Cloud-radiative heating (CRH) affects the dynamics of extratropical cyclones and near-tropopause circulations. Previous studies on the impact of CRH were mostly limited to simulations of idealized baroclinic life cycles. To bridge the gap between idealized studies and practical applications, we investigate the impact of CRH on the dynamics of North Atlantic cyclones. Using the ICOsahedral Nonhydrostatic (ICON) model, we simulate four cyclones during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) field campaign, and apply the Clouds On-Off Klimate model Intercomparison Experiment (COOKIE) method to compare simulations with and without CRH. We find that CRH systematically affects latent heating, vertical motion, and precipitation rates within the ascending regions of the cyclones, and that the impact of CRH is more prominent at upper levels. Furthermore, we investigate the impact of CRH on near-tropopause dynamics by diagnosing the evolution of differences in potential vorticity (PV). Consistent with idealized studies, CRH affects North Atlantic cyclones and PV near the tropopause mainly through changes in latent heating, and subsequently through changes in the divergent and rotational flows. Finally, we perform simulations with different ice optical parameterizations and radiation solvers. These simulations show that uncertainties in CRH can indeed affect the evolution of cyclones and PV near the tropopause. Our study highlights the importance of correctly simulating CRH for model predictions of extratropical cyclones.

How to cite: Keshtgar, B., Voigt, A., and Hoose, C.: Cloud-radiative impact on the dynamics of extratropical cyclones during NAWDEX, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5700, https://doi.org/10.5194/egusphere-egu25-5700, 2025.

We propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low-pressure systems (LPSs) in a given data set. We use the state-of-the-art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high-impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, and tropical-like cyclones (subtropical storm and polar low). The framework thus provides the first global tropical-like cyclones (TLC) detection scheme by detecting similar physical features to TCs among non-tropical system candidates and optimizing detection thresholds against subjective data sets. The vertical cross section composite of the four types of high-impact LPS we detect each shows distinct structural characteristics. 

The classification process involves disentangling high-altitude and drier LPSs, differentiating tropical and non-tropical LPSs using novel criteria, and optimizing for the detection of the four types of high-impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances, and a median error of 6 hours in determining extratropical transition completion time. We demonstrate that the SyCLoPS framework is valuable for investigating various aspects of mid-latitude storms and post-TCs in climate data, such as the evolution of a single storm track at every stage, patterns of storm frequencies, and precipitation or wind influence associated with impactful mid-latitude storms.

How to cite: Han, Y. and Ullrich, P.: The System for Classification of Low-Pressure Systems (SyCLoPS): An All-In-One Objective Framework for Large-Scale Data Sets, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15800, https://doi.org/10.5194/egusphere-egu25-15800, 2025.

We assess the evolution of Northeast Atlantic and German Bight storm activity in the CMIP6 multi-model ensemble, as well as the Max Planck Institute Grand Ensemble with CMIP6 forcing (MPI-GE), using historical forcing and three emission scenarios. We define storm activity as upper percentiles of geostrophic wind speeds, obtained from horizontal gradients of mean sea-level pressure. We detect robust downward trends for Northeast Atlantic storm activity in all scenarios, and weaker but still downward trends for German Bight storm activity. In both the multi-model ensemble and the MPI-GE, we find a projected increase in the frequency of westerly winds over the Northeast Atlantic and northwesterly winds over the German Bight, and a decrease in the frequency of easterly and southerly winds over the respective regions. We also show that despite the projected increase in the frequency of wind directions associated with increased cyclonic activity, the upper percentiles of wind speeds from these directions decrease, leading to lower overall storm activity. Lastly, we detect that the change in wind speeds strongly depends on the region and percentile considered, and that the most extreme storms may become stronger or more likely in the German Bight in a future climate despite reduced overall storm activity.

How to cite: Krieger, D. and Weisse, R.: CMIP6 Multi-model Assessment of Northeast Atlantic and German Bight Storm Activity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9818, https://doi.org/10.5194/egusphere-egu25-9818, 2025.

Most of the day-to-day variability in weather in Europe, including damaging events, is caused by extratropical cyclones (ETCs). ETCs are very different from one another and to more easily study their development, intensity, and structure, various ETC classification schemes have been proposed. Here, we propose an intensity-based scheme in which we first identify necessary ETC intensity measures to describe ETC intensity comprehensively from both dynamical and impact-relevant perspective, and then use them to produce an ETC classification.

ERA5 reanalysis data from 1979 to 2022 was used to track ETCs and compute their intensity measures in the extended winter season (October-March). A total of 7361 ETC tracks were identified in the North Atlantic and Europe. Eleven intensity measures were analysed including 850-hPa relative vorticity, mean sea level pressure, wind speeds at various levels, wind gust, wind footprint, precipitation, and storm severity index. Among the 11 intensity measures, relevant ones were identified by analysing their correlation with each other combined with a sparse principal component analysis (sPCA). The selected measures were used to classify the ETCs by performing a cluster analysis with Gaussian mixture modelling.

Based on the sPCA and relationships between the intensity measures, the set was reduced to 5 measures: 850-hPa relative vorticity, 850-hPa wind speed, wind footprint, precipitation, and storm severity index. Therefore, to describe ETC intensity comprehensively, one needs to use more than one or two intensity measures. The cluster analysis with these 5 measures as input produced 4 discernible clusters. Between these clusters ETCs differed in terms of their intensity, life cycle characteristics, and geographical location. Despite only 9 % of all ETCs belonging to the most intense cluster, it contained 17 out of 21 investigated impactful named storms, which demonstrates the relevance of the classification and its ability to identify potentially impactful ETCs.

How to cite: Cornér, J., Bouvier, C., Doiteau, B., Pantillon, F., and Sinclair, V. A.: Intensity-based classification of North Atlantic and European extratropical cyclones, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10092, https://doi.org/10.5194/egusphere-egu25-10092, 2025.

Extratropical cyclones (ETCs) are the primary drivers of winter precipitation across the United States, accounting for up to 85% of total precipitation. This study uses the GFDL SPEAR models at atmospheric resolutions of 100 km, 50 km, and 25 km to examine how ETC dynamics impact precipitation patterns and biases across the United States. Higher-resolution models reduce ETC-related precipitation biases in the Southwest and Midwest but increase biases in coastal regions, including the West Coast and the Eastern United States. To understand these biases, we decompose ETC-related precipitation biases into those driven by precipitation frequency and intensity. Coastal precipitation biases are mainly due to overestimations of both the occurrence and intensity of precipitation, which are related to ETC frequency and intensity, respectively. In inland areas, biases are largely driven by occurrence bias associated with ETC frequency. Notably, higher-resolution models simulate amplified ETC frequency and intensity biases in coastal regions, while showing a decrease in ETC frequency bias in inland regions. This increase is especially linked to the overestimation of small-scale ETCs, which considerably inflate frequency-driven precipitation bias. Additionally, improvements in AMIP runs suggest that these biases are partly connected to SST bias. These findings emphasize the sensitivity of precipitation representation to ETC dynamics and underscore the importance of addressing resolution-dependent and SST related biases to improve midlatitude precipitation simulations in climate models.

How to cite: Lee, J., Yang, X., and Chang, E.: Resolution-Dependent Impact of Extratropical Cyclones on Winter U.S. Precipitation Bias in the GFDL SPEAR Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14002, https://doi.org/10.5194/egusphere-egu25-14002, 2025.

In early June 2016 a large rainband with an embedded subtropical cyclone, associated with a deep upper-level trough, brought extensive heavy rainfall along Australia’s east coast, from southern Queensland to Tasmania. In the lead-up to this event, sea-surface temperatures (SSTs) in the Coral and Tasman Seas were the warmest on record for the time of year. 
To investigate how the anomalously high SST, and its distribution, influenced the development of the cyclone, a high-resolution configuration of the Australian Community Climate and Earth System Simulator (ACCESS) over Australia, known as AUS2200, has been run under different SST scenarios. All simulations were run from 0000 UTC 3 June to 0000 UTC 8 June 2016, and use ERA5 data for the SST calculations.
A more intense subtropical cyclone develops off the New South Wales (NSW) coast in two simulations run with observed SST — one with fixed initial SST (Control) and the other with daily evolving SST (Evolving) — compared with a simulation using 3 June climatological SST (Climatology). The cyclone also stalls longer near the NSW coast in the observed SST runs.
Two additional simulations examine the role of the East Australian Current in the Tasman Sea. One smooths a prominent warm eddy (Smooth), and another replaces the Tasman Sea SST with climatological values (Tasclim). Both simulations retain the cyclone intensification seen in Control. A final simulation that replaces the Coral Sea SST with climatological values (Corclim) produces a weaker cyclone similar to Climatology.
Taken together, the results indicate that the anomalously warm Coral Sea SSTs were more important for the cyclone intensification than those of the Tasman Sea even though the greatest intensification occurred over the Tasman Sea. The greater cyclone intensity and slower southward movement over the Tasman Sea resulted in stronger and more prolonged onshore winds along the southern NSW coast, increasing the potential for coastal damage.
The greater intensity of the subtropical cyclone seen in Control, Evolving, Smooth, and Tasclim is associated with the formation of a warmer deep-tropospheric storm core than seen in Climatology and Corclim. This is linked to a greater reservoir of deep-tropospheric warm air that develops when using observed SST over the Coral Sea. These findings highlight the critical role of the Coral Sea’s warm SST as a driver of the cyclone’s development and intensification.

How to cite: Chambers, C., Huang, Y., and Roberts, D.: Warm core intensification of a Tasman Sea cyclone linked to Coral Sea sea-surface temperatures., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14515, https://doi.org/10.5194/egusphere-egu25-14515, 2025.

Atmospheric bomb cyclones that form off the United States east coast are high impact, complex weather systems. Many ingredients must come together to produce a storm of this magnitude. In recent years, high-resolution studies have indicated that one such critical ingredient is fine-scale Gulf Stream sea-surface temperature (SST) variability. However, studies still lack consensus on which particular aspect of the variability is most critical (e.g. absolute SST vs. the SST gradient, pre-conditioning vs. direct influence). Through novel high-resolution simulations in Community Earth System Model 2 (CESM2), this study attempts to isolate the influence of the fine-scale SST gradient specifically, motivated by the impact fine-scale heat flux gradients are expected to have on lower-level frontogenesis and subsequent cyclone development. Through targeted fine-scale SST gradient perturbations, the results illustrate how preexisting SST gradients can impact the frequency and intensity of bomb cyclones and may offer useful information regarding seasonal forecasting of these systems.

How to cite: Hair, J., Parfitt, R., Wills, R., and Müller, J.: Investigating the Impact of Fine-Scale Gulf Stream SST Gradients on the Development of Bomb Cyclones in the Community Earth System Model 2, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15631, https://doi.org/10.5194/egusphere-egu25-15631, 2025.

Extratropical cyclones (ETCs) are dominant meteorological structures playing a crucial role in midlatitudes climate. ETCs are also responsible for heavy precipitation events, strong surface winds and wind gusts exposing populations to hazards and causing widespread and significant damages. The response of ETCs to a warming atmosphere is characterized by substantial uncertainty. This arises primarily from two key factors: significant inter-annual variability, which complicates trend detection, and the interplay of non-linear and potentially compensating mechanisms, which render future changes in the ETC climate challenging to evaluate, understand and predict. Additionally, North Atlantic ETC trend evaluation and understanding crucially depend on methodological analysis choices regarding datasets (e.g., observations, reanalysis, proxies, model simulations and analysis period) and approaches to examine storm features (i.e., Eulerian vs. Lagrangian).

Here, we present and preliminarily evaluate a novel dataset of European windstorms associated with ETCs based on the whole ERA5 reanalysis period (1940-present). This dataset is produced within the Copernicus Climate Change Service (C3S) Enhanced Operational Windstorm Service (EWS), to promote a knowledge-based assessment of the nature and temporal evolution of European windstorms associated with ETC. Such a dataset is primarily thought to provide high-quality, standardized data on windstorms which support various industrial sectors, particularly insurance and risk management, by offering insights into the intensity, frequency, vulnerability and impact of windstorms. EWS includes two datasets: windstorm tracks, based on two tracking algorithms (TRACK and TempestExtremes), and windstorm footprints, produced considering both original-resolution ERA5 variables and statistically downscaled ERA5 variables, with a target grid at 1 km resolution.

A preliminary analysis of the datasets shows increasing trends of cold-semester windstorm frequency and of the associated footprint magnitude over a portion of the European territory. The choice of the tracking algorithm is shown to be an important factor in the analysis process, as it results in non-negligible uncertainties in main windstorm statistics.

How to cite: Sangelantoni, L., Tibaldi, S., Cavicchia, L., Scoccimarro, E., Vidale, P. L., Hodges, K., Mavel, V., Almansi, M., Cagnazzo, C., and Almond, S.: Enhanced C3S Windstorm Service: A Novel Dataset of European Extratropical Cyclone Windstorms Based on ERA5 Reanalysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16278, https://doi.org/10.5194/egusphere-egu25-16278, 2025.

In a warming climate, storm tracks are projected to intensify on their poleward side. Here we use large-ensemble CO₂ ramp-up and ramp-down simulations to show that these changes are not reversed when CO₂ concentrations are reduced. If CO₂ is removed from the atmosphere following CO₂ increase, the North Atlantic storm track keeps strengthening until the middle of the CO₂ removal, while the recovery of the North Pacific storm track during ramp-down is stronger than its shift during ramp-up. By contrast, the Southern Hemisphere storm track weakens during ramp-down at a rate much faster than its strengthening in the warming period. Compared with the present climate, the Northern Hemisphere storm track becomes stronger and the Southern Hemisphere storm track becomes weaker at the end of CO₂ removal. These hemispherically asymmetric storm-track responses are attributable to the weakened Atlantic meridional overturning circulation and the delayed cooling of the Southern Ocean.

How to cite: son, S., Hwang, J., Garfinkel, C. I., Woollings, T., Yoon, H., An, S.-I., Yeh, S.-W., Min, S.-K., Kug, J.-S., and Shin, J.: Asymmetric hysteresis response of mid-latitude storm tracks to CO2 removal, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2792, https://doi.org/10.5194/egusphere-egu25-2792, 2025.