Articles | Volume 17, issue 16
https://doi.org/10.5194/gmd-17-6137-2024
© 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/gmd-17-6137-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
Philip G. Sansom
Faculty of Environment, Science and Economy, University of Exeter, North Park Road, Exeter, EX4 4QE, UK
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Jennifer L. Catto
CORRESPONDING AUTHOR
Faculty of Environment, Science and Economy, University of Exeter, North Park Road, Exeter, EX4 4QE, UK
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Jacob William Maddison, Jennifer Louise Catto, Sandra Hansen, Ching Ho Justin Ng, and Stefan Siegert
EGUsphere, https://doi.org/10.5194/egusphere-2025-2138, https://doi.org/10.5194/egusphere-2025-2138, 2025
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Strong winds and heavy precipitation in extratropical cyclones can cause significant damage, and also considerable losses. Here, we estimate the worst case scenarios in terms of impacts that could occur in todays climate resulting from wind and precipitation in extratropical cyclones. We find impacts roughly 1.5 times more severe than any in the historical record for 14 countries considered in Northwestern/Central Europe. These damages would incur costs into the billions of pounds for insurers.
Raphaël Rousseau-Rizzi, Shira Raveh-Rubin, Jennifer L. Catto, Alice Portal, Yonatan Givon, and Olivia Martius
Weather Clim. Dynam., 5, 1079–1101, https://doi.org/10.5194/wcd-5-1079-2024, https://doi.org/10.5194/wcd-5-1079-2024, 2024
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We identify situations when rain and wind, rain and wave, or heat and dust hazards co-occur within Mediterranean cyclones. These hazard combinations are associated with risk to infrastructure, risk of coastal flooding and risk of respiratory issues. The presence of Mediterranean cyclones is associated with increased probability of all three hazard combinations. We identify weather configurations and cyclone structures, particularly those associated with specific co-occurrence combinations.
Alice Portal, Shira Raveh-Rubin, Jennifer L. Catto, Yonatan Givon, and Olivia Martius
Weather Clim. Dynam., 5, 1043–1060, https://doi.org/10.5194/wcd-5-1043-2024, https://doi.org/10.5194/wcd-5-1043-2024, 2024
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Mediterranean cyclones are associated with extended rain, wind, and wave impacts. Although beneficial for regional water resources, their passage may induce extreme weather, which is especially impactful when multiple hazards combine together. Here we show how the passage of Mediterranean cyclones increases the likelihood of rain–wind and wave–wind compounding and how compound–cyclone statistics vary by region and season, depending on the presence of specific airflows around the cyclone.
Jacob William Maddison, Jennifer Louise Catto, Sandra Hansen, Ching Ho Justin Ng, and Stefan Siegert
EGUsphere, https://doi.org/10.5194/egusphere-2024-686, https://doi.org/10.5194/egusphere-2024-686, 2024
Preprint archived
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In this work we estimate the impact of the most extreme European windstorms that could occur in the current climate. Using a large dataset of windstorm footprints created seasonal forecast model output, we find windstorms that are more extreme than any previously observed for most of the countries considered. Impacts from these extreme windstorms are expected to be around 1.5 times stronger than the most extreme storm on record. This information is highly valuable in the insurance industry.
Yonatan Givon, Or Hess, Emmanouil Flaounas, Jennifer Louise Catto, Michael Sprenger, and Shira Raveh-Rubin
Weather Clim. Dynam., 5, 133–162, https://doi.org/10.5194/wcd-5-133-2024, https://doi.org/10.5194/wcd-5-133-2024, 2024
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A novel classification of Mediterranean cyclones is presented, enabling a separation between storms driven by different atmospheric processes. The surface impact of each cyclone class differs greatly by precipitation, winds, and temperatures, providing an invaluable tool to study the climatology of different types of Mediterranean storms and enhancing the understanding of their predictability, on both weather and climate scales.
Victoria A. Sinclair and Jennifer L. Catto
Weather Clim. Dynam., 4, 567–589, https://doi.org/10.5194/wcd-4-567-2023, https://doi.org/10.5194/wcd-4-567-2023, 2023
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We studied the relationship between the strength of mid-latitude cyclones and their precipitation, how this may change in the future, and whether it depends of the type of cyclone. The relationship between cyclone strength and precipitation increases in warmer climates and depends strongly on the type of cyclone. For some cyclone types there is no relation between cyclone strength and precipitation. For all cyclone types, precipitation increases with uniform warming and polar amplification.
Matthew D. K. Priestley and Jennifer L. Catto
Weather Clim. Dynam., 3, 337–360, https://doi.org/10.5194/wcd-3-337-2022, https://doi.org/10.5194/wcd-3-337-2022, 2022
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We use the newest set of climate model experiments from CMIP6 to investigate changes to mid-latitude storm tracks and cyclones from global warming. The overall number of cyclones will decrease. However in winter there will be more of the most intense cyclones, and these intense cyclones are likely to be stronger. Cyclone wind speeds will increase in winter, and as a result the area of strongest wind speeds will increase. By 2100 the area of strong wind speeds may increase by over 30 %.
Cited articles
Berry, G., Jakob, C., and Reeder, M.: Recent global trends in atmospheric fronts, Geophys. Res. Lett., 38, 1–6, https://doi.org/10.1029/2011GL049481, 2011a. a, b
Bitsa, E., Flocas, H. A., Kouroutzoglou, J., Galanis, G., Hatzaki, M., Latsas, G., Rudeva, I., and Simmonds, I.: A Mediterranean cold front identification scheme combining wind and thermal criteria, Int. J. Climatol., 41, 6497–6510, https://doi.org/10.1002/joc.7208, 2021. a
Browning, K. A.: Conceputal Models of Precipitation Systems, Weather Forecast., 1, 23–41, https://doi.org/10.1175/1520-0434(1986)001<0023:CMOPS>2.0.CO;2, 1986. a
Browning, K. A.: The sting at the end of the tail: Damaging winds associated with extratropical cyclones, Q. J. Roy. Meteor. Soc., 130, 375–399, https://doi.org/10.1256/qj.02.143, 2004. a
Catto, J. L. and Dowdy, A. J.: Understanding compound hazards from a weather system perspective, Weather and Climate Extremes, 32, 100313, https://doi.org/10.1016/j.wace.2021.100313, 2021. a, b, c
Catto, J. L. and Pfahl, S.: The importance of fronts for extreme precipitation, J. Geophys. Res.-Atmos., 118, 10791–10801, https://doi.org/10.1002/jgrd.50852, 2013. a, b, c
Catto, J. L. and Raveh-Rubin, S.: Climatology and dynamics of the link between dry intrusions and cold fronts during winter. Part I: global climatology, Clim. Dynam., 53, 1873–1892, https://doi.org/10.1007/s00382-019-04745-w, 2019. a
Catto, J. L., Jakob, C., Berry, G., and Nicholls, N.: Relating global precipitation to atmospheric fronts, Geophys. Res. Lett., 39, 1–6, https://doi.org/10.1029/2012GL051736, 2012. a, b
Catto, J. L., Nicholls, N., Jakob, C., and Shelton, K. L.: Atmospheric fronts in current and future climates, Geophys. Res. Lett., 41, 7642–7650, https://doi.org/10.1002/2014GL061943, 2014. a, b
Catto, J. L., Ackerley, D., Booth, J. F., Champion, A. J., Colle, B. A., Pfahl, S., Pinto, J. G., Quinting, J. F., and Seiler, C.: The Future of Midlatitude Cyclones, Current Climate Change Reports, 5, 407–420, https://doi.org/10.1007/s40641-019-00149-4, 2019. a
Davies-Jones, R.: An efficient and accurate method for computing the wet-bulb temperature along pseudoadiabats, Mon. Weather Rev., 136, 2764–2785, https://doi.org/10.1175/2007MWR2224.1, 2008. a, b
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a, b
ECMWF: Part IV: Physical processes, in: IFS Documentation CY47R3, ECMWF, https://doi.org/10.21957/eyrpir4vj, 2021. a
FORTRAN 77: ANSI x3.9-1978. American National Standard – Programming Language FORTRAN, American National Standards Institute, New York, New York, https://nvlpubs.nist.gov/nistpubs/Legacy/FIPS/fipspub69-1.pdf (last access: 15 August 2024), 1978. 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
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023. a
Hewson, T. D.: Objective fronts, Meteorol. Appl., 5, 37–65, https://doi.org/10.1017/S1350482798000553, 1998. a
Hewson, T. D.: Objective identification of fronts, frontal waves and potential waves, in: Cost Action 78 Final Report – Improvement of Nowcasting Techniques, edited by: Lagouvardos, K., Liljas, E., Conway, B., and Sunde, J., European Commission EUR 19544, Cambridge University Press, Luxembourg, 285–290, 2001. a
Hewson, T. D. and Titley, H. A.: Objective identification, typing and tracking of the complete life-cycles of cyclonic features at high spatial resolution, Meteorol. Appl., 17, 355–381, https://doi.org/10.1002/met.204, 2010. a, b, c
Hope, P., Keay, K., Pook, M., Catto, J. L., Simmonds, I., Mills, G., Mcintosh, P., Risbey, J., and Berry, G.: A comparison of automated methods of front recognition for climate studies: A case study in southwest Western Australia, Mon. Weather Rev., 142, 343–363, https://doi.org/10.1175/MWR-D-12-00252.1, 2014. a
Jenkner, J., Sprenger, M., Schwenk, I., Schwierz, C., Dierer, S., and Leuenberger, D.: Detection and climatology of fronts in a high-resolution model reanalysis over the Alps, Meteorol. Appl., 17, 1–18, https://doi.org/10.1002/met.142, 2010. a, b, c
Leung, L. R., Boos, W. R., Catto, J. L., A. DeMott, C., Martin, G. M., Neelin, J. D., O'Brien, T. A., Xie, S., Feng, Z., Klingaman, N. P., Kuo, Y., Lee, R. W., Martinez-Villalobos, C., Vishnu, S., Priestley, M. D. K., Tao, C., and Zhou, Y.: Exploratory Precipitation Metrics: Spatiotemporal Characteristics, Process-Oriented, and Phenomena-Based, J. Climate, 35, 3659–3686, https://doi.org/10.1175/JCLI-D-21-0590.1, 2022. a
NCL: The NCAR Command Language, UCAR/NCAR/CISL/TDD, Boulder, Colorado, https://doi.org/10.5065/D6WD3XH5, 2011. a
Papritz, L., Pfahl, S., Rudeva, I., Simmonds, I., Sodemann, H., and Wernli, H.: The Role of Extratropical Cyclones and Fronts for Southern Ocean Freshwater Fluxes, J. Climate, 27, 6205–6224, https://doi.org/10.1175/JCLI-D-13-00409.1, 2014. a
Parfitt, R., Czaja, A., Minobe, S., and Kuwano-Yoshida, A.: The atmospheric frontal response to SST perturbations in the Gulf Stream region, Geophys. Res. Lett., 43, 2299–2306, https://doi.org/10.1002/2016GL067723, 2016. a
Parfitt, R., Czaja, A., and Kwon, Y.-O.: The impact of SST resolution change in the ERA-Interim reanalysis on wintertime Gulf Stream frontal air-sea interaction, Geophys. Res. Lett., 44, 3246–3254, https://doi.org/10.1002/2017GL073028, 2017a. a
Parfitt, R., Czaja, A., and Seo, H.: A simple diagnostic for the detection of atmospheric fronts, Geophys. Res. Lett., 44, 4351–4358, https://doi.org/10.1002/2017GL073662, 2017b. a, b, c, d
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, https://www.r-project.org (last access: November 2022), 2021. a
Raveh-Rubin, S. and Catto, J. L.: Climatology and dynamics of the link between dry intrusions and cold fronts during winter, Part II: Front-centred perspective, Clim. Dynam., 53, 1893–1909, https://doi.org/10.1007/s00382-019-04793-2, 2019. a, b
Renard, R. J. and Clarke, L. C.: Experiments in Numerical Objective Frontal Analysis 1, Mon. Weather Rev., 93, 547–556, https://doi.org/10.1175/1520-0493(1965)093<0547:einofa>2.3.co;2, 1965. a
Rüdisühli, S., Sprenger, M., Leutwyler, D., Schär, C., and Wernli, H.: Attribution of precipitation to cyclones and fronts over Europe in a kilometer-scale regional climate simulation, Weather Clim. Dynam., 1, 675–699, https://doi.org/10.5194/wcd-1-675-2020, 2020. a
Satyamurty, P. and de Mattos, L. F.: Climatological Lower Tropospheric Frontogenesis in the Midlatitudes Due to Horizontal Deformation and Divergence, Mon. Weather Rev., 117, 1355–1364, https://doi.org/10.1175/1520-0493(1989)117<1355:CLTFIT>2.0.CO;2, 1989. a
Schemm, S., Rudeva, I., and Simmonds, I.: Extratropical fronts in the lower troposphere-global perspectives obtained from two automated methods, Q. J. Roy. Meteor. Soc., 141, 1686–1698, https://doi.org/10.1002/qj.2471, 2015. a
Schemm, S., Sprenger, M., Martius, O., Wernli, H., and Zimmer, M.: Increase in the number of extremely strong fronts over Europe? A study based on ERA-Interim reanalysis (1979–2014), Geophys. Res. Lett., 44, 553–561, https://doi.org/10.1002/2016GL071451, 2017. a
Simmonds, I., Keay, K., and Bye, J. A. T.: Identification and climatology of Southern Hemisphere mobile fronts in a modern reanalysis, J. Climate, 25, 1945–1962, https://doi.org/10.1175/JCLI-D-11-00100.1, 2012. a
Sinclair, V. A. and Keyser, D.: Force balances and dynamical regimes of numerically simulated cold fronts within the boundary layer, Q. J. Roy. Meteor. Soc., 141, 2148–2164, https://doi.org/10.1002/qj.2512, 2015. a
Soster, F. and Parfitt, R.: On Objective Identification of Atmospheric Fronts and Frontal Precipitation in Reanalysis Datasets, J. Climate, 35, 4513–4534, https://doi.org/10.1175/JCLI-D-21-0596.1, 2022. a
Thomas, C. and Schultz, D.: What are the Best Thermodynamic Quantity and Function to Define a Front in Gridded Model Output?, B. Am. Meteorol. Soc., 100, 873–895, https://doi.org/10.1175/BAMS-D-18-0137.1, 2019. a
Uppala, S. M., Kallberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Holm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., McNally, A. P., Mahfouf, J. F., Morcrette, J. J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40 re-analysis, Q. J. Roy. Meteor. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176, 2005. a
Short summary
Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We...