Articles | Volume 3, issue 4
https://doi.org/10.5194/wcd-3-1359-2022
© 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-3-1359-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Can low-resolution CMIP6 ScenarioMIP models provide insight into future European post-tropical-cyclone risk?
Elliott Michael Sainsbury
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, Berkshire, UK
Reinhard K. H. Schiemann
National Centre for Atmospheric Science, University of Reading,
Reading, Berkshire, UK
Kevin I. Hodges
National Centre for Atmospheric Science, University of Reading,
Reading, Berkshire, UK
Alexander J. Baker
National Centre for Atmospheric Science, University of Reading,
Reading, Berkshire, UK
Len C. Shaffrey
National Centre for Atmospheric Science, University of Reading,
Reading, Berkshire, UK
Kieran T. Bhatia
North America Peril Advisory, Guy Carpenter, New York, USA
Stella Bourdin
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ-Université Paris-Saclay, Gif-sur-Yvette, France
Related authors
No articles found.
Isabel H. Smith, Paul D. Williams, and Reinhard Schiemann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2378, https://doi.org/10.5194/egusphere-2025-2378, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Mountain wave turbulence (MWT) has a dangerous and costly impact on the aviation sector. There's a lack of research into future projected MWT with global warming. Overall, MWT trends are seasonally and location dependent. Over several mountain ranges an increase arose particularly over Greenland and regions in Asia. A drop in MWT also developed over the Alps, the Rockys, Atlas and northern and central Andes. Southern Andes and the Himalayas had seasonal differences resulting in a mix of trends.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
EGUsphere, https://doi.org/10.5194/egusphere-2025-509, https://doi.org/10.5194/egusphere-2025-509, 2025
Short summary
Short summary
The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025, https://doi.org/10.5194/essd-17-135-2025, 2025
Short summary
Short summary
Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
Lorenzo Sangelantoni, Stefano Tibaldi, Leone Cavicchia, Enrico Scoccimarro, Pier Luigi Vidale, Kevin Hodges, Vivien Mavel, Mattia Almansi, Chiara Cagnazzo, and Samuel Almond
EGUsphere, https://doi.org/10.5194/egusphere-2024-4157, https://doi.org/10.5194/egusphere-2024-4157, 2025
Preprint archived
Short summary
Short summary
We introduce a new dataset of European windstorms linked to extratropical cyclones, spanning whole ERA5 reanalysis period (1940–present). Developed under Copernicus Climate Change Service, the dataset provides standardized, high-quality information on windstorm tracks and footprints for industries like insurance and risk management. Preliminary findings show an increase in cold-season windstorms and their impacts in parts of Europe. Tracking methods contribute to uncertainties in key statistics.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Henri Rossi Pinheiro, Kevin Ivan Hodges, and Manoel Alonso Gan
Weather Clim. Dynam., 5, 881–894, https://doi.org/10.5194/wcd-5-881-2024, https://doi.org/10.5194/wcd-5-881-2024, 2024
Short summary
Short summary
Cut-off lows (COLs) are weather systems with varied structures and lifecycles, from upper atmospheric to deep vortices. Deep, strong COLs are common around Australia and the southwestern Pacific in autumn and spring, while shallow, weak COLs occur more in summer near the Equator. Jet streams play a crucial role in COL development, with different jets influencing its depth and strength. The study also emphasizes the need for better representation of diabatic processes in reanalysis data.
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024, https://doi.org/10.5194/nhess-24-2115-2024, 2024
Short summary
Short summary
The risk posed to ships by Arctic cyclones has seldom been quantified due to the lack of publicly available historical Arctic ship track data. This study investigates historical Arctic ship tracks, cyclone tracks, and shipping incident reports to determine the number of shipping incidents caused by the passage of Arctic cyclones. Results suggest that Arctic cyclones have not been hazardous to ships and that ships are resilient to the rough sea conditions caused by Arctic cyclones.
Charlie C. Suitters, Oscar Martínez-Alvarado, Kevin I. Hodges, Reinhard K. H. Schiemann, and Duncan Ackerley
Weather Clim. Dynam., 4, 683–700, https://doi.org/10.5194/wcd-4-683-2023, https://doi.org/10.5194/wcd-4-683-2023, 2023
Short summary
Short summary
Atmospheric blocking describes large and persistent high surface pressure. In this study, the relationship between block persistence and smaller-scale systems is examined. Persistent blocks result from more interactions with small systems, but a block's persistence does not depend as strongly on the strength of these smaller features. This work is important because it provides more knowledge as to how blocks can be allowed to persist, which is something we still do not fully understand.
Davide Faranda, Stella Bourdin, Mireia Ginesta, Meriem Krouma, Robin Noyelle, Flavio Pons, Pascal Yiou, and Gabriele Messori
Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, https://doi.org/10.5194/wcd-3-1311-2022, 2022
Short summary
Short summary
We analyze the atmospheric circulation leading to impactful extreme events for the calendar year 2021 such as the Storm Filomena, Westphalia floods, Hurricane Ida and Medicane Apollo. For some of the events, we find that climate change has contributed to their occurrence or enhanced their intensity; for other events, we find that they are unprecedented. Our approach underscores the importance of considering changes in the atmospheric circulation when performing attribution studies.
Rafaela Jane Delfino, Gerry Bagtasa, Kevin Hodges, and Pier Luigi Vidale
Nat. Hazards Earth Syst. Sci., 22, 3285–3307, https://doi.org/10.5194/nhess-22-3285-2022, https://doi.org/10.5194/nhess-22-3285-2022, 2022
Short summary
Short summary
We showed the effects of altering the choice of cumulus schemes, surface flux options, and spectral nudging with a high level of sensitivity to cumulus schemes in simulating an intense typhoon. We highlight the advantage of using an ensemble of cumulus parameterizations to take into account the uncertainty in simulating typhoons such as Haiyan in 2013. This study is useful in addressing the growing need to plan and prepare for as well as reduce the impacts of intense typhoons in the Philippines.
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
Short summary
Short summary
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.
Stella Bourdin, Sébastien Fromang, William Dulac, Julien Cattiaux, and Fabrice Chauvin
Geosci. Model Dev., 15, 6759–6786, https://doi.org/10.5194/gmd-15-6759-2022, https://doi.org/10.5194/gmd-15-6759-2022, 2022
Short summary
Short summary
When studying tropical cyclones in a large dataset, one needs objective and automatic procedures to detect their specific pattern. Applying four different such algorithms to a reconstruction of the climate, we show that the choice of the algorithm is crucial to the climatology obtained. Mainly, the algorithms differ in their sensitivity to weak storms so that they provide different frequencies and durations. We review the different options to consider for the choice of the tracking methodology.
Ambrogio Volonté, Andrew G. Turner, Reinhard Schiemann, Pier Luigi Vidale, and Nicholas P. Klingaman
Weather Clim. Dynam., 3, 575–599, https://doi.org/10.5194/wcd-3-575-2022, https://doi.org/10.5194/wcd-3-575-2022, 2022
Short summary
Short summary
In this study we analyse the complex seasonal evolution of the East Asian summer monsoon. Using reanalysis data, we show the importance of the interaction between tropical and extratropical air masses converging at the monsoon front, particularly during its northward progression. The upper-level flow pattern (e.g. the westerly jet) controls the balance between the airstreams and thus the associated rainfall. This framework provides a basis for studies of extreme events and climate variability.
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
Short summary
Short summary
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.
Mark R. Muetzelfeldt, Reinhard Schiemann, Andrew G. Turner, Nicholas P. Klingaman, Pier Luigi Vidale, and Malcolm J. Roberts
Hydrol. Earth Syst. Sci., 25, 6381–6405, https://doi.org/10.5194/hess-25-6381-2021, https://doi.org/10.5194/hess-25-6381-2021, 2021
Short summary
Short summary
Simulating East Asian Summer Monsoon (EASM) rainfall poses many challenges because of its multi-scale nature. We evaluate three setups of a 14 km global climate model against observations to see if they improve simulated rainfall. We do this over catchment basins of different sizes to estimate how model performance depends on spatial scale. Using explicit convection improves rainfall diurnal cycle, yet more model tuning is needed to improve mean and intensity biases in simulated summer rainfall.
Frederick W. Letson, Rebecca J. Barthelmie, Kevin I. Hodges, and Sara C. Pryor
Nat. Hazards Earth Syst. Sci., 21, 2001–2020, https://doi.org/10.5194/nhess-21-2001-2021, https://doi.org/10.5194/nhess-21-2001-2021, 2021
Short summary
Short summary
Windstorms during the last 40 years in the US Northeast are identified and characterized using the spatial extent of extreme wind speeds at 100 m height from the ERA5 reanalysis. During all of the top 10 windstorms, wind speeds exceeding the local 99.9th percentile cover at least one-third of the land area in this high-population-density region. These 10 storms followed frequently observed cyclone tracks but have intensities 5–10 times the mean values for cyclones affecting this region.
Cited articles
Andrews, M. B., Ridley, J. K., Wood, R. A., Andrews, T., Blockley, E. W.,
Booth, B., Burke, E., Dittus, A. J., Florek, P., Gray, L. J., Haddad, S.,
Hardiman, S. C., Hermanson, L., Hodson, D., Hogan, E., Jones, G. S., Knight, J. R., Kuhlbrodt, T., Misios, S., Mizielinski, M. S., Ringer, M. A., Robson, J., and Sutton, R. T.: Historical Simulations With HadGEM3-GC3.1 for CMIP6, J. Adv. Model. Earth Syst., 12, e2019MS001995, https://doi.org/10.1029/2019MS001995, 2020.
Arnault, J. and Roux, F.: Characteristics of African easterly waves
associated with tropical cyclogenesis in the Cape Verde Islands region in
July–August–September of 2004-=2008, Atmos. Res., 100, 61–82,
https://doi.org/10.1016/j.atmosres.2010.12.028, 2011.
Avila, L. A. and Cangialosi, J.: Tropical Cyclone Report – Hurricane Irene, National Hurricane Center, 21–28, https://www.nhc.noaa.gov/data/tcr/AL092011_Irene.pdf (last access: 16 November 2022), 2011.
Baatsen, M., Haarsma, R. J., Van Delden, A. J., and de Vries, H.: Severe
Autumn storms in future Western Europe with a warmer Atlantic Ocean, Clim. Dynam., 45, 949–964, https://doi.org/10.1007/s00382-014-2329-8, 2015.
Baker, A., Roberts, M. J., Vidale, P. L., Hodges, K. I., Seddon, J.,
Vanniere, B., Haarsma, R. J., Schiemann, R. K. H., Kapetanakis, D.,
Tourigny, E., Lohmann, K., Roberts, C. D., and Terray, L.: Extratropical
transition of tropical cyclones in a multiresolution ensemble of
atmosphere-only and fully coupled global climate models, J. Climate, 35,
5283–5306, https://doi.org/10.1175/JCLI-D-21-0801.1, 2022.
Baker, A. J., Hodges, K. I., Schiemann, R. K. H., and Vidale, P. L.:
Historical variability and lifecycles of North Atlantic midlatitude cyclones originating in the tropics, J. Geophys. Res.-Atmos., 126, e2020JD033924, https://doi.org/10.1029/2020jd033924, 2021.
Bender, M. A., Knutson, T. R., Tuleya, R. E., Sirutis, J. J., Vecchi, G. A.,
Garner, S. T., and Held, I. M.: Modeled impact of anthropogenic warming on
the frequency of intense Atlantic hurricanes, Science, 327,
454–458, https://doi.org/10.1126/science.1180568, 2010.
Bengtsson, L., Hodges, K. I., Esch, M., Keenlyside, N., Kornblueh, L., Luo,
J. J., and Yamagata, T.: How may tropical cyclones change in a warmer
climate?, Tellus Ser. A Dyn. Meteorol. Oceanogr., 59A, 539–561,
https://doi.org/10.1111/j.1600-0870.2007.00251.x, 2007.
Bhatia, K. T., Vecchi, G. A., Murakami, H., Underwood, S. D., and Kossin, J. P.: Projected Response of Tropical Cyclone Intensity and Intensification in a Global Climate Model, J. Climate, 31, 8281–8303,
https://doi.org/10.1175/JCLI-D-17-0898.1, 2018.
Bieli, M., Camargo, S. J., Sobel, A. H., Evans, J. L., and Hall, T.: A
global climatology of extratropical transition. Part I: Characteristics
across basins, J. Climate, 32, 3557–3582,
https://doi.org/10.1175/JCLI-D-17-0518.1, 2019.
Bieli, M., Sobel, A. H., Camargo, S. J., Murakami, H., and Vecchi, G. A.:
Application of the Cyclone Phase Space to Extratropical Transition in a
Global Climate Model, J. Adv. Model. Earth Syst., 12, e2019MS001878,
https://doi.org/10.1029/2019MS001878, 2020.
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y.,
Bastrikov, V., Bekki, S., Bonnet, R., Bony, S., Bopp, L., Braconnot, P.,
Brockmann, P., Cadule, P., and Caubel, A.: Presentation and evaluation of
the IPSL-CM6A-LR climate model, J. Adv. Model. Earth Syst., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010, 2020.
Bourdin, S., Fromang, S., Dulac, W., Cattiaux, J., and Chauvin, F.: Intercomparison of Four Tropical Cyclones Detection Algorithms on ERA5, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-179, 2022.
Camargo, S. J.: Global and regional aspects of tropical cyclone activity in
the CMIP5 models, J. Climate, 26, 9880–9902,
https://doi.org/10.1175/JCLI-D-12-00549.1, 2013.
Colbert, A. J. and Soden, B. J.: Climatological variations in North Atlantic
tropical cyclone tracks, J. Climate, 25, 657–673,
https://doi.org/10.1175/JCLI-D-11-00034.1, 2012.
Dekker, M. M., Haarsma, R. J., Vries, H. de, Baatsen, M., and van Delden, A. J.: Characteristics and development of European cyclones with tropical
origin in reanalysis data, Clim. Dynam., 50, 445–455,
https://doi.org/10.1007/s00382-017-3619-8, 2018.
Elsner, J. B., Lehmiller, G. S., and Kimberlain, T. B.: Objective
Classification of Atlantic Hurricanes, J. Climate, 9, 2880–2889,
https://doi.org/10.1175/1520-0442(1996)009<2880:OCOAH>2.0.CO;2, 1996.
Emanuel, K.: Response of global tropical cyclone activity to increasing CO2:
Results from downscaling CMIP6 models, J. Climate, 34, 57–70,
https://doi.org/10.1175/JCLI-D-20-0367.1, 2021.
Emanuel, K. and Nolan, D. S.: Tropical Cyclone Activity and the Global
Climate System, in: 26th Conference on Hurricanes and Tropical Meteorology,
240–241, http://ams.confex.com/ams/pdfpapers/75463.pdf (last access: 15 November 2022), 2004.
Emanuel, K. A.: An Air-Sea Interaction Theory for Tropical Cyclones. Part I:
Steady-State Maintenance, J. Atmos. Sci., 43, 585–605,
https://doi.org/10.1175/1520-0469(1986)043<0585:AASITF>2.0.CO;2, 1986.
Emanuel, K. A.: Downscaling CMIP5 climate models shows increased tropical
cyclone activity over the 21st century, P. Natl. Acad. Sci. USA,
110, 12219–12224, https://doi.org/10.1073/pnas.1301293110, 2013.
Emanuel, K. A., Sundararajan, R., and Williams, J.: Hurricanes and global
warming, B. Am. Meteorol. Soc., 89, 347–368,
https://doi.org/10.1175/BAMS-89-3-347, 2008.
Evans, C., Wood, K. M., Aberson, S. D., Archambault, H. M., Milrad, S. M.,
Bosart, L. F., Corbosiero, K. L., Davis, C. A., Pinto, J. R. D., Doyle, J.,
Fogarty, C., Galarneau, T. J., Grams, C. M., Griffin, K. S., Gyakum, J.,
Hart, R. E., Kitabatake, N., Lentink, H. S., Mctaggart-Cowan, R., Perrie,
W., Quinting, J. F. D., Reynolds, C. A., Riemer, M., Ritchie, E. A., Sun,
Y., and Zhang, F.: The extratropical transition of tropical cyclones. Part
I: Cyclone evolution and direct impacts, Mon. Weather Rev., 145, 4317–4344,
https://doi.org/10.1175/MWR-D-17-0027.1, 2017.
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.
Gilford, D. M.: pyPI (v1.3): Tropical Cyclone Potential Intensity Calculations in Python, Geosci. Model Dev., 14, 2351–2369, https://doi.org/10.5194/gmd-14-2351-2021, 2021 (code available at: https://github.com/dgilford/tcpyPI, last access: 1 August 2022).
Gualdi, S., Scoccimarro, E., and Navarra, A.: Changes in Tropical Cyclone
Activity due to Global Warming: Results from a High-Resolution Coupled
General Circulation Model, J. Climate, 21, 5204–5228,
https://doi.org/10.1175/2008JCLI1921.1, 2008.
Haarsma, R.: European windstorm risk of post Tropical Cyclones and the
impact of climate change, Geophys. Res. Lett., 40, 1783–1788,
https://doi.org/10.1029/2020gl091483, 2021.
Haarsma, R. J., Mitchell, J. F. B., and Senior, C. A.: Tropical disturbances in a GCM, Clim. Dynam., 8, 247–257, https://doi.org/10.1007/BF00198619, 1993.
Haarsma, R. J., Hazeleger, W., Severijns, C., De Vries, H., Sterl, A.,
Bintanja, R., Van Oldenborgh, G. J., and Van Den Brink, H. W.: More
hurricanes to hit western Europe due to global warming, Geophys. Res. Lett.,
40, 1783–1788, https://doi.org/10.1002/grl.50360, 2013.
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.
Han, Y., Zhang, M. Z., Xu, Z., and Guo, W.: Assessing the performance of 33
CMIP6 models in simulating the large-scale environmental fields of tropical
cyclones, Clim. Dynam., 58, 1683–1698,
https://doi.org/10.1007/s00382-021-05986-4, 2022.
Harvey, B. J., Cook, P., Shaffrey, L. C., and Schiemann, R. K. H.: The
Response of the Northern Hemisphere Storm Tracks and Jet Streams to Climate
Change in the CMIP3 , CMIP5 , and CMIP6 Climate Models Journal of
Geophysical Research: Atmospheres, J. Geophys. Res.-Atmos., 125, e2020JD032701, https://doi.org/10.1029/2020JD032701, 2020.
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. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020 (data available at: https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5, last access: 1 September 2022).
Hodges, K., Cobb, A., and Vidale, P. L.: How well are tropical cyclones
represented in reanalysis datasets?, J. Climate, 30, 5243–5264,
https://doi.org/10.1175/JCLI-D-16-0557.1, 2017.
Hodges, K. I.: A general method for tracking analysis and its application to meteorological data, Mon. Weather Rev., 122, 2573–2586,
https://doi.org/10.1175/1520-0493(1994)122<2573:AGMFTA>2.0.CO;2, 1994 (data available at: https://gitlab.act.reading.ac.uk/track/track, last access: 1 August 2022).
Hodges, K. I.: Feature Tracking on the Unit Sphere, Mon. Weather Rev., 123,
3458–3465, https://doi.org/10.1175/1520-0493(1995)123<3458:ftotus>2.0.co;2, 1995.
Hodges, K. I.: Spherical nonparametric estimators applied to the UGAMP model integration for AMIP, Mon. Weather Rev., 124, 2914–2932, https://doi.org/10.1175/1520-0493(1996)124<2914:SNEATT>2.0.CO;2, 1996.
Hodges, K. I.: Adaptive constraints for feature tracking, Mon. Weather Rev., 127, 1362–1373, https://doi.org/10.1175/1520-0493(1999)127<1362:acfft>2.0.co;2, 1999.
Jing, R., Lin, N., Emanuel, K. A., Vecchi, G. A., and Knutson, T. R.: A
Comparison of Tropical Cyclone Projections in a High-Resolution Global
Climate Model and from Downscaling by Statistical and
Statistical-Deterministic Methods, J. Climate, 34, 9349–9364,
https://doi.org/10.1175/JCLI-D-21-0071.1, 2021.
Jones, S. C., Harr, P. A., Abraham, J., Bosart, L. F., Bowyer, P. J., Evans,
J. L., Hanley, D. E., Hanstrum, B. N., Hart, R. E., Lalaurette, F.,
Sinclair, M. R., Smith, R. K., and Thorncroft, C.: The extratropical
transition of tropical cyclones: Forecast challenges, current understanding,
and future directions, Weather Forecast., 18, 1052–1092,
https://doi.org/10.1175/1520-0434(2003)018<1052:TETOTC>2.0.CO;2, 2003.
Jung, C. and Lackmann, G. M.: Extratropical Transition of Hurricane Irene
(2011) in a Changing Climate, J. Climate, 32, 4847–4871,
https://doi.org/10.1175/jcli-d-18-0558.1, 2019.
Jung, C. and Lackmann, G. M.: The response of extratropical transition of
tropical cyclones to climate change: Quasi-idealized numerical experiments,
J. Climate, 34, 4361–4381, https://doi.org/10.1175/JCLI-D-20-0543.1, 2021.
Knutson, T., Camargo, S. J., Chan, J. C. L., Emanuel, K., Ho, C. H., Kossin,
J., Mohapatra, M., Satoh, M., Sugi, M., Walsh, K., and Wu, L.: Tropical
cyclones and climate change assessment. Part II: Projected Response to
Anthropogenic Warming, B. Am. Meteorol. Soc., 100, 1987–2007,
https://doi.org/10.1175/BAMS-D-18-0189.1, 2019.
Knutson, T. R., McBride, J. L., Chan, J. C. L., Emanuel, K. A., Holland, G., Landsea, C. W., Held, I. M., Kossin, J. P., Srivastava, A. K., and Sugi, M.: tropical cyclones and climate change, Nat. Geosci., 3, 157–163,
https://doi.org/10.1038/ngeo779, 2010.
Kossin, J. P., Camargo, S. J., and Sitkowski, M.: Climate modulation of
north atlantic hurricane tracks, J. Climate, 23, 3057–3076,
https://doi.org/10.1175/2010JCLI3497.1, 2010.
Kossin, J. P., Emanuel, K. A., and Vecchi, G. A.: The poleward migration of
the location of tropical cyclone maximum intensity, Nature, 509, 349–352,
https://doi.org/10.1038/nature13278, 2014.
Kossin, J. P., Knapp, K. R., Olander, T. L., and Velden, C. S.: Global
increase in major tropical cyclone exceedance probability over the past four decades, P. Natl. Acad. Sci. USA, 117, 11975–11980,
https://doi.org/10.1073/pnas.2021573117, 2020.
Landsea, C. W. and Franklin, J. L.: Atlantic hurricane database uncertainty
and presentation of a new database format, Mon. Weather Rev., 141,
3576–3592, https://doi.org/10.1175/MWR-D-12-00254.1, 2013 (data available at: https://www.aoml.noaa.gov/hrd/hurdat/, last access: 30 September 2019).
Liu, M., Vecchi, G. A., Smith, J. A., and Murakami, H.: The present-day
simulation and twenty-first-century projection of the climatology of
extratropical transition in the North Atlantic, J. Climate, 30, 2739–2756,
https://doi.org/10.1175/JCLI-D-16-0352.1, 2017.
Liu, M., Yang, L., Smith, J. A., and Vecchi, G. A.: Response of Extreme
Rainfall for Landfalling Tropical Cyclones Undergoing Extratropical
Transition to Projected Climate Change: Hurricane Irene (2011), Earth's
Futur., 8, e2019EF001360, https://doi.org/10.1029/2019EF001360, 2020.
Michaelis, A. C. and Lackmann, G. M.: Climatological changes in the
extratropical transition of tropical cyclones in high-resolution global
simulations, J. Climate, 32, 8733–8753,
https://doi.org/10.1175/JCLI-D-19-0259.1, 2019.
Pak, G., Noh, Y., Lee, M. I., Yeh, S. W., Kim, D., Kim, S. Y., Lee, J. L.,
Lee, H. J., Hyun, S. H., Lee, K. Y., Lee, J. H., Park, Y. G., Jin, H., Park,
H., and Kim, Y. H.: Korea Institute of Ocean Science and Technology Earth
System Model and Its Simulation Characteristics, Ocean Sci. J., 56, 18–45,
https://doi.org/10.1007/s12601-021-00001-7, 2021.
Rantanen, M., Räisänen, J., Sinclair, V. A., Lento, J., and
Järvinen, H.: The extratropical transition of Hurricane Ophelia (2017)
as diagnosed with a generalized omega equation and vorticity equation,
Tellus, Ser. A Dyn. Meteorol. Oceanogr., 72, 1–26,
https://doi.org/10.1080/16000870.2020.1721215, 2020.
Rathman, N. M., Yang, S., and Kaas, E.: Tropical cyclones in enhanced
resolution CMIP5 experiments, Clim. Dynam., 42, 665–681,
https://doi.org/10.1007/s00382-013-1818-5, 2014.
Roberts, M. J., Vidale, P. L., Mizielinski, M. S., Demory, M. E., Schiemann,
R., Strachan, J., Hodges, K., Bell, R., and Camp, J.: Tropical cyclones in
the UPSCALE ensemble of high-resolution global climate models, J. Climate, 28,
574–596, https://doi.org/10.1175/JCLI-D-14-00131.1, 2015.
Roberts, M. J., Camp, J., Seddon, J., Vidale, P. L., Hodges, K., Vanniere,
B., Mecking, J., Haarsma, R., Bellucci, A., Scoccimarro, E., Caron, L. P.,
Chauvin, F., Terray, L., Valcke, S., Moine, M. P., Putrasahan, D., Roberts,
C., Senan, R., Zarzycki, C., and Ullrich, P.: Impact of model resolution on
tropical cyclone simulation using the HighResMIP-PRIMAVERA multimodel
ensemble, J. Climate, 33, 2557–2583,
https://doi.org/10.1175/JCLI-D-19-0639.1, 2020a.
Roberts, M. J., Camp, J., Seddon, J., Vidale, P. L., Hodges, K.,
Vannière, B., Mecking, J., Haarsma, R., Bellucci, A., Scoccimarro, E.,
Caron, L. P., Chauvin, F., Terray, L., Valcke, S., Moine, M. P., Putrasahan,
D., Roberts, C. D., Senan, R., Zarzycki, C., Ullrich, P., Yamada, Y.,
Mizuta, R., Kodama, C., Fu, D., Zhang, Q., Danabasoglu, G., Rosenbloom, N.,
Wang, H., and Wu, L.: Projected Future Changes in Tropical Cyclones Using
the CMIP6 HighResMIP Multimodel Ensemble, Geophys. Res. Lett., 47, e2020GL088662, https://doi.org/10.1029/2020GL088662, 2020b.
Sainsbury, E. M., Schiemann, R. K. H., Hodges, K. I., Shaffrey, L. C.,
Baker, A. J., and Bhatia, K. T.: How Important Are Post-Tropical Cyclones
for European Windstorm Risk?, Geophys. Res. Lett., 47, e2020GL089853,
https://doi.org/10.1029/2020GL089853, 2020.
Sainsbury, E. M., Schiemann, R. K. H., Hodges, K. I., Baker, A. J.,
Shaffrey, L. C., and Bhatia, K. T.: What Governs the Interannual Variability
of Recurving North Atlantic Tropical Cyclones?, J. Climate, 35, 3627–3641,
https://doi.org/10.1175/jcli-d-21-0712.1, 2022a.
Sainsbury, E. M., Schiemann, R. K. H., Hodges, K. I., Baker, A. J.,
Shaffrey, L. C., and Bhatia, K. T.: Why do some Post-Tropical Cyclones
impact Europe?, Mon. Weather Rev., 150, 2553–2571, 2022b.
Seager, R., Cane, M., Henderson, N., Lee, D. E., Abernathey, R., and Zhang,
H.: Strengthening tropical Pacific zonal sea surface temperature gradient
consistent with rising greenhouse gases, Nat. Clim. Chang., 9, 517–522,
https://doi.org/10.1038/s41558-019-0505-x, 2019.
Stewart, S. R.: Tropical Cyclone Report: Hurricane Ophelia, National Hurricane Center, 1–32,
https://www.nhc.noaa.gov/data/tcr/AL172017_Ophelia.pdf (last access: 16 November 2022), 2018.
Studholme, J., Fedorov, A. V., Gulev, S. K., Emanuel, K., and Hodges, K.:
Poleward expansion of tropical cyclone latitudes in warming climates, Nat.
Geosci., 15, 14–28, https://doi.org/10.1038/s41561-021-00859-1, 2022.
Sugi, M., Noda, A., and Sato, N.: Influence of the global warming on
tropical cyclone climatology an experiment with the JMA global model, J.
Meteorol. Soc. Jpn., 80, 249–272, https://doi.org/10.2151/jmsj.80.249,
2002.
Sugi, M., Yamada, Y., Yoshida, K., Mizuta, R., Nakano, M., Kodama, C., and
Satoh, M.: Future Changes in the Global Frequency of Tropical Cyclone Seeds,
Sci. Online Lett. Atmos., 16, 70–74, https://doi.org/10.2151/sola.2020-012,
2020.
Tatebe, H., Ogura, T., Nitta, T., Komuro, Y., Ogochi, K., Takemura, T., Sudo, K., Sekiguchi, M., Abe, M., Saito, F., Chikira, M., Watanabe, S., Mori, M., Hirota, N., Kawatani, Y., Mochizuki, T., Yoshimura, K., Takata, K., O'ishi, R., Yamazaki, D., Suzuki, T., Kurogi, M., Kataoka, T., Watanabe, M., and Kimoto, M.: Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6, Geosci. Model Dev., 12, 2727–2765, https://doi.org/10.5194/gmd-12-2727-2019, 2019.
Thorncroft, C. and Hodges, K.: African easterly wave variability and its
relationship to Atlantic tropical cyclone activity, J. Climate, 14,
1166–1179, https://doi.org/10.1175/1520-0442(2001)014<1166:AEWVAI>2.0.CO;2, 2001.
Ting, M., Camargo, S. J., Li, C., and Kushnir, Y.: Natural and Forced North
Atlantic Hurricane Potential Intensity Change in CMIP5 Models, J. Climate,
28, 3926–3942, https://doi.org/10.1175/jcli-d-14-00520.1, 2015.
Vecchi, G. A., Delworth, T., Gudgel, R., Kapnick, S., Rosati, A.,
Wittenberg, A. T., Zeng, F., Anderson, W., Balaji, V., Dixon, K., Jia, L.,
Kim, H. S., Krishnamurthy, L., Msadek, R., Stern, W. F., Underwood, S. D.,
Villarini, G., Yang, X., and Zhang, S.: On the seasonal forecasting of
regional tropical cyclone activity, J. Climate, 27, 7994–8016,
https://doi.org/10.1175/JCLI-D-14-00158.1, 2014.
Vecchi, G. A., Delworth, T. L., Murakami, H., Underwood, S. D., Wittenberg, A. T., Zeng, F., Zhang, W., Baldwin, J. W., Bhatia, K. T., Cooke, W., He, J., Kapnick, S. B., Knutson, T. R., Villarini, G., van der Wiel, K., Anderson, W., Balaji, V., Chen, J.-H., Dixon, K. W., Gudgel, R., Harris, L. M., Jia, L., Johnson, N. C., Lin, S. J., Liu, M., Ng, C. H. J., Rosati, A., Smith, J. A., and Yang, X.: Tropical cyclone sensitivities to CO2 doubling: roles of atmospheric resolution, synoptic variability and background climate changes, Clim. Dynam., 53, 5999–6033, https://doi.org/10.1007/s00382-019-04913-y, 2019.
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.
Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., Colin, J., Guérémy, J.-F., Michou, M., Moine, M.-P., Nabat, P., Roehrig, R., Salas Y Mélia, D., Séférian, R., Valcke, S., Beau, I., Belamari, S., Berthet, S., Cassou, C., Cattiaux, J., Deshayes,
J., Douville, H., Ethé, C., Franchistéguy, L., Geoffroy, O.,
Lévy, C., Madec, G., Meurdesoif, Y., Msadek, R., Ribes, A.,
Sanchez-Gomez, E., Terray, L., and Waldman, R.: Evaluation of CMIP6 DECK
Experiments With CNRM-CM6-1, J. Adv. Model. Earth Syst., 11, 2177–2213,
https://doi.org/10.1029/2019MS001683, 2019.
Walsh, K., Camargo, S. J., Knutson, T. R., Kossin, J. P., Lee, T.-C.,
Murakami, H., and Patricola, C. M.: Tropical cyclones and climate change,
Trop. Cyclone Res. Rev., 8, 240–250,
https://doi.org/10.1016/j.tcrr.2020.01.004, 2019.
Walsh, K. J. E., Camargo, S. J., Vecchi, G. A., Daloz, A. S., Elsner, J.,
Emanuel, K., Horn, M., Lim, Y. K., Roberts, M., Patricola, C., Scoccimarro,
E., Sobel, A. H., Strazzo, S., Villarini, G., Wehner, M., Zhao, M., Kossin,
J. P., La Row, T., Oouchi, K., Schubert, S., Wang, H., Bacmeister, J.,
Chang, P., Chauvin, F., Jablonowski, C., Kumar, A., Murakami, H., Ose, T.,
Reed, K. A., Saravanan, R., Yamada, Y., Zarzycki, C. M., Luigi Vidale, P.,
Jonas, J. A., and Henderson, N.: Hurricanes and climate: The U.S. Clivar
working group on hurricanes, B. Am. Meteorol. Soc., 96, 997–1017,
https://doi.org/10.1175/BAMS-D-13-00242.1, 2015.
Yamada, Y., Kodama, C., Satoh, M., Sugi, M., Roberts, M. J., Mizuta, R.,
Noda, A. T., Nasuno, T., Nakano, M., and Vidale, P. L.: Evaluation of the
contribution of tropical cyclone seeds to changes in tropical cyclone
frequency due to global warming in high-resolution multi-model ensemble
simulations, Prog. Earth Planet. Sci., 8, 1–17, 2021.
Yang, W., Hsieh, T.-L., and Vecchi, G. A.: Hurricane annual cycle controlled by both seeds and genesis probability, P. Natl. Acad. Sci. USA, 118, , https://doi.org/10.1073/pnas.2108397118, 2021.
Short summary
Post-tropical cyclones (PTCs) can bring severe weather to Europe. By tracking and identifying PTCs in five global climate models, we investigate how the frequency and intensity of PTCs may change across Europe by 2100. We find no robust change in the frequency or intensity of Europe-impacting PTCs in the future. This study indicates that large uncertainties surround future Europe-impacting PTCs and provides a framework for evaluating PTCs in future generations of climate models.
Post-tropical cyclones (PTCs) can bring severe weather to Europe. By tracking and identifying...