Articles | Volume 7, issue 3
https://doi.org/10.5194/wcd-7-1525-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-7-1525-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multi-model high-resolution analysis of Tropical-Like Cyclone Daniel with WRF and ICON: peculiarities and sensitivity to convection schemes
Piero Serafini
CORRESPONDING AUTHOR
UNIVAQ (DSFC) – University of L'Aquila, Department of Physical and Chemical Sciences, L'Aquila, Italy
CETEMPS – Center of Excellence in Telesensing of Environment and Model Prediction of Severe Events, L'Aquila, Italy
Antonio Ricchi
UNIVAQ (DSFC) – University of L'Aquila, Department of Physical and Chemical Sciences, L'Aquila, Italy
CETEMPS – Center of Excellence in Telesensing of Environment and Model Prediction of Severe Events, L'Aquila, Italy
Chiara Marsigli
ARPAE – Regional Agency for Environmental Protection in Emilia-Romagna, Bologna, Italy
Cristiano D'Amico
UNIVAQ (DSFC) – University of L'Aquila, Department of Physical and Chemical Sciences, L'Aquila, Italy
CETEMPS – Center of Excellence in Telesensing of Environment and Model Prediction of Severe Events, L'Aquila, Italy
Matteo Nastasi
UNIVAQ (DSFC) – University of L'Aquila, Department of Physical and Chemical Sciences, L'Aquila, Italy
CETEMPS – Center of Excellence in Telesensing of Environment and Model Prediction of Severe Events, L'Aquila, Italy
Renata Pelosini
ARPAP – Regional Agency for Environmental Protection in Piemonte, Torino, Italy
Rossella Ferretti
UNIVAQ (DSFC) – University of L'Aquila, Department of Physical and Chemical Sciences, L'Aquila, Italy
CETEMPS – Center of Excellence in Telesensing of Environment and Model Prediction of Severe Events, L'Aquila, Italy
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EGUsphere, https://doi.org/10.5194/egusphere-2026-2285, https://doi.org/10.5194/egusphere-2026-2285, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Florian Pantillon, Silvio Davolio, Elenio Avolio, Carlos Calvo-Sancho, Diego Saul Carrió, Stavros Dafis, Emanuele Silvio Gentile, Juan Jesus Gonzalez-Aleman, Suzanne Gray, Mario Marcello Miglietta, Platon Patlakas, Ioannis Pytharoulis, Didier Ricard, Antonio Ricchi, Claudio Sanchez, and Emmanouil Flaounas
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Cyclone Ianos of September 2020 was a high-impact but poorly predicted medicane (Mediterranean hurricane). A community effort of numerical modelling provides robust results to improve prediction. It is found that the representation of local thunderstorms controlled the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help us understand the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
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We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Michele Salmi, Chiara Marsigli, and Manfred Dorninger
Adv. Sci. Res., 19, 29–38, https://doi.org/10.5194/asr-19-29-2022, https://doi.org/10.5194/asr-19-29-2022, 2022
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High resolution, probabilistic weather prediction systems are increasingly able to model lightning activity with unprecedented accuracy. Is the probabilistic approach skillful when applied to localized, deep convection? This work shows that the ensemble prediction system maintained by the German Weather Service is able to provide a useful forecast of lightning activity at a scale of around 200 km and that the probabilistic approach can anticipate possible lack of accuracy in both time and space.
Cited articles
Argüeso, D., Marcos, M., and Amores, A.: Storm Daniel fueled by anomalously high sea surface temperatures in the Mediterranean, npj Clim. Atmos. Sci., 7, 307, https://doi.org/10.1038/s41612-024-00872-2, 2024. a
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell, M. J., Vitart, F., and Balsamo, G.: Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales, Q. J. Roy. Meteor. Soc., 134, 1337–1351, https://doi.org/10.1002/qj.289, 2008. a, b
Biswas, M. K., Bernardet, L., and Dudhia, J.: Sensitivity of hurricane forecasts to cumulus parameterizations in the HWRF model, Geophys. Res. Lett., 41, 9113–9119, https://doi.org/10.1002/2014GL062071, 2014. a
Brumer, S. E., Pantillon, F., Pianezze, J., Le Péru-Morvan, Y., Ragu-Fonta, M., Grand, L., Ricchi, A., Barboni, A., and Bouin, M.-N.: On the Tropical Nature of an Intense Mediterranean Cyclone in the Ocean-Atmosphere System, J. Geophys. Res.-Atmos., 131, https://doi.org/10.1029/2025JD046105, 2026. a
Carniel, C. E., Ricchi, A., Ferretti, R., Curci, G., Miglietta, M. M., Reale, M., Serafini, P., Wellmeyer, E. D., Davolio, S., Zardi, D., and Kantha, L.: A high-resolution climatological study of explosive cyclones in the Mediterranean region: Frequency, intensity and synoptic drivers, Q. J. Roy. Meteor. Soc., 150, 5561–5582, https://doi.org/10.1002/qj.4889, 2024. a
CETEMPS: Center of Excellence in Telesensing of Environment and Model Prediction of Severe Event (CETEMPS) – Meteorological Modeling, https://cetemps.aquila.infn.it/modellistica/ (last access: 22 July 2026), 2026. a
Choi, H.-J. and Hong, S.-Y.: An updated subgrid orographic parameterization for global atmospheric forecast models, J. Geophys. Res.-Atmos., 120, 12445–12457, https://doi.org/10.1002/2015JD024230, 2015. a, b
CMCC: Euro-Mediterranean Center on Climate Change (CMCC) – Weather Research and Forecasting (WRF) Model, https://www.cmcc.it/models/wrf (last access: 22 July 2026), 2026. a
Deutscher Wetterdienst: Working with the ICON model: ICON Tutorial 2025, p. 107, Tech. rep., Deutscher Wetterdienst (DWD), https://doi.org/10.5676/DWD_pub/nwv/icon_tutorial2025, 2025. a
Diakakis, M., Sarantopoulou, A., Gogou, M., Filis, C., Nastos, P., Kapris, I., Vassilakis, E., Konsolaki, A., and Lekkas, E.: Cascade effects induced by extreme storms and floods: The case of storm daniel (2023) in greece, Water, 17, 912, https://doi.org/10.3390/w17070912, 2025. a
Doiteau, B., Pantillon, F., Plu, M., Descamps, L., and Rieutord, T.: Systematic evaluation of the predictability of different Mediterranean cyclone categories, Weather Clim. Dynam., 5, 1409–1427, https://doi.org/10.5194/wcd-5-1409-2024, 2024. a
DWD: Numerical Weather Prediction Forecast Data, Deutscher Wetterdienst (DWD), https://www.dwd.de/EN/ourservices/nwp_forecast_data/nwp_forecast_data.html (last access: 22 July 2026), 2026. a
ECMWF: IFS Documentation CY48R1 – Part II: Data Assimilation, 2, ECMWF, https://doi.org/10.21957/a744f32e74, 2023. a
Emanuel, K.: 100 years of progress in tropical cyclone research, Meteor. Mon., 59, 15–1, https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0016.1, 2018. a, b, c
Flaounas, E., Dafis, S., Davolio, S., Faranda, D., Ferrarin, C., Hartmuth, K., Hochman, A., Koutroulis, A., Khodayar, S., Miglietta, M. M., Pantillon, F., Patlakas, P., Sprenger, M., and Thurnherr, I.: Dynamics, predictability, impacts and climate change considerations of the catastrophic Mediterranean Storm Daniel (2023), Weather Clim. Dynam., 6, 1515–1538, https://doi.org/10.5194/wcd-6-1515-2025, 2025. a, b, c
Han, J. and Pan, H.-L.: Revision of convection and vertical diffusion schemes in the NCEP Global Forecast System, Weather Forecast., 26, 520–533, https://doi.org/10.1175/WAF-D-10-05038.1, 2011. a, b
Hart, R. E.: A Cyclone Phase Space Derived from Thermal Wind and Thermal Asymmetry, Mon. Weather Rev., 131, 585–616, https://doi.org/10.1175/1520-0493(2003)131<0585:ACPSDF>2.0.CO;2, 2003. a, b
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 single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023a. a, b
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, 2023b. a, b
Hewson, T., Ashoor, A., Boussetta, S., Emanuel, K., Lagouvardos, K., Lavers, D., Magnusson, L., Pillosu, F., and Zsoter, E.: Medicane Daniel: An extraordinary cyclone with devastating impacts, ECMWF Newsletters, 179, 33–47, https://doi.org/10.21957/th3wxk861d, 2024. a
Hogan, R. J. and Bozzo, A.: A flexible and efficient radiation scheme for the ECMWF model, J. Adv. Model. Earth Sy., 10, 1990–2008, https://doi.org/10.1029/2018MS001364, 2018. a, b
Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with an explicit treatment of entrainment processes, Mon. Weather Rev., 134, 2318–2341, https://doi.org/10.1175/MWR3199.1, 2006. a, b
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Tan, J.: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07, Goddard Earth Sciences Data and Information Services Center (GES DISC), Greenbelt, MD [data set], https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHH_07/summary?keywords=%22IMERG%20final%22 (last access: 12 November 2025), 2023. a, b
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res.-Atmos., 113, https://doi.org/10.1029/2008JD009944, 2008. a, b
IOM: Libya – Storm Daniel Flash Update 8 (13 October 2023), Global Data Institute Displacement Tracking Matrix, International Organization for Migration, https://dtm.iom.int/fr/node/30081 (last access: 18 February 2026), 2023. a
ItaliaMeteo: National Agency for Meteorology and Climatology (ItaliaMeteo) – Short-Range Forecasts for Italy, https://www.agenziaitaliameteo.it/meteo/previsioni/previsioni-a-breve-termine-italia/ (last access: 22 July 2026), 2026. a
Katsanos, D., Retalis, A., Kalogiros, J., Psiloglou, B. E., Roukounakis, N., and Anagnostou, M.: Performance Evaluation of Satellite Precipitation Products During Extreme Events – The Case of the Medicane Daniel in Thessaly, Greece, Remote Sens., 16, 4216, https://doi.org/10.3390/rs16224216, 2024. a
Khodayar, S., Kushta, J., Catto, J. L., Dafis, S., Davolio, S., Ferrarin, C., Flaounas, E., Groenemeijer, P., Hatzaki, M., Hochman, A., Kotroni, V., Landa, J., Láng-Ritter, I., Lazoglou, G., Liberato, M. L. R., Miglietta, M. M., Papagiannaki, K., Patlakas, P., Stojanov, R., and Zittis, G.: Mediterranean Cyclones in a Changing Climate: A Review on Their Socio-Economic Impacts, Rev. Geophys., 63, https://doi.org/10.1029/2024RG000853, 2025. a
Kolios, S. and Papavasileiou, N.: Daily Rainfall Patterns During Storm “Daniel” Based on Different Satellite Data, Atmosphere, 15, 1277, https://doi.org/10.3390/atmos15111277, 2024. a
Kwon, Y. C. and Hong, S.-Y.: A mass-flux cumulus parameterization scheme across gray-zone resolutions, Mon. Weather Rev., 145, 583–598, https://doi.org/10.1175/MWR-D-16-0034.1, 2017. a, b
Lagouvardos, K., Kotroni, V., Bezes, A., Koletsis, I., Kopania, T., Lykoudis, S., Mazarakis, N., Papagiannaki, K., and Vougioukas, S.: The automatic weather stations NOANN network of the National Observatory of Athens: operation and database, Geosci. Data J., 4, 4–16, https://doi.org/10.1002/gdj3.44, 2017. a, b
Lim, K.-S. S. and Hong, S.-Y.: Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models, Mon. Weather Rev., 138, 1587–1612, https://doi.org/10.1175/2009MWR2968.1, 2010. a, b
MeteoGalicia: Galician Meteorological Service (MeteoGalicia) – Numerical Prediction Models, http://www.meteogalicia.gal/web/modelos-numericos (last access: 22 July 2026), 2026. a
MeteoSwiss: Federal Office of Meteorology and Climatology (MeteoSwiss) – ICON Numerical Weather Prediction System, https://www.meteosvizzera.admin.ch/tempo/sistemi-di-allerta-e-previsione/sistema-di-previsione-numerica-icon.html (last access: 22 July 2026), 2026. a
Miglietta, M. M.: Mediterranean Tropical-Like Cyclones (Medicanes), Atmosphere, 10, 206, https://doi.org/10.3390/atmos10040206, 2019. a
Miglietta, M. M. and Rotunno, R.: Development mechanisms for Mediterranean tropical‐like cyclones (medicanes), Q. J. Roy. Meteor. Soc., 145, 1444–1460, https://doi.org/10.1002/qj.3503, 2019. a
Miglietta, M. M., Mastrangelo, D., and Conte, D.: Influence of physics parameterization schemes on the simulation of a tropical-like cyclone in the Mediterranean Sea, Atmos. Res., 153, 360–375, https://doi.org/10.1016/j.atmosres.2014.09.008, 2015. a, b
Miglietta, M. M., Buscemi, F., Dafis, S., Papa, A., Tiesi, A., Conte, D., Davolio, S., Flaounas, E., Levizzani, V., and Rotunno, R.: A high-impact meso-beta vortex in the Adriatic Sea, Q. J. Roy. Meteor. Soc., 149, 637–656, https://doi.org/10.1002/qj.4432, 2023. a
Miglietta, M. M., Flaounas, E., González-Alemán, J. J., Panegrossi, G., Gaertner, M. A., Pantillon, F., Pasquero, C., Schultz, D. M., D'Adderio, L. P., Dafis, S., Husson, R., Ricchi, A., Carrió Carrió, D. S., Davolio, S., Fita, L., Picornell, M. Á., Pytharoulis, I., Raveh-Rubin, S., Scoccimarro, E., Bernini, L., Cavicchia, L., Conte, D., Ferretti, R., Flocas, H., Gutiérrez-Fernández, J., Hatzaki, M., Homar Santaner, V., Jansà, A., and Patlakas, P.: Defining medicanes: Bridging the knowledge gap between tropical and extratropical cyclones in the Mediterranean, B. Am. Meteorol. Soc., 106, E1955–E1971, https://doi.org/10.1175/BAMS-D-24-0289.1, 2025. a, b, c, d
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res.-Atmos., 116, https://doi.org/10.1029/2010JD015140, 2011. a, b
Orr, A., Bechtold, P., Scinocca, J., Ern, M., and Janiskova, M.: Improved middle atmosphere climate and forecasts in the ECMWF model through a nonorographic gravity wave drag parameterization, J. Climate, 23, 5905–5926, https://doi.org/10.1175/2010JCLI3490.1, 2010. a, b
Picornell, M. A., Campins, J., and Jansà, A.: Detection and thermal description of medicanes from numerical simulation, Nat. Hazards Earth Syst. Sci., 14, 1059–1070, https://doi.org/10.5194/nhess-14-1059-2014, 2014. a
Pytharoulis, I., Kartsios, S., Tegoulias, I., Feidas, H., Miglietta, M. M., Matsangouras, I., and Karacostas, T.: Sensitivity of a mediterranean tropical-like cyclone to physical parameterizations, Atmosphere, 9, 436, https://doi.org/10.3390/atmos9110436, 2018. a, b
Ricchi, A., Miglietta, M., Barbariol, F., Benetazzo, A., Bergamasco, A., Bonaldo, D., Cassardo, C., Falcieri, F., Modugno, G., Russo, A., Sclavo, M., and Carniel, S.: Sensitivity of a Mediterranean Tropical-Like Cyclone to Different Model Configurations and Coupling Strategies, Atmosphere, 8, 92, https://doi.org/10.3390/atmos8050092, 2017. a, b
Ricchi, A., Miglietta, M. M., Bonaldo, D., Cioni, G., Rizza, U., and Carniel, S.: Multi-Physics Ensemble versus Atmosphere–Ocean Coupled Model Simulations for a Tropical-Like Cyclone in the Mediterranean Sea, Atmosphere, 10, 202, https://doi.org/10.3390/atmos10040202, 2019. a, b
Roberts, N. M. and Lean, H. W.: Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events, Mon. Weather Rev., 136, 78–97, https://doi.org/10.1175/2007MWR2123.1, 2008. a, b
Saraceni, M., Silvestri, L., Bechtold, P., and Bongioannini Cerlini, P.: Mediterranean tropical-like cyclone forecasts and analysis using the ECMWF ensemble forecasting system with physical parameterization perturbations, Atmos. Chem. Phys., 23, 13883–13909, https://doi.org/10.5194/acp-23-13883-2023, 2023. a, b
Schimanke, S., Ridal, M., Le Moigne, P., Berggren, L., Undén, P., Randriamampianina, R., Andrea, U., Bazile, E., Bertelsen, A., Brousseau, P., Dahlgren, P., Edvinsson, L., El Said, A., Glinton, M., Hopsch, S., Isaksson, L., Mladek, R., Olsson, E., Verrelle, A., and Wang, Z. Q.: CERRA sub-daily regional reanalysis data for Europe on single levels from 1984 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.622a565a, 2021. a
Seifert, A. and Beheng, K. D.: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys., 92, 45–66, https://doi.org/10.1007/s00703-005-0112-4, 2006. a, b
Serafini, P.: Ser-Piero/HIMPACT-cyclones-tracker (Version v1.6), Zenodo [code], https://doi.org/10.5281/zenodo.19695732, 2026. a
Skamarock, W., Klemp, J., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D., and Huang, X.-Y.: A Description of the Advanced Research WRF Model Version 4.3, NCAR Technical Notes, https://doi.org/10.5065/1dfh-6p97, 2021. a
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in large-scale models, Mon. Weather Rev., 117, 1779–1800, https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a, b
Tous, M. and Romero, R.: Medicanes: cataloguing criteria and exploration of meteorological environments, Tethys, https://www.tethys.cat/en/article/medicanes-cataloguing-criteria-and-exploration-meteorological-environments (last access: 15 July 2026), 2011. a
WMO: Storm Daniel leads to extreme rain and floods in Mediterranean, heavy loss of life in Libya, World Meteorological Organization, https://wmo.int/media/news/storm-daniel-leads-extreme-rain-and-floods-mediterranean-heavy-loss-of-life-libya (last access: 2 February 2026), 2023. a
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Short summary
We studied the 2023 Mediterranean Hurricane Daniel, an extreme storm that is difficult to predict. Using two high-resolution weather models, we analysed how different representations of clouds affect the results. Although the storm's path was clear, the intensity of the wind and rain varied significantly. The results show that precise settings are vital for effective warnings, improving the ability to predict these rare weather events to better protect the region.
We studied the 2023 Mediterranean Hurricane Daniel, an extreme storm that is difficult to...