Orals: Thu, 1 May | Room 0.11/12
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.
Climate change projections of windstorms associated with extratropical cyclones for Europe are highly uncertain. This is due to differences between models and large internal variability present. Furthermore, year-to-year variations are very high, and the different representations of the driving extratropical cyclones are large, resulting in any forced changes from a warming climate being hard to detect. Windstorms and the associated extratropical cyclones are objectively identified in 20 CMIP6 models, and then Generalized Linear Models and a weighted median estimation are used to extract forced trends for a number of storm impact metrics. Trends are assessed over time, but also as a function of global mean surface temperature changes. Trends in aggregate severity are attributed to changes in storm average severity, frequency, and area impacted, with changes in area being the dominant driver of changes to average storm severity. Using a large ensemble we find that trends between individual members can vary significantly, however the uncertainty due to internal variability is generally 2-3 times lower than model variability. With largest uncertainty coming from model differences, a large proportion of uncertainty in future windstorms is therefore potentially reducible with modelling advances.
How to cite: Priestley, M., Stephenson, D., Scaife, A., and Bannister, D.: Forced trends and internal variability in projections of European windstorms associated with extratropical cyclones, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6685, https://doi.org/10.5194/egusphere-egu25-6685, 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.
Extratropical cyclone clustering significantly impacts European weather extremes, such as heavy rainfall, strong winds, and flooding, often causing severe socio-economic consequences. Despite its importance, the long-term trends and variability of cyclone clustering remain poorly understood. In this work, we analyze the temporal and spatial evolution of extratropical cyclone clustering affecting Europe from 1940 to 2024, utilizing the high-resolution hourly ERA5 reanalysis dataset. This study provides unprecedented insights into century-scale changes in storminess and explores the underlying mechanisms driving these patterns. Our findings aim to enhance the understanding of extratropical cyclone behavior and their potential links to climate change, offering critical implications for risk assessment and adaptation strategies in Europe.
How to cite: Li, Z.-B., Heuzé, C., Song, J., and Chen, D.: Is Europe becoming stormier? Extratropical cyclone clustering over the last century, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2146, https://doi.org/10.5194/egusphere-egu25-2146, 2025.
The Tibetan Plateau (TP), known as the "Asian Water Tower," plays a crucial role in regional water resources, with summer storms contributing significantly to annual precipitation. However, the spatial structural changes of these storms remain understudied. This study analyzed satellite-retrieved precipitation data from 2001 to 2020 to investigate the changes in the spatial structure of summer storms over the TP and their underlying mechanisms. Results showed distinct regional differences: in the monsoon-dominated zone, reduced precipitation particularly at the storm center, led to a "dulling" of storm structures. In contrast, in the westerly-dominated and transition zones, a greater increase in precipitation was found at the center compared to other regions of storms, especially for extreme storms, resulted in a "sharpening" of storm structures. Ignoring the changes of spatial structural changes may overestimate the changes of storm-induced precipitation. Further analysis linked these changes to dynamic environmental factors, particularly stronger variations in vertical velocity near the storm center, driven by large-scale circulation changes around the TP.
How to cite: Jin, G. and Zou, L.: Spatial structural changes of summer storms over the Tibetan Plateau during 2001-2020 based on GPM IMERG data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2966, https://doi.org/10.5194/egusphere-egu25-2966, 2025.
Traditionally, European windstorms – the costliest meteorological hazards in Europe, are associated with extratropical cyclones in winter. However, in recent years, unorthodox cyclones such as Ophelia (2017), Leslie (2018), and Kirk (2024) have had noticeable impacts on Europe during autumn. These cyclones, referred to as Cyclones of Tropical Origin (CTOs), form in tropical or subtropical regions and can migrate toward Europe during their lifecycle. Although CTOs do not always cause significant impacts, they can exhibit exceptional intensity, posing unique hazards distinct from typical extratropical cyclones.
This raises important questions: Are these isolated events? Will these events become more common in future climates? Current efforts to quantify the risk posed by CTOs are hindered by limited observational data and an incomplete theoretical understanding of these phenomena. As a result, Europe may face an unseen hazard from CTOs.
In this presentation, we analyse CTO events using a physically consistent UNSEEN event set constructed from twentieth-century seasonal hindcast outputs (CSF-20C and SEAS5-20C). Our results show that while CTOs are rare, they are not isolated. We examine the interdecadal variability of CTO impact potentials—including wind, rainfall, and compound hazards—and assess their impact probabilities during the twentieth century. Finally, we present preliminary findings that highlight the genuine and previously unseen risk posed by CTOs to Europe.
How to cite: Ng, K. S. and Leckebusch, G. C.: Is Europe under UNSEEN Risk of Cyclones of Tropical Origin?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6430, https://doi.org/10.5194/egusphere-egu25-6430, 2025.
Extra-tropical winter storms are one of the most impactful natural hazards for the European insurance market causing large socio-economic damages.
AXA has been developing stochastic natural hazard models (also called natural catastrophe models) to quantify the impact of such events on its portfolios, including European extra-tropical cyclones. However, the correct representation of windspeeds and their spatial distribution across Europe during a storm is crucial to determine the risk posed by an event. The characterization of uncertainties in natural catastrophe models stemming from the hazard data used and its resolution is crucial to understand their limitations and guide decision-making.
We rely on a novel publicly available dataset of 50 extreme European windstorms for the period 1995–2015 (Flynn et al., 2024; doi:10.5194/essd-2024-298) with wind gust footprints derived consistently from four different datasets with different horizontal resolutions. Risk being a function of hazard, vulnerability and exposure, we set constant vulnerability and portfolio, and we quantify the range of uncertainties in the reproduction of historical insured losses stemming from the sole hazard component. We compare the losses derived from AXA’s model to the range of losses derived from this novel extreme windstorms dataset.
How to cite: Rakotoarimanga, H., Meynadier, R., Messori, G., and Pinto, J. G.: Multi-model assessment of hazard uncertainties in a European windstorm NatCat model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10733, https://doi.org/10.5194/egusphere-egu25-10733, 2025.
Extratropical cyclones (ETCs) are a major hazard for Europe as they cause most of the windstorms and floods in the mid-latitudes, resulting in high economic and social costs.
Sting jets (SJ) are responsible for windstorm damages well ahead the cyclone center. In this study we employ dedicated diagnostics and modeling approaches that identify -along with cyclone tracks- the spatial extent where actual impacts take place. The fine scales of processes involved in SJ generation demand exceptionally high spatial resolutions and dense vertical levels in model simulations (Rivière et al. 2020).
In this study we use the WRF model to simulate 143 historical ETC from 1980 to 2018 that potentially involve SJs. The model simulations use two domains: one parent domain that encompasses the whole cyclone track at a resolution of about 15 km, and another, square-sized domain with each side measuring 1300 km. The nested domain always follows the ETC centers, aiming to resolve explicitly the development of SJs. SJ detection has been achieved through lagrangian modeling, by identifying airstreams that sharply descend ahead of the cloud head and behind the cold front of the cyclones. Historical ETC footprints from ERA-5 and WRF physical downscaling of ERA-5 in convection-permitting resolutions are then used to assess the impact in term of financial losses of an explicit simulation of sting-jets processes.
How to cite: Flaounas, E., Meynadier, R., Rakotoarimanga, H., Diouf, A., and Mustafa, R.: Explicit risk modelling of sting-jet extratropical cyclones. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15033, https://doi.org/10.5194/egusphere-egu25-15033, 2025.
This study uses high-resolution simulations and Lagrangian diagnostics to identify the sources of moisture contributing to precipitation at the deepest stage of extratropical cyclones (ECs) over the North Atlantic (NATL). Precipitation was associated with target regions defined by a radius, warm conveyor belt (WCB) footprint, and square root spiral contours centred on the cyclone. The NATL region was divided into sectors for detailed analysis. In the northern North Atlantic (NNATL), moisture sources extend westward across the ocean. Subtropical moisture supports precipitation in non-central areas of ECs, which intensify over the central and western NNATL. The moisture uptake patterns of ECs in the higher latitudes of the western North Atlantic (WNATL) are similar to those in the NNATL, with southwestward extension and moisture uptake from the eastern American coast. For ECs in the lower latitudes of the WNATL, moisture uptake is more symmetric around the cyclone centre, with major contributions from the Caribbean and limited moisture flow from the Gulf of Mexico due to migrating anticyclones. For ECs in the eastern NATL, moisture comes from the surrounding ocean. Overall, 75% of the moisture gain occurs below 600 hPa, with a significant concentration observed around 800 hPa. Continental mass influence is observed for ECs deepening near the coasts of East America and Western Europe. ECs at higher latitudes in the WNATL and NNATL exhibit extensive synoptic-scale disturbances, with moisture sources for WCB and spiral precipitation extending 3,000 to 4,000 km southwest of their centres. The most intense moisture uptake occurs over the WNATL, particularly for lower latitude ECs.
How to cite: Nieto, R., Coll-Hidalgo, P., Fernández-Alvarez, J. C., and Gimeno, L.: Assessment of the origin of moisture for the precipitation of North-Atlantic extratropical cyclones, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15755, https://doi.org/10.5194/egusphere-egu25-15755, 2025.
The Indian subcontinent experiences winter precipitation (December, January, and February) due to Western Disturbances (WDs), which are synoptic scale weather systems embedded in subtropical westerly jets (SWJs) at upper tropospheric levels. For Himalayan rivers, WDs precipitation is crucial for hydrological budget as it causes heavy precipitation, flooding, and snowfall. The precipitation caused by WDs is beneficial for agricultural activities such as sowing of wheat crop, barley etc. WDs and NON-WDs precipitation are classified into active and break phase. Active and break peaks of WDs and NON-WDs are computed based on the maximum precipitation occurring in each WDs and NON-WDs days. This study, highlights the changes in precipitation climatology of active WDs and NON-WDs during 1987-2020 using hourly ERA5 reanalysis dataset. Various statistical techniques such as Theil-Sen slope test is used to calculate the trend and to investigate the decline in frequency of active WDs precipitation. Further, the structure, dynamics, and moisture availability associated with changing WDs and NON-WDs are also examined in this work. It has been observed that some characteristics of WDs have changed in the recent decade due to climate change. This is associated with decrease in active WDs precipitation but the precipitation amount is increasing in the recent years. Active WDs precipitation pattern has primarily been shifted towards the months of January and February. The dynamics showed that active NON-WDs days derive moisture from Bay of Bengal region which is due to ‘Ω shape’ amalgamated structure and ‘∞ shape’ wind formation leading to precipitation forming mechanism over Western Himalayas. This study helps in insightful understanding of WDs and NON-WDs precipitation during the recent years which is necessary to improve headwater storage policies and meet agricultural demands.
How to cite: Pooja, P. and Dimri, A. P.: Changing characteristics of Western Disturbances precipitation over Western Himalayas , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1559, https://doi.org/10.5194/egusphere-egu25-1559, 2025.
When severe European winter windstorms cluster in time, socioeconomic impacts and losses are magnified. Yet, the behaviour and drivers on shorter, intra-seasonal timescales have not been fully investigated. The impact-relevant footprint of the storm system is identified using the wind-based impact-oriented tracking algorithm WiTRACK (Leckebusch et al., 2008), for the core winter seasons (DJF) 1980/01-2022/23 from ERA5 reanalysis. Derived from a Poisson Process, we quantify the magnitude of clustering through the widely established dispersion statistic (Mailier et al., 2006). On fixed 45- and 30-day timescales, the spatial distribution of the dispersion statistic has been analysed. The time-development of the dispersion statistic on shorter time horizons is investigated through 21-, 15- and 11-day moving windows. Preliminary results reveal an increase in clustering in the latter half of the winter season on the fixed 45- and 30-day timescales. Shorter time horizons reveal clear peaks at the middle and the end of the season.
To analyse mechanisms that drive the defined intra-seasonal behaviour on the shorter time horizons (<30 -days), we examined the roles of several large-scale variability modes, namely the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA), and the Scandinavian pattern (SCA). Results reveal a correlation between intra-seasonal variability of clustering and the occurrence of such large-scale modes, suggesting the EA as a key driver for increasing clustering. In addition, the individual contributions of large-scale modes to clustering at different times of the season can be diagnosed.
How to cite: Feltz, S., Ng, K., Allen, C., Kruschke, T., Angus, M., Quinn, A., and Leckebusch, G. C.: Temporal clustering of severe European winter windstorms on intra-seasonal timescales and the explanatory power of large-scale modes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17891, https://doi.org/10.5194/egusphere-egu25-17891, 2025.
