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The accurate prediction of intense precipitation events is one of the main objectives of operational weather services. This task is even more relevant nowadays, with the rapid progression of global warming which intensifies these events. Numerical weather prediction models have improved continuously over time, providing uncertainty estimation with dynamical ensembles. However, direct precipitation forecasting is still challenging. Greater availability of machine‐learning tools paves the way to a hybrid forecasting approach, with the optimal combination of physical models, event statistics, and user‐oriented postprocessing. Here we describe a specific chain, based on a random‐forest (RF) pipeline, specialised in recognising favourable synoptic conditions leading to precipitation extremes and subsequently classifying extremes into predefined types. The application focuses on northern and central Italy, taken as a testbed region, but is seamlessly extensible to other regions and time‐scales. The system is called MaLCoX (Machine Learning model predicting Conditions for eXtreme precipitation) and is running daily at the Italian regional weather service of ARPAE Emilia‐Romagna. MalCoX has been trained with the ARCIS gridded high‐resolution precipitation dataset as the target truth, using the last 20 years of the European Centre for Medium‐Range Weather Forecasts (ECMWF) reforecast dataset as input predictors. We show that, with a long enough training period, the optimal blend of larger‐scale information with direct model output improves the probabilistic forecast accuracy of extremes in the medium range. In addition, with specific methods, we provide a useful diagnostic to convey to forecasters the underlying physical storyline which makes a meteorological event extreme. [ABSTRACT FROM AUTHOR]

In recent years, there has been growing evidence that latent heat release in midlatitude weather systems such as warm conveyor belts (WCBs) contributes significantly to the onset and maintenance of blocking anticyclones (blocked weather regimes). Still, numerical weather prediction (NWP) and climate models struggle to correctly predict and represent atmospheric blocking in particular over Europe. Here, we elucidate the representation of WCB activity in 20 years of extended winter (1997–2017) of European Centre for Medium‐Range Weather Forecast's IFS reforecasts around the onset of blocking over Europe (EuBL) employing different perspectives. First, we show that the model struggles to predict EuBL onsets already at 10–14 days lead time in line with a misrepresentation of WCB activity in the ensemble mean. However, we also find cases with accurate EuBL forecasts even in pentad 4 (15–19 days). This subset of successful forecasts at extended‐range lead times goes in line with accurate WCB forecasts over the North Atlantic several days prior to the blocking onset. Second, investigating the time‐lagged relationship of blocking onset and WCB activity, we find that WCB activity over the North Atlantic emerges well prior to the onset of the block and that different pathways into EuBL exist in the reforecasts compared to reanalysis. Finally, we find indication of predictability associated with a Rossby wave train emerging from the North Pacific. Although our study can not disentangle the roles of intrinsic predictability limits and model deficiencies, we show that correct predictions of EuBL go along with distinct patterns of WCB activity. Plain Language Summary: Warm conveyor belts (WCBs) are weather systems associated with low pressure systems which occur predominantly over the ocean regions of the midlatitudes. Several recent studies highlight the role of latent heat release due to cloud formation in WCBs for the development of long‐lived high pressure systems. However, current weather prediction and climate models struggle to accurately predict these high pressure systems, particularly over Europe (EuBL). This study, based on 20 years (1997–2017) of forecast data, reveals challenges in predicting WCB activity together with the onset of EuBL, especially within a lead time of 10–14 days. Successful predictions at extended lead times (15–19 days) align with precise forecasts of WCB activity over the North Atlantic and North Pacific, indicating a connection between these regions. Examining the timing of the onset of EuBL and WCB activity, we show that WCB activity over the North Atlantic precedes EuBL. Additionally, we identify both correct and incorrect pathways leading to EuBL and suggest that predictability of EuBL may arise from specific atmospheric patterns, particularly related to Rossby waves in the North Pacific. Key Points: Warm conveyor belt (WCB) activity around the onset of atmospheric blocking over Europe (EuBL) is analyzed in reanalysis and sub‐seasonal reforecastsCorrect WCB prediction provides a sub‐seasonal window of forecast opportunity for EuBL onsetSynoptic activity over the North Pacific supports the development of a teleconnection that affects EuBL onset [ABSTRACT FROM AUTHOR]

Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operational numerical weather prediction models account for aerosol direct effects by using climatological mean concentrations and neglect indirect effects. This simplification may lead to shortcomings in model forecasts during outbreaks of Saharan dust towards Europe, when climatological mean dust concentrations deviate strongly from actual concentrations. This study investigates errors in model analyses and short‐range forecasts during such events. We investigate a pronounced dust event in March 2021 using the pre‐operational ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON‐ART) with prognostic calculation of dust and the operational European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) model, which deploys a dust climatology. We compare model analysis and forecast with measurements from satellite and in situ instruments. We find that inclusion of prognostic aerosol and direct radiative effects from dust improves forecasts of surface radiation during clear‐sky conditions. However, dust‐induced cirrus clouds are strongly underestimated, highlighting the importance of representing indirect effects adequately. These findings are corroborated by systematic quantification of forecast errors against satellite measurements. For this we construct an event catalogue with 49 dust days over Central Europe between January 2018 and March 2022. We classify model cells by simulated and observed cloudiness and simulated dustiness in the total atmospheric column. We find significant overestimations of brightness temperature for cases with dust compared with cases without dust. For surface shortwave radiation, we find median overestimations of 6.2% during cloudy conditions with dust optical depth greater than 0.1, however these are not significant compared with cloudy conditions without dust. Our findings show that the pre‐operational ICON‐ART and the operational IFS model still do not reproduce cloudiness adequately during events with Saharan dust over Central Europe. Missing implementations of prognostic dust, particularly of indirect effects on cloud formation, lead to significant underestimations of cloudiness and potentially overestimations of surface radiation. [ABSTRACT FROM AUTHOR]

Warm conveyor belts (WCBs) are rapidly ascending air streams associated with extratropical cyclones. WCBs exert a substantial influence on the evolution of the large‐scale midlatitude flow and have previously been related to increased forecast uncertainty in case studies. This study provides a first systematic investigation of the role of WCBs for errors in medium‐range ensemble forecasts in the Atlantic–European region. The study is enabled through a unique data set, allowing for a Lagrangian detection of WCBs in three years of operational ensemble forecasts from the European Centre for Medium‐Range Weather Forecasts. By analysing the relationship between commonly used error metrics of variables that characterise the large‐scale flow and WCBs, the study aims to shed light on the question of the extent to which WCBs act as a source of forecast errors and as an amplifier of pre‐existing errors in a state‐of‐the‐art global operational numerical weather prediction model. We show that forecasts with high WCB activity are on average characterised by an amplified Rossby‐wave pattern and anticyclonic flow anomalies downstream. We find that the forecast skill is generally reduced when the WCB activity is high, and that WCB activity is particularly increased when the error growth is largest. To establish a causal relationship, we employ two composite approaches. The first focuses on the time of largest error growth and the second calculates normalised forecast error fields centered on WCB objects. Both approaches yield a consistent picture: anomalously high errors are initially associated with misrepresentations of an upstream trough. In regions of WCB ascent and outflow, the errors grow rapidly in terms of magnitude and scale and are projected onto the upper‐level large‐scale circulation. We also find indications that WCBs can cause errors even when the upstream flow is well represented. Notwithstanding, evidence is robust for WCBs acting as an amplifier of forecast uncertainty. [ABSTRACT FROM AUTHOR]

The prediction skill of sub‐seasonal forecast models is evaluated for seven year‐round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA‐Interim reanalysis. Results show that predicting weather regimes as a proxy for the large‐scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year‐round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so‐called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi‐model assessment of year‐round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision‐making. [ABSTRACT FROM AUTHOR]

Renewable power generation from wind and solar energy is strongly dependent on the weather. To plan future sustainable energy systems that are robust to weather variability, a better understanding of why and when periods of low wind and solar power output occur is valuable. We call such periods of low wind speed and insolation "Dunkelflauten", the German word for "dark wind lulls". In this article, we analyse the meteorological conditions during Dunkelflauten in Germany by applying the concept of weather regimes. Weather regimes are quasi‐stationary, recurrent and persistent large‐scale circulation patterns that explain multi‐day atmospheric variability (5–15 days). We use a regime definition that allows us to distinguish four different types of blocked regimes, characterized by high‐pressure situations in the North Atlantic‐European region. We find that Dunkelflauten in Germany occur mainly in winter when the solar power output is low due to the seasonal cycle of solar irradiance and wind power output drops for several consecutive days. A high‐pressure system over Germany, associated with the European Blocking regime, is responsible for most of the Dunkelflauten. Dunkelflauten during the Greenland Blocking regime are associated with colder temperatures than usual, causing higher electricity demand, and would present a particular challenge as space heating becomes electrified in the future. Furthermore, we show that Dunkelflauten occur predominantly when a weather regime is well established and persists longer than usual. Our study provides novel insight into the occurrence and meteorological characteristics of Dunkelflauten, which is essential for planning resilient energy systems and supporting grid operators to prepare for potential shortages in supply. [ABSTRACT FROM AUTHOR]

Extra‐tropical cyclones are an important source of weather variability in the mid‐latitudes. Multiple occurrences in a short period of time at a particular location are denominated serial cyclone clustering (SCC), and potentially lead to large societal impacts. We investigate the relationship between SCC affecting Western Europe and large‐scale weather regimes (WRs) in the North Atlantic‐European region in boreal winter. We find that SCC in low latitudes (45°N) is predominantly associated with the anticyclonic Greenland Blocking WR. In contrast, SCC in mid and high latitudes (55°N, 65°N) is mostly linked to different cyclonic WRs. Thereby, SCC occurs typically within a well‐established WR that builds up prior to SCC and decays after SCC. Thus, SCC events are closely associated with recurrent, quasi‐stationary and persistent large‐scale flow patterns (WRs). This mutual relationship reveals the potential of WRs in forecasting storm series and associated impacts on sub‐seasonal to seasonal time scales. Plain Language Summary: Serial cyclone clustering describes the occurrence of multiple extra‐tropical cyclones within a certain time frame and a spatially restricted region. Since extra‐tropical cyclones can be associated with strong winds and heavy precipitation, multiple occurrences can lead to large cumulative impacts in the affected areas. We analyze the relationship between serial cyclone clustering (SCC) in Western Europe and so‐called weather regimes (WRs) in the North Atlantic‐European region in boreal winter. These regimes describe slow evolving and enduring large‐scale atmospheric circulation patterns. Relationships with certain regime types are identified but depend on the latitude at which the clustered frequency of extra‐tropical cyclones is found. When SCC occurs in low latitudes (45°N), it mostly appears coincident with anticyclonic large‐scale flow patterns. In contrast, SCC in mid and high latitudes (55°N, 65°N) often occurs simultaneously with different cyclonic regimes. We find that periods of SCC occur typically within WR life cycles pointing to the fact that both, the WRs and SCC periods, are interlinked. This relationship may facilitate forecasting storm series and associated impacts on time scales beyond 2 weeks. Key Points: A close relationship is found between serial cyclone clustering (SCC) at 5°W and weather regimes (WRs) in the North Atlantic‐European regionSCC in mid and high latitudes (55°N, 65°N) is mainly associated with cyclonic and in low latitudes (45°N) with anticyclonic WR life cyclesRegardless of the selected latitude, SCC occurs mostly during an active regime life cycle and is manifested in a well‐established WR [ABSTRACT FROM AUTHOR]

The stochastically perturbed parametrisation tendency (SPPT) scheme is a well‐established technique in ensemble forecasting to address model uncertainty by introducing perturbations into the tendencies provided by the physics parametrisations. The magnitude of the perturbations scales with the local net parametrisation tendency, resulting in large perturbations where diabatic processes are active. Rapidly ascending air streams, such as warm conveyor belts (WCBs) and organized tropical convection, are often driven by cloud diabatic processes and are therefore prone to such perturbations. This study investigates the effects of SPPT and initial condition perturbations on rapidly ascending air streams by computing trajectories in sensitivity experiments with the European Centre for Medium‐Range Weather Forecasts (ECMWF) ensemble prediction system, which are set up to disentangle the effects of initial conditions and physics perturbations. The results demonstrate that SPPT systematically increases the frequency of rapidly ascending air streams. The effect is observed globally, but is enhanced in regions where the latent heating along the trajectories is larger. Despite the frequency changes, there are only minor modifications to the physical properties of the trajectories due to SPPT. In contrast to SPPT, initial condition perturbations do not affect WCBs and tropical convection systematically. An Eulerian perspective on vertical velocities reveals that SPPT increases the frequency of strong upward motions compared with experiments with unperturbed model physics. Consistent with the altered vertical motions, precipitation rates are also affected by the model physics perturbations. The unperturbed control member shows the same characteristics as the experiments without SPPT regarding rapidly ascending air streams. We make use of this to corroborate the findings from the sensitivity experiments by analyzing the differences between perturbed and unperturbed members in operational ensemble forecasts of ECMWF. Finally, we give an explanation of how symmetric, zero‐mean perturbations can lead to a unidirectional response when applied in a nonlinear system. [ABSTRACT FROM AUTHOR]

Sudden stratospheric warmings (SSWs) can have a strong impact on the troposphere. Their fingerprint is often associated with the negative phase of the Northern Annular Mode (NAM) and the North Atlantic Oscillation (NAO), and extreme weather with high societal impact. However, the mechanisms behind this downward impact are not well understood. We investigate this surface impact through its associated predictability limits, by studying the 2018 SSW event. We search for predictability barriers that occurred after the onset of the SSW and before its surface impact. It is found that dynamical tropospheric events consisting of two cyclogenesis events were the main reasons for these predictability barriers in the prediction of negative NAM/NAO anomalies reaching the surface. This work corroborates that individual synoptic events might constitute predictability barriers during the downward impact of SSW events, and thereby sheds light on stratosphere‐troposphere coupling. Plain Language Summary: Sudden stratospheric warmings (SSWs) can have a strong impact on near‐surface weather. They have the potential to alter the atmospheric circulation and associated extreme events, thus affecting society. However, the way the stratosphere couples with surface weather is not fully understood. In this work, we investigate this relationship by analyzing the predictability of the surface impact of a stratospheric warming event that occurred in 2018, and which left widespread societal impacts over Europe due to a severe cold spell and extraordinary rainy and windy conditions. We find that the impact of this SSW event on the surface was regulated by two low‐pressure systems that developed over the North Atlantic. Even though the SSW event was well developed, alternative behavior of these systems could have led to drastically different weather conditions over Europe. Thus, this study highlights the role of the tropospheric circulation in the effectiveness of the stratospheric impact on surface weather. Key Points: The surface impact of the sudden stratospheric warming in 2018 was associated with a Greenland blocking in the troposphereMedium‐range uncertainties in the prediction of the Greenland blocking were linked to two cyclogenesis events over the North AtlanticIndividual synoptic events constitute "predictability barriers" for subsequent forecast lead times after sudden stratospheric warming events [ABSTRACT FROM AUTHOR]

The subseasonal variability of the extratropical large‐scale atmospheric flow is characterized by recurrent or quasi‐stationary circulation anomalies, termed weather regimes. Despite the usefulness of these regimes in numerous meteorological and socioeconomic applications, there is an ongoing debate as to whether they represent physical modes of the atmosphere, or are merely useful statistical categorizations. Here, we answer this question for wintertime Atlantic‐European regimes. We argue that dynamical systems theory applied to a refined regime definition provides strong evidence in support of most weather regimes being physically meaningful. This finding underpins the broad relevance of weather regimes, for understanding the response of the atmosphere to external forcing, supporting subseasonal weather forecasting, and down scaling of climate projections. Plain Language Summary: The weather situation over the North Atlantic and Europe region is dominated by steady large‐scale atmospheric circulation patterns that occur repeatedly, often termed weather regimes. Despite their usefulness in weather forecasting, it is questioned whether these regimes have a clear physical grounding, or are merely useful statistical classifications. By showing that the atmospheric circulation indeed settles down in a comparably steady state during certain regimes, we provide strong evidence in support of their physical foundation. This finding underpins the broad relevance of weather regimes in supporting weather forecasting several weeks ahead and, in addition, understanding the impacts of climate change on our atmosphere. Key Points: We assess the physical grounding of Atlantic‐European winter weather regimes (WR) using dynamical systems (DS) theoryMost WR display distinct and predictable flow characteristics at their maximum stage, and unpredictable flow at onset and decayThe agreement between the statistical classification and the DS analysis provides strong evidence for most WR being physically meaningful [ABSTRACT FROM AUTHOR]

Weather regime forecasts are a prominent use case of sub-seasonal prediction in the midlatitudes. A systematic evaluation and understanding of year-round sub-seasonal regime forecast performance is still missing, however. Here we evaluate the representation of and forecast skill for seven year-round Atlantic-European weather regimes in sub-seasonal reforecasts from the European Centre for Medium-Range Weather Forecasts. Forecast calibration improves regime frequency biases and forecast skill most strongly in summer, but scarcely in winter, due to considerable large-scale flow biases in summer. The average regime skill horizon in winter is about 5 days longer than in summer and spring, and 3 days longer than in autumn. The Zonal Regime and Greenland Blocking tend to have the longest year-round skill horizon, which is driven by their high persistence in winter. The year-round skill is lowest for the European Blocking, which is common for all seasons but most pronounced in winter and spring. For the related, more northern Scandinavian Blocking, the skill is similarly low inwinter and spring but higher in summer and autumn. We further show that the winter average regime skill horizon tends to be enhanced following a strong stratospheric polar vortex (SPV), but reduced following a weak SPV. Likewise, the year-round average regime skill horizon tends to be enhanced following phases 4 and 7 of the Madden-Julian Oscillation (MJO) but reduced following phase 2, driven by winter but also autumn and spring. Our study thus reveals promising potential for year-round sub-seasonal regime predictions. Further model improvements can be achieved by reduction of the considerable large-scale flow biases in summer, better understanding and modeling of blocking in the European region, and better exploitation of the potential predictability provided by weak SPV states and specific MJO phases in winter and the transition seasons. [ABSTRACT FROM AUTHOR]

Meteorologists in the energy industry increasingly draw upon the potential for enhanced sub‐seasonal predictability of European surface weather following anomalous states of the winter stratospheric polar vortex (SPV). How the link between the SPV and the large‐scale tropospheric flow translates into forecast skill for surface weather in individual countries – a spatial scale that is particularly relevant for the energy industry – remains an open question. Here we quantify the effect of anomalously strong and weak SPV states at forecast initial time on the probabilistic extended‐range reforecast skill of the European Centre for Medium‐Range Weather Forecasts (ECMWF) in predicting country‐ and month‐ahead‐averaged anomalies of 2 m temperature, 10 m wind speed, and precipitation. After anomalous SPV states, specific surface weather anomalies emerge, which resemble the opposing phases of the North Atlantic Oscillation. We find that forecast skill is, to first order, only enhanced for countries that are entirely affected by these anomalies. However, the model has a flow‐dependent bias for 2 m temperature (T2M): it predicts the warm conditions in Western, Central and Southern Europe following strong SPV states well, but is overconfident with respect to the warm anomaly in Scandinavia. Vice versa, it predicts the cold anomaly in Scandinavia following weak SPV states well, but struggles to capture the strongly varying extent of the cold air masses into Central and Southern Europe. This tends to reduce skill (in some cases significantly) for Scandinavian countries following strong SPV states, and most pronounced, for many Central, Southern European, and Balkan countries following weak SPV states. As most of the weak SPV states are associated with sudden stratospheric warmings (SSWs), our study thus advices particular caution when interpreting sub‐seasonal regional T2M forecasts following SSWs. In contrast, it suggests that the model benefits from enhanced predictability for a considerable part of Europe following strong SPV states. [ABSTRACT FROM AUTHOR]

The El Niño phase of the El Niño Southern Oscillation (ENSO) is typically associated with below‐average cool‐season rainfall in southeastern Australia (SEA). However, there is also large case‐to‐case variability on monthly time‐scales. Despite recent progress in understanding the links between remote climate drivers and this variability, the underlying dynamical processes are not fully understood. This reanalysis‐based study aims to advance the dynamical understanding by quantifying the contribution of midlatitude weather systems to monthly precipitation anomalies over SEA during the austral winter–spring season. A k‐means clustering reveals four rainfall anomaly patterns with above‐average rainfall (Cluster 1), below‐average rainfall (Cluster 2), above‐average rainfall along the East Coast (Cluster 3) and along the South Coast (Cluster 4). Cluster 2 occurs most frequently during El Niño, which highlights the general suppression of SEA rainfall during these events. However, the remaining three clusters with local above‐average rainfall are found in ∼52% of all El Niño months. Changes of weather system frequency determine the respective rainfall anomaly pattern. Results indicate significantly more cut‐off lows and warm conveyor belts (WCBs) over SEA in El Niño Cluster 1 and significantly fewer in El Niño Cluster 2. In El Niño Cluster 3, enhanced blocking south of Australia favours cut‐off lows leading to increased rainfall along the East Coast. Positive rainfall anomalies along the South Coast in El Niño Cluster 4 are associated with frontal rainfall due to an equatorward shift of the midlatitude storm track. Most of the rainfall is produced by WCBs and cut‐off lows but the contributions strongly vary between the clusters. In all clusters, rainfall anomalies result from changes in rainfall frequency more than in rainfall intensity. Backward trajectories of WCB and cut‐off low rainfall highlight the importance of moist air masses from the Coral Sea and the northwest coast of Australia during wet months. [ABSTRACT FROM AUTHOR]

Extreme states of the stratospheric polar vortex can have long‐lasting impacts on extratropical circulation patterns, such as the North Atlantic Oscillation (NAO). This provides windows of subseasonal predictability beyond the typical weather forecast horizon of about 10 days. Subseasonal forecasts of surface weather are of significant interest in weather‐dependent socio‐economic sectors. For example, demand and supply for electricity and gas are weather dependent and therefore accurate forecasts are important for the energy industry and energy trading. Here we investigate the subseasonal impact of stratospheric conditions on surface weather events relevant to the energy industry in five subregions of Europe in winter. We use a definition of seven Atlantic–European weather regimes to describe the variability of the large‐scale circulation on subseasonal time scales. Results indicate that weather events are often associated with more than one preferred weather regime. In turn, some weather regimes project onto a specific NAO phase, while others are independent of the NAO. As expected, anomalous stratospheric polar vortex states predominantly modulate the occurrence of regimes related to the NAO and affect the likelihood of their associated weather events. In contrast, the occurrence of weather regimes which do not project well onto the NAO is not affected by anomalous stratospheric polar vortex states. These regimes provide pathways to unexpected weather events in extreme stratospheric polar vortex states. For example, weak stratospheric polar vortex states enhance the likelihood of negative NAO. High wind events in Central Europe predominantly occur during the zonal regime, strongly projecting onto positive NAO. However, these events also occur during the Atlantic trough regime, which is unaffected by anomalous stratospheric polar vortex states and thus provides a pathway to Central European high wind events during weak stratospheric polar vortex states. A correct NAO prediction alone is therefore not sufficient to correctly predict surface weather after extreme stratospheric polar vortex states. Moreover, weather regime life cycles independent of the NAO also need to be forecast accurately. [ABSTRACT FROM AUTHOR]

Despite huge progress made, state‐of‐the‐art numerical weather prediction systems occasionally experience severe forecast busts for the large‐scale extratropical circulation. This study investigates one of the most severe forecast busts for Europe in the European Centre for Medium‐Range Weather Forecasts integrated forecasting system (IFS) in recent years. The forecast bust occurred in March 2016 and was associated with a misforecast of the onset of a blocking regime. We investigate the evolution of the forecast error in the IFS ensemble by employing a potential vorticity perspective combined with Lagrangian diagnostics. We show that the error grows rapidly from an initially small perturbation in the detailed structure of an upper‐level trough near Newfoundland. This trough triggers strong diabatic warm conveyor belt activity in the North Atlantic region. The misrepresentation of this warm conveyor belt activity in the ensemble forecast amplifies the initial condition error and communicates it downstream into Europe. Specifically, the ensemble underestimates poleward warm conveyor belt ascent and associated warm conveyor belt outflow into high latitudes. Instead, all ensemble members forecast too strong warm conveyor belt outflow further to the south, which ultimately results in a wrong forecast of the upper‐level Rossby wave pattern over Europe. This case study shows that warm conveyor belts and the associated latent heat release in slantwise ascending air can trigger a nonlinear feedback mechanism that amplifies forecast error strongly and communicates it into regions far downstream. It corroborates the fact that multiscale interactions and moist‐and dry‐dynamical processes ranging from microphysical to synoptic scales need to be represented accurately in numerical weather prediction, in order to predict the extratropical large‐scale circulation correctly. The onset, decay, and transition of large‐scale flow regimes constitute a key challenge in subseasonal numerical weather prediction and are prone to forecast error. In this study, we document one of the severest forecast busts in the ECMWF IFS ensemble in recent years. We show that, during the onset of European blocking, a poorly forecast warm conveyor belt amplified and propagated downstream an initial condition error, corroborating the need to represent cloud diabatic processes correctly in order to improve extended‐range forecasts. [ABSTRACT FROM AUTHOR]

At the turn of the years 2015/2016, maximum surface temperature in the Arctic reached record-high values, exceeding the melting point, which led to a strong reduction of the Arctic sea ice extent in the middle of the cold season. Here we show, using a Lagrangian method, that a combination of very different airstreams contributed to this event: (i) warm low-level air of subtropical origin, (ii) initially cold low-level air of polar origin heated by surface fluxes, and (iii) strongly descending air heated by adiabatic compression. The poleward transport of these warm airstreams occurred along an intense low-level jet between a series of cyclones and a quasi-stationary anticyclone. The complex 3-D configuration that enabled this transport was facilitated by continuous warm conveyor belt ascent into the upper part of the anticyclone. This study emphasizes the combined role of multiple transport processes and transient synoptic-scale dynamics for establishing an extreme Arctic warm event. [ABSTRACT FROM AUTHOR]

This study reconciles two perspectives on wintertime atmospheric variability in the North Atlantic-European sector: the zonal-mean framework comprising three preferred locations of the eddy-driven jet (southern, central, northern), and the weather regime framework comprising four classical North Atlantic-European regimes (Atlantic ridge AR, zonal ZO, European/Scandinavian blocking BL, Greenland anticyclone GA). A k-means clustering algorithm is used to characterize the two-dimensional variability of the eddy-driven jet stream, defined by the lower tropospheric zonal wind in the ERA-Interim reanalysis. The first three clusters capture the central jet and northern jet, along with a new mixed-jet configuration; a fourth cluster is needed to recover the southern jet. The mixed cluster represents a split or strongly tilted jet, neither of which is well described in the zonal-mean framework, and has a persistence of about one week, similar to the other clusters. Connections between the preferred jet locations and weather regimes are corroborated - southern to GA, central to ZO, and northern to AR. In addition, the new mixed cluster is found to be linked to European/Scandinavian blocking, whose relation to the eddy-driven jet was previously unclear. [ABSTRACT FROM AUTHOR]

Alpine heavy precipitation events often affect small catchments, although the circulation pattern leading to the event extends over the entire North Atlantic. The various scale interactions involved are particularly challenging for the numerical weather prediction of such events. Unlike previous studies focusing on the southern Alps, here a comprehensive study of a heavy precipitation event in the northern Alps in October 2011 is presented with particular focus on the role of the large-scale circulation in the North Atlantic/European region. During the event exceptionally high amounts of total precipitable water occurred in and north of the Alps. This moisture was initially transported along the flanks of a blocking ridge over the North Atlantic. Subsequently, strong and persistent northerly flow established at the upstream flank of a trough over Europe and steered the moisture towards the northern Alps. Lagrangian diagnostics reveal that a large fraction of the moisture emerged from the West African coast where a subtropical upper-level cut-off low served as an important moisture collector. Wave activity flux diagnostics show that the ridge was initiated as part of a low-frequency, large-scale Rossby wave train while convergence of fast transients helped to amplify it locally in the North Atlantic. A novel diagnostic for advective potential vorticity tendencies sheds more light on this amplification and further emphasizes the role of the ridge in amplifying the trough over Europe. Operational forecasts misrepresented the amplitude and orientation of this trough. For the first time, this study documents an important pathway for northern Alpine flooding, in which the interaction of synoptic-scale to large-scale weather systems and of long-range moisture transport from the Tropics are dominant. Moreover, the trapping of moisture in a subtropical cut-off near the West African coast is found to be a crucial precursor to the observed European high-impact weather. [ABSTRACT FROM AUTHOR]

A feature-based approach is introduced to assess the quality of the representation of warm conveyor belts (WCBs) in high-resolution forecasts of the European Centre for Medium-range Weather Forecasts (ECMWF). WCBs are moist ascending airstreams in extratropical cyclones, which transport boundary-layer air within 1-2 days poleward to the upper troposphere. The WCB outflow is typically characterised by low potential vorticity (PV), amplifying upper-level ridges and in turn modifying the jet stream and downstream Rossby wave evolution. Therefore the correct representation of WCBs can be essential for medium-range weather prediction. A three-component verification measure PAL is introduced, measuring errors in the WCB outflow's PV anomaly ( P component), the amplitude of the WCB ( A component), and the location of the outflow ( L component). The PAL approach is applied to North Atlantic WCBs in ECMWF forecasts during three winters between 2002/2003 and 2010/2011. For the latest winter, the PAL results are also compared to the anomaly correlation coefficient (ACC) of upper-level PV. It is shown that (i) the representation of WCBs improves for forecasts with a shorter lead time, (ii) PAL values are on average better for more recent forecasts, (iii) recent model versions show no systematic over- or underestimation of WCB intensity, (iv) individual medium-range forecasts can be associated with large errors in particular in the amplitude of WCBs, and (v) the comparison of PAL and the ACC indicates that several poor forecasts in terms of ACC are indeed associated with significant errors in the representation of WCBs. Limitations of this study are also discussed. [ABSTRACT FROM AUTHOR]

Extratropical transition (ET) of a tropical cyclone (TC) can modify the midlatitude flow and thus have implications for the weather and predictability in downstream regions such as North America or Europe. Albeit recurving and undergoing ET, the downstream impact of Typhoon Jangmi in September 2008 during the THORPEX Pacific Asian Regional Campaign (T-PARC) was weak. In this study, we explore the physical processes inhibiting the reintensification of Jangmi and governing the forecast uncertainty during ET. The focus is on the relative contribution of the TC and the midlatitude flow. Quasi-geostrophic diagnostics reveal that Jangmi is located south of and in phase with a midlatitude trough. Jangmi does not couple with the region favourable for reintensification ahead of the trough and subsequently decays. Instead, a weak frontal wave-like cyclone develops. The role of the phasing of Typhoon Jangmi and the midlatitude Rossby wave pattern is tested in sensitivity experiments with the COSMO model in which Jangmi has been relocated. The simulations reveal two contrasting groups of scenarios. The first group reflects the weak actual ET and subsequent decay accompanied by a broad ridge over the Pacific. The second group is characterized by a strong ET with extratropical reintensification, the triggering of a pronounced Rossby wave train and downstream cyclogenesis. The displacement of Jangmi's initial position in the two contrasting groups is less than 1.25° (130 km). In the frame moving with the environmental background flow a critical bifurcation point for the track of Jangmi exists. The relative position to this bifurcation point determines whether Jangmi decays or reintensifies and triggers a Rossby wave train. A simple discrimination parameter is derived that allows for classifying the scenarios. The observed behaviour gives a simple explanation for the reduced predictability of the track and of the midlatitude flow in downstream regions during ET. [ABSTRACT FROM AUTHOR]

This study identifies the key physical process that governs the direct impact of the extratropical transition (ET) of Typhoon Jangmi on the midlatitude flow in September 2008. Jangmi was the strongest tropical cyclone (TC) in the western North Pacific in 2008 and occurred during the THORPEX Pacific Asian Regional Campaign (T-PARC). A distinct outflow-jet interaction resulted in ridgebuilding directly downstream of the ET system and a strongly accelerated upper-level jet streak over Japan. A combination of model and observational data is used to investigate the interaction of the transforming TC with the midlatitude flow and a potential vorticity (PV) surgery technique based on PV inversion is developed to further quantify the contribution of the TC to the modification of the midlatitude flow during ET. The joint interaction of the TC circulation with the midlatitude baroclinic zone and of the TC outflow with the upper-level jet is found to be responsible for a substantial diabatically enhanced vertical transport of lower tropospheric air that arrives at jet level with nearly zero PV. This process explains the ridgebuilding and evolution of the jet streak to the northeast of the ET system. The quantification of Jangmi's role in the outflow-jet interaction revealed the diabatic reduction and isentropic transport of upper-tropospheric PV into the jet region as the key physical process responsible for the direct impact of ET. This is manifested in a ridgebuilding with upper-level PV being 6 PVU lower and a midlatitude jet streak being at least 25 m s−1 faster in the presence of Jangmi. The study corroborates the crucial role that ET has on the modification of the midlatitude flow directly downstream of a transforming TC. The remote, downstream impact of the ET of Jangmi is investigated in a companion paper. [ABSTRACT FROM AUTHOR]

The article offers information on a study for planning aircraft measurements in warm conveyor belts (WCBs). An aircraft experiment study was conducted from October 8-26, 2012 to study the diabatic processes in WCBs as well as the effect of their potential misrepresentation in numerical-weather-prediction (NWP) models. The conclusion and outlook for the study is also outlined.