Sting Jet Research Articles

The origins of Storm Ciarán: From diabatic Rossby wave to warm‐seclusion cyclone with a sting jet

AbstractThe evolution of Storm Ciarán was different from what is commonly attributed to windstorms affecting northwest Europe. Ciarán initially developed as a diabatic Rossby wave, driven by low‐level latent heat release and with negligible upper tropospheric forcing. It then crossed the jet stream, intensifying explosively while developing a low‐level warm seclusion and producing extreme near‐surface winds, including sting jets. Ciarán is an example of an extreme windstorm following this pathway and highlights the need of a systematic assessment of its relevance in our warming climate.

Extreme low‐level wind jets in Storm Ciarán

AbstractSatellite imagery of Storm Ciarán as it approached the UK early on 1 November 2023 showed characteristic banding that fuelled media reports that Ciarán could contain a sting jet, with enhanced likelihood of damaging surface winds and gusts. Here operational numerical weather prediction model output is used with trajectory analysis to reveal the existence of at least two wind speed maxima attributed to sting jets. The small‐scale sting jets are located beneath, and likely affected by, far broader overrunning strong wind regions attributed to a deeply descending dry intrusion, thus highlighting the likely interaction of these airstreams at low levels.

Identification of high-wind features within extratropical cyclones using a probabilistic random forest – Part 2: Climatology over Europe

Abstract. Strong winds associated with extratropical cyclones are one of the most dangerous natural hazards in Europe. These high winds are mostly associated with five mesoscale features: the warm (conveyor belt) jet (WJ); the cold (conveyor belt) jet (CJ); cold frontal convection (CFC); strong cold-sector (CS) winds; and, in some cases, the sting jet (SJ). The timing within the cyclone's life cycle, the location relative to the cyclone core and further characteristics differ between these features and, hence, likely also their associated forecast errors. In Part 1 of this study (Eisenstein et al., 2022a), we introduced the objective and flexible identification tool RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification), which distinguishes between the WJ, CFC and CS as well as CJ and SJ combined. RAMEFI is based on a probabilistic random forest trained on station observations of 12 storm cases over Europe. Being independent of spatial distribution, RAMEFI can also be applied to gridded data. Here, we use RAMEFI to compile a climatology over 19 extended winter seasons (October–March 2000–2019) based on high-resolution regional reanalyses of the German Consortium for Small-scale Modelling (COSMO) model over Europe. This allows the first ever long-term objective statistical analysis of the mesoscale wind features, including their occurrence frequency, geographical distribution and characteristics. For western and central Europe, we demonstrate that the CS is prominent in most winter storms, while CFC is the least common cause of high winds, both in terms of frequency and affected area. However, probably due to convective momentum transport, CFC is on average the cause of the highest gusts after the CJ and has the highest gust factor. As expected, CFC high-wind areas show high levels of humidity and overcast conditions. In contrast, the CS is characterised by sunnier conditions interspersed by patchy cumulus clouds, leading to a broader cloud cover distribution than for other features. The WJ produces the weakest winds on average but affects a larger area than CJ. Central Europe is more strongly affected by WJ and CFC winds, while the CJ usually occurs farther north over the North and Baltic seas, northern Germany, Denmark and southern Scandinavia. System-relative composites show that the WJ and CFC tend to occur earlier in the cyclone life cycle than the CJ and CS. Consistently, the CS is the most common cause of high winds over eastern Europe, where cyclones tend to occlude, represented by a narrowing warm sector and weakening cold front. The WJ mostly occurs within the south-eastern quadrant of a cyclone bordered by the narrow CFC in the west. However, the location of CFC varies greatly between cases. The CS occurs in the south-western quadrant, while the CJ appears closer to the cyclone centre, sometimes stretching into the south-eastern quadrant. This objective climatology largely confirms previous, more subjective investigations but puts these into climatological context. It allows a more detailed analysis of feature properties and provides a solid foundation for model assessment and forecast evaluation in future studies.

Assessment of Extreme Ocean Winds within Intense Wintertime Windstorms over the North Pacific Using SMAP L-Band Radiometer Observations

Here, we examine extreme ocean winds associated with intense wintertime extratropical windstorms over the North Pacific. The study was mainly based on NASA Soil Moisture Active Passive (SMAP) L-band radiometer observations allowing the retrieval of ocean wind speeds up to 70 m/s regardless of precipitation intensity. Additionally, we assessed the ability of atmospheric reanalysis ERA5 and the Climate Forecast System Version 2 (CFSv2) to reproduce high-wind features within severe windstorms, particularly those associated with “explosive” cyclogenesis. The analysis identified 145 windstorm events with hurricane-force (HF) wind zones within the SMAP L-band radiometer swath from 2015 to 2023. These windstorms develop most frequently over two areas: southeast of Kamchatka and south of Alaska, spanning 40–47°N latitudes. Both reanalysis datasets significantly underestimated HF wind speeds compared to SMAP measurements, but CFSv2 tends to reproduce more-intense windstorms than ERA5. Among the notable new findings is that the SMAP data revealed two distinct groups in maximum wind speed distribution, indicating the existence of a separate class of severe windstorm events with a distinct mechanism for extreme wind formation related probably to a Shapiro–Keyser cyclogenesis and the presence of sting jet (SJ) feature. The study highlights the potential of SMAP measurements to study wind extremes and underscores the need for improvements in operational predictive models to better reproduce the formation of SJ windstorms.

Strong surface winds in Storm Eunice. Part 1: storm overview and indications of sting jet activity from observations and model data

Strong surface winds in Storm <i>Eunice</i>. Part 1: storm overview and indications of sting jet activity from observations and model data

Projected increase in windstorm severity and contribution from sting jets over the UK and Ireland

Extratropical windstorms can lead to extreme impacts in the UK; however, future changes in windstorm frequency and intensity are uncertain due to natural variability and lack of model consensus. Further uncertainty arises due to unresolved or poorly represented processes which can reduce the validity of traditional coarse resolution climate models. This study demonstrates the added value of higher resolution simulations in their representation of extreme windstorms. It also assesses future changes in windstorms in the first ensemble of convection-permitting model (CPM, 2.2 km grid spacing) projections over the UK, released as part of the UKCP18 project, and compares these to changes in the driving 60 km global climate model (GCM) and 12 km regional climate model (RCM). The representation of wind gusts in the CPM and RCM is improved with respect to ERA-Interim reanalysis data compared to observations. Both models are largely similar except over areas with orographic influences where the CPM provides greater detail and simulates higher wind gusts. In contrast, the GCM simulates lower wind gusts and underestimates windstorm intensity; the improvements from the RCM and CPM are partially linked to better representation of cold conveyor belts and sting jets at km-scale. The CPM projects an increase in the frequency of extreme windstorms. In line with a previous study, a large contribution comes from storms that develop sting jets which now seems to be a robust response of windstorms to a warming climate. Similar projected increases are also found in the coarser resolution models, although differences in projections exist at a regional scale in the CPM compared to the RCM and GCM. Overall, higher resolution simulations improve the representation of windstorms, offering greater detail at the local scale which may provide better information for impact modelling, though large-scale projected changes in the assessed storm severity index are insensitive to the model resolutions in the simulations tested here.

Identification of high-wind features within extratropical cyclones using a probabilistic random forest – Part 1: Method and case studies

Abstract. Strong winds associated with extratropical cyclones are one of the most dangerous natural hazards in Europe. These high winds are mostly associated with five mesoscale dynamical features: the warm (conveyor belt) jet (WJ); the cold (conveyor belt) jet (CJ); cold frontal convection (CFC); strong cold-sector winds (CS); and, at least in some storms, the sting jet (SJ). The timing within the cyclone's life cycle, the location relative to the cyclone core and some further characteristics differ between these features and, hence, likely also the associated forecast errors. Here, we present a novel objective identification approach for these high-wind features using a probabilistic random forest (RF) based on each feature’s most important characteristics in near-surface wind, rainfall, pressure and temperature evolution. As the CJ and SJ are difficult to distinguish in near-surface observations alone, these two features are considered together here. A strength of the identification method is that it works flexibly and is independent of local characteristics and horizontal gradients; thus, it can be applied to irregularly spaced surface observations and to gridded analyses and forecasts of different resolution in a consistent way. As a reference for the RF, we subjectively identify the four storm features (WJ, CS, CFC, and CJ and SJ) in 12 winter storm cases between 2015 and 2020 in both hourly surface observations and high-resolution reanalyses of the German Consortium for Small-scale Modeling (COSMO) model over Europe, using an interactive data analysis and visualisation tool. The RF is then trained on station observations only. The RF learns physically consistent relations and reveals the mean sea level pressure (tendency), potential temperature, precipitation amount and wind direction to be most important for the distinction between the features. From the RF, we get probabilities of each feature occurring at the single stations, which can be interpolated into areal information using Kriging. The results show a reliable identification for all features, especially for the WJ and CFC. We find difficulties in the distinction of the CJ and CS in extreme cases, as the features have rather similar meteorological characteristics. Mostly consistent results in observations and reanalysis data suggest that the novel approach can be applied to other data sets without the need for adaptation. Our new software RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification) is made publicly available for straightforward use by the atmospheric community and enables a wide range of applications, such as working towards a climatology of these features for multi-decadal time periods (see Part 2 of this paper; Eisenstein et al., 2022d), analysing forecast errors in high-resolution COSMO ensemble forecasts and developing feature-dependent post-processing procedures.

Extreme windstorms and sting jets in convection-permitting climate simulations over Europe

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a sting jet are extremely damaging. A sting jet is a mesoscale core of very high wind speeds that occurs in Shapiro–Keyser type cyclones, and high-resolution models are required to adequately model sting jets. Here, we develop a low-cost methodology to automatically detect sting jets, using the characteristic warm seclusion of Shapiro–Keyser cyclones and the slantwise descent of high wind speeds, within pan-European 2.2 km convection-permitting climate model (CPM) simulations. The representation of wind gusts is improved with respect to ERA-Interim reanalysis data compared to observations; this is linked to better representation of cold conveyor belts and sting jets in the CPM. Our analysis indicates that Shapiro–Keyser cyclones, and those that develop sting jets, are the most damaging windstorms in present and future climates. The frequency of extreme windstorms is projected to increase by 2100 and a large contribution comes from sting jet storms. Furthermore, extreme wind speeds and their future changes are underestimated in the global climate model (GCM) compared to the CPM. We conclude that the CPM adds value in the representation of extreme winds and surface wind gusts and can provide improved input for impact models compared to coarser resolution models.

How will climate change impact North Atlantic storms?

North Atlantic storms present one of the major weather risks for North West (NW) Europe. Their associated strong winds and heavy precipitation can result in wind damage and both coastal and inland flooding. Notable recent examples include the St Jude's Day storm of October 2013 which brought hurricane-force winds to NW Europe, including record-strong winds in Denmark and the loss of 17 lives. In November and December of that year, intense rainfall associated with a series of storms led to widespread UK flooding which was particularly severe over the Somerset Levels, and the timing of storm Xaver on 5 December 2013 generated a storm surge which led to coastal flooding around both the North and Irish Seas. Understanding and predicting how North Atlantic storms might respond to climate change is therefore essential for assessing future weather risks and informing climate change adaptation strategies. This briefing focuses on the North Atlantic storm track which traverses the North Atlantic Ocean and extends over NW Europe, with the strongest impacts usually occurring in autumn and winter. Over most of the Northern Hemisphere, climate models project that the midlatitude storm tracks will, on average, shift further poleward under climate change. Coupled with the shift is a general decrease in the number of storms. If this pattern occurred in the North Atlantic, one might expect a reduction in the number of storms impacting NW Europe. This is indeed the case in summer, but the wintertime North Atlantic storm track does not follow this simple picture; instead, it is projected to extend more strongly eastward over NW Europe resulting in an enhanced storm risk in this region. Comprehensive analyses of wintertime North Atlantic storms across a wide range of global climate models suggest an increase in storm occurrence of 2–4% by the end of the century (Zappa et al., 2013). The quoted range represents scenario uncertainty associated with two different future greenhouse gas emissions pathways, corresponding to global warming levels of approximately 2–4 degC respectively. There are additional uncertainties not accounted for, particularly due to internal variability of the climate system. A full analysis of North Atlantic storms in the most recent generation of climate models (CMIP6) has yet to be completed, but initial studies indicate broadly similar changes per degree of global warming (Harvey et al., 2020). On the level of individual storms, substantial and robust increases in precipitation are expected. The same suite of global climate model simulations quoted above project a 9–18% increase in the average precipitation per storm from wintertime storms impacting NW Europe. Although the strongest winds associated with storms are expected to weaken, wintertime North Atlantic storms again do not follow the simple picture with a modest 0.4–0.9% increase in the strongest near-surface wind speeds expected by the end of the century. Increases in the occurrence and severity of coastal flooding are also expected, predominantly due to rising sea levels (Murphy et al., 2018). North Atlantic storms are generated by the large-scale contrast in temperature that exists between the tropics and the Arctic. Climate change is expected to warm the Arctic more than the tropics through a process known as polar amplification, acting to generally reduce storminess in the midlatitudes. However, the intensification of the wintertime North Atlantic storm track over NW Europe bucks this trend and the reasons for this are not fully understood. It may partly arise from a region of slower ocean warming in the central North Atlantic, associated with changes in the ocean circulation, resulting is a local increase of the north–south temperature gradient over the ocean surface and stronger potential for storm growth there (Gervais et al., 2019). Alternatively, more hemispheric-scale dynamical changes may be playing a role (Ciasto et al., 2016). On the level of individual storms, the projected increases in precipitation are consistent with the increased availability of moisture associated with increased air temperatures. One key research question currently being addressed is the extent to which the current generation of climate models accurately represent North Atlantic storms. For example, small-scale atmospheric processes not fully resolved by these models, including sting jets and embedded convective precipitation, have the potential to locally amplify both precipitation and wind impacts in a manner not currently captured by global climate projections.

Downscaling the ERA5 reanalysis for ‘Hurricane’ Debbie (1961): evidence of both cold‐conveyor belt and sting jets

Downscaling the ERA5 reanalysis for ‘Hurricane’ <i>Debbie</i> (1961): evidence of both cold‐conveyor belt and sting jets

2019 Atlantic Hurricane Forecasts from the Global-Nested Hurricane Analysis and Forecast System: Composite Statistics and Key Events

AbstractNOAA’s Hurricane Analysis and Forecast System (HAFS) is an evolving FV3-based hurricane modeling system that is expected to replace the operational hurricane models at the National Weather Service. Supported by the Hurricane Forecast Improvement Program (HFIP), global-nested and regional versions of HAFS were run in real time in 2019 to create the first baseline for the HAFS advancement. In this study, forecasts from the global-nested configuration of HAFS (HAFS-globalnest) are evaluated and compared with other operational and experimental models. The forecasts by HAFS-globalnest covered the period from July through October during the 2019 hurricane season. Tropical cyclone (TC) track, intensity, and structure forecast verifications are examined. HAFS-globalnest showed track skill superior to several operational hurricane models and comparable intensity and structure skill, although the skill in predicting rapid intensification was slightly inferior to the operational model skill. HAFS-globalnest correctly predicted that Hurricane Dorian would slow and turn north in the Bahamas and also correctly predicted structural features in other TCs such as a sting jet in Hurricane Humberto during extratropical transition. Humberto was also a case where HAFS-globalnest had better track forecasts than a regional version of HAFS (HAFS-SAR) due to a better representation of the large-scale flow. These examples and others are examined through comparisons with airborne tail Doppler radar from the NOAA WP-3D to provide a more detailed evaluation of TC structure prediction. The results from this real-time experiment motivate several future model improvements, and highlight the promise of HAFS-globalnest for improved TC prediction.

Development of a prototype real‐time sting‐jet precursor tool for forecasters

Damaging surface winds in some European storms have been attributed to descending mesoscale airstreams termed sting jets. The development of a prototype real-time tool that Met Office forecasters can use to identify favourable conditions for sting jet occurrence in extratropical cyclones is presented. The motivation is to improve national severe weather warnings. We have previously developed a convective-instability-based tool to identify sting-jet precursors for research purposes and applied it to storms in reanalyses and climate models with insufficient spatial resolution to represent sting jets. Here we describe the challenges of applying this research-derived diagnostic to output from an operational forecast system and demonstrate its usefulness for a recent winter storm. Through close collaboration with the researchers and forecasters from the Met Office, the diagnostic has been adapted to work on output from the Met Office’s operational global ensemble forecasts as it becomes available. Since autumn 2019, forecasters have been able to view graphical output informing them whether storms impacting the UK and Europe (up to seven days in the future) have the precursor. The tool has already proven useful in informing guidance for severe weather warnings, including those issued by the Met Office's impact-based National Severe Weather Warning Service that goes out to seven days ahead and is the primary hazardous weather warning service for the public and emergency responders.

Damaging Convective and Non-Convective Winds in Southwestern Iberia during Windstorm Xola

On 23/12/2009, windstorm Xola struck mainland Portugal, causing serious damage in a small area north of Lisbon (Oeste region) and in the south region, inflicting economic losses of over EUR 100 million. In both areas, several power towers, designed to withstand up to 46 m s−1 winds, were destroyed. The causes of these two distinct damaging wind events were investigated. Xola was revealed to have a prominent cloud head and a split cold front structure. In the southern region, the damages were due to downburst winds, associated with a mesovortex, observed in a bow echo line triggered by an upper cold front. The cloud head presented several dry air intrusion signatures, co-located with tops progressively lowering towards the hooked tip. This tip revealed features consistent with the presence of slantwise convection, the descending branches of which may have been strengthened by evaporating cooling. At the reflectivity cloud head tip, a jet streak pattern was identified on weather radar, with Doppler velocities exceeding 55 m s−1, just 400 m above ground. This signature is coherent with the presence of a Sting jet, and this phenomenon was associated with the strongest wind gusts (over 40 m s−1) and the largest damages in the Oeste region.

Front–orography interactions during landfall of the 1992 New Year's Day Storm

Abstract. Although following a common synoptic evolution for this region, the 1992 New Year's Day Storm was associated with some of the strongest winds observed along the Norwegian west coast. The narrow wind band along its bent-back front became famous as the “poisonous tail” and paved the way towards today's sting jet terminology. This article re-examines the storm's landfall with a particular focus on the interaction with the orography. Sensitivity analyses based on WRF simulations demonstrate that the formation and the evolution of the warm-air seclusion and its poisonous tail are largely independent of orography. In contrast, the warm sector of the storm undergoes considerable orographically induced modifications. While moving over the orography, both warm and cold fronts are eroded rapidly. This development fits neither the cold-air-damming paradigm nor the passive-advection paradigm describing front–orography interactions. The warm sector is lifted over the orography, thereby accelerating the occlusion process. The insensitivity of the warm-air seclusion to the orographic modifications of the warm sector raises the question of to which extent these entities are still interacting after the onset of the occlusion process.

The downward transport of momentum to the surface in idealized sting‐jet cyclones

AbstractProcesses leading to the formation of strong surface wind gusts within an idealized sting‐jet extratropical cyclone are investigated using a high‐resolution mesoscale model. It is motivated by real case studies that have shown that damaging surface winds ahead of the bent‐back warm front of an extratropical cyclone are often due to the presence of a sting jet, which is a low‐level mesoscale jet, the air masses of which descend from the cloud head to the top of the boundary layer. Different numerical simulations show that surface winds below the leading edge of the sting jet increase with increased horizontal resolution and surface roughness. For typical land‐surface roughness, the intensity of near‐surface wind gusts increases rapidly with horizontal resolution, while the sting‐jet intensity above the boundary layer does not vary with resolution. A focus on the 1‐km grid‐spacing simulation with land‐surface roughness is then made. It shows stronger surface winds ahead of the bent‐back warm front than near the cold conveyor‐belt jet. It also exhibits multiple bands of strong surface wind speed, similar to real sting‐jet cyclones. These multiple bands are closely linked with multiple resolved convective rolls in the boundary layer, the descending branches of which are responsible for the downward transfer of momentum. Sensitivity experiments and a stability analysis show that cooling due to sublimation and melting of precipitating ice hydrometeors below the leading edge of the sting jet triggers and invigorates boundary‐layer convective rolls by reducing the buoyancy of air masses near the precipitation base and below. Closer to the surface, the transfer of momentum is predominantly taken over by subgrid‐scale turbulent fluxes.

Idealised simulations of cyclones with robust symmetrically unstable sting jets

Abstract. Idealised simulations of Shapiro–Keyser cyclones developing a sting jet (SJ) are presented. Thanks to an improved and accurate implementation of thermal wind balance in the initial state, it was possible to use more realistic environments than in previous idealised studies. As a consequence, this study provides further insight into SJ evolution and dynamics and explores SJ robustness to different environmental conditions, assessed via a wide range of sensitivity experiments. The control simulation contains a cyclone that fits the Shapiro–Keyser conceptual model and develops a SJ whose dynamics are associated with the evolution of mesoscale instabilities along the airstream, including symmetric instability (SI). The SJ undergoes a strong descent while leaving the cloud-head banded tip and markedly accelerating towards the frontal-fracture region, revealed as an area of buckling of the already-sloped moist isentropes. Dry instabilities, generated by vorticity tilting via slantwise frontal motions in the cloud head, exist in similar proportions to moist instabilities at the start of the SJ descent and are then released along the SJ. The observed evolution supports the role of SI in the airstream’s dynamics proposed in a conceptual model outlined in a previous study. Sensitivity experiments illustrate that the SJ is a robust feature of intense Shapiro–Keyser cyclones, highlighting a range of different environmental conditions in which SI contributes to the evolution of this airstream, conditional on the model having adequate resolution. The results reveal that several environmental factors can modulate the strength of the SJ. However, a positive relationship between the strength of the SJ, both in terms of peak speed and amount of descent, and the amount of instability occurring along it can still be identified. In summary, the idealised simulations presented in this study show the robustness of SJ occurrence in intense Shapiro–Keyser cyclones and support and clarify the role of dry instabilities in SJ dynamics.

Dynamics of sting‐jet storm Egon over continental Europe: Impact of surface properties and model resolution

AbstractIntense Shapiro–Keyser cyclones are often accompanied by a sting jet (SJ), an air stream that descends from the cloud head into the frontal‐fracture region and can cause extreme surface gusts. Previous case‐studies have concentrated on the North Atlantic and the British Isles. Here we present the first‐ever detailed analysis of an SJ over continental Europe and investigate the influence of topography on its dynamical evolution based on observations and high‐resolution simulations using the ICOsahedral Nonhydrostatic model (ICON). Windstorm Egon intensified over the English Channel and then tracked from northern France to Poland on 12–13 January 2017, causing gusts of almost 150 km·h−1 and important damage. ICON reproduces the storm dynamics, although it delays the explosive deepening, shifts the track southward over Belgium and Germany and underestimates gusts over land. Storm characteristics show weak sensitivity to varying grid spacing between 1.6 and 6.5 km, while switching off the convection parametrization at 3.3 km grid spacing improves correlations with surface observations but deteriorates the mean error. Trajectories reveal typical SJ characteristics such as mid‐level descent, strong acceleration and conditional symmetric and other mesoscale instabilities, while evaporative cooling is stronger than in previous cases from the literature, preventing drying during descent. The SJ identification and the occurrence of mesoscale instabilities depend considerably on model resolution, convective parametrization, output frequency and employed thresholds for trajectory selection. Sensitivity experiments with modified surface characteristics show that the combined effects of warm‐air blocking by the Alps, higher roughness over land and reduced surface fluxes cause Egon to fill more quickly and to move on a faster, more northern track across Germany. While the SJ response is complex, showing some compensating effects, surface gusts strongly increase when roughness is reduced. These results suggest that weather forecasters in continental Europe should be more aware of the potential risks associated with SJs.

Can Mountain Waves Contribute to Damaging Winds Far Away from the Lee Slope?

AbstractOn 25 December 2016, a 984-hPa cyclone departed Colorado and moved onto the northern plains, drawing a nearby Arctic front into the circulation and wrapping it cyclonically around the equatorward side of the cyclone. A 130-km-wide and 850-km-long swath of surface winds exceeding 25 m s−1 originated underneath the comma head of the lee cyclone and followed the track of the Arctic front from Colorado to Minnesota. These strong winds formed in association with a downslope windstorm and mountain wave over Colorado and Wyoming, producing an elevated jet of strong winds. Central to the distribution of winds in this case is the Arctic air mass, which both shielded the elevated winds from surface friction behind the front and facilitated the mixing of the elevated jet down to the surface just behind the Arctic front, due to steep lapse rates associated with cold-air advection. The intense circulation south of the cyclone center transported the Arctic front and the elevated jet away from the mountains and out across Great Plains. This case is compared to an otherwise similar cyclone that occurred on 28–29 February 2012 in which a downslope windstorm occurred, but no surface mesoscale wind maximum formed due to the absence of a well-defined Arctic front and postfrontal stable layer. Despite the superficial similarities of this surface wind maximum to a sting jet (e.g., origin in the midtroposphere within the comma head of the cyclone, descent evaporating the comma head, acceleration to the top of the boundary layer, and an existence separate from the cold conveyor belt), this swath of winds was not caused by a sting jet.

Origin of Strong Winds in an Explosive Mediterranean Extratropical Cyclone

AbstractDuring 2–3 December 2012, the Black Sea and east coast of Romania were affected by a rapidly deepening Mediterranean cyclone. The cyclone developed a bent-back front along which short-lived (2–4 h) strong winds up to 38 m s−1 were recorded equatorward of the cyclone center. A mesoscale model simulation was used to analyze the evolution of the wind field, to investigate the physical processes that were responsible for the strong winds and their acceleration, and to investigate the relative importance of the stability of the boundary layer to those strong winds. The origin of the air in the wind maximum equatorward of the cyclone center was twofold. The first was associated with a sting jet, a descending airstream from the midlevels of the cloud head and the lower part of the cyclonic branch of the warm conveyor belt. The sting jet started to descend west of the cyclone center, ending at the frontolytic tip of the bent-back front. The second was a low-level airstream associated with the cold conveyor belt that originated northeast of the cyclone center and traveled below 900 hPa along the cold side of the bent-back front, ending behind the cold front. Both airstreams were accelerated by the along-flow pressure gradient force, with the largest accelerations acting on the sting-jet air before entering into the near-surface strong-wind area. The sensible heat fluxes destabilized the boundary layer to near-neutral conditions south of the cyclone center, facilitating downward mixing and allowing the descending air to reach the surface. Mesoscale instabilities appeared to be unimportant in the sting-jet formation.

Forecasting wind gusts in winter storms using a calibrated convection‐permitting ensemble

Windstorms associated with low‐pressure systems from the North Atlantic are the most important natural hazards for central Europe. Although their predictability has generally improved over the last decades, forecasting wind gusts is still challenging, due to the multiple scales involved. One of the first ensemble prediction systems at convection‐permitting resolution, COSMO‐DE‐EPS, offers a novel 2.8‐km dataset over Germany for the 2011–2016 period. The high resolution allows representation of mesoscale features that are barely captured by global models, while the long period allows both investigation of rare storms and application of statistical post‐processing. Ensemble model output statistics based on a truncated logistic distribution substantially improve forecasts of wind gusts in the whole dataset. However, some winter storms exhibit uncharacteristic forecast errors that cannot be reduced by post‐processing. During the passage of the most severe storm, gusts related to a cold jet are predicted relatively well at the time of maximum intensity, whereas those related to a warm jet are poorly predicted at an early phase. Wind gusts are overestimated during two cases of frontal convection, which suggests that even higher resolution is needed to resolve fully the downward mixing of momentum and the stabilization resulting from convective dynamics. In contrast, extreme gusts are underestimated during a rare case involving a possible sting jet, but this arises from the representation of the synoptic rather than the mesoscale. The synoptic scale also controls the ensemble spread, which is inherited mostly from the initial and boundary conditions. This is unsurprising, but leads to high forecast uncertainty in the case of a small, fast‐moving cyclone crossing the model domain. These results illustrate how statistical post‐processing can help identify the limits of predictability across scales in convection‐permitting ensemble forecasts. They may guide the development of regime‐dependent statistical methods to improve forecasts of wind gusts in winter storms further.