Articles | Volume 6, issue 4
https://doi.org/10.5194/wcd-6-1831-2025
© Author(s) 2025. 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-6-1831-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A climatology of atmospheric rivers over Scandinavia and associated precipitation
Erik Holmgren
Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Sweden
Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Sweden
Related authors
Lizz Ultee, Finn Wimberly, Sloan Coats, Jonathan Mackay, and Erik Holmgren
The Cryosphere, 20, 1339–1361, https://doi.org/10.5194/tc-20-1339-2026, https://doi.org/10.5194/tc-20-1339-2026, 2026
Short summary
Short summary
Runoff from glaciers can be an important water source in mountain regions. Global climate models used to understand future changes in the water cycle do not include glacier changes. We simulated glacier change in all available glacier models using information from global climate models as input. We found that for analysis of future drought, it is more important to understand the climate input than to use all available glacier models together.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary
Short summary
Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
Lloyd Villanueva, Hans W. Chen, Gabriella Wallentin, and Luisa Ickes
EGUsphere, https://doi.org/10.5194/egusphere-2026-6039, https://doi.org/10.5194/egusphere-2026-6039, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
In the Arctic winter, clouds act like a blanket that slows the loss of heat from the ground. Clouds often stack in layers, but the cause is not well known. Using weather balloon and radar data from Svalbard, we found that warm, moist air from the south brings stacked clouds twice as often as cold northern air. In cold air, stacked clouds keep the ground warmer than single clouds, but in warm air layering makes no clear difference. This could help climate models represent Arctic clouds better.
Ziqian Zhong, Hans Chen, Fuxiao Jiang, and Luyao Liu
EGUsphere, https://doi.org/10.5194/egusphere-2026-5126, https://doi.org/10.5194/egusphere-2026-5126, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
European forests are increasingly exposed to drier air and stronger sunlight, but their combined effect on carbon uptake is uncertain. Using measurements from European forest sites, we found that strong sunlight makes forests more sensitive to dry air, with leaf pores closing more strongly and photosynthesis declining. This interaction could weaken forests' ability to remove carbon dioxide from the atmosphere, so climate projections should consider both changes together.
Lizz Ultee, Finn Wimberly, Sloan Coats, Jonathan Mackay, and Erik Holmgren
The Cryosphere, 20, 1339–1361, https://doi.org/10.5194/tc-20-1339-2026, https://doi.org/10.5194/tc-20-1339-2026, 2026
Short summary
Short summary
Runoff from glaciers can be an important water source in mountain regions. Global climate models used to understand future changes in the water cycle do not include glacier changes. We simulated glacier change in all available glacier models using information from global climate models as input. We found that for analysis of future drought, it is more important to understand the climate input than to use all available glacier models together.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary
Short summary
Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
Cited articles
Allison, B., Marquardt Collow C. A., Guan, B., Kim, S., Manuel Lora, J., McClenny, E., Nardi, K., Payne, A. E., Reid, K., Shearer, E. J., Tome, R., Wille, J. D., Ramos, A. M., Gorodetskaya, I. V., Leung, L. R., O'Brien, T. A., Ralph, F. M., Rutz, J. J., Ullrich, P. A., and Wehner, M. F.: Atmospheric River Tracking Method Intercomparison Project Tier 2 Reanalysis Source Data and Catalogues, NSF National Center for Atmospheric Research [data set], https://doi.org/10.26024/rawv-yx53, last access: 11 December, 2025. a
Arabzadeh, A., Ehsani, M. R., Guan, B., Heflin, S., and Behrangi, A.: Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products, J. Geophys. Res.-Atmos., 125, e2020JD033021, https://doi.org/10.1029/2020JD033021, 2020. a
Bahmani, B., Moseley, B., Vattani, A., Kumar, R., and Vassilvitskii, S.: Scalable K-Means++, arXiv [preprint], https://doi.org/10.48550/arXiv.1203.6402, 29 March 2012. a
Bao, J.-W., Michelson, S. A., Neiman, P. J., Ralph, F. M., and Wilczak, J. M.: Interpretation of Enhanced Integrated Water Vapor Bands Associated with Extratropical Cyclones: Their Formation and Connection to Tropical Moisture, Mon. Weather Rev., 134, 1063–1080, https://doi.org/10.1175/MWR3123.1, 2006. a
Collow, A. B. M., Shields, C. A., Guan, B., Kim, S., Lora, J. M., McClenny, E. E., Nardi, K., Payne, A., Reid, K., Shearer, E. J., Tomé, R., Wille, J. D., Ramos, A. M., Gorodetskaya, I. V., Leung, L. R., O'Brien, T. A., Ralph, F. M., Rutz, J., Ullrich, P. A., and Wehner, M.: An Overview of ARTMIP's Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and Their Associated Precipitation, J. Geophys. Res.-Atmos., 127, e2021JD036, https://doi.org/10.1029/2021JD036155, 2022. a, b
Copernicus Climate Change Service: CDS, Copernicus Climate Change Service [data set], https://cds.climate.copernicus.eu, last access: 11 November 2025. a
Dettinger, M. D.: Atmospheric Rivers as Drought Busters on the U.S. West Coast, J. Hydrometeorol., 14, 1721–1732, https://doi.org/10.1175/JHM-D-13-02.1, 2013. a
Dettinger, M. D., Ralph, F. M., Das, T., Neiman, P. J., and Cayan, D. R.: Atmospheric Rivers, Floods and the Water Resources of California, Water, 3, 445–478, https://doi.org/10.3390/w3020445, 2011. a
Deza, M. M. and Deza, E.: Encyclopedia of Distances, Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-662-52844-0, ISBN 978-3-662-52843-3, 978-3-662-52844-0, 2016. a
Gimeno, L., Nieto, R., Vázquez, M., and Lavers, D. A.: Atmospheric Rivers: A Mini-Review, Frontiers in Earth Science, 2, https://doi.org/10.3389/feart.2014.00002, 2014. a
Guan, B. and Waliser, D. E.: Detection of Atmospheric Rivers: Evaluation and Application of an Algorithm for Global Studies: Detection of Atmospheric Rivers, J. Geophys. Res.-Atmos., 120, 12514–12535, https://doi.org/10.1002/2015JD024257, 2015. a, b
Guan, B. and Waliser, D. E.: Atmospheric Rivers in 20 Year Weather and Climate Simulations: A Multimodel, Global Evaluation, J. Geophys. Res.-Atmos., 122, 5556–5581, https://doi.org/10.1002/2016JD026174, 2017. a
Hagos, S. M., Leung, L. R., Yoon, J.-H., Lu, J., and Gao, Y.: A Projection of Changes in Landfalling Atmospheric River Frequency and Extreme Precipitation over Western North America from the Large Ensemble CESM Simulations, Geophys. Res. Lett., 43, 1357–1363, 2016. 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
Holmgren, E.: Holmgren825/ARs_Scandinavia: v1.0 (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.17856929, 2025. a
Hoskins, B. J. and Hodges, K. I.: The Annual Cycle of Northern Hemisphere Storm Tracks. Part I: Seasons, J. Climate, 32, 1743–1760, https://doi.org/10.1175/JCLI-D-17-0870.1, 2019. a
Hurrell, J. W. and Deser, C.: North Atlantic Climate Variability: The Role of the North Atlantic Oscillation, J. Marine Syst., 79, 231–244, https://doi.org/10.1016/j.jmarsys.2009.11.002, 2010. a
Ionita, M., Nagavciuc, V., and Guan, B.: Rivers in the sky, flooding on the ground: the role of atmospheric rivers in inland flooding in central Europe, Hydrol. Earth Syst. Sci., 24, 5125–5147, https://doi.org/10.5194/hess-24-5125-2020, 2020. a
Kim, J., Moon, H., Guan, B., Waliser, D. E., Choi, J., Gu, T.-Y., and Byun, Y.-H.: Precipitation Characteristics Related to Atmospheric Rivers in East Asia, Int. J. Climatol., 41, E2244–E2257, 2021. a
Lavers, D. A. and Villarini, G.: The Contribution of Atmospheric Rivers to Precipitation in Europe and the United States, J. Hydrol., 522, 382–390, https://doi.org/10.1016/j.jhydrol.2014.12.010, 2015. a
Lavers, D. A., Villarini, G., Allan, R. P., Wood, E. F., and Wade, A. J.: The Detection of Atmospheric Rivers in Atmospheric Reanalyses and Their Links to British Winter Floods and the Large-scale Climatic Circulation, J. Geophys. Res.-Atmos., 117, 2012JD018027, https://doi.org/10.1029/2012JD018027, 2012. a
Lavers, D. A., Allan, R. P., Villarini, G., Lloyd-Hughes, B., Brayshaw, D. J., and Wade, A. J.: Future Changes in Atmospheric Rivers and Their Implications for Winter Flooding in Britain, Environ. Res. Lett., 8, 034010, https://doi.org/10.1088/1748-9326/8/3/034010, 2013. a
Mattingly, K. S., Mote, T. L., and Fettweis, X.: Atmospheric River Impacts on Greenland Ice Sheet Surface Mass Balance, J. Geophys. Res.-Atmos., 123, 8538–8560, https://doi.org/10.1029/2018JD028714, 2018. a
McClenny, E. E., Ullrich, P. A., and Grotjahn, R.: Sensitivity of Atmospheric River Vapor Transport and Precipitation to Uniform Sea Surface Temperature Increases, J. Geophys. Res.-Atmos., 125, e2020JD033421, https://doi.org/10.1029/2020JD033421, 2020. a, b, c
Mundhenk, B. D., Barnes, E. A., and Maloney, E. D.: All-Season Climatology and Variability of Atmospheric River Frequencies over the North Pacific, J. Climate, 29, 4885–4903, https://doi.org/10.1175/JCLI-D-15-0655.1, 2016. a
Nayak, M. A., Villarini, G., and Lavers, D. A.: On the Skill of Numerical Weather Prediction Models to Forecast Atmospheric Rivers over the Central United States, Geophys. Res. Lett., 41, 4354–4362, https://doi.org/10.1002/2014GL060299, 2014. a
NOAA Climate Prediction Center: Daily NAO Index since 1950, National Weather Service Climate Prediction Center [data set], https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml#publication (last access: 11 December 2025), 2025. a
Ralph, F. M. and Dettinger, M. D.: Storms, Floods, and the Science of Atmospheric Rivers, Eos Transactions American Geophysical Union, 92, 265–266, https://doi.org/10.1029/2011EO320001, 2011. a
Ralph, F. M., Neiman, P. J., and Wick, G. A.: Satellite and CALJET Aircraft Observations of Atmospheric Rivers over the Eastern North Pacific Ocean during the Winter of 1997/98, Mon. Weather Rev., 132, 1721–1745, https://doi.org/10.1175/1520-0493(2004)132<1721:SACAOO>2.0.CO;2, 2004. a, b
Ralph, F. M., Neiman, P. J., and Rotunno, R.: Dropsonde Observations in Low-Level Jets over the Northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: Mean Vertical-Profile and Atmospheric-River Characteristics, Mon. Weather Rev., 133, 889–910, https://doi.org/10.1175/MWR2896.1, 2005. a, b
Ramos, A. M., Tomé, R., Trigo, R. M., Liberato, M. L., and Pinto, J. G.: Projected Changes in Atmospheric Rivers Affecting Europe in CMIP5 Models, Geophys. Res. Lett., 43, 9315–9323, 2016. a
Reid, K. J., King, A. D., Lane, T. P., and Short, E.: The Sensitivity of Atmospheric River Identification to Integrated Water Vapor Transport Threshold, Resolution, and Regridding Method, J. Geophys. Res.-Atmos., 125, e2020JD032897, https://doi.org/10.1029/2020JD032897, 2020. a
Rhoades, A. M., Jones, A. D., O'Brien, T. A., O'Brien, J. P., Ullrich, P. A., and Zarzycki, C. M.: Influences of North Pacific Ocean Domain Extent on the Western U.S. Winter Hydroclimatology in Variable-Resolution CESM, J. Geophys. Res.-Atmos., 125, e2019JD031977, https://doi.org/10.1029/2019JD031977, 2020. a
Roe, G. H.: Orographic Precipitation, Annu. Rev. Earth Pl. Sc., 33, 645–671, https://doi.org/10.1146/annurev.earth.33.092203.122541, 2005. a
Rutz, J. J. and Steenburgh, W. J.: Quantifying the Role of Atmospheric Rivers in the Interior Western United States, Atmos. Sci. Lett., 13, 257–261, https://doi.org/10.1002/asl.392, 2012. a
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: Climatological Characteristics of Atmospheric Rivers and Their Inland Penetration over the Western United States, Mon. Weather Rev., 142, 905–921, https://doi.org/10.1175/MWR-D-13-00168.1, 2014. a, b
Rutz, J. J., Shields, C. A., Lora, J. M., Payne, A. E., Guan, B., Ullrich, P., O'Brien, T., Leung, L. R., Ralph, F. M., Wehner, M., Brands, S., Collow, A., Goldenson, N., Gorodetskaya, I., Griffith, H., Kashinath, K., Kawzenuk, B., Krishnan, H., Kurlin, V., Lavers, D., Magnusdottir, G., Mahoney, K., McClenny, E., Muszynski, G., Nguyen, P. D., Mr. Prabhat, Qian, Y., Ramos, A. M., Sarangi, C., Sellars, S., Shulgina, T., Tome, R., Waliser, D., Walton, D., Wick, G., Wilson, A. M., and Viale, M.: The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology, J. Geophys. Res.-Atmos., 124, 13777–13802, https://doi.org/10.1029/2019JD030936, 2019. a, b
Shields, C. A., Rutz, J. J., Leung, L.-Y., Ralph, F. M., Wehner, M., Kawzenuk, B., Lora, J. M., McClenny, E., Osborne, T., Payne, A. E., Ullrich, P., Gershunov, A., Goldenson, N., Guan, B., Qian, Y., Ramos, A. M., Sarangi, C., Sellars, S., Gorodetskaya, I., Kashinath, K., Kurlin, V., Mahoney, K., Muszynski, G., Pierce, R., Subramanian, A. C., Tome, R., Waliser, D., Walton, D., Wick, G., Wilson, A., Lavers, D., Prabhat, Collow, A., Krishnan, H., Magnusdottir, G., and Nguyen, P.: Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design, Geosci. Model Dev., 11, 2455–2474, https://doi.org/10.5194/gmd-11-2455-2018, 2018. a, b
Shields, C. A., Payne, A. E., Shearer, E. J., Wehner, M. F., O'Brien, T. A., Rutz, J. J., Leung, L. R., Ralph, F. M., Marquardt Collow, A. B., Ullrich, P. A., Dong, Q., Gershunov, A., Griffith, H., Guan, B., Lora, J. M., Lu, M., McClenny, E., Nardi, K. M., Pan, M., Qian, Y., Ramos, A. M., Shulgina, T., Viale, M., Sarangi, C., Tomé, R., and Zarzycki, C.: Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment, Geophys. Res. Lett., 50, e2022GL102091, https://doi.org/10.1029/2022GL102091, 2023. a, b
Stohl, A., Forster, C., and Sodemann, H.: Remote Sources of Water Vapor Forming Precipitation on the Norwegian West Coast at 60° N – a Tale of Hurricanes and an Atmospheric River, J. Geophys. Res.-Atmos., 113, https://doi.org/10.1029/2007JD009006, 2008. a
Ullrich, P. A. and Zarzycki, C. M.: TempestExtremes: a framework for scale-insensitive pointwise feature tracking on unstructured grids, Geosci. Model Dev., 10, 1069–1090, https://doi.org/10.5194/gmd-10-1069-2017, 2017. a
Wick, G. A., Neiman, P. J., Ralph, F. M., and Hamill, T. M.: Evaluation of Forecasts of the Water Vapor Signature of Atmospheric Rivers in Operational Numerical Weather Prediction Models, Weather Forecast., 28, 1337–1352, https://doi.org/10.1175/WAF-D-13-00025.1, 2013. a
Zhang, L., Zhao, Y., Cheng, T. F., and Lu, M.: Future Changes in Global Atmospheric Rivers Projected by CMIP6 Models, J. Geophys. Res.-Atmos., 129, e2023JD039359, https://doi.org/10.1029/2023JD039359, 2024. a
Zhou, Y., Kim, H., and Guan, B.: Life Cycle of Atmospheric Rivers: Identification and Climatological Characteristics, J. Geophys. Res.-Atmos., 123, 12715–12725, https://doi.org/10.1029/2018JD029180, 2018. a
Zhu, Y. and Newell, R. E.: A Proposed Algorithm for Moisture Fluxes from Atmospheric Rivers, Mon. Weather Rev., 126, 725–735, https://doi.org/10.1175/1520-0493(1998)126<0725:APAFMF>2.0.CO;2, 1998. a, b
Short summary
In this paper, we present a new study on atmospheric rivers (ARs) over Scandinavia and how they influence the regional precipitation. Although ARs are fairly well studied in other parts of the world, their influence on the Scandinavian climate remains less explored. Our results show that although ARs occur relatively infrequently over Scandinavia, they exert a large influence on the regional precipitation, contributing up to 40 % of the annual precipitation.
In this paper, we present a new study on atmospheric rivers (ARs) over Scandinavia and how they...