arctic amplification on mid-latitude weather and climate. Curr. Climate Change Rep., 4, 238249, https://doi.org/10.1007/s40641-018-0105-2.

    • Search Google Scholar
    • Export Citation
  • Wakabayashi, S., and R. Kawamura, 2004: Extraction of major teleconnection patterns possibly associated with the anomalous summer climate in Japan. J. Meteor. Soc. Japan, 82, 15771588, https://doi.org/10.2151/jmsj.82.1577.

    • Search Google Scholar
    • Export Citation
  • Wallace, J. M., and D. S. Gutzler, 1981: Teleconnections in the geopotential height field during the Northern Hemisphere winter. Mon. Wea. Rev., 109, 784812, https://doi.org/10.1175/1520-0493(1981)109<0784:TITGHF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wallace, J. M., C. Smith, and C. S. Bretherton, 1992: Singular value decomposition of wintertime sea surface temperature and 500-mb height anomalies. J. Climate, 5, 561576, https://doi.org/10.1175/1520-0442(1992)005<0561:SVDOWS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, B., R. Wu, and X. Fu, 2000: Pacific–East Asian teleconnection: How does ENSO affect East Asian climate? J. Climate, 13, 15171536, https://doi.org/10.1175/1520-0442(2000)013<1517:PEATHD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, B., Q. Ding, X. Fu, I.-S. Kang, K. Jin, J. Shukla, and F. Doblas-Reyes, 2005: Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys. Res. Lett., 32, L15711, https://doi.org/10.1029/2005GL022734.

    • Search Google Scholar
    • Export Citation
  • Wang, L., P. Xu, W. Chen, and Y. Liu, 2017: Interdecadal variations of the Silk Road pattern. J. Climate, 30, 99159932, https://doi.org/10.1175/JCLI-D-17-0340.1.

    • Search Google Scholar
    • Export Citation
  • Webster, F., 1961: The effect of meanders on the kinetic energy balance of the Gulf Stream. Tellus, 13, 392401, https://doi.org/10.3402/tellusa.v13i3.9515.

    • Search Google Scholar
    • Export Citation
  • Webster, P. J., and J. R. Holton, 1982: Cross-equatorial response to middle-latitude forcing in a zonally varying basic state. J. Atmos. Sci., 39, 722733, https://doi.org/10.1175/1520-0469(1982)039<0722:CERTML>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Webster, P. J., and H.-R. Chang, 1998: Atmospheric wave propagation in heterogeneous flow: Basic flow controls on tropical-extratropical interaction and equatorial wave modification. Dyn. Atmos. Oceans, 27, 91134, https://doi.org/10.1016/S0377-0265(97)00003-1.

    • Search Google Scholar
    • Export Citation
  • Wu, B., T. Zhou, C. Li, W. A. Müller, and J. Lin, 2019: Improved decadal prediction of Northern-Hemisphere summer land temperature. Climate Dyn., 53, 13571369, https://doi.org/10.1007/s00382-019-04658-8.

    • Search Google Scholar
    • Export Citation
  • Yeh, S.-W., and Coauthors, 2018: ENSO atmospheric teleconnections and their response to greenhouse gas forcing. Rev. Geophys., 56, 185206, https://doi.org/10.1002/2017RG000568.

    • Search Google Scholar
    • Export Citation
  • Yuan, X., M. R. Kaplan, and M. A. Cane, 2018: The interconnected global climate system—A review of tropical–polar teleconnections. J. Climate, 31, 57655792, https://doi.org/10.1175/JCLI-D-16-0637.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 1155 1155 58
Full Text Views 516 516 27
PDF Downloads 389 389 9