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Variability in the stratosphere, especially extreme events such as sudden stratospheric warmings (SSWs), can impact surface weather. Understanding stratospheric prediction uncertainty is therefore crucial for skillful surface weather forecasts on weekly to monthly timescales. Using ECMWF subseasonal hindcasts, this study finds that stratospheric uncertainty is most strongly linked to tropospheric uncertainty over the North Pacific and Northern Europe, regions that can modulate but also respond to stratospheric variability, suggesting a two-way propagation of uncertainty. A case study of the 2018 SSW event shows an initial poleward and upward propagation of uncertainty from tropical convection, followed by a downward propagation where ensemble members that accurately predict the SSW are also better at predicting its downward impacts. These findings highlight the locations in the troposphere that are linked to stratospheric uncertainty and suggest that improved model representation of tropospheric mechanisms linked to polar vortex variability could enhance both stratospheric and extratropical surface prediction.

In this study we provide a systematic characterization of Rossby wave activity during the 25 sudden stratospheric warming (SSW) and 31 strong polar vortex (SPV) events that occurred in the period 1979–2021, identifying the specific tropospheric and stratospheric waves displaying anomalous behaviour during such events. Space–time spectral analysis is applied to ERA5 data for this purpose, so that both the wavenumber and the zonal phase speed of the waves can be assessed. We find that SSW events are associated with a reduction in the phase speed of Rossby waves, first in the stratosphere and then in the troposphere; SPV events are tied to a simultaneous increase of phase speed across vertical levels. Phase speed anomalies become significant around the event and persist for 2–3 weeks afterwards. Changes of Rossby wave properties in the stratosphere during SSW and SPV events are dominated by changes in the background flow, with a systematic reduction or increase, respectively, in eastward propagation of the waves across most wavenumbers. In the troposphere, on the other hand, the effect of the background flow is also complemented by changes in wave properties, with a shift towards higher wavenumbers during SSW events and towards lower wavenumbers for SPV events. The opposite response between SSW and SPV events is also visible in the meridional heat and momentum flux co-spectra, which highlight from a novel perspective the connection between stratospheric Rossby waves and upward propagation of waves.

Winter windstorms are among the most significant natural hazards in Europe linked to fatalities and substantial damage. However, projections of windstorm impact in Europe under climate change are highly uncertain. This study combines climate projections from 30 general circulation models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) with the climate risk assessment model CLIMADA to obtain projections of windstorm-induced damage over Europe in a changing climate. We conduct an uncertainty–sensitivity analysis and find large uncertainties in the projected changes in the damage, with climate model uncertainty being the dominant factor of uncertainty in the projections. We investigate the spatial patterns of the climate change-induced modifications in windstorm damage and find an increase in the damage in northwestern and northern central Europe and a decrease over the rest of Europe, in agreement with an eastward extension of the North Atlantic storm track into Europe. We combine all 30 available climate models in an ensemble-of-opportunity approach and find evidence for an intensification of future climate windstorm damage, in which damage with return periods of 100 years under current climate conditions becomes damage with return periods of 28 years under future SSP585 climate scenarios. Our findings demonstrate the importance of climate model uncertainty for the CMIP6 projections of windstorms in Europe and emphasize the increasing need for risk mitigation due to extreme weather in the future.

Persistent and organized convective cloud systems that arise in convergence zones can lead to the formation of synoptic cloud bands extending from the tropics to the extratropics. These cloud bands are responsible for heavy precipitation and are often a combination of tropical intrusions of extratropical Rossby waves and processes originating from the tropics. Detecting these cloud bands presents a valuable opportunity to enhance our understanding of the variability of these systems and the underlying processes that govern their behavior and that connect the tropics and the extratropics. This paper presents a new atmospheric cloud band detection method based on outgoing longwave radiation using computer vision techniques, which offers enhanced capabilities to identify long cloud bands across diverse gridded datasets and variables. The method is specifically designed to detect extended tropical–extratropical convective cloud bands, ensuring accurate identification and analysis of these dynamic atmospheric features in convergence zones. The code allows for easy configuration and adaptation of the algorithm to meet specific research needs. The method handles cloud band merging and splitting, which allows for an understanding of the life cycle of cloud bands and their climatology. This algorithm lays the groundwork for improving our understanding of the large-scale processes that are involved in the formation and life cycle of cloud bands and the connections between tropical and extratropical regions as well as evaluating the differences in cloud band types between different ocean basins.

Extreme stratospheric polar vortex events, such as sudden stratospheric warmings (SSWs) or extremely strong polar vortex events, can have a significant impact on surface weather in winter. SSWs are most often associated with negative North Atlantic Oscillation (NAO) conditions, cold air outbreaks in the Arctic and a southward-shifted midlatitude storm track in the North Atlantic, while strong polar vortex events tend to be followed by a positive phase of the NAO, relatively warm conditions in the extratropics and a poleward-shifted storm track. Such changes in the storm track position and associated extratropical cyclone frequency over the North Atlantic and Europe can increase the risk of extreme windstorm, flooding or heavy snowfall over populated regions. Skillful predictions of the downward impact of stratospheric polar vortex extremes can therefore improve the predictability of extratropical winter storms on subseasonal timescales. However, there exists a strong inter-event variability in these downward impacts on the tropospheric storm track. Using ECMWF reanalysis data and reforecasts from the Subseasonal to Seasonal (S2S) Prediction Project database, we investigate the stratospheric influence on extratropical cyclones, identified with a cyclone detection algorithm. Following SSWs, there is an equatorward shift in cyclone frequency over the North Atlantic and Europe in reforecasts, and the opposite response is observed after strong polar vortex events, consistent with the response in reanalysis. However, although the response of cyclone frequency following SSWs with a canonical surface impact is typically captured well during weeks 1–4, less than 25 % of the reforecasts manage to capture the response following SSWs with a “non-canonical” impact. This suggests a possible overconfidence in the reforecasts with respect to reanalysis in predicting the canonical response after SSWs, although it only occurs in about two-thirds of the events. The cyclone forecasts following strong polar vortex events are generally more successful. Understanding the role of the stratosphere in subseasonal variability and predictability of storm tracks during winter can provide a key for reliable forecasts of midlatitude storms and their surface impacts.

Since the Madden–Julian oscillation (MJO) is a major source for tropical and extratropical variability on weekly to monthly timescales, the intrinsic predictability of its global teleconnections is of great interest. As the tropical diabatic heating associated with the MJO ultimately drives these teleconnections, the variability in heating among ensemble forecasts initialized from the same episode of the MJO will limit this predictability. In order to assess this limitation, a suite of 60 d ensemble reforecasts has been carried out with the ECMWF forecast model, spanning 13 starting dates from 1 November and 1 January for different years. The initial dates were chosen so that phases 2 and 3 of the MJO (with anomalous tropical heating in the Indian Ocean sector) were present in the observed initial conditions. The 51 members of an individual ensemble use identical initial conditions for the atmosphere and ocean. Stochastic perturbations to the tendencies produced by the atmospheric physics parameterizations are applied only over the Indian Ocean region (50–120∘ E). This guarantees that the spread between reforecasts within an ensemble is due to perturbations in heat sources only in the Indian Ocean sector. The point-wise spread in the intra-ensemble (or error) variance of vertically integrated tropical heating Q is larger than the average ensemble mean signal even at early forecast times; however the planetary wave (PW) component of Q (zonal waves 1–3) is predictable for 25 to 45 d, the time taken for the error variance to reach 50 % to 70 % of saturation. These scales never reach 90 % of saturation during the forecasts. The upper-level tropical PW divergence is even more predictable than Q (40 to 50 d). In contrast, the PW component of the 200 hPa Rossby wave source, which is responsible for propagating the influence of tropical heating to the extratropics, is only predictable for 20 to 30 d. A substantial ensemble spread of 300 hPa meridional wind propagates from the tropics to the Northern Hemisphere storm-track regions by days 15–16. Following the growth of upper-tropospheric spread in planetary wave heat flux, the stratosphere provides a feedback in enhancing the error via downward propagation towards the end of the reforecasts.

El Niño–Southern Oscillation (ENSO) is a major source for teleconnections, including towards the tropical North Atlantic (TNA) region, whereby TNA sea surface temperatures (SSTs) are positively correlated with ENSO in boreal spring following an ENSO event. However, the Pacific–Atlantic connection can be impacted by different ENSO characteristics, such as the amplitude, location, and timing of Pacific SST anomalies (SSTAs). Indeed, the TNA SSTAs may respond nonlinearly to strong and extreme El Niño events. However, observational data for the number of extreme ENSO events remain limited, restricting our ability to investigate the influence of observed extreme ENSO events. To overcome this issue and to further evaluate the nonlinearity of the TNA SSTA response, two coupled climate models are used, namely the Community Earth System Model version 1 – Whole Atmosphere Community Climate Model (CESM-WACCM) and the Flexible Ocean and Climate Infrastructure version 1 (FOCI). In both models the TNA SSTAs respond linearly to ENSO during extreme El Niño events but nonlinearly to extreme La Niña events for CESM-WACCM. We investigate differences by using indices for all major mechanisms that connect ENSO to the TNA and compare them with reanalysis. CESM-WACCM and FOCI overall represent the teleconnection well, including that the tropical and extratropical pathways are similar to observations. Our results also show that a large portion of the nonlinearity during La Niña is explained by the interaction between Pacific SSTAs and the overlying upper-level divergence.

On average every 2 years, the stratospheric polar vortex exhibits extreme perturbations known as sudden stratospheric warmings (SSWs). The impact of these events is not limited to the stratosphere: but they can also influence the weather at the surface of the Earth for up to 3 months after their occurrence. This downward effect is observed in particular for SSW events with extended recovery timescales. This long-lasting stratospheric impact on surface weather can be leveraged to significantly improve the performance of weather forecasts on timescales of weeks to months. In this paper, we present a fully data-driven procedure to improve the performance of long-range forecasts of the stratosphere around SSW events with an extended recovery. We first use unsupervised machine learning algorithms to capture the spatio-temporal dynamics of SSWs and to create a continuous scale index measuring both the frequency and the strength of persistent stratospheric perturbations. We then uncover three-dimensional spatial patterns maximizing the correlation with positive index values, allowing us to assess when and where statistically significant early signals of SSW occurrence can be found. Finally, we propose two machine learning (ML) forecasting models as competitors for the state-of-the-art sub-seasonal European Centre for Medium-Range Weather Forecasts (ECMWF) numerical prediction model S2S (sub-seasonal to seasonal): while the numerical model performs better for lead times of up to 25 d, the ML models offer better predictive performance for greater lead times. We leverage our best-performing ML forecasting model to successfully post-process numerical ensemble forecasts and increase their performance by up to 20 %.

Sudden stratospheric warmings (SSWs) have a long-lasting effect within the stratosphere as well as impacts on the underlying troposphere. However, sub-seasonal forecasts of the winter polar stratosphere fail to use their full potential for predictability as they tend to underestimate the magnitude and persistence of these events already within the stratosphere. The origin of this underestimation is unknown. Here, we demonstrate that the associated polar stratospheric cold bias following SSW events in sub-seasonal hindcasts can be halved by increasing vertical model resolution, suggesting a potential sensitivity to gravity wave forcing. While the predictability of the planetary Rossby wave flux into the stratosphere at lead times longer than a week is limited, the existence of a critical layer for gravity waves with a low zonal phase speed caused by the disturbed polar vortex provides predictability to the upper stratosphere. Gravity wave breaking near that critical layer can, therefore, decelerate the zonal flow consistently with anomalous subsidence over the polar cap leading to warmer temperatures in the middle polar stratosphere. Since the spectrum of gravity waves involves vertical wavelengths of less than 4000 m, as estimated by wavelet analysis, a high vertical model resolution is needed to resolve the positive feedback between gravity wave forcing and the state of the polar vortex. Specifically, we find that at a spectral resolution of TCo639 (approximate horizontal grid spacing of 18 km) at least 198 levels are needed to correctly resolve the spectrum of gravity waves in the ECMWF Integrated Forecasting System. Increasing vertical resolution in operational forecasts will help to mitigate stratospheric temperature biases and improve sub-seasonal predictions of the stratospheric polar vortex.

Ozone in the Arctic stratosphere is subject to large interannual variability, driven by both chemical ozone depletion and dynamical variability. Anomalies in Arctic stratospheric ozone become particularly important in spring, when returning sunlight allows them to alter stratospheric temperatures via shortwave heating, thus modifying atmospheric dynamics. At the same time, the stratospheric circulation undergoes a transition in spring with the final stratospheric warming (FSW), which marks the end of winter. A causal link between stratospheric ozone anomalies and FSWs is plausible and might increase the predictability of stratospheric and tropospheric responses on sub-seasonal to seasonal timescales. However, it remains to be fully understood how ozone influences the timing and evolution of the springtime vortex breakdown. Here, we contrast results from chemistry climate models with and without interactive ozone chemistry to quantify the impact of ozone anomalies on the timing of the FSW and its effects on surface climate. We find that ozone feedbacks increase the variability in the timing of the FSW, especially in the lower stratosphere. In ozone-deficient springs, a persistent strong polar vortex and a delayed FSW in the lower stratosphere are partly due to the lack of heating by ozone in that region. High-ozone anomalies, on the other hand, result in additional shortwave heating in the lower stratosphere, where the FSW therefore occurs earlier. We further show that FSWs in high-ozone springs are predominantly followed by a negative phase of the Arctic Oscillation (AO) with positive sea level pressure anomalies over the Arctic and cold anomalies over Eurasia and Europe. These conditions are to a significant extent (at least 50 %) driven by ozone. In contrast, FSWs in low-ozone springs are not associated with a discernible surface climate response. These results highlight the importance of ozone–circulation coupling in the climate system and the potential value of interactive ozone chemistry for sub-seasonal to seasonal predictability.

Extreme events in the stratospheric polar vortex can lead to changes in the tropospheric circulation and impact the surface climate on a wide range of timescales. The austral stratospheric vortex shows its largest variability in spring, and a weakened polar vortex is associated with changes in the spring to summer surface climate, including hot and dry extremes in Australia. However, the robustness and extent of the connection between polar vortex strength and surface climate on interannual timescales remain unclear. We assess this relationship by using reanalysis data and time-slice simulations from two chemistry-climate models (CCMs), building on previous work that is mainly based on observations. The CCMs show a similar downward propagation of anomalies in the polar vortex strength to the reanalysis data: a weak polar vortex is on average followed by a negative tropospheric Southern Annular Mode (SAM) in spring to summer, while a strong polar vortex is on average followed by a positive SAM. The signature in the surface climate following polar vortex weakenings is characterized by high surface pressure and warm temperature anomalies over Antarctica, the region where surface signals are most robust across all model and observational datasets. However, the tropospheric SAM response in the two CCMs considered is inconsistent with observations. In one CCM, the SAM is more negative compared to the reanalysis after weak polar vortex events, whereas in the other CCM, it is less negative. In addition, neither model reproduces all the regional changes in midlatitudes, such as the warm and dry anomalies over Australia. We find that these inconsistencies are linked to model biases in the basic state, such as the latitude of the eddy-driven jet and the persistence of the SAM. These results are largely corroborated by models that participated in the Chemistry-Climate Model Initiative (CCMI). Furthermore, bootstrapping of the data reveals sizable uncertainty in the magnitude of the surface signals in both models and observations due to internal variability. Our results demonstrate that anomalies of the austral stratospheric vortex have significant impacts on surface climate, although the ability of models to capture regional effects across the Southern Hemisphere is limited by biases in their representation of the stratospheric and tropospheric circulation.

Equatorial Pacific sea surface temperature anomalies (SSTAs) associated with El Niño–Southern Oscillation (ENSO) can influence the North Atlantic European (NAE) region. ENSO tends to be negatively correlated with the North Atlantic Oscillation in winter, while this connection is less clear in boreal spring and summer when the ENSO teleconnection encounters altered background conditions (i.e., a weaker subtropical jet), which can modulate the signal on the way to the NAE region. One such region that modulates the ENSO teleconnection to the NAE region is the tropical North Atlantic (TNA). While several mechanisms exist for this modulation, we center our analysis on the Caribbean region and the Walker cells. In order to isolate the relevant mechanism, we force an idealized atmospheric circulation model with three different seasonally varying sea surface temperature patterns that represent an ENSO event with or without the influence of the TNA, focusing on the decaying phase of ENSO in boreal spring and summer. We find that in boreal spring, the TNA modulates the ENSO teleconnection to the NAE primarily through a propagating Rossby wave train, while in summer, the TNA's influence tends to strengthen the ENSO influence over the NAE sector. Overall, this study offers a deeper understanding of the inter-basin interactions through the Walker cell following an ENSO event and the central role of tropical Atlantic SSTAs in modulating the teleconnection to the NAE region in boreal spring and summer.

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere.

Major disruptions of the winter season, high-latitude stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research. We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortex disturbances for surface predictability in subseasonal to seasonal forecast models. Based on a set of controlled, subseasonal ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models. Fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts.

Extreme stratospheric events such as sudden stratospheric warming (SSW) and strong vortex events can have downward impacts on surface weather that can last for several weeks to months. Hence, successful predictions of these stratospheric events can be beneficial for extended-range weather prediction. However, the predictability of extreme stratospheric events is most often limited to around 2 weeks or less. The predictability strongly differs within events of the same type and also between event types. The reasons for the observed differences in the predictability, however, are not resolved. We extend the analysis of the predictability of stratospheric extreme events to include wind deceleration and acceleration events, with SSW and strong vortex events as subsets, to conduct a systematic comparison of sub-seasonal predictability between events in the European Centre for Medium-Range Weather Forecasts (ECMWF) prediction system. Events of stronger magnitude are found to be less predictable than weaker events for both wind deceleration and acceleration events, with both types of events showing a close to linear dependence of predictability on event magnitude. There are, however, deviations from this linear behaviour for very strong magnitude events. The difficulties of the prediction system in predicting extremely strong anomalies can be traced to a poor predictability of extreme wave activity fluxes in the lower stratosphere, which impacts the prediction of deceleration events and, interestingly, also acceleration events. Our study suggests that improvements in the understanding of the wave amplification that is associated with extremely strong wave activity fluxes and accurately representing these processes in the model are expected to enhance the predictability of stratospheric extreme events and, by extension, their impacts on surface weather and climate.

The simulated Northern Hemisphere winter stationary wave (SW) field is investigated in 11 Subseasonal-to-Seasonal (S2S) prediction project models. It is shown that while most models considered can well simulate the stationary wavenumbers 1 and 2 during the first 2 weeks of integration, they diverge from observations following week 3. Those models with a poor resolution in the stratosphere struggle to simulate the waves, in both the troposphere and the stratosphere, even during the first 2 weeks. Focusing on the tropospheric regions where SWs peak in amplitude reveals that the models generally do a better job in simulating the northwestern Pacific stationary trough, while certain models struggle to simulate the stationary ridges in both western North America and the North Atlantic. In addition, a strong relationship is found between regional biases in the stationary height field and model errors in simulated upward propagation of planetary waves into the stratosphere. In the stratosphere, biases are mostly in wave 2 in those models with high stratospheric resolution, whereas in those models with low resolution in the stratosphere, a wave 1 bias is evident, which leads to a strong bias in the stratospheric mean zonal circulation due to the predominance of wave 1 there. Finally, biases in both amplitude and location of mean tropical convection and the subsequent subtropical downwelling are identified as possible contributors to biases in the regional SW field in the troposphere.

Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere–troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could further benefit these rapidly evolving predictions.

Major sudden stratospheric warmings (SSWs) are extreme wintertime circulation events of the Arctic stratosphere that are accompanied by a breakdown of the polar vortex and are considered an important source of predictability of tropospheric weather on subseasonal to seasonal timescales over the Northern Hemisphere midlatitudes and high latitudes. However, SSWs themselves are difficult to predict, with a predictability limit of around 1 to 2 weeks. The predictability limit for determining the type of event, i.e., wave-1 or wave-2 events, is even shorter. Here we analyze the dynamics of the vortex breakdown and look for early signs of the vortex deceleration process at lead times beyond the current predictability limit of SSWs. To this end, we employ a mode decomposition analysis to study the potential vorticity (PV) equation on the 850 K isentropic surface by decomposing each term in the PV equation using the empirical orthogonal functions of the PV. The first principal component (PC) is an indicator of the strength of the polar vortex and starts to increase from around 25 d before the onset of SSWs, indicating a deceleration of the polar vortex. A budget analysis based on the mode decomposition is then used to characterize the contribution of the linear and nonlinear PV advection terms to the rate of change (tendency) of the first PC. The linear PV advection term is the main contributor to the PC tendency at 25 to 15 d before the onset of SSW events for both wave-1 and wave-2 events. The nonlinear PV advection term becomes important between 15 and 1 d before the onset of wave-2 events, while the linear PV advection term continues to be the main contributor for wave-1 events. By linking the PV advection to the PV flux, we find that the linear PV flux is important for both types of SSWs from 25 to 15 d prior to the events but with different wave-2 spatial patterns, while the nonlinear PV flux displays a wave-3 wave pattern, which finally leads to a split of the polar vortex. Early signs of SSW events arise before the 1- to 2-week prediction limit currently observed in state-of-the-art prediction systems, while signs for the type of event arise at least 1 week before the event onset.

Every spring, the stratospheric polar vortex transitions from its westerly wintertime state to its easterly summertime state due to seasonal changes in incoming solar radiation, an event known as the “final stratospheric warming” (FSW). While FSWs tend to be less abrupt than reversals of the boreal polar vortex in midwinter, known as sudden stratospheric warming (SSW) events, their timing and characteristics can be significantly modulated by atmospheric planetary-scale waves. While SSWs are commonly classified according to their wave geometry, either by how the vortex evolves (whether the vortex displaces off the pole or splits into two vortices) or by the dominant wavenumber of the vortex just prior to the SSW (wave-1 vs. wave-2), little is known about the wave geometry of FSW events. We here show that FSW events for both hemispheres in most cases exhibit a clear wave geometry. Most FSWs can be classified into wave-1 or wave-2 events, but wave-3 also plays a significant role in both hemispheres. The timing and classification of the FSW are sensitive to which pressure level the FSW central date is defined, particularly in the Southern Hemisphere (SH) where trends in the FSW dates associated with ozone depletion and recovery are more evident at 50 than 10 hPa. However, regardless of which FSW definition is selected, we find the wave geometry of the FSW affects total column ozone anomalies in both hemispheres and tropospheric circulation over North America. In the Southern Hemisphere, the timing of the FSW is strongly linked to both total column ozone before the event and the tropospheric circulation after the event.

Marine cold air outbreaks (MCAOs) in the northeastern North Atlantic occur due to the advection of extremely cold air over an ice-free ocean. MCAOs are associated with a range of severe weather phenomena, such as polar lows, strong surface winds and intense cooling of the ocean surface. Given these extreme impacts, the identification of precursors of MCAOs is crucial for improved long-range prediction of associated impacts on Arctic infrastructure and human lives. MCAO frequency has been linked to the strength of the stratospheric polar vortex, but the study of connections to the occurrence of extreme stratospheric events, known as sudden stratospheric warmings (SSWs), has been limited to cold extremes over land. Here, the influence of SSW events on MCAOs over the North Atlantic ocean is studied using reanalysis datasets. Overall, SSW events are found to be associated with more frequent MCAOs in the Barents Sea and the Norwegian Sea compared to climatology and less frequent MCAOs in the Labrador Sea. In particular, SSW events project onto an anomalous dipole pattern of geopotential height 500 hPa, which consists of a ridge anomaly over Greenland and a trough anomaly over Scandinavia. By affecting the variability of the large-scale circulation patterns in the North Atlantic, SSW events contribute to the strong northerly flow over the Barents and Norwegian seas and thereby increase the likelihood of MCAOs in these regions. In contrast, the positive geopotential height anomaly over Greenland reduces the probability of MCAOs in the Labrador Sea after SSW events. As SSW events tend to have a long-term influence on surface weather, these results are expected to benefit the predictability of MCAOs in the Nordic Seas for winters with SSW events.

Sudden stratospheric warming (SSW) events can significantly impact tropospheric weather for a period of several weeks, in particular in the North Atlantic–European (NAE) region. While the stratospheric forcing often projects onto the North Atlantic Oscillation (NAO), the tropospheric response to SSW events, if any, is highly variable, and what determines the existence, location, timing, and strength of the downward impact remains an open question. We here explore how the variable tropospheric response to SSW events in the NAE region can be characterized in terms of a refined set of seven weather regimes and if the tropospheric flow in the North Atlantic region around the onset of SSW events is an indicator of the subsequent downward impact. The weather regime analysis reveals the Greenland blocking (GL) and Atlantic trough (AT) regimes as the most frequent large-scale patterns in the weeks following an SSW. While the GL regime is dominated by high pressure over Greenland, AT is dominated by a southeastward-shifted storm track in the North Atlantic. The flow evolution associated with GL and the associated cold conditions over Europe in the weeks following an SSW occur most frequently if a blocking situation over western Europe and the North Sea (European blocking) prevailed around the SSW onset. In contrast, an AT regime associated with mild conditions over Europe is more likely following the SSW event if GL occurs already around SSW onset. For the remaining tropospheric flow regimes during SSW onset we cannot identify a dominant flow evolution. Although it remains unclear what causes these relationships, the results suggest that specific tropospheric states in the days around the onset of the SSW are an indicator of the subsequent tropospheric flow evolution in the aftermath of an SSW, which could provide crucial guidance for subseasonal prediction.

The El Niño–Southern Oscillation (ENSO) can exert a remote impact on North Atlantic and European (NAE) winter climate. This teleconnection is driven by the superposition and interaction of different influences, which are generally grouped into two main pathways, namely the tropospheric and stratospheric pathways. In this study, we focus on the tropospheric pathway through the North Pacific and across the North American continent. Due to the possible nonstationary behavior and the limited time period covered by reanalysis datasets, the potential nonlinearity of this pathway remains unclear. In order to address this question, we use a simplified physics atmospheric model forced with seasonally varying prescribed sea surface temperatures (SST) following the evolution of different ENSO phases with linearly varying strength at a fixed location. To isolate the tropospheric pathway the zonal mean stratospheric winds are nudged towards the model climatology. The model experiments indicate that the tropospheric pathway of ENSO to the North Atlantic exhibits significant nonlinearity with respect to the tropical SST forcing, both in terms of the location and amplitude of the impacts. For example, strong El Niño leads to a significantly stronger impact on the North Atlantic Oscillation (NAO) than a La Niña forcing of the same amplitude. For La Niña forcings, there is a saturation in the response, with no further increase in the NAO impact even when doubling the SST forcing, while this is not the case for El Niño. These findings may have important consequences for long-range prediction of the North Atlantic and Europe.

Abstract El Niño Southern Oscillation (ENSO) exerts a remote impact on the North Pacific and North American winter climate. Both observational and model studies have suggested nonlinearities in this teleconnection. However, it remains unclear if possible nonlinearities arise from the forcing strength or the forcing location in the tropical Pacific, or from factors external to the tropical Pacific. To separate these factors, an idealized model is forced with seasonally varying sea surface temperature with linearly varying strength at a fixed location. Whereas for moderate events the North Pacific response is more linear, strong events exhibit significant nonlinearity both in terms of the strength and location of the impact. The nonlinearity can be traced back to the relationship between sea surface temperature and tropical convection. Nonlinearity in the North Pacific response can have important impacts for long‐range prediction and for potential changes in the diversity of ENSO with climate change.

We investigate changes in the seasonal cycle of the Atlantic Ocean meridional heat transport (OHT) in a climate projection experiment with the Max Planck Institute Earth System Model (MPI-ESM) performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). Specifically, we compare a Representative Concentration Pathway (RCP) RCP 8.5 climate change scenario, covering the simulation period from 2005 to 2300, to a historical simulation, covering the simulation period from 1850 to 2005. In RCP 8.5, the OHT declines by 30–50 % in comparison to the historical simulation in the North Atlantic by the end of the 23rd century. The decline in the OHT is accompanied by a change in the seasonal cycle of the total OHT and its components. We decompose the OHT into overturning and gyre component. For the OHT seasonal cycle, we find a northward shift of 5° and latitude-dependent shifts between 1 and 6 months that are mainly associated with changes in the meridional velocity field. We find that the changes in the OHT seasonal cycle predominantly result from changes in the wind-driven surface circulation, which projects onto the overturning component of the OHT in the tropical and subtropical North Atlantic. This leads in turn to latitude-dependent shifts between 1 and 6 months in the overturning component. In comparison to the historical simulation, in the subpolar North Atlantic, in RCP 8.5 we find a reduction of the North Atlantic Deep Water formation and changes in the gyre heat transport result in a strongly weakened seasonal cycle with a weakened amplitude by the end of the 23rd century.