Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5239-2024
© Author(s) 2024. 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-18-5239-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Extending the Center for Western Weather and Water Extremes (CW3E) atmospheric river scale to the polar regions
Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
F. Martin Ralph
Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
Brian Kawzenuk
Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
Minghua Zheng
Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
Irina V. Gorodetskaya
CIIMAR | Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Porto, Portugal
Penny M. Rowe
NorthWest Research Associates, Redmond, WA, USA
David H. Bromwich
Polar Meteorology Group, Byrd Polar and Climate Research Center, The Ohio State University, Columbus, OH, USA
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The Antarctic Circumnavigation Expedition surveyed a large number of variables describing the dynamic state of ocean and atmosphere, freshwater cycle, atmospheric chemistry, ocean biogeochemistry, and microbiology in the Southern Ocean. To reduce the dimensionality of the dataset, we apply a sparse principal component analysis and identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and
hotspotsof interaction. Code and data are open access.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Iris Thurnherr, Katharina Hartmuth, Lukas Jansing, Josué Gehring, Maxi Boettcher, Irina Gorodetskaya, Martin Werner, Heini Wernli, and Franziska Aemisegger
Weather Clim. Dynam., 2, 331–357, https://doi.org/10.5194/wcd-2-331-2021, https://doi.org/10.5194/wcd-2-331-2021, 2021
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Extratropical cyclones are important for the transport of moisture from low to high latitudes. In this study, we investigate how the isotopic composition of water vapour is affected by horizontal temperature advection associated with extratropical cyclones using measurements and modelling. It is shown that air–sea moisture fluxes induced by this horizontal temperature advection lead to the strong variability observed in the isotopic composition of water vapour in the marine boundary layer.
Maialen Iturbide, José M. Gutiérrez, Lincoln M. Alves, Joaquín Bedia, Ruth Cerezo-Mota, Ezequiel Cimadevilla, Antonio S. Cofiño, Alejandro Di Luca, Sergio Henrique Faria, Irina V. Gorodetskaya, Mathias Hauser, Sixto Herrera, Kevin Hennessy, Helene T. Hewitt, Richard G. Jones, Svitlana Krakovska, Rodrigo Manzanas, Daniel Martínez-Castro, Gemma T. Narisma, Intan S. Nurhati, Izidine Pinto, Sonia I. Seneviratne, Bart van den Hurk, and Carolina S. Vera
Earth Syst. Sci. Data, 12, 2959–2970, https://doi.org/10.5194/essd-12-2959-2020, https://doi.org/10.5194/essd-12-2959-2020, 2020
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We present an update of the IPCC WGI reference regions used in AR5 for the synthesis of climate change information. This revision was guided by the basic principles of climatic consistency and model representativeness (in particular for the new CMIP6 simulations). We also present a new dataset of monthly CMIP5 and CMIP6 spatially aggregated information using the new reference regions and describe a worked example of how to use this dataset to inform regional climate change studies.
Cited articles
Adusumilli, S., Fish, A. M., Fricker, H. A., and Medley, B.: Atmospheric river precipitation contributed to rapid increases in surface height of the west Antarctic ice sheet in 2019, Geophys. Res. Lett., 48, e2020GL091076, https://doi.org/10.1029/2020GL091076, 2021.
Alley, R. B., Clark, P. U., Huybrechts, P., and Joughin, I.: Ice-sheet and sea-level changes, Science, 310, 456–460, https://doi.org/10.1126/science.1114613, 2005.
Antarctic Meteorological Research and Data Center: Dome C II Automatic Weather Station, 2022 quality-controlled observational data, AMRDC Data Repository [data set], https://doi.org/10.48567/x7a9-cx26, 2022.
Baiman, R., Winters, A. C., Lenaerts, J., and Shields, C. A.: Synoptic drivers of atmospheric river induced precipitation near Dronning Maud Land, Antarctica, J. Geophys. Res.-Atmos., 128, e2022JD037859, https://doi.org/10.1029/2022JD037859, 2023.
Bonne, J. L., Steen-Larsen, H. C., Risi, C., Werner, M., Sodemann, H., Lacour, J. L., Fettweis, X., Cesana, G., Delmotte, M., Cattani, O., and Vallelonga, P.: The summer 2012 Greenland heat wave: In situ and remote sensing observations of water vapor isotopic composition during an atmospheric river event, J. Geophys. Res.-Atmos., 120, 2970–2989, https://doi.org/10.1002/2014JD022602, 2015.
Box, J. E., Nielsen, K. P., Yang, X., Niwano, M., Wehrlé, A., van As, D., Fettweis, X., Køltzow, M. A., Palmason, B., Fausto, R. S., and van den Broeke, M. R.: Greenland ice sheet rainfall climatology, extremes and atmospheric river rapids, Meteorol. Appl., 30, e2134, https://doi.org/10.1002/met.2134, 2023.
Bozkurt, D., Rondanelli, R., Marín, J. C., and Garreaud, R.: Foehn event triggered by an atmospheric river underlies record-setting temperature along continental Antarctica, J. Geophys. Res.-Atmos., 123, 3871–3892, https://doi.org/10.1002/2017JD027796, 2018.
Bromwich, D. H., Gorodetskaya, I. V., Carpentier, S., et al.: Winter Targeted Observing Periods during the Year of Polar Prediction in the Southern Hemisphere (YOPP-SH), B. Am. Meteorol. Soc., 105, E1662–E1684, https://doi.org/10.1175/BAMS-D-22-0249.1, 2024.
Chang, E. K., Guo, Y., and Xia, X.: CMIP5 multimodel ensemble projection of storm track change under global warming, J. Geophys. Res.-Atmos., 117, D23118, https://doi.org/10.1029/2012JD018578, 2012.
Coggins, J. H. and McDonald, A. J.: The influence of the Amundsen Sea Low on the winds in the Ross Sea and surroundings: Insights from a synoptic climatology, J. Geophys. Res.-Atmos., 120, 2167–2189, https://doi.org/10.1002/2014JD022830, 2015.
Colosio, P., Tedesco, M., Ranzi, R., and Fettweis, X.: Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019), The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, 2021.
Debbage, N., Miller, P., Poore, S., Morano, K., Mote, T., and Marshall Shepherd, J.: A climatology of atmospheric river interactions with the southeastern United States coastline, Int. J. Climatol., 37, 4077–4091, https://doi.org/10.1002/joc.5000, 2017.
DeFlorio, M. J., Sengupta, A., Castellano, C. M., Wang, J., Zhang, Z., Gershunov, A., Guirguis, K., and Luna Niño, R.: From California's Extreme Drought to Major Flooding: Evaluating and Synthesizing Experimental Seasonal and Subseasonal Forecasts of Landfalling Atmospheric Rivers and Extreme Precipitation during Winter 2022/23, B. Am. Meteorol. Soc., 105, E84–E104, https://doi.org/10.1175/BAMS-D-22-0208.1, 2024.
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.
Dutton, A., Carlson, A. E., Long, A. J., Milne, G. A., Clark, P. U., DeConto, R., Horton, D. P., and Rahmstorf, S.: Sea-level rise due to polar ice-sheet mass loss during past warm periods, Science, 349, aaa4019, https://doi.org/10.1126/science.aaa4019, 2015.
Eiras-Barca, J., Ramos, A. M., Pinto, J. G., Trigo, R. M., Liberato, M. L. R., and Miguez-Macho, G.: The concurrence of atmospheric rivers and explosive cyclogenesis in the North Atlantic and North Pacific basins, Earth Syst. Dynam., 9, 91–102, https://doi.org/10.5194/esd-9-91-2018, 2018.
Francis, D., Mattingly, K. S., Temimi, M., Massom, R., and Heil, P.: On the crucial role of atmospheric rivers in the two major Weddell Polynya events in 1973 and 2017 in Antarctica, Sci. Adv., 6, eabc2695, https://doi.org/10.1126/sciadv.abc2695, 2020.
González-Herrero, S., Barriopedro, D., Trigo, R. M., López-Bustins, J. A., and Oliva, M.: Climate warming amplified the 2020 record-breaking heatwave in the Antarctic Peninsula, Commun. Earth Environ., 3, 122, https://doi.org/10.1038/s43247-022-00450-5, 2022.
Gorodetskaya, I. V., Tsukernik, M., Claes, K., Ralph, M. F., Neff, W. D., and Van Lipzig, N. P.: The role of atmospheric rivers in anomalous snow accumulation in East Antarctica, Geophys. Res. Lett., 41, 6199–6206, https://doi.org/10.1002/2014GL060881, 2014.
Gorodetskaya, I. V., Silva, T., Schmithüsen, H., and Hirasawa, N.: Atmospheric river signatures in radiosonde profiles and reanalyses at the Dronning Maud Land coast, East Antarctica, Adv. Atmos. Sci., 37, 455–476, https://doi.org/10.1007/s00376-020-9221-8, 2020.
Gorodetskaya, I. V., Durán-Alarcón, C., González-Herrero, S., Clem, K. R., Zou, X., Rowe, P., Rodriguez Imazio, P., and Campos, D., Leroy-Dos Santos, C., Dutrievoz, N., and Wille, J. D.: Record-high Antarctic Peninsula temperatures and surface melt in February 2022: a compound event with an intense atmospheric river, NPJ Clim. Atmos. Sci., 6, 202, https://doi.org/10.1038/s41612-023-00529-6, 2023.
Guan, B. and Waliser, D. E.: Tracking atmospheric rivers globally: Spatial distributions and temporal evolution of life cycle characteristics, J. Geophys. Res.-Atmos., 124, 12523–12552, https://doi.org/10.1029/2019JD031205, 2019.
Guan, B., Molotch, N. P., Waliser, D. E., Fetzer, E. J., and Neiman, P. J.: Extreme snowfall events linked to atmospheric rivers and surface air temperature via satellite measurements, Geophys. Res. Lett., 37, L20401, https://doi.org/10.1029/2010GL044696, 2010.
Guan, B., Waliser, D. E., and Ralph, F. M.: Global Application of the Atmospheric River Scale, J. Geophys. Res.-Atmos., 128, e2022JD037180, https://doi.org/10.1029/2022JD037180, 2023.
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.: Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate, Copernicus Climate Change Service (C3S) Data Store (CDS) [data set], https://doi.org/10.24381/cds.143582cf, 2017.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., and Simmons, A.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
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.
Jones, M. E., Bromwich, D. H., Nicolas, J. P., Carrasco, J., Plavcová, E., Zou, X., and Wang, S. H.: Sixty years of widespread warming in the southern middle and high latitudes (1957–2016), J. Climate, 32, 6875–6898, https://doi.org/10.1175/JCLI-D-18-0565.1, 2019.
Kromer, J. D. and Trusel, L. D.: Identifying the impacts of sea ice variability on the climate and surface mass balance of West Antarctica, Geophys. Res. Lett., 50, e2023GL104436, https://doi.org/10.1029/2023GL104436, 2023.
Lavers, D. A. and Villarini, G.: The nexus between atmospheric rivers and extreme precipitation across Europe, Geophys. Res. Lett., 40, 3259–3264, https://doi.org/10.1002/grl.50636, 2013.
Li, L., Cannon, F., Mazloff, M. R., Subramanian, A. C., Wilson, A. M., and Ralph, F. M.: Impact of atmospheric rivers on Arctic sea ice variations, The Cryosphere, 18, 121–137, https://doi.org/10.5194/tc-18-121-2024, 2024.
Liang, K., Wang, J., Luo, H., and Yang, Q.: The Role of Atmospheric Rivers in Antarctic Sea Ice Variations, Geophys. Res. Lett., 50, e2022GL102588, https://doi.org/10.1029/2022GL102588, 2023.
Maclennan, M. L., Lenaerts, J. T., Shields, C., and Wille, J. D.: Contribution of atmospheric rivers to antarctic precipitation, Geophys. Res. Lett., 49, e2022GL100585, https://doi.org/10.1029/2022GL100585, 2022.
Maclennan, M. L., Lenaerts, J. T. M., Shields, C. A., Hoffman, A. O., Wever, N., Thompson-Munson, M., Winters, A. C., Pettit, E. C., Scambos, T. A., and Wille, J. D.: Climatology and surface impacts of atmospheric rivers on West Antarctica, The Cryosphere, 17, 865–881, https://doi.org/10.5194/tc-17-865-2023, 2023.
Martin, A., Ralph, F. M., Demirdjian, R., DeHaan, L., Weihs, R., Helly, J., Reynolds, D., and Iacobellis, S.: Evaluation of atmospheric river predictions by the WRF model using aircraft and regional mesonet observations of orographic precipitation and its forcing, J. Hydrometeorol., 19, 1097–1113, https://doi.org/10.1175/JHM-D-17-0098.1, 2018.
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.
Mattingly, K. S., Mote, T. L., Fettweis, X., Van As, D., Van Tricht, K., Lhermitte, S., Pettersen, C., and Fausto, R. S.: Strong summer atmospheric rivers trigger Greenland Ice Sheet melt through spatially varying surface energy balance and cloud regimes, J. Climate, 33, 6809–6832, https://doi.org/10.1175/JCLI-D-19-0835.1, 2020.
Mattingly, K. S., Turton, J. V., Wille, J. D., Noël, B., Fettweis, X., Rennermalm, Å. K., and Mote, T. L.: Increasing extreme melt in northeast Greenland linked to foehn winds and atmospheric rivers, Nat. Commun., 14, 1743, https://doi.org/10.1038/s41467-023-37434-8, 2023.
Newman, M., Kiladis, G. N., Weickmann, K. M., Ralph, F. M., and Sardeshmukh, P. D.: Relative contributions of synoptic and low-frequency eddies to time-mean atmospheric moisture transport, including the role of atmospheric rivers, J. Climate, 25, 7341–7361, https://doi.org/10.1175/JCLI-D-11-00665.1, 2012.
Nicolas, J. P. and Bromwich, D. H.: Climate of West Antarctica and influence of marine air intrusions, J. Climate, 24, 49–67, https://doi.org/10.1175/2010JCLI3522.1, 2011.
O'Brien, T. A., Payne, A. E., Shields, C. A., Rutz, J., Brands, S., Castellano, C., Chen, J., Cleveland, W., DeFlorio, M. J., Goldenson, N., and Gorodetskaya, I. V.: Detection uncertainty matters for understanding atmospheric rivers, B. Am. Meteorol. Soc., 101, E790–E796, https://doi.org/10.1175/BAMS-D-19-0348.1, 2020.
Payne, A. E., Demory, M. E., Leung, L. R., Ramos, A. M., Shields, C. A., Rutz, J. J., Siler, N., Villarini, G., Hall, A., and Ralph, F. M.: Responses and impacts of atmospheric rivers to climate change, Nat. Rev. Earth Environ., 1, 143–157, https://doi.org/10.1038/ s43017-020-0030-5, 2020.
Picard, G. and Fily, M.: Surface melting observations in Antarctica by microwave radiometers: Correcting 26-year time series from changes in acquisition hours,Remote Sens. Environ., 104, 325–336, https://doi.org/10.1016/j.rse.2006.05.010, 2006.
Prince, H. D., Cullen, N. J., Gibson, P. B., Conway, J., and Kingston, D. G.: A climatology of atmospheric rivers in New Zealand, J. Climate, 34, 4383–4402, https://doi.org/10.1175/JCLI-D-20-0664.1, 2021.
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.
Ralph, F. M., Coleman, T., Neiman, P. J., Zamora, R. J., and Dettinger, M. D.: Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal northern California, J. Hydrometeorol., 14, 443–459, https://doi.org/10.1175/JHM-D-12-076.1, 2013.
Ralph, F. M., Dettinger, M. D., Cairns, M. M., Galarneau, T. J., and Eylander, J.: Defining “atmospheric river”: How the Glossary of Meteorology helped resolve a debate, B. Am. Meteorol. Soc., 99, 837–839, https://doi.org/10.1175/BAMS-D-17-0157.1, 2018.
Ralph, F. M., Rutz, J. J., Cordeira, J. M., Dettinger, M., Anderson, M., Reynolds, D., Schick, L. J., and Smallcomb, C.: A scale to characterize the strength and impacts of atmospheric rivers, B. Am. Meteorol. Soc., 100, 269–289, https://doi.org/10.1175/BAMS-D-18-0023.1, 2019.
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., and Brands, S.: 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.
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.
Shields, C. A., Wille, J. D., Marquardt Collow, A. B., Maclennan, M., and Gorodetskaya, I. V.: Evaluating uncertainty and modes of variability for Antarctic atmospheric rivers, Geophys. Res. Lett., 49, e2022GL099577, https://doi.org/10.1029/2022GL099577, 2022.
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., and Dong, Q.: 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.
Shu, J., Shamseldin, A. Y., and Weller, E.: The impact of atmospheric rivers on rainfall in New Zealand, Sci. Rep., 11, 5869, https://doi.org/10.1038/s41598-021-85297-0, 2021.
Torinesi, O., Fily, M., and Genthon, C.: Variability and trends of the summer melt period of Antarctic ice margins since 1980 from microwave sensors, J. Climate, 16, 1047–1060, https://doi.org/10.1175/1520-0442(2003)016<1047:VATOTS>2.0.CO;2, 2003.
Trusel, L. D., Frey, K. E., Das, S. B., Karnauskas, K. B., Kuipers Munneke, P., Van Meijgaard, E., and Van Den Broeke, M. R.: Divergent trajectories of Antarctic surface melt under two twenty-first-century climate scenarios, Nat. Geosci., 8, 927–932, https://doi.org/10.1038/NGEO2563, 2015.
Viale, M., Valenzuela, R., Garreaud, R. D., and Ralph, F. M.: Impacts of atmospheric rivers on precipitation in southern South America, J. Hydrometeorol., 19, 1671–1687, https://doi.org/10.1175/JHM-D-18-0006.1, 2018.
Viceto, C., Gorodetskaya, I. V., Rinke, A., Maturilli, M., Rocha, A., and Crewell, S.: Atmospheric rivers and associated precipitation patterns during the ACLOUD and PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model, Atmos. Chem. Phys., 22, 441–463, https://doi.org/10.5194/acp-22-441-2022, 2022.
Waliser, D. and Guan, B.: Extreme winds and precipitation during landfall of atmospheric rivers, Nat. Geosci., 10, 179–183, https://doi.org/10.1038/NGEO2894, 2017.
Warner, M. D. and Mass, C. F.: Changes in the climatology, structure, and seasonality of northeast Pacific atmospheric rivers in CMIP5 climate simulations, J. Hydrometeorol., 18, 2131–2141, https://doi.org/10.1175/JHM-D-16-0200.1, 2017.
Warner, M. D., Mass, C. F., and Salathé, E. P.: Changes in winter atmospheric rivers along the North American west coast in CMIP5 climate models, J. Hydrometeorol., 16, 118–128, https://doi.org/10.1175/JHM-D-14-0080.1, 2015.
Wille, J. D., Favier, V., Dufour, A., Gorodetskaya, I. V., Turner, J., Agosta, C., and Codron, F.: West Antarctic surface melt triggered by atmospheric rivers, Nat. Geosci., 12, 911–916, https://doi.org/10.1038/s41561-019-0460-1, 2019.
Wille, J. D., Favier, V., Gorodetskaya, I. V., Agosta, C., Kittel, C., Beeman, J. C., Jourdain, N. C., Lenaerts, J. T., and Codron, F.: Antarctic atmospheric river climatology and precipitation impacts, J. Geophys. Res.-Atmos., 126, e2020JD033788, https://doi.org/10.1029/2020JD033788, 2021.
Wille, J. D., Favier, V., Jourdain, N. C., Kittel, C., Turton, J. V., Agosta, C., Gorodetskaya, I. V., Picard, G., Codron, F., Santos, C. L. D., and Amory, C.: Intense atmospheric rivers can weaken ice shelf stability at the Antarctic Peninsula, Commun. Earth Environ., 3, 90, https://doi.org/10.1038/s43247-022-00422-9, 2022,
Wille, J. D., Alexander, S. P., Amory, C., Baiman, R., Barthélemy, L., Bergstrom, D. M., Berne, A., Binder, H., Blanchet, J., Bozkurt, D., and Bracegirdle, T. J.: The extraordinary March 2022 East Antarctica “heat” wave, Part I: observations and meteorological drivers, J. Climate, 37, 757–778, https://doi.org/10.1175/JCLI-D-23-0175.1, 2024a.
Wille, J. D., Alexander, S. P., Amory, C., Baiman, R., Barthélemy, L., Bergstrom, D. M., Berne, A., Binder, H., Blanchet, J., Bozkurt, D., and Bracegirdle, T. J.: The extraordinary March 2022 East Antarctica “heat” wave, Part II: impacts on the Antarctic ice sheet, J. Climate, 37, 779–799, https://doi.org/10.1175/JCLI-D-23-0176.1, 2024b.
Yin, J. H.: A consistent poleward shift of the storm tracks in simulations of 21st century climate, Geophys. Res. Lett., 32, L18701, https://doi.org/10.1029/2005GL023684, 2005.
Zhang, P., Chen, G., Ting, M., Ruby Leung, L., Guan, B., and Li, L.: More frequent atmospheric rivers slow the seasonal recovery of Arctic sea ice, Nat. Clim. Change, 13, 266–273, https://doi.org/10.1038/s41558-023-01599-3, 2023.
Zhang, Z. and Ralph, F. M.: The influence of antecedent atmospheric river conditions on extratropical cyclogenesis, Mon. Weather Rev., 149, 1337–1357, https://doi.org/10.1175/MWR-D-20-0212.1, 2021.
Zhang, Z., Ralph, F. M., and Zheng, M.: The relationship between extratropical cyclone strength and atmospheric river intensity and position, Geophys. Res. Lett., 46, 1814–1823, https://doi.org/10.1029/2018GL079071, 2019.
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.
Zou, X., Rowe, P. M., Gorodetskaya, I. V., Bromwich, D. H., Lazzara, M. A., Cordero, R. R., Zhang, Z., Kawzenuk, B., Cordeira, J. M., Wille, J. D., and Ralph, F. M.: Strong warming over the Antarctic Peninsula during combined atmospheric river and foehn events: contribution of shortwave radiation and turbulence, J. Geophys. Res.-Atmos., 128, e2022JD038138, https://doi.org/10.1029/2022JD038138, 2023.
Short summary
Atmospheric rivers (ARs) are long, narrow corridors of strong water vapor transport in the atmosphere. ARs play an important role in extreme weather in polar regions, including heavy rain and/or snow, heat waves, and surface melt. The standard AR scale is developed based on the midlatitude climate and is insufficient for polar regions. This paper introduces an extended version of the AR scale tuned to polar regions, aiming to quantify polar ARs objectively based on their strength and impact.
Atmospheric rivers (ARs) are long, narrow corridors of strong water vapor transport in the...