Ambrogio Volonté

Machine‐learning weather prediction (MLWP) has emerged as a powerful new forecasting tool, with the potential to complement or even replace numerical weather prediction (NWP) in early warning systems. MLWP models are computationally cheap once trained, offering more timely, accessible, and energy‐efficient forecasts than NWP. Yet their ability to capture weather extremes, particularly strong winds associated with extra‐tropical cyclones, remains insufficiently understood. This study provides the first comprehensive evaluation of MLWP performance for dynamically diverse UK windstorms, addressing a critical evidence gap before these models can be responsibly deployed in weather risk management. We evaluate eight state‐of‐the‐art MLWP models against reanalysis, NWP analysis, and an operational NWP ensemble for six contrasting UK cyclones from winter 2023/24. We find substantial inter‐storm and inter‐model variability in forecast skill at 24‐h lead time. Forecast accuracy is found to be linked to the underlying atmospheric dynamics and spatial scales of the wind‐producing features: wind maxima associated with mesoscale structures are systematically underestimated across all MLWP models. Significant variability is also found in the representation of mesoscale storm structure, and the highest‐resolution MLWP model (Aurora‐0.1) does not deliver uniform improvements across the cyclone set. In‐depth analysis of two mature Shapiro–Keyser cyclones reveals a consistent tendency for MLWP models to smooth sharp frontal gradients and misrepresent key mesoscale features, including bent‐back warm fronts and frontal‐fracture regions. These deficiencies are physically consistent with the underestimation of localised extreme winds. Overall, our findings highlight the current limitations of MLWP for underpinning UK wind warnings. While these models are not yet suitable to replace NWP for hazardous windstorm prediction entirely, their demonstrated skill in capturing storm tracks and synoptic‐scale evolution points to promising complementary roles in future national weather forecasting and resilience frameworks.

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.

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.

The new film ‘Pressure’ brings renewed attention to one of the most dramatic weather forecasts ever. In June 1944, James Stagg faced the unenviable task of advising whether conditions would allow the D‐Day landings to proceed, with the lives of 160 000 troops and the fate of the war in the balance. Using AIFS‐ENS, the ECMWF machine‐learning ensemble forecast system, we recreate the forecasts in the days before 6th June. Even at short range, AIFS‐ENS moves the storm too rapidly into the Norwegian Sea giving undue confidence for favourable conditions for the landing in Normandy.

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.

Climate change is increasing marine heatwave (MHW) frequency and intensity and intensifying rainfall from extratropical cyclones. Storm Babet, the United Kingdom's most impactful 2023 extratropical cyclone, followed ∼ 7 weeks of MHW conditions in the North Sea and cooled it by ∼ 1 °C. The storm produced extreme rainfall, widespread flooding, and severe coastal erosion across northern regions of the UK. Its prolonged southeasterly winds generated above 8 m significant wave heights and up to 60 cm surge in the North Sea coastline of the UK. We show the MHW was generated at the surface by persistent anticyclonic conditions: clearer skies boosted shortwave heating, weaker winds reduced mixing and latent cooling. Subsequent short spells of cyclonic conditions allowed heat to penetrate at depth and be retained throughout the depth of the shallow North Sea. Using a state-of-the-art regional coupled model, we assess how pre-existing MHW conditions influenced the storm’s evolution and associated hazards. The warm shelf seas boosted evaporation, energised the boundary layer and deepened the cyclone. Indeed, the fast, relatively dry and cold southeasterly low-level jet saw amplified latent and sensible heat fluxes over the MHW. These extremely intense air-sea fluxes led to the decay of the MHW whilst loading the storm with additional moisture. Relative to a cooler ocean counterfactual, the MHW amplified multihazard outcomes across the Northeast of the UK, increasing river discharge (12 %–18 %), coastal wave power (∼ 9 %), and storm surge (∼ 20 %). These results highlight the role of MHWs as amplifiers of multi-hazard storm impacts over the shallow Northwest European Shelf, where extra ocean heat cannot escape to depth.

Sting jets (SJs) are airstreams that can lead to exceptionally strong and damaging winds in intense extratropical cyclones. Whilst there is extensive evidence that SJ descent can be associated with the release of symmetric instability (SI), the individual diabatic processes driving the onset of this instability have not yet been identified and characterised. In our study we tackle this question by analysing a near-operational numerical weather prediction model simulation of Storm Ciarán (1 November 2023), that featured a SJ associated with damaging winds and characterised by the development of SI (indicated by negative potential vorticity, PV) during its evolution. Diabatic tendencies are included in the output of this simulation and are used in our study, including by being traced on Lagrangian trajectories, to illustrate the contributions of the individual diabatic processes to the onset of SI during the evolution of the SJ. The SJ in our simulation is consistent in terms of magnitude, timing and structure with operational forecasts, observations and literature. This SJ develops in an environment characterised by multiple bands of negative PV in the cloud head. It becomes part of one of such filaments as it ascends near the bent-back warm front before descending off the tip of the cloud head. The decrease in PV along the SJ captured by diabatic tendencies is mainly associated with four moist processes: condensation of water vapour, evaporation of cloud water, melting of ice and snow and sublimation of snow. The first three show large variability across trajectories and, particularly for condensation, positive and negative extremes near the trajectories. The limited decrease in PV caused by the sublimation of snow is instead robust and consistent across trajectories. The reduction in buoyancy caused by the cooling from snow sublimation and melting favours the start of SJ descent, rather than the continuation of ascent. Conditions allowing the formation of SJ-like airstreams from negative PV filaments persist as the storm develops and are associated with condensation and melting. Sublimation of snow is only present when conditions are most favourable and lead to the formation of the main SJ. The decrease in PV observed on the SJ trajectories at this time is only partially captured by diabatic tendencies. This substantial discrepancy exposes the limitations of the methodology and can be ascribed to the use of offline trajectories computed from hourly instantaneous model data in an environment characterised by fast-changing and non-linear processes and by fully three-dimensional and small-scale patterns. This is particularly true in the narrow region near the bent-back warm front and the tip of the cloud head, in which the SJ travels as SI develops along it. In summary, in this study we analyse diabatic tendencies in a model simulation of Storm Ciarán, acknowledging their limitations, to reveal the role of different moist processes in causing the onset of instability on a SJ and therefore driving its intensification. The complex interplay between these processes highlights the unique properties of the narrow region in the cloud head in which the SJ develops before descending towards the surface and bringing damaging winds.

Intense extratropical cyclones contain a range of mesoscale features capable of producing hazardous surface wind gusts. Well‑established examples include the cold conveyor belt, the evocatively named sting jet, and lines of locally enhanced convection along narrow cold frontal zones. These features are now routinely represented in convection‑permitting numerical weather prediction models, whose horizontal resolution approaches kilometre scale, and have been extensively studied using both idealised simulations and case‑study analyses.While such models are commonly used in research to investigate storm structure and underlying physical mechanisms, operational meteorologists are uniquely placed to identify emerging or poorly documented features through continual real‑time interrogation of high‑resolution forecasts. In this study, a previously under‑recognised wind‑producing feature is identified within operational forecasts from the UKV, the Met Office’s kilometre‑scale limited area model, during Shapiro–Keyser type extratropical cyclones.This feature occurs within a region of the cyclone traditionally considered to be of relatively low wind hazard, and is therefore not typically a focus of operational attention. Enhanced surface gusts associated with this feature may come as a surprise, particularly as it is not well represented in coarser‑resolution global models. As a result, there is potential for mistimed wind warnings and insufficient preparedness if reliance is placed solely on conceptual models or lower‑resolution guidance. Evidence for the existence of this feature is supported by surface and near‑surface observations during recent high‑impact windstorms.The identification of this feature, together with subsequent investigation of its dynamical mechanisms, frequency of occurrence and predictability, has clear potential to improve the timing and targeting of wind warnings for future storms. More broadly, this work highlights the value of operational experience in complementing research‑driven model analysis and advancing understanding of high‑impact weather.

Sting jets (SJs) are airstreams that can lead to exceptionally strong and damaging winds in intense extratropical cyclones. Whilst there is extensive evidence that SJ descent can be associated with the release of symmetric instability (SI), the individual diabatic processes driving the onset of this instability have not yet been identified and characterised. In our study we tackle this question by analysing a near-operational IFS simulation of Storm Ciarán, that featured a SJ associated with damaging winds and characterised by the development of SI (indicated by negative potential vorticity, PV) during its evolution. Diabatic tendencies are included in the output of this simulation and are used in our study, including by being traced on Lagrangian trajectories, to illustrate the contributions of the individual diabatic processes to the onset of SI during the evolution of the SJ. The SJ in our simulation is consistent in terms of magnitude, timing and structure with operational forecasts, observations and literature. This SJ develops in an environment characterised by multiple bands of negative PV in the cloud head. It becomes part of one of such filaments as it ascends near the bent-back warm front before descending off the tip of the cloud head. The decrease in PV observed on the SJ trajectories at this time is only partially captured by diabatic tendencies. This large discrepancy exposes the limitations of the methodology and can be ascribed to the use of offline trajectories computed from hourly instantaneous model data in an environment characterised by fast-changing and non-linear processes and by fully three-dimensional and small-scale patterns. This is particularly true in the narrow region near the bent-back warm front and the tip of the cloud head, in which the SJ travels as SI develops along it. The decrease in PV along the SJ captured by diabatic tendencies is mainly associated with four moist processes: condensation of water vapour, evaporation of cloud water, melting of ice and snow and sublimation of snow. The first three show large variability across trajectories and, particularly for condensation, positive and negative extremes near the trajectories. The small decrease in PV caused by the sublimation of snow is instead consistent across trajectories. The reduction in buoyancy caused by the cooling from snow sublimation and melting favours the start of SJ descent, rather than the continuation of ascent. In summary, in this study we analyse diabatic tendencies in a model simulation of Storm Ciarán, acknowledging their limitations, to reveal the role of different moist processes in causing the onset of instability on a SJ and therefore driving its intensification. The complex interplay between these processes highlights the unique properties of the narrow region in the cloud head in which the SJ develops before descending towards the surface and bringing damaging winds.

Climate change is increasing marine heatwave (MHW) frequency and intensity and intensifying rainfall from extratropical cyclones. Storm Babet, the United Kingdom’s most impactful 2023 extratropical cyclone, followed ∼7 weeks of MHW conditions in the North Sea and cooled it by ∼1 °C. The storm produced extreme rainfall, widespread flooding, and severe coastal erosion across northern regions of the UK. Its prolonged southeasterly winds generated above 8 m significant wave heights and up to 60 cm surge in the North Sea coastline of the UK. We show the MHW was generated at the surface by persistent anticyclonic conditions: clearer skies boosted shortwave heating, weaker winds reduced mixing and latent cooling. Subsequent short spells of cyclonic conditions allowed heat to penetrate at depth and be retained throughout the depth of the shallow North Sea. Using a state-of-the-art regional coupled model, we assess how pre-existing marine heatwave conditions influenced the storm’s evolution and associated hazards. The warm shelf seas boosted evaporation, energised the boundary layer and deepened the cyclone. Indeed, the fast, relatively dry and cold southeasterly low-level jet saw amplified latent and sensible heat fluxes over the MHW. These extremely intense air-sea fluxes led to the decay of the MHW whilst loading the storm with additional moisture. Relative to a cooler ocean counterfactual, the MHW amplified multihazard outcomes across the Northeast of the UK, increasing river discharge (12–18 %), coastal wave power (∼9 %), and storm surge (∼20 %). These results highlight the role of MHWs as amplifiers of multi-hazard storm impacts over the shallow Northwest European Shelf, where extra ocean heat cannot escape to depth.