Articles | Volume 20, issue 8
https://doi.org/10.5194/tc-20-4585-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-4585-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Aug 2026
Research article |
| 20 Aug 2026
| 20 Aug 2026
Relationships between Arctic sea-ice concentration, temperature, and specific humidity in the lower troposphere during 1980–2021
Tereza Uhlíková
CORRESPONDING AUTHOR
Finnish Meteorological Institute, 00101 Helsinki, Finland
Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
Timo Vihma
Finnish Meteorological Institute, 00101 Helsinki, Finland
Alexey Yu Karpechko
Finnish Meteorological Institute, 00101 Helsinki, Finland
Petteri Uotila
Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
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Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Adam A. Scaife, Mark P. Baldwin, Amy H. Butler, Andrew J. Charlton-Perez, Daniela I. V. Domeisen, Chaim I. Garfinkel, Steven C. Hardiman, Peter Haynes, Alexey Yu Karpechko, Eun-Pa Lim, Shunsuke Noguchi, Judith Perlwitz, Lorenzo Polvani, Jadwiga H. Richter, John Scinocca, Michael Sigmond, Theodore G. Shepherd, Seok-Woo Son, and David W. J. Thompson
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Great progress has been made in computer modelling and simulation of the whole climate system, including the stratosphere. Since the late 20th century we also gained a much clearer understanding of how the stratosphere interacts with the lower atmosphere. The latest generation of numerical prediction systems now explicitly represents the stratosphere and its interaction with surface climate, and here we review its role in long-range predictions and projections from weeks to decades ahead.
Yu Yan, Wei Gu, Andrea M. U. Gierisch, Yingjun Xu, and Petteri Uotila
Geosci. Model Dev., 15, 1269–1288, https://doi.org/10.5194/gmd-15-1269-2022, https://doi.org/10.5194/gmd-15-1269-2022, 2022
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Tropical Pacific sea surface temperatures (El Niño) affect the global climate. The Pacific-to-Europe connection relies on interactions of large atmospheric waves with winds and surface pressure. We looked at how mean errors in a climate model affect its ability to simulate the Pacific-to-Europe connection. We found that even large errors in the seasonal winds did not affect the response of the model to an El Niño event, which is good news for seasonal forecasts which rely on these connections.
Cited articles
Andreas, E. L.: A theory for the scalar roughness and scalar transfer coefficients over snow and ice, Bound.-Lay. Meteorol., 38, 159–184, 1987. a
Andreas, E. L. and Cash, B. A.: Convective heat transfer over wintertime leads and polynyas, J. Geophys. Res., 104, 25721–25734, https://doi.org/10.1029/1999JC900241, 1999. a
Andreas, E. L., Paulson, C. A., William, R. M., Lindsay, R. W., and Businger, J. A.: The turbulent heat flux from Arctic leads, Bound.-Lay. Meteorol., 17, 57–91, https://doi.org/10.1007/BF00121937, 1979. a
Andreas, E. L., Guest, P. S., Persson, P. O. G., Fairall, C. W., Horst, T. W., Moritz, R. E., and Semmer, S. R.: Near-surface water vapor over polar sea ice is always near saturation, J. Geophys. Res.-Oceans, 107, 8033, https://doi.org/10.1029/2000JC000411, 2002. a
Årthun, M., Eldevik, T., Smedsrud, L. H., Skagseth, Ã., and Ingvaldsen, R. B.: Quantifying the Influence of Atlantic Heat on Barents Sea Ice Variability and Retreat, J. Climate, 25, 4736–4743, https://doi.org/10.1175/JCLI-D-11-00466.1, 2012. a
Aue, L., Vihma, T., Uotila, P., and Rinke, A.: New Insights into Cyclone Impacts on Sea Ice in the Atlantic Sector of the Arctic Ocean in Winter, Geophys. Res. Lett., 49, e2022GL100051, https://doi.org/10.1029/2022GL100051, 2022. a
Bange, J., Beyrich, F., and Engelbart, D.: Airborne measurements of turbulent fluxes during LITFASS-98: Comparison with ground measurements and remote sensing in a case study, Theor. Appl. Climatol., 73, 35–51, https://doi.org/10.1007/s00704-002-0692-6, 2002. a
Batrak, Y. and Müller, M.: On the Warm Bias in Atmospheric Reanalyses Induced by the Missing Snow over Arctic Sea-Ice, Nat. Commun., 10, 4170, https://doi.org/10.1038/s41467-019-11975-3, 2019. a
Boggs, P. T., Donaldson, J. T., Schnabel, R. B., and Spiegelman, C. H.: A Computational Examination of Orthogonal Distance Regression, J. Econometrics, 38, 169–201, https://doi.org/10.1016/0304-4076(88)90032-2, 1988. a
Boisvert, L. N. and Stroeve, J. C.: The Arctic Is Becoming Warmer and Wetter as Revealed by the Atmospheric Infrared Sounder, Geophys. Res. Lett., 42, 4439–4446, https://doi.org/10.1002/2015GL063775, 2015. a
Boisvert, L. N., Wu, D. L., and Shie, C.-L.: Increasing Evaporation Amounts Seen in the Arctic Between 2003 and 2013 from AIRS Data, J. Geophys. Res.-Atmos., 120, 6865–6881, https://doi.org/10.1002/2015JD023258, 2015. a
Boisvert, L. N., Parker, C., and Valkonen, E.: A Warmer and Wetter Arctic: Insights From a 20-Year AIRS Record, J. Geophys. Res.-Atmos., 128, e2023JD038793, https://doi.org/10.1029/2023JD038793, 2023. a
Brümmer, B. and Thiemann, S.: The atmospheric boundary layer in an Arctic wintertime on-ice flow, Bound.-Lay. Meteorol., 104, 53–72, 2002. a
Buck, A. L.: New equations for computing vapor pressure and enhancement factor, J. Appl. Meteorol., 20, 1527–1532, https://doi.org/10.1175/1520-0450(1981)020<1527:NEFCVP>2.0.CO;2, 1981. a
Döscher, R., Vihma, T., and Maksimovich, E.: Recent advances in understanding the Arctic climate system state and change from a sea ice perspective: a review, Atmos. Chem. Phys., 14, 13571–13600, https://doi.org/10.5194/acp-14-13571-2014, 2014. a
Efstathiou, E., Eldevik, T., Årthun, M., and Lind, S.: Spatial Patterns, Mechanisms, and Predictability of Barents Sea Ice Change, J. Climate, 35, 2961–2973, https://doi.org/10.1175/JCLI-D-21-0044.1, 2022. a
Francis, J. A. and Vavrus, S. J.: Evidence linking Arctic amplification to extreme weather in mid-latitudes, Geophys. Res. Lett., 39, L06801, https://doi.org/10.1029/2012GL051000, 2012. a
Glendening, J. W. and Burk, S. D.: Turbulent transport from an Arctic lead: A large-eddy simulation, Bound.-Lay. Meteorol., 59, 315–339, https://doi.org/10.1007/BF02215457, 1992. a
Graham, R. M., Cohen, L., Ritzhaupt, N., Segger, B., Graversen, R. G., Rinke, A., Walden, V. P., Granskog, M. A., and Hudson, S. R.: Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer., J. Climate, 32, 4121–4143, https://doi.org/10.1175/JCLI-D-18-0643.1, 2019. a
Groves, D. G. and Francis, J. A.: Moisture budget of the Arctic atmosphere from TOVS satellite data., J. Geophys. Res, 107, ACL 11-1–ACL 11-21, https://doi.org/10.1029/2001JD001191, 2002. a
Gryschka, M., Gryanik, V. M., Lüpkes, C., Mostafa, Z., Sühring, M., Witha, B., and Raasch, S.: Turbulent heat exchange over polar leads revisited: A large eddy simulation study, J. Geophys. Res.-Atmos., 128, e2022JD038236, https://doi.org/10.1029/2022JD038236, 2023. a, b, c
Haapala, J., Muilwijk, M., Merkouriadi, I., Duarte, P., Fer, I., Granskog, M. A., Guemas, V., Hattermann, T., Hordoir, R., Iovino, D., Itkin, P., Pirazzini, R., Pithan, F., Polyakov, I., Rinke, A., Tedesco, L., Uotila, P., Vancoppenolle, M., Vichi, M., and Vihma, T.: Processes Driving Drift-Ice Evolution and Its Interaction with the Oceanic and Atmospheric Boundary Layers, Rev. Geophys., 64, e2024RG000874, https://doi.org/10.1029/2024RG000874, 2026. a
Hanna, E., Cropper, T. E., Hall, R. J., Cornes, R. C., and Barriendos, M.: Extended North Atlantic Oscillation and Greenland Blocking Indices 1800–2020 from New Meteorological Reanalysis, Atmosphere, 13, 436, https://doi.org/10.3390/atmos13030436, 2022. a
Holland, M. M. and Hunke, E. C.: A Review of Arctic Sea Ice Climate Predictability in Large-Scale Earth System Models, Oceanography, 35, 20–27, https://doi.org/10.5670/oceanog.2022.113, 2022. a
Huang, Y., Dong, X., Xi, B., Dolinar, E. K., Stanfield, R. E., and Qiu, S.: Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations, J. Climate, 30, 8007–8029, 2017. a
Jakobson, E., Vihma, T., Palo, T., Jakobson, L., Keernik, H., and Jaagus, J.: Validation of atmospheric reanalyses over the central Arctic Ocean, Geophys. Res. Lett., 39, L10802, https://doi.org/10.1029/2012GL051591, 2012. a
Jakobson, L., Vihma, T., and Jakobson, E.: Relationships between sea ice concentration and wind speed over the Arctic Ocean during 1979–2015, J. Climate, https://doi.org/10.1175/JCLI-D-19-0271.1, 2019. a
Jun, S. Y., Ho, C. H., Jeong, J. H., Choi, Y. S., and Kim, B. M.: Recent changes in winter Arctic clouds and their relationships with sea ice and atmospheric conditions, Tellus A, 68, https://doi.org/10.3402/tellusa.v68.29130, 2016. a
Kay, J. E., Raeder, K., Gettelman, A., and Anderson, J.: The boundary layer response to recent Arctic sea ice loss and implications for high-latitude climate feedbacks, J. Climate, 24, 428–447, 2011. a
Kim, K.-Y., Hamlington, B. D., Na, H., and Kim, J.: Mechanism of seasonal Arctic sea ice evolution and Arctic amplification, The Cryosphere, 10, 2191–2202, https://doi.org/10.5194/tc-10-2191-2016, 2016. a
Kong, B., Liu, N., Fan, L., Lin, L., Yang, L., Chen, H., Wang, Y., Zhang, Y., and Xu, Y.: Evaluation of Surface Meteorology Parameters and Heat Fluxes from CFSR and ERA5 over the Pacific Arctic Region, Q. J. Roy. Meteor. Soc., 148, 2973–2990, https://doi.org/10.1002/qj.4346, 2022. a
Kruglova, E. E. and Myslenkov, S. A.: Increased storm activity in the eastern sector of the Russian Arctic, Arctic: Ecology and Economy, 14, 522–535, https://doi.org/10.25283/2223-4594-2024-4-522-535, 2024. a
Launiainen, J. and Vihma, T.: Derivation of turbulent surface fluxes – An iterative flux-profile method allowing arbitrary observing heights, Environmental Software, 5, 113–124, https://doi.org/10.1016/0266-9838(90)90021-W, 1990. a
Liang, Y., Frankignoul, C., Kwon, Y.-O., Gastineau, G., Manzini, E., Danabasoglu, G., Suo, L., Yeager, S., Gao, Y., Attema, J. J., Cherchi, A., Ghosh, R., Matei, D., Mecking, J. V., and Tian, T., and Zhang, Y.: Impacts of Arctic Sea Ice on Cold Season Atmospheric Variability and Trends Estimated from Observations and a Multi-Model Large Ensemble, J. Climate, 34, 8419–8443, https://doi.org/10.1175/JCLI-D-20-0578.1, 2021. a
Lindsay, R., Wensnahan, M., Schweiger, A., and Zhang, J.: Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic, J. Climate, 27, 2588–2606, https://doi.org/10.1175/JCLI-D-13-00014.1, 2014. a
Lüpkes, C., Vihma, T., Birnbaum, G., and Wacker, U.: Influence of leads in sea ice on the temperature of the atmospheric boundary layer during polar night, Geophys. Res. Lett., 35, L03805, https://doi.org/10.1029/2007GL032461, 2008. a, b
Lüpkes, C., Vihma, T., Jakobson, E., König-Langlo, G., and Tetzlaff, A.: Meteorological observations from ship cruises during summer to the central Arctic: A comparison with reanalysis data, Geophys. Res. Lett., 37, L09810, https://doi.org/10.1029/2010GL042724, 2010. a
Lüpkes, C., Vihma, T., Birnbaum, G., Dierer, S., Garbrecht, T., Gryanik, V. M., Gryschka, M., Hartmann, J., Heinemann, G., Kaleschke, L., Raasch, S., Savijärvi, H., Schlünzen K. H., and Wacker, U.: Mesoscale modelling of the Arctic atmospheric boundary layer and its interaction with sea ice, in: Arctic Climate Change – The ACSYS Decade and Beyond, edited by: Lemke, P. and Jacobi, H.-W., vol. 43 of Atmospheric and Oceanographic Sciences Library, Springer, https://doi.org/10.1007/978-94-007-2027-5, 2012. a
Michaelis, J., Lüpkes, C., Schmitt, A. U., and Hartmann, J.: Modelling and parametrization of the convective flow over leads in sea ice and comparison with airborne observations, Q. J. Roy. Meteor. Soc., 147, 914–943, https://doi.org/10.1002/qj.3953, 2021. a
Michaelis, J., Schmitt, A. U., Lüpkes, C., Hartmann, J., Birnbaum, G., and Vihma, T.: Observations of marine cold-air outbreaks: a comprehensive data set of airborne and dropsonde measurements from the Springtime Atmospheric Boundary Layer Experiment (STABLE), Earth Syst. Sci. Data, 14, 1621–1637, https://doi.org/10.5194/essd-14-1621-2022, 2022. a, b
Mioduszewski, J., Vavrus, S., and Wang, M.: Diminishing Arctic sea ice promotes stronger surface winds, J. Climate, 31, 8101–8119, https://doi.org/10.1175/JCLI-D-18-0109.1, 2018. a
Naakka, T., Nygård, T., Vihma, T., Sedlar, J., and Graversen, R.: Atmospheric moisture transport between mid-latitudes and the Arctic: Regional, seasonal and vertical distributions, Int. J. Climatol., 39, 2862–2879, https://doi.org/10.1002/joc.5988, 2019. a, b
Naakka, T., Köhler, D., Nordling, K., Räisänen, P., Lund, M. T., Makkonen, R., Merikanto, J., Samset, B. H., Sinclair, V. A., Thomas, J. L., and Ekman, A. M. L.: Polar winter climate change: strong local effects from sea ice loss, widespread consequences from warming seas, Atmos. Chem. Phys., 25, 8127–8145, https://doi.org/10.5194/acp-25-8127-2025, 2025. a
Onarheim, I. H., Eldevik, T., Smedsrud, L. H., and Stroeve, J. C.: Seasonal and Regional Manifestation of Arctic Sea Ice Loss, J. Climate, 31, 4917–4932, https://doi.org/10.1175/JCLI-D-17-0427.1, 2018. a, b
Parker, C. L., Mooney, P. A., Webster, M. A., and Boisvert, L. N.: The Influence of Recent and Future Climate Change on Spring Arctic Cyclones, Nat. Commun., 13, 6514, https://doi.org/10.1038/s41467-022-34126-7, 2022. a
Persson, P. O. G., Fairall, C. W., Andreas, E. L., Guest, P. S., and Perovich, D. K.: Measurements near the Atmospheric Surface Flux Group tower at SHEBA: Near-surface conditions and surface energy budget, J. Geophys. Res., 107, 8045, https://doi.org/10.1029/2000JC000705, 2002. a, b
Petoukhov, V. and Semenov, V. A.: A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents, J. Geophys. Research, 115, D21111, https://doi.org/10.1029/2009JD013568, 2010. a
Pinto, J. O., Alam, A., Maslanik, J. A., Curry, J. A., and Stone, R. S.: Surface characteristics and atmospheric footprint of springtime Arctic leads at SHEBA, J. Geophys. Res.-Oceans, 108, 8051, https://doi.org/10.1029/2000JC000473, 2003. a
Raddatz, R. L., Galley, R. J., Candlish, L. M., Asplin, M. G., and Barber, D. G.: Integral Profile Estimates of Sensible Heat Flux from an Unconsolidated Sea-Ice Surface, Atmos. Ocean, 51, 135–144, https://doi.org/10.1080/07055900.2012.759900, 2013. a
Rinke, A., Maslowski, W., Dethloff, K., and Clement, J.: Influence of Sea Ice on the Atmosphere: A Study with an Arctic Atmospheric Regional Climate Model, J. Geophys. Res.-Atmos., 111, D16103, https://doi.org/10.1029/2005JD006957, 2006. a
Ruffieux, D., Persson, P. O. G., Fairall, C. W., and Wolfe, D. E.: Ice pack and lead surface energy budgets during LEADEX 1992, J. Geophys. Res.-Oceans, 100, 4593–4612, https://doi.org/10.1029/94JC02425, 1995. a
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R., Gayno, G., Wang, J., Hou, Y.-T., Chuang, H.-Y., Juang, H.-M. H., Sela, J., Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., van den Dool, H., Kumar, A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K., Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.-Z., Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and Goldberg, M.: NCEP Climate Forecast System Reanalysis (CFSR) 6-hourly Products, January 1979 to December 2010, NSF National Center for Atmospheric Research [data set], https://doi.org/10.5065/D69K487J, 2010. a, b
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., Tripp, P., Kistler, R., Woollen, J., Behringer, D., Liu, H., Stokes, D., Grumbine, R., Gayno, G., Wang, J., Hou, Y.-T., Chuang, H.-Y., Juang, H.-M. H., Sela, J., Iredell, M., Treadon, R., Kleist, D., Van Delst, P., Keyser, D., Derber, J., Ek, M., Meng, J., Wei, H., Yang, R., Lord, S., van den Dool, H., Kumar, A., Wang, W., Long, C., Chelliah, M., Xue, Y., Huang, B., Schemm, J.-K., Ebisuzaki, W., Lin, R., Xie, P., Chen, M., Zhou, S., Higgins, W., Zou, C.-Z., Liu, Q., Chen, Y., Han, Y., Cucurull, L., Reynolds, R. W., Rutledge, G., and Goldberg, M.: NCEP Climate Forecast System Version 2 (CFSv2) 6-hourly Products, NSF National Center for Atmospheric Research [data set], https://doi.org/10.5065/D69K487J, 2011. a, b
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D., Hou, Y.-T., ya Chuang, H., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M. P., van den Dool, H., Zhang, Q., Wang, W., Chen, M., and Becker, E.: The NCEP Climate Forecast System Version 2, J. Climate, 27, 2185–2208, https://journals.ametsoc.org/view/journals/clim/27/6/jcli-d-12-00823.1.xml (last access: 1 August 2025), 2014. a
Schmitt, A. U. and Lüpkes, C.: Attributing near-surface atmospheric trends in the Fram Strait region to regional sea ice conditions, The Cryosphere, 17, 3115–3136, https://doi.org/10.5194/tc-17-3115-2023, 2023. a
Schnell, R., Barry, R., Miles, M., Andreas, E. L., Radke, L. F., Brock, C. A., McCormick, M. P., and Moore, J. L.: Lidar detection of leads in Arctic sea ice, Nature, 339, 530–532, https://doi.org/10.1038/339530a0, 1989. a
Screen, J. A. and Simmonds, I.: The central role of diminishing sea ice in recent Arctic temperature amplification, Nature, 464, 1334–1337, https://doi.org/10.1038/nature09051, 2010. a
Screen, J. A. and Simmonds, I.: Exploring links between Arctic amplification and mid-latitude weather, Geophys. Res. Lett., 40, 959–964, https://doi.org/10.1002/grl.50174, 2013. a, b
Sedlar, J., Shupe, M. D., and Tjernström, M.: On the Relationship between Thermodynamic Structure and Cloud Top, and Its Climate Significance in the Arctic, J. Climate, 25, 2374–2393, https://doi.org/10.1175/JCLI-D-11-00186.1, 2012. a
Serreze, M. C. and Barry, R. G.: Processes and Impacts of Arctic Amplification: A Research Synthesis, Global Planet. Change, 77, 85–96, https://doi.org/10.1016/j.gloplacha.2011.03.004, 2011. a
Serreze, M. C., Maslanik, J. A., Rehder, M. C., Schnell, R. C., Kahl, J. D., and Andreas, E. L.: Theoretical heights of buoyant convection above open leads in the winter Arctic pack ice cover, J. Geophys. Res., 97, 9411–9422, 1992. a
Steele, M., Ermold, W., and Zhang, J.: Arctic Ocean Surface Warming Trends over the Past 100 Years, Geophys. Res. Lett., 35, L02614, https://doi.org/10.1029/2007GL031651, 2008. a
Tastula, E.-M., Vihma, T., Andreas, E. L., and Galperin, B.: Validation of the diurnal cycles in atmospheric reanalyses over Antarctic sea ice, J. Geophys. Res.-Atmos., 118, 4194–4204, https://doi.org/10.1002/jgrd.50336, 2013. a
Taylor, P. C., Hegyi, B. M., Boeke, R. C., and Boisvert, L. N.: On the Increasing Importance of Air–Sea Exchanges in a Thawing Arctic: A Review, Atmosphere, 9, 41, https://doi.org/10.3390/atmos9020041, 2018. a
Tetzlaff, A., Kaleschke, L., Lüpkes, C., Ament, F., and Vihma, T.: The impact of heterogeneous surface temperatures on the 2-m air temperature over the Arctic Ocean under clear skies in spring, The Cryosphere, 7, 153–166, https://doi.org/10.5194/tc-7-153-2013, 2013. a
Uhlíková, T., Vihma, T., Karpechko, A. Y., and Uotila, P.: Effects of Arctic sea-ice concentration on surface radiative fluxes in four atmospheric reanalyses, The Cryosphere, 19, 1031–1046, https://doi.org/10.5194/tc-19-1031-2025, 2025. a, b
Uotila, P., Uhlíková, T., and Vihma, T.: Codes used to create figures and tables in article 'Relationships between Arctic sea-ice concentration, temperature, and specific humidity in the lower troposphere during 1980–2021', Zenodo [software], https://doi.org/10.5281/zenodo.17165083, 2025. a
Valkonen, E., Cassano, J. J., and Cassano, E. N.: Arctic Cyclones and Their Interactions with the Declining Sea Ice: A Recent Climatology, J. Geophys. Res.-Atmos., 126, e2020JD034366, https://doi.org/10.1029/2020JD034366, 2021. a
Valkonen, T., Vihma, T., and Doble, M.: Mesoscale modelling of the atmospheric boundary layer over the Antarctic sea ice: a late autumn case study, Mon. Weather Rev., 136, 1457–1474, https://doi.org/10.1175/2007MWR2232.1, 2008. a, b
Vihma, T.: Subgrid parameterization of surface heat and momentum fluxes over polar oceans, J. Geophys. Res., 100, https://doi.org/10.1029/95JC02498, 1995. a
Vihma, T.: Effects of Arctic Sea Ice Decline on Weather and Climate: A Review, Surv. Geophys., 35, 1175–1214, https://doi.org/10.1007/s10712-014-9284-0, 2014. a
Vihma, T. and Pirazzini, R.: On the factors controlling the snow surface and 2-m air temperatures over the Arctic sea ice in winter, Bound.-Lay. Meteorol., 117, 73–90, 2005. a
Walsh, J. E. and Chapman, W. L.: Arctic Cloud–Radiation–Temperature Associations in Observational Data and Atmospheric Re-analyses, J. Climate, 11, 3030–3045, https://doi.org/10.1175/1520-0442(1998)011<3030:ACRTAI>2.0.CO;2, 1998. a, b
Wang, S., Wang, Q., Wang, M., Lohmann, G., and Qiao, F.: Arctic Ocean freshwater in CMIP6 coupled models, Earth's Future, 10, e2022EF002878, https://doi.org/10.1029/2022EF002878, 2022. a
Weinbrecht, S. and Raasch, S.: High-resolution simulations of the turbulent flow in the vicinity of an Arctic lead, J. Geophys. Res., 106, 27035–270046, 2001. a
Wickström, S., Jonassen, M., Vihma, T., and Uotila, P.: Trends in cyclones in the high latitude North Atlantic during 1979-2016., Q. J. Roy. Meteor. Soc., 146, 762–779, https://doi.org/10.1002/qj.3707, 2020. a
Wilks, D. S.: “The Stippling Shows Statistically Significant Grid Points”: How Research Results are Routinely Overstated and Overinterpreted, and What to Do about It, B. Am. Meteorol. Soc., 97, 2263–2273, https://doi.org/10.1175/BAMS-D-15-00267.1, 2016. a
Yu, H., Screen, J. A., Xu, M., Hay, S., and Catto, J. L.: Comparing the Atmospheric Responses to Reduced Arctic Sea Ice, a Warmer Ocean, and Increased CO2 and Their Contributions to Projected Change at 2 °C Global Warming, J. Climate, 37, 6367–6380, https://doi.org/10.1175/JCLI-D-24-0104.1, 2024. a
Zampieri, L., Arduini, G., Holland, M., Keeley, S. P. E., Mogensen, K., Shupe, M. D., and Tietsche, S.: A Machine Learning Correction Model of the Winter Clear-Sky Temperature Bias over the Arctic Sea Ice in Atmospheric Reanalyses, Mon. Weather Rev., 151, 1443–1458, https://doi.org/10.1175/MWR-D-22-0130.1, 2023. a
Zhang, X., Tang, H., Zhang, J., Walsh, J. E., Roesler, E. L., Hillman, B., Ballinger, T. J., and Weijer, W.: Arctic cyclones have become more intense and longer-lived over the past seven decades, Communications Earth & Environment, 4, 348, https://doi.org/10.1038/s43247-023-01003-0, 2023. a
Zulauf, M. A. and Krueger, S. K.: Two-dimensional cloud-resolving modelling of the atmospheric effects of Arctic leads based upon midwinter conditions at the surface heat budget of the Arctic Ocean ice camp, J. Geophys. Res., 108, https://doi.org/10.1029/2002JD002643, 2003. a
Short summary
Understanding of the local effects of sea-ice concentration variations on the Arctic atmosphere is a prerequisite for assessing the role of Arctic sea-ice decline in the climate system, including its influence on mid-latitudes. In our study, using data from atmospheric reanalysis, we present how the relationships of sea-ice concentration, temperature, and specific humidity and their direction change depending on region and season over the Arctic.
Understanding of the local effects of sea-ice concentration variations on the Arctic atmosphere...
