Preprints
https://doi.org/10.5194/egusphere-2026-4757
https://doi.org/10.5194/egusphere-2026-4757
13 Aug 2026
 | 13 Aug 2026
Status: this preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).

Contrasting sensitivities of Mediterranean cyclone forecasts to model resolution and physics across cyclone types

Andressa Andrade Cardoso, Suzanne L. Gray, Ambrogio Volonté, Ben J. Harvey, and Claudio Sánchez

Abstract. Hazardous Mediterranean cyclones, including tropical-like medicanes, produce some of the most damaging wind and rainfall events in southern Europe, yet their prediction remains challenging because they are often small in scale and their evolution can be strongly controlled by diabatic processes. While previous research has assessed the role of diabatic processes in individual case studies and/or using resolutions that require parametrization of convection, it remains unclear whether the sensitivity of modelled Mediterranean cyclones to explicit representation of convection is robust across cyclone types. Using a consistent multi-case framework, we identify systematic rather than case-dependent sensitivities. Simulations of seven hazardous MedCys, with a range of characteristics, are performed using four limited-area configurations of the Met Office weather forecast model downscaled from ECMWF IFS analyses. The currently operational physics packages for the global (GAL9) and limited area (RAL3) versions of the model are used with 12-km and convection-permitting, 2.2-km grid spacing, respectively; an experimental package with the scale-aware convection scheme, CoMorph, is also used at both resolutions to cleanly identify resolution dependence.

Sensitivity of dynamical variables and hazards to model configuration depends strongly on cyclone type, with medicanes exhibiting substantially greater and more robust dependence than more extratropical systems. The 2.2 km CoMorph configuration consistently over-intensifies medicanes, producing much lower minimum mean-sea-level pressures, and stronger winds and gusts than other simulations, especially for medicanes Ianos and Apollo. In contrast, the 12-km GAL9 configuration generally produces the weakest medicanes and tracks that is displaced eastward or southward; these biases are reduced using the 12-km CoMorph configuration. An in-depth analysis of medicane Ianos, which deepens by at least 20 hPa more in the 2.2-km CoMorph simulation than in the other simulations is presented. This CoMorph simulation yields a Ianos with a stronger potential vorticity tower, ascent and latent heat fluxes, and an eyewall structure resembling a tropical cyclone. These results demonstrate that the forecast skill of hazardous Mediterranean cyclones depends critically on the interaction between model resolution and physical parameterisations, implying that improvements in kilometre-scale forecasting require advances in model physics as well as increased resolution.

Competing interests: One of the co-authors is a member of the editorial board of Weather and Climate Dynamics.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Andressa Andrade Cardoso, Suzanne L. Gray, Ambrogio Volonté, Ben J. Harvey, and Claudio Sánchez

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Andressa Andrade Cardoso, Suzanne L. Gray, Ambrogio Volonté, Ben J. Harvey, and Claudio Sánchez
Andressa Andrade Cardoso, Suzanne L. Gray, Ambrogio Volonté, Ben J. Harvey, and Claudio Sánchez
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Short summary
We studied whether high-resolution weather models that simulate thunderstorm clouds directly, rather than estimating their effects, improve forecasts of hazardous Mediterranean storms. Unlike more typical Mediterranean storms, tropical-cyclone-like medicanes became much stronger in the high-resolution simulations. However, the results also depended on how physical processes were represented, showing that more accurate forecasts require both better model design and higher resolution.
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