Articles | Volume 3, issue 3
https://doi.org/10.5194/wcd-3-951-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-3-951-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Aug 2022
Research article |
| 17 Aug 2022
| 17 Aug 2022
Improved teleconnection between Arctic sea ice and the North Atlantic Oscillation through stochastic process representation
Kristian Strommen
CORRESPONDING AUTHOR
Department of Physics, University of Oxford, Oxford, United Kingdom
Stephan Juricke
Mathematics and Logistics, Jacobs University, Bremen, Germany
Helmholtz Centre for Polar and Marine Research, Alfred Wegener Institute, Bremerhaven, Germany
Fenwick Cooper
Department of Physics, University of Oxford, Oxford, United Kingdom
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This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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The Southern Annular Mode (SAM) is a key driver of Southern Hemisphere climate variability, but global models often overestimate its persistence in summer. Using high-resolution models, we show this bias can be reduced, along with some improvements in jet latitude and likely a better-resolved eddy-mean flow feedback. Controlled experiments reveal the potential roles of sea surface temperature biases and ocean mesoscales, underscoring the complex mechanisms shaping SAM persistence.
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We present evidence which strongly suggests that decadal variations in the intensity of the North Atlantic winter jet stream can be predicted by current forecast models but that decadal variations in its position appear to be unpredictable. It is argued that this skill at predicting jet intensity originates from the slow, predictable variability in sea surface temperatures in the sub-polar North Atlantic.
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We investigate how well current state-of-the-art climate models reproduce the wintertime weather of the North Atlantic and western Europe by studying how well different "regimes" of weather are captured. Historically, models have struggled to capture these regimes, making it hard to predict future changes in wintertime extreme weather. We show models can capture regimes if the right method is used, but they show biases, partially as a result of biases in jet speed and eddy strength.
Kristian Strommen, Hannah M. Christensen, Dave MacLeod, Stephan Juricke, and Tim N. Palmer
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Due to computational limitations, climate models cannot fully resolve the laws of physics below a certain scale – a large source of errors and uncertainty. Stochastic schemes aim to account for this by randomly sampling the possible unresolved states. We develop new stochastic schemes for the EC-Earth climate model and evaluate their impact on model performance. While several benefits are found, the impact is sometimes too strong, suggesting such schemes must be carefully calibrated before use.
Ting-Chen Chen, Hugues Goosse, Matthias Aengenheyster, Kristian Strommen, Christopher Roberts, Malcolm Roberts, Rohit Ghosh, Jin-Song von Storch, and Stephy Libera
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The Southern Annular Mode (SAM) is a key driver of Southern Hemisphere climate variability, but global models often overestimate its persistence in summer. Using high-resolution models, we show this bias can be reduced, along with some improvements in jet latitude and likely a better-resolved eddy-mean flow feedback. Controlled experiments reveal the potential roles of sea surface temperature biases and ocean mesoscales, underscoring the complex mechanisms shaping SAM persistence.
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We present evidence which strongly suggests that decadal variations in the intensity of the North Atlantic winter jet stream can be predicted by current forecast models but that decadal variations in its position appear to be unpredictable. It is argued that this skill at predicting jet intensity originates from the slow, predictable variability in sea surface temperatures in the sub-polar North Atlantic.
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Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
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We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Joshua Dorrington, Kristian Strommen, and Federico Fabiano
Weather Clim. Dynam., 3, 505–533, https://doi.org/10.5194/wcd-3-505-2022, https://doi.org/10.5194/wcd-3-505-2022, 2022
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We investigate how well current state-of-the-art climate models reproduce the wintertime weather of the North Atlantic and western Europe by studying how well different "regimes" of weather are captured. Historically, models have struggled to capture these regimes, making it hard to predict future changes in wintertime extreme weather. We show models can capture regimes if the right method is used, but they show biases, partially as a result of biases in jet speed and eddy strength.
Kristian Strommen, Hannah M. Christensen, Dave MacLeod, Stephan Juricke, and Tim N. Palmer
Geosci. Model Dev., 12, 3099–3118, https://doi.org/10.5194/gmd-12-3099-2019, https://doi.org/10.5194/gmd-12-3099-2019, 2019
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Due to computational limitations, climate models cannot fully resolve the laws of physics below a certain scale – a large source of errors and uncertainty. Stochastic schemes aim to account for this by randomly sampling the possible unresolved states. We develop new stochastic schemes for the EC-Earth climate model and evaluate their impact on model performance. While several benefits are found, the impact is sometimes too strong, suggesting such schemes must be carefully calibrated before use.
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Johannes Riebold, Andy Richling, Uwe Ulbrich, Henning Rust, Tido Semmler, and Dörthe Handorf
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Hannah L. Croad, John Methven, Ben Harvey, Sarah P. E. Keeley, and Ambrogio Volonté
Weather Clim. Dynam., 4, 617–638, https://doi.org/10.5194/wcd-4-617-2023, https://doi.org/10.5194/wcd-4-617-2023, 2023
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The interaction between Arctic cyclones and the sea ice surface in summer is investigated by analysing the friction and sensible heat flux processes acting in two cyclones with contrasting evolution. The major finding is that the effects of friction on cyclone strength are dependent on a particular feature of cyclone structure: whether they have a warm or cold core during growth. Friction leads to cooling within both cyclone types in the lower atmosphere, which may contribute to their longevity.
Stephen Outten, Camille Li, Martin P. King, Lingling Suo, Peter Y. F. Siew, Hoffman Cheung, Richard Davy, Etienne Dunn-Sigouin, Tore Furevik, Shengping He, Erica Madonna, Stefan Sobolowski, Thomas Spengler, and Tim Woollings
Weather Clim. Dynam., 4, 95–114, https://doi.org/10.5194/wcd-4-95-2023, https://doi.org/10.5194/wcd-4-95-2023, 2023
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Strong disagreement exists in the scientific community over the role of Arctic sea ice in shaping wintertime Eurasian cooling. The observed Eurasian cooling can arise naturally without sea-ice loss but is expected to be a rare event. We propose a framework that incorporates sea-ice retreat and natural variability as contributing factors. A helpful analogy is of a dice roll that may result in cooling, warming, or anything in between, with sea-ice loss acting to load the dice in favour of cooling.
Tim Woollings, Camille Li, Marie Drouard, Etienne Dunn-Sigouin, Karim A. Elmestekawy, Momme Hell, Brian Hoskins, Cheikh Mbengue, Matthew Patterson, and Thomas Spengler
Weather Clim. Dynam., 4, 61–80, https://doi.org/10.5194/wcd-4-61-2023, https://doi.org/10.5194/wcd-4-61-2023, 2023
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This paper investigates large-scale atmospheric variability in polar regions, specifically the balance between large-scale turbulence and Rossby wave activity. The polar regions are relatively more dominated by turbulence than lower latitudes, but Rossby waves are found to play a role and can even be triggered from high latitudes under certain conditions. Features such as cyclone lifetimes, high-latitude blocks, and annular modes are discussed from this perspective.
Thomas Caton Harrison, Stavroula Biri, Thomas J. Bracegirdle, John C. King, Elizabeth C. Kent, Étienne Vignon, and John Turner
Weather Clim. Dynam., 3, 1415–1437, https://doi.org/10.5194/wcd-3-1415-2022, https://doi.org/10.5194/wcd-3-1415-2022, 2022
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Easterly winds encircle Antarctica, impacting sea ice and helping drive ocean currents which shield ice shelves from warmer waters. Reanalysis datasets give us our most complete picture of how these winds behave. In this paper we use satellite data, surface measurements and weather balloons to test how realistic recent reanalysis estimates are. The winds are generally accurate, especially in the most recent of the datasets, but important short-term variations are often misrepresented.
Alexander F. Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Weather Clim. Dynam., 3, 1097–1112, https://doi.org/10.5194/wcd-3-1097-2022, https://doi.org/10.5194/wcd-3-1097-2022, 2022
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Understanding the location and intensity of hazardous weather across the Arctic is important for assessing risks to infrastructure, shipping, and coastal communities. This study describes the typical lifetime and structure of intense winter and summer Arctic cyclones. Results show the composite development and structure of intense summer Arctic cyclones are different from intense winter Arctic and North Atlantic Ocean extra-tropical cyclones and from conceptual models.
Costanza Rodda, Uwe Harlander, and Miklos Vincze
Weather Clim. Dynam., 3, 937–950, https://doi.org/10.5194/wcd-3-937-2022, https://doi.org/10.5194/wcd-3-937-2022, 2022
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We report on a set of laboratory experiments that reproduce a global warming scenario. The experiments show that a decreased temperature difference between the poles and subtropics slows down the eastward propagation of the mid-latitude weather patterns. Another consequence is that the temperature variations diminish, and hence extreme temperature events might become milder in a global warming scenario. Our experiments also show that the frequency of such events increases.
Amélie Simon, Guillaume Gastineau, Claude Frankignoul, Vladimir Lapin, and Pablo Ortega
Weather Clim. Dynam., 3, 845–861, https://doi.org/10.5194/wcd-3-845-2022, https://doi.org/10.5194/wcd-3-845-2022, 2022
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The influence of the Arctic sea-ice loss on atmospheric circulation in midlatitudes depends on persistent sea surface temperatures in the North Pacific. In winter, Arctic sea-ice loss and a warm North Pacific Ocean both induce depressions over the North Pacific and North Atlantic, an anticyclone over Greenland, and a stratospheric anticyclone over the Arctic. However, the effects are not additive as the interaction between both signals is slightly destructive.
Steve Delhaye, Thierry Fichefet, François Massonnet, David Docquier, Rym Msadek, Svenya Chripko, Christopher Roberts, Sarah Keeley, and Retish Senan
Weather Clim. Dynam., 3, 555–573, https://doi.org/10.5194/wcd-3-555-2022, https://doi.org/10.5194/wcd-3-555-2022, 2022
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It is unclear how the atmosphere will respond to a retreat of summer Arctic sea ice. Much attention has been paid so far to weather extremes at mid-latitude and in winter. Here we focus on the changes in extremes in surface air temperature and precipitation over the Arctic regions in summer during and following abrupt sea ice retreats. We find that Arctic sea ice loss clearly shifts the extremes in surface air temperature and precipitation over terrestrial regions surrounding the Arctic Ocean.
Patrick Johannes Stoll
Weather Clim. Dynam., 3, 483–504, https://doi.org/10.5194/wcd-3-483-2022, https://doi.org/10.5194/wcd-3-483-2022, 2022
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Polar lows are small but intense cyclones and constitute one of the major natural hazards in the polar regions. To be aware of when and where polar lows occur, this study maps polar lows globally by utilizing new atmospheric datasets. Polar lows develop in all marine areas adjacent to sea ice or cold landmasses, mainly in the winter half year. The highest frequency appears in the Nordic Seas. Further, it is found that polar lows are rather similar in the different ocean sub-basins.
Matthew T. Bray and Steven M. Cavallo
Weather Clim. Dynam., 3, 251–278, https://doi.org/10.5194/wcd-3-251-2022, https://doi.org/10.5194/wcd-3-251-2022, 2022
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Tropopause polar vortices (TPVs) are a high-latitude atmospheric phenomenon that impact weather inside and outside of polar regions. Using a set of long-lived TPVs to gain insight into the conditions that are most supportive of TPV survival, we describe patterns of vortex formation and movement. In addition, we analyze the characteristics of these TPVs and how they vary by season. These results help us to better understand TPVs which, in turn, may improve forecasts of related weather events.
Katharina Hartmuth, Maxi Boettcher, Heini Wernli, and Lukas Papritz
Weather Clim. Dynam., 3, 89–111, https://doi.org/10.5194/wcd-3-89-2022, https://doi.org/10.5194/wcd-3-89-2022, 2022
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In this study, we introduce a novel method to objectively define and identify extreme Arctic seasons based on different surface variables. We find that such seasons are resulting from various combinations of unusual seasonal conditions. The occurrence or absence of different atmospheric processes strongly affects the character of extreme Arctic seasons. Further, changes in sea ice and sea surface temperature can strongly influence the formation of such a season in distinct regions.
Sonja Murto, Rodrigo Caballero, Gunilla Svensson, and Lukas Papritz
Weather Clim. Dynam., 3, 21–44, https://doi.org/10.5194/wcd-3-21-2022, https://doi.org/10.5194/wcd-3-21-2022, 2022
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This study uses reanalysis data to investigate the role of atmospheric blocking, prevailing high-pressure systems and mid-latitude cyclones in driving high-Arctic wintertime warm extreme events. These events are mainly preceded by Ural and Scandinavian blocks, which are shown to be significantly influenced and amplified by cyclones in the North Atlantic. It also highlights processes that need to be well captured in climate models for improving their representation of Arctic wintertime climate.
Lukas Papritz, David Hauswirth, and Katharina Hartmuth
Weather Clim. Dynam., 3, 1–20, https://doi.org/10.5194/wcd-3-1-2022, https://doi.org/10.5194/wcd-3-1-2022, 2022
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Water vapor profoundly impacts the Arctic, for example by contributing to sea ice melt. A substantial portion of water vapor in the Arctic originates at mid-latitudes and is transported poleward in a few episodic and intense events. This transport is accomplished by low- and high-pressure systems occurring in specific regions or following particular tracks. Here, we explore how the type of weather system impacts where the water vapor is coming from and how it is transported poleward.
Suzanne L. Gray, Kevin I. Hodges, Jonathan L. Vautrey, and John Methven
Weather Clim. Dynam., 2, 1303–1324, https://doi.org/10.5194/wcd-2-1303-2021, https://doi.org/10.5194/wcd-2-1303-2021, 2021
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This research demonstrates, using feature identification and tracking, that anticlockwise rotating vortices at about 7 km altitude called tropopause polar vortices frequently interact with storms developing in the Arctic region, affecting their structure and where they occur. This interaction has implications for the predictability of Arctic weather, given the long lifetime but a relatively small spatial scale of these vortices compared with the density of the polar observation network.
Corwin J. Wright, Richard J. Hall, Timothy P. Banyard, Neil P. Hindley, Isabell Krisch, Daniel M. Mitchell, and William J. M. Seviour
Weather Clim. Dynam., 2, 1283–1301, https://doi.org/10.5194/wcd-2-1283-2021, https://doi.org/10.5194/wcd-2-1283-2021, 2021
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Major sudden stratospheric warmings (SSWs) are some of the most dramatic events in the atmosphere and are believed to help cause extreme winter weather events such as the 2018 Beast from the East in Europe and North America. Here, we use unique data from the European Space Agency's new Aeolus satellite to make the first-ever measurements at a global scale of wind changes due to an SSW in the lower part of the atmosphere to help us understand how SSWs affect the atmosphere and surface weather.
Clio Michel, Erica Madonna, Clemens Spensberger, Camille Li, and Stephen Outten
Weather Clim. Dynam., 2, 1131–1148, https://doi.org/10.5194/wcd-2-1131-2021, https://doi.org/10.5194/wcd-2-1131-2021, 2021
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Climate models still struggle to correctly represent blocking frequency over the North Atlantic–European domain. This study makes use of five large ensembles of climate simulations and the ERA-Interim reanalyses to investigate the Greenland blocking frequency and one of its drivers, namely cyclonic Rossby wave breaking. We particularly try to understand the discrepancies between two specific models, out of the five, that behave differently.
Marcel Meyer, Iuliia Polkova, Kameswar Rao Modali, Laura Schaffer, Johanna Baehr, Stephan Olbrich, and Marc Rautenhaus
Weather Clim. Dynam., 2, 867–891, https://doi.org/10.5194/wcd-2-867-2021, https://doi.org/10.5194/wcd-2-867-2021, 2021
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Novel techniques from computer science are used to study extreme weather events. Inspired by the interactive 3-D visual analysis of the recently released ERA5 reanalysis data, we improve commonly used metrics for measuring polar winter storms and outbreaks of cold air. The software (Met.3D) that we have extended and applied as part of this study is freely available and can be used generically for 3-D visualization of a broad variety of atmospheric processes in weather and climate data.
Patrick Johannes Stoll, Thomas Spengler, Annick Terpstra, and Rune Grand Graversen
Weather Clim. Dynam., 2, 19–36, https://doi.org/10.5194/wcd-2-19-2021, https://doi.org/10.5194/wcd-2-19-2021, 2021
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Polar lows are intense meso-scale cyclones occurring at high latitudes. The research community has not agreed on a conceptual model to describe polar-low development. Here, we apply self-organising maps to identify the typical ambient sub-synoptic environments of polar lows and find that they can be described as moist-baroclinic cyclones that develop in four different environments characterised by the vertical wind shear.
Lilian Schuster, Fabien Maussion, Lukas Langhamer, and Gina E. Moseley
Weather Clim. Dynam., 2, 1–17, https://doi.org/10.5194/wcd-2-1-2021, https://doi.org/10.5194/wcd-2-1-2021, 2021
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Precipitation and moisture sources over an arid region in northeast Greenland are investigated from 1979 to 2017 by a Lagrangian moisture source diagnostic driven by reanalysis data. Dominant winter moisture sources are the North Atlantic above 45° N. In summer local and north Eurasian continental sources dominate. In positive phases of the North Atlantic Oscillation, evaporation and moisture transport from the Norwegian Sea are stronger, resulting in more precipitation.
Hilla Afargan-Gerstman, Iuliia Polkova, Lukas Papritz, Paolo Ruggieri, Martin P. King, Panos J. Athanasiadis, Johanna Baehr, and Daniela I. V. Domeisen
Weather Clim. Dynam., 1, 541–553, https://doi.org/10.5194/wcd-1-541-2020, https://doi.org/10.5194/wcd-1-541-2020, 2020
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We investigate the stratospheric influence on marine cold air outbreaks (MCAOs) in the North Atlantic using ERA-Interim reanalysis data. MCAOs are associated with severe Arctic weather, such as polar lows and strong surface winds. Sudden stratospheric events are found to be associated with more frequent MCAOs in the Barents and the Norwegian seas, affected by the anomalous circulation over Greenland and Scandinavia. Identification of MCAO precursors is crucial for improved long-range prediction.
Mauro Hermann, Lukas Papritz, and Heini Wernli
Weather Clim. Dynam., 1, 497–518, https://doi.org/10.5194/wcd-1-497-2020, https://doi.org/10.5194/wcd-1-497-2020, 2020
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We find, by tracing backward in time, that air masses causing extensive melt of the Greenland Ice Sheet originate from further south and lower altitudes than usual. Their exceptional warmth further arises due to ascent and cloud formation, which is special compared to near-surface heat waves in the midlatitudes or the central Arctic. The atmospheric systems and transport pathways identified here are crucial in understanding and simulating the atmospheric control of the ice sheet in the future.
Peter Yu Feng Siew, Camille Li, Stefan Pieter Sobolowski, and Martin Peter King
Weather Clim. Dynam., 1, 261–275, https://doi.org/10.5194/wcd-1-261-2020, https://doi.org/10.5194/wcd-1-261-2020, 2020
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Arctic sea ice loss has been linked to changes in mid-latitude weather and climate. However, the literature offers differing views on the strength, robustness, and even existence of these linkages. We use a statistical tool (Causal Effect Networks) to show that one proposed pathway linking Barents–Kara ice and mid-latitude circulation is intermittent in observations and likely only active under certain conditions. This result may help explain apparent inconsistencies across previous studies.
Erik A. Lindgren and Aditi Sheshadri
Weather Clim. Dynam., 1, 93–109, https://doi.org/10.5194/wcd-1-93-2020, https://doi.org/10.5194/wcd-1-93-2020, 2020
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Sudden stratospheric warmings (SSWs) are extreme events that influence surface weather up to 2 months after onset. We remove wave–wave interactions (WWIs) in vertical sections of a general circulation model to investigate the role of WWIs in SSW formation. We show that the effects of WWIs depend strongly on the pressure levels where they occur and the zonal structure of the wave forcing in the troposphere. Our results highlight the importance of upper-level processes in stratospheric dynamics.
Cited articles
Alexander, M. A., Matrosova, L., Penland, C., Scott, J. D., and Chang, P.:
Forecasting Pacific SSTs: Linear inverse model predictions of the PDO,
J. Climate, 21, 385–402, 2008. a
Baker, L. H., Shaffrey, L. C., Sutton, R. T., Weisheimer, A., and Scaife,
A. A.: An Intercomparison of Skill and Overconfidence/Underconfidence of the
Wintertime North Atlantic Oscillation in Multimodel Seasonal Forecasts,
Geophys. Res. Lett., 45, 7808–7817, https://doi.org/10.1029/2018GL078838, 2018. a
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi,
M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification
from Field Site to Terrestrial Water Storage and Impact in the Integrated
Forecast System, J. Hydrometeorol., 10, 623–643,
https://doi.org/10.1175/2008JHM1068.1, 2009. a
Barnes, E. A. and Screen, J. A.: The impact of Arctic warming on the
midlatitude jet-stream: Can it? Has it? Will it?, WIREs Clim. Change, 6, 277–286, https://doi.org/10.1002/wcc.337, 2015. a
Berner, J., Achatz, U., Batté, L., Bengtsson, L., De La Cámara,
A., Weisheimer, A., Weniger, M., Williams, P. D., and Yano, J.-I.:
Stochastic parameterizations: Toward a New View of Weather and Climate
Models, B. Am. Meteorol. Soc., 98, 565–588,
https://doi.org/10.1175/BAMS-D-15-00268.1, 2017. a, b, c
Blackport, R. and Screen, J. A.: Observed Statistical Connections Overestimate
the Causal Effects of Arctic Sea Ice Changes on Midlatitude Winter Climate,
J. Climate, 34, 3021–3038, https://doi.org/10.1175/JCLI-D-20-0293.1, 2021. a, b, c, d
Brankart, J.-M., Candille, G., Garnier, F., Calone, C., Melet, A., Bouttier, P.-A., Brasseur, P., and Verron, J.: A generic approach to explicit simulation of uncertainty in the NEMO ocean model, Geosci. Model Dev., 8, 1285–1297, https://doi.org/10.5194/gmd-8-1285-2015, 2015. a
Brayshaw, D. J., Hoskins, B., and Blackburn, M.: The Basic Ingredients of the
North Atlantic Storm Track. Part II: Sea Surface Temperatures, J.
Atmos. Sci., 68, 1784–1805, https://doi.org/10.1175/2011JAS3674.1, 2011. a
Caian, M., Koenigk, T., Döscher, R., and Devasthale, A.: An interannual
link between Arctic sea-ice cover and the North Atlantic Oscillation, Clim.
Dynam., 50, 423–441, https://doi.org/10.1007/s00382-017-3618-9, 2018. a, b, c
Chapman, W. and National Center for Atmospheric Research Staff (Eds.):
MS Windows NT Kernel Description,
https://climatedataguide.ucar.edu/climate-data/walsh-and-chapman-northern-hemisphere-sea-ice (last access: 8 August 2022),
2013. a
Christensen, H. M., Berner, J., Coleman, D. R., and Palmer, T. N.: Stochastic
parameterization and El Niño-southern oscillation, J. Climate,
30, 17–38, https://doi.org/10.1175/JCLI-D-16-0122.1, 2017. a, b
Davini, P., von Hardenberg, J., Corti, S., Christensen, H. M., Juricke, S., Subramanian, A., Watson, P. A. G., Weisheimer, A., and Palmer, T. N.: Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model, Geosci. Model Dev., 10, 1383–1402, https://doi.org/10.5194/gmd-10-1383-2017, 2017. a
Dawson, A. and Palmer, T. N.: Simulating weather regimes: impact of model
resolution and stochastic parameterization, Clim. Dynam., 44,
2177–2193, https://doi.org/10.1007/s00382-014-2238-x, 2015. a
Deser, C., Walsh, J. E., and Timlin, M. S.: Arctic sea ice variability in the
context of recent atmospheric circulation trends, J. Climate, 13, 617–633,
https://doi.org/10.1175/1520-0442(2000)013<0617:ASIVIT>2.0.CO;2, 2000. a
Deser, C., Tomas, R. A., and Peng, S.: The Transient Atmospheric Circulation
Response to North Atlantic SST and Sea Ice Anomalies, J. Climate, 20,
4751–4767, https://doi.org/10.1175/JCLI4278.1, 2007. a, b, c, d
Deser, C., Sun, L., Tomas, R. A., and Screen, J.: Does ocean coupling matter
for the northern extratropical response to projected Arctic sea ice loss?,
Geophys. Res. Lett., 43, 2149–2157,
https://doi.org/10.1002/2016GL067792, 2016. a, b
Dunstone, N., Smith, D., Scaife, A., Hermanson, L., Eade, R., Robinson, N.,
Andrews, M., and Knight, J.: Skilful predictions of the winter North
Atlantic Oscillation one year ahead, Nat. Geosci., 9, 809–814,
https://doi.org/10.1038/ngeo2824, 2016. a, b
Eade, R., Smith, D., Scaife, A., Wallace, E., Dunstone, N., Hermanson, L., and
Robinson, N.: Do seasonal-to-decadal climate predictions underestimate the
predictability of the real world?, Geophys. Res. Lett., 41,
5620–5628, https://doi.org/10.1002/2014GL061146, 2014. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Frankignoul, C., Czaja, A., and L’Heveder, B.: Air–Sea Feedback in the
North Atlantic and Surface Boundary Conditions for Ocean Models, J.
Climate, 11, 2310–2324,
https://doi.org/10.1175/1520-0442(1998)011<2310:ASFITN>2.0.CO;2, 1998. a
García-Serrano, J., Frankignoul, C., Gastineau, G., and de la Cámara, A.: On
the Predictability of the Winter Euro-Atlantic Climate: Lagged Influence of
Autumn Arctic Sea Ice, J. Climate, 28, 5195–5216,
https://doi.org/10.1175/JCLI-D-14-00472.1, 2015. a, b
Gent, P. R. and Mcwilliams, J. C.: Isopycnal Mixing in Ocean Circulation
Models, J. Phys. Oceanogr., 20, 150–155,
https://doi.org/10.1175/1520-0485(1990)020<0150:IMIOCM>2.0.CO;2, 1990. a
Haarsma, R., Acosta, M., Bakhshi, R., Bretonnière, P.-A., Caron, L.-P., Castrillo, M., Corti, S., Davini, P., Exarchou, E., Fabiano, F., Fladrich, U., Fuentes Franco, R., García-Serrano, J., von Hardenberg, J., Koenigk, T., Levine, X., Meccia, V. L., van Noije, T., van den Oord, G., Palmeiro, F. M., Rodrigo, M., Ruprich-Robert, Y., Le Sager, P., Tourigny, E., Wang, S., van Weele, M., and Wyser, K.: HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR – description, model computational performance and basic validation, Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, 2020. a, b, c, d
Haarsma, R. J., Roberts, M. J., Vidale, P. L., Senior, C. A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N. S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J.-J., Mao, J., Mizielinski, M. S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.-S.: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geosci. Model Dev., 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016. a, b
Hawkins, E. and Sutton, R.: Decadal predictability of the Atlantic Ocean in a
coupled GCM: Forecast skill and optimal perturbations using linear inverse
modeling, J. Climate, 22, 3960–3978, 2009. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J.-N.: ERA5 hourly data on single levels from 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons,
A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati,
G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M.,
Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global
reanalysis, Q. J. Roy. Meteor. Soc., 146,
1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hoskins, B. J. and Karoly, D. J.: The Steady Linear Response of a Spherical
Atmosphere to Thermal and Orographic Forcing, J. Atmos.
Sci., 38, 1179–1196,
https://doi.org/10.1175/1520-0469(1981)038<1179:TSLROA>2.0.CO;2, 1981. a
Hurrell, J. W., Kushnir, Y., Otterson, G., and Visbeck, M.: An Overview of the
North Atlantic Oscillation, in: The North Atlantic Oscillation: Climatic
Significance and Environmental Impact, 1st edn., volume 134, ISBN 9780875909943, https://doi.org/10.1029/GM134, 2003. a
Juricke, S., Goessling, H. F., and Jung, T.: Potential sea ice predictability
and the role of stochastic sea ice strength perturbations, Geophys.
Res. Lett., 41, 8396–8403, https://doi.org/10.1002/2014GL062081,
2014. a, b, c
Juricke, S., MacLeod, D., Weisheimer, A., Zanna, L., and Palmer, T. N.:
Seasonal to annual ocean forecasting skill and the role of model and
observational uncertainty, Q. J. Roy. Meteor.
Soc., 144, 1947–1964, https://doi.org/10.1002/qj.3394, 2018. a, b, c
Keeley, S. P., Sutton, R. T., and Shaffrey, L. C.: The impact of North
Atlantic sea surface temperature errors on the simulation of North Atlantic
European region climate, Q. J. Roy. Meteor.
Soc., 138, 1774–1783, https://doi.org/10.1002/qj.1912, 2012. a
Kelleher, M. and Screen, J.: Atmospheric precursors of and response to
anomalous Arctic sea ice in CMIP5 models, Adv. Atmos. Sci.,
35, 27–37, 2018. a
Kim, B.-M., Son, S.-W., Min, S.-K., Jeong, J.-H., Kim, S.-J., Zhang, X., Shim,
T., and Yoon, J.-H.: Weakening of the stratospheric polar vortex by Arctic
sea-ice loss, Nat. Commun., 5, 4646, https://doi.org/10.1038/ncomms5646, 2014. a
Kolstad, E. W. and Screen, J. A.: Nonstationary Relationship Between Autumn
Arctic Sea Ice and the Winter North Atlantic Oscillation, Geophys.
Res. Lett., 46, 7583–7591, https://doi.org/10.1029/2019GL083059,
2019. a
Kretschmer, M., Coumou, D., Donges, J. F., and Runge, J.: Using Causal Effect
Networks to Analyze Different Arctic Drivers of Midlatitude Winter
Circulation, J. Climate, 29, 4069–4081,
https://doi.org/10.1175/JCLI-D-15-0654.1, 2016. a, b
Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49–78, https://doi.org/10.5194/tc-13-49-2019, 2019. a
Madec, G. and the NEMO team: NEMO ocean engine, Note du Pôle de modélisation, Institut Pierre-Simon Laplace (IPSL), France, No 27, ISSN 1288-1619, 2008. a
Magnusdottir, G., Deser, C., and Saravanan, R.: The Effects of North Atlantic
SST and Sea Ice Anomalies on the Winter Circulation in CCM3. Part I: Main
Features and Storm Track Characteristics of the Response, J. Climate,
17, 857–876, https://doi.org/10.1175/1520-0442(2004)017<0857:TEONAS>2.0.CO;2, 2004. a
Mori, M., Kosaka, Y., Watanabe, M., Nakamura, H., and Kimoto, M.: A reconciled
estimate of the influence of Arctic sea-ice loss on recent Eurasian cooling,
Nat. Clim. Change, 9, 123–129, https://doi.org/10.1038/s41558-018-0379-3,
2019a. a, b, c
Mori, M., Kosaka, Y., Watanabe, M., Taguchi, B., Nakamura, H., and Kimoto, M.:
Reply to: Is sea-ice-driven Eurasian cooling too weak in models?, Nat.
Clim. Change, 9, 937–939, https://doi.org/10.1038/s41558-019-0636-0,
2019b. a, b, c
Newman, M., Sardeshmukh, P. D., and Penland, C.: How Important Is Air–Sea
Coupling in ENSO and MJO Evolution?, J. Climate, 22, 2958–2977,
https://doi.org/10.1175/2008JCLI2659.1, 2009. a
Notz, D. and SIMIP Community: Arctic Sea Ice in CMIP6, Geophys. Res.
Lett., 47, e2019GL086749, https://doi.org/10.1029/2019GL086749, 2020. a
Palmer, T. N.: Towards the probabilistic Earth-system simulator: A vision for
the future of climate and weather prediction, Q. J. Roy.
Meteor. Soc., 138, 841–861, https://doi.org/10.1002/qj.1923, 2012. a
Peings, Y.: Ural Blocking as a Driver of Early-Winter Stratospheric Warmings,
Geophys. Res. Lett., 46, 5460–5468,
https://doi.org/10.1029/2019GL082097, 2019. a
Peings, Y. and Magnusdottir, G.: Response of the Wintertime Northern Hemisphere
Atmospheric Circulation to Current and Projected Arctic Sea Ice Decline: A
Numerical Study with CAM5, J. Climate, 27, 244–264,
https://doi.org/10.1175/JCLI-D-13-00272.1, 2014. a
Sanchez, C., Williams, K. D., and Collins, M.: Improved stochastic physics
schemes for global weather and climate models, Q. J. Roy.
Meteor. Soc., 142, 147–159, https://doi.org/10.1002/qj.2640,
2016. a
Scaife, A. A. and Smith, D.: A signal-to-noise paradox in climate science, npj
Climate and Atmospheric Science, 1, 28, https://doi.org/10.1038/s41612-018-0038-4, 2018. a
Screen, J. A., Deser, C., Smith, D. M., Zhang, X., Blackport, R., Kushner,
P. J., Oudar, T., McCusker, K. E., and Sun, L.: Consistency and discrepancy
in the atmospheric response to Arctic sea-ice loss across climate models,
Nat. Geosci., 11, 155–163, 2018. a
Shepherd, T. G.: Atmospheric circulation as a source of uncertainty in climate
change projections, Nat. Geosci., 7, 703–708, https://doi.org/10.1038/ngeo2253,
2014. a
Siegert, S., Stephenson, D. B., Sansom, P. G., Scaife, A. A., Eade, R., and
Arribas, A.: A Bayesian framework for verification and recalibration of
ensemble forecasts: How uncertain is NAO predictability?, J.
Climate, 29, 995–1012, https://doi.org/10.1175/JCLI-D-15-0196.1, 2016. a
Siew, P. Y. F., Li, C., Sobolowski, S. P., and King, M. P.: Intermittency of Arctic–mid-latitude teleconnections: stratospheric pathway between autumn sea ice and the winter North Atlantic Oscillation, Weather Clim. Dynam., 1, 261–275, https://doi.org/10.5194/wcd-1-261-2020, 2020. a
Siew, P. Y. F., Li, C., Ting, M., Sobolowski, S. P., Wu, Y., and Chen, X.:
North Atlantic Oscillation in winter is largely insensitive to autumn
Barents-Kara sea ice variability, Science Advances, 7, eabg4893,
https://doi.org/10.1126/sciadv.abg4893, 2021. a, b, c, d
Stroeve, J. and Notz, D.: Changing state of Arctic sea ice across all seasons, Environ. Res. Lett., 13, 103001,
https://doi.org/10.1088/1748-9326/aade56, 2018. a
Strommen, K.: PRIMAVERA_UOXF_Stochastic_Experiments, Zenodo [data set], https://doi.org/10.5281/zenodo.5256102, 2021. a
Strommen, K. and Palmer, T. N.: Signal and noise in regime systems: A
hypothesis on the predictability of the North Atlantic Oscillation, Q.
J. Roy. Meteor. Soc., 145, 147–163,
https://doi.org/10.1002/qj.3414, 2019. a, b
Strommen, K., Christensen, H. M., Berner, J., and Palmer, T. N.: The impact of
stochastic parametrisations on the representation of the Asian summer
monsoon, Clim. Dynam., 50, 2269–2282, https://doi.org/10.1007/s00382-017-3749-z, 2017. a, b
Strommen, K., Christensen, H. M., MacLeod, D., Juricke, S., and Palmer, T. N.: Progress towards a probabilistic Earth system model: examining the impact of stochasticity in the atmosphere and land component of EC-Earth v3.2, Geosci. Model Dev., 12, 3099–3118, https://doi.org/10.5194/gmd-12-3099-2019, 2019. a, b, c
Strong, C. and Magnusdottir, G.: The Role of Rossby Wave Breaking in Shaping
the Equilibrium Atmospheric Circulation Response to North Atlantic Boundary
Forcing, J. Climate, 23, 1269–1276, https://doi.org/10.1175/2009JCLI2676.1,
2010.
a
Sun, L., Deser, C., and Tomas, R. A.: Mechanisms of Stratospheric and
Tropospheric Circulation Response to Projected Arctic Sea Ice Loss, J. Climate, 28, 7824–7845, https://doi.org/10.1175/JCLI-D-15-0169.1, 2015. a
Vancoppenolle, M., Bouillon, S., Fichefet, T., Goosse, H., Lecomte, O., Morales Maqueda, M. A., and Madec, G.: The Louvain-la-Neuve sea ice model, Notes du pole de modélisation, Institut Pierre-Simon Laplace (IPSL), Paris, France, no. 31, ISSN No 1288-1619, 2012. a
Vidale, P. L., Hodges, K., Vannière, B., Davini, P., Roberts, M. J., Strommen,
K., Weisheimer, A., Plesca, E., and Corti, S.: Impact of Stochastic Physics
and Model Resolution on the Simulation of Tropical Cyclones in Climate GCMs,
J. Climate, 34, 4315–4341, https://doi.org/10.1175/JCLI-D-20-0507.1, 2021. a
Vinje, T.: Anomalies and Trends of Sea-Ice Extent and Atmospheric Circulation
in the Nordic Seas during the Period 1864–1998, J. Climate, 14, 255–267, https://doi.org/10.1175/1520-0442(2001)014<0255:AATOSI>2.0.CO;2, 2001. a
von Storch, J.-S.: Signatures of Air–Sea Interactions in a Coupled
Atmosphere–Ocean GCM, J. Climate, 13, 3361–3379,
https://doi.org/10.1175/1520-0442(2000)013<3361:SOASII>2.0.CO;2, 2000. a
Wang, C., Zhang, L., Lee, S.-K., Wu, L., and Mechoso, C. R.: A global
perspective on CMIP5 climate model biases, Nat. Clim. Change, 4,
201–205, 2014. a
Wang, L., Ting, M., and Kushner, P. J.: A robust empirical seasonal prediction
of winter NAO and surface climate, Scientific Reports, 7, 279,
https://doi.org/10.1038/s41598-017-00353-y, 2017. a, b
Warner, J. L., Screen, J. A., and Scaife, A. A.: 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, 2020. a
Watson, P. A. G., Berner, J., Corti, S., Davini, P., von Hardenberg, J.,
Sanchez, C., Weisheimer, A., and Palmer, T. N.: The impact of stochastic
physics on tropical rainfall variability in global climate models on daily to
weekly timescales, J. Geophys. Res.-Atmos., 122,
5738–5762, https://doi.org/10.1002/2016JD026386, 2017. a
Woollings, T., Hannachi, A., and Hoskins, B.: Variability of the North
Atlantic eddy-driven jet stream, Q. J. Roy.
Meteor. Soc., 136, 856–868, https://doi.org/10.1002/qj.625, 2010. a
Short summary
Observational data suggest that the extent of Arctic sea ice influences mid-latitude winter weather. However, climate models generally fail to reproduce this link, making it unclear if models are missing something or if the observed link is just a coincidence. We show that if one explicitly represents the effect of unresolved sea ice variability in a climate model, then it is able to reproduce this link. This implies that the link may be real but that many models simply fail to simulate it.
Observational data suggest that the extent of Arctic sea ice influences mid-latitude winter...
