Potential flow theory predicts bulk fluid motion driven by spatially separated sources and sinks of mass. In the atmosphere, such exchanges are dominated by the hydrological cycle: subtropical sources of water vapour combine with equatorial and high-latitude sinks to induce meridional source–sink flows in each hemisphere. Conventional gas-phase frameworks that represent mean meridional circulations as purely cellular neglect these throughflows. Here, these flows are identified as atmospheric branches of coupled ocean–atmosphere circulations termed Latent cells. Evidence indicates that they dominate among mechanisms effecting large-scale transport of inert tracers, and they may influence atmospheric momentum budgets.
We present a diagnostic framework of daily rainfall regimes during the Indian Summer Monsoon (ISM) for June–September 1961–2018. Using high-resolution (0.25°) daily rainfall and unsupervised k-means clustering, eleven objectively defined spatial rainfall patterns were identified and linked with characteristic low-level winds, sea-level pressure and moisture fields, separating different synoptic patterns of ISM rainfall. The dataset provides (i) centroid rainfall patterns of each regime and (ii) daily cluster IDs, enabling reconstruction of the full temporal sequence of rainfall regimes and calculation of transition probabilities between states. Transition analysis confirms that break phases are the most persistent while monsoon depressions are more transient, mirroring observed synoptic life cycles. A decomposition of rainfall change between 1961–1989 and 1990–2018 shows that drying in Northeast India (∼ 9 %) is driven by a reduction in frequency of break clusters associated with localized rainfall over the region (Cluster 2), whereas Gangetic Plain drying (∼ 7 %) is linked to reduction in both rainfall intensity and frequency (Clusters 2 and 8). Over the western India, the increasing rainfall (∼ 15 %) is mainly driven by increasing remnants of depressions and mid-tropospheric cyclones (Cluster 9). This regime-based approach provides a powerful diagnostic tool to examine synoptic drivers, long-term changes in rainfall intensity and frequency, regime transition dynamics, and can be useful to evaluate model representation of ISM variability, teleconnections and trend attribution.
In late October 2024, the western Mediterranean (WMed) region experienced an extreme precipitation event (EPE) centred over Valencia, southeastern Spain, associated with a quasi-stationary cut-off low (COL), producing record rainfall, flash floods, and severe societal impacts. The COL generated an atmospheric-river-like moisture plume from northwestern Africa, while additional moisture originated from the warm Mediterranean Sea. Interaction with regional orography under a highly unstable environment, favoured deep convection and intense local rainfall. To assess the influence of anthropogenic climate change on the synoptic-scale thermodynamic evolution of the event, we analyse high-resolution (∼ 9 km) storyline simulations from the European Union's Destination Earth initiative, using the coupled IFS-FESOM model spectrally nudged with ERA5. Two climate scenarios are compared: Factual (present-day) and Counterfactual (∼ 1950), isolating thermodynamic responses while preserving the observed large-scale circulation. Long-term IFS-FESOM and ERA5 datasets provide a climatological reference for event extremeness using percentile-based thresholds of selected key variables. Results show that the synoptic configuration alone was sufficient to produce extreme rainfall, but human-induced warming substantially enhanced its magnitude. Moisture content and transport increased by 18 %–24 %, convective instability by ∼ 25 %, and precipitation over Valencia increased by ∼ 20 % in the Factual scenario. Sea surface temperatures in the Western Mediterranean were ∼ 2 °C warmer, amplifying evaporation. Peak precipitation rates exhibited nonlinear amplification, on 29 October were about 36 % higher in the Factual scenario, exceeding the Clausius–Clapeyron scaling expected from the mean warming between scenarios. These findings indicate that anthropogenic warming can intensify EPEs in the WMed even when synoptic drivers alone would generate extreme rainfall, highlighting thermodynamic amplification as a key mechanism in Mediterranean flood events. High-resolution, physically consistent storyline simulations offer a robust framework for event-based attribution and improve understanding of future climate risks in vulnerable coastal regions.
Atmospheric rivers (ARs) represent the main intrusions of moisture and heat into Antarctica, exerting a major influence on the continent's surface mass balance. Yet, due to geometric and directional constraints, existing detection algorithms often fail to track their evolution inland after landfall or in regions where abrupt directional changes occur. We introduce DARK (Detecting ARs using their Kurvature), a new Antarctic AR detection framework designed to overcome these limitations. DARK applies a strict 98th-percentile threshold to total integrated vapor transport and computes AR length along the curved axis to evaluate the 2000 km AR criterion. This enables the continuous detection of ARs with complex geometries, including those that curve, overturn, or extend across the South Pole. An additional AR-children module identifies smaller but still intense moisture remnants that detach from parent ARs after landfall yet continue to transport vapor and heat inland. The resulting climatology shows that DARK ARs account for about 18 % of total Antarctic precipitation and are linked to roughly half of top 1 % daily precipitation anomalies, 60 % of top 1 % daily maximum temperature anomalies, and 80 % of compound warm-and-wet events. DARK provides a more detailed assessment of AR-related precipitation and temperature impacts in the South Pole region. Despite slightly higher occurrence, risk ratio analysis shows that DARK ARs more effectively capture the most intense events than earlier Antarctic schemes. Including AR-children further strengthens these associations, especially over Victoria Land, where they contribute to about one third of AR-related precipitation.
The development of extratropical cyclones (ETCs) is often significantly altered by diabatic processes, yet the representation of these processes in numerical weather prediction models has been shown to lead to significant forecast biases. To provide a systematic quantification of 12-h ETC forecast errors, this study uses a cyclone-centred composite framework for North Atlantic wintertime (DJF) ETCs using the ERA5 reanalysis for the period 1979 to 2022. Cyclones are categorised into strong and weak diabatic heating at the time of their maximum intensification based on the domain-averaged 70th and 30th percentiles of vertically integrated diabatic heating.While both groups exhibit a systematic underestimation of cyclone intensity, the error structures are markedly distinct. The weak heating group is characterised by an intensity underestimation near the cyclone core, whereas the strong heating group features a pronounced southwestward displacement bias together with a domain-wide intensity underestimation.After removing the displacement bias, the strong heating group exhibits distinct structural errors. In the warm sector, a clear underestimation of moisture transport and temperature, combined with an underdeveloped upper-level ridge, indicates a mis-representation of the intense moisture transport pathways and associated warm-sector moist processes. Conversely, in the cold sector, low-level winds are overestimated within the cold conveyor belt (CCB), sting jet (SJ), and dry intrusion (DI) regions. The wind field biases are accompanied by a pronounced overestimation of 850 hPa kinematic frontogenesis near the centre. The strong frontogenesis is associated with an enhanced secondary circulation and vertical velocity, yielding the overestimation of total column liquid water observed along the bent-back warm front. In contrast, cyclones in the weak heating group exhibit an underestimation of wind speed and moisture near the centre, consistent with the near-centre intensity underestimation. Overall, our findings demonstrate the critical impact of diabatic heating on structural forecast biases, highlighting that the representation of moist processes and the interaction with atmospheric dynamics through diabatic processes is a key area for future model developments.
The teleconnections of the Quasi-Biennial Oscillation are revisited using ∼65 000 years of model output contributed by four modeling centers to the Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP). The large ensemble size (at least 10, and in many cases 50) allows isolation of weak signals that are usually hidden by internal variability, as well as better quantification of the role of internal variability in possible model–observation discrepancies in the magnitude of the signals. All four models simulate a Holton–Tan effect, and two of the models also simulate a subtropical downward arching wind horseshoe teleconnection that is most prominent in the Pacific sector. The magnitudes of these teleconnections are statistically indistinguishable from those observed in two of the models but not in the other two; this is a notable improvement from previous work that analyzed small ensembles. These large-scale teleconnections lead to surface temperature and precipitation anomalies over the mid-latitude continents, including an impact on western North America surface temperature which appears to have not been noted before. Furthermore, all models show impacts of the QBO on tropical surface temperature and precipitation, however the nature of these responses differs across the models due, in part, to qualitatively different interactions with El Niño. Remarkably, one of the models simulates a connection between the QBO and the Madden Julian Oscillation that mimics observations, although it remains too weak. Finally, the LESFMIP simulations allow an exploration of external forcings impacting the magnitude of teleconnections. Among these experiments, greenhouse gas forcing is seen to significantly strengthen the subtropical wind horseshoe of the QBO.
Atmospheric blocking is a key driver of midlatitude weather extremes, including heatwaves and cold spells. Yet general circulation models (GCMs) struggle to capture the frequency, persistence, and spatial characteristics of blocking. Here, we evaluate atmospheric blocking in next-generation storm-resolving Earth system models from the nextGEMS, EERIE, and DestinE projects, focusing on ICON and IFS-FESOM with ∼ 10 km atmospheric and ∼ 5 km ocean grid spacing. We also provide first insights into the IFS-FESOM under SSP3-7.0 forcing.Blocking frequency, duration, and size are assessed in historical simulations spanning 30 years for IFS and 27 years for ICON, relative to ERA5 reanalysis and a CMIP6 multi-model ensemble of eight models. We further examine links between blocking biases and the background flow, sea surface temperatures (SSTs), and storm-track activity. In the CMIP6 ensemble, persistent biases in blocking frequency, duration, and spatial extent are evident, particularly over the Euro-Atlantic sector, consistent with previous studies. Several of these biases persist in the storm-resolving coupled simulations or are even amplified, indicating that increased horizontal resolution alone does not systematically improve blocking representation. Among the storm-resolving models, performance varies regionally and seasonally. ICON exhibits larger winter biases, including overly zonal jets and an underestimation of Euro-Atlantic blocking compared to IFS. The coupled IFS configuration shows intermediate performance, reproducing some aspects of blocking variability but retaining substantial biases associated with SST errors and jet structure. In contrast, the atmosphere-only IFS simulation (IFS AMIP), which is forced with observed SSTs, reproduces blocking frequency and jet structure more realistically over both the North Atlantic and North Pacific. This highlights the strong sensitivity of blocking to sea surface temperatures and ocean–atmosphere coupling, and underscores the importance of realistic SST boundary conditions for improving blocking representation.Under SSP3-7.0 forcing, IFS projects reduced winter blocking at high latitudes (e.g., northern Europe) and reduced summer blocking frequency over the North Atlantic, northern Europe, and Russia. Changes in magnitude, spatial pattern, and persistence are often of the same order as the model biases, indicating that projected blocking responses are difficult to disentangle from systematic errors related to jet structure, SST biases, and storm-track activity.Overall, storm-resolving models show local improvements in blocking representation, particularly when forced with realistic SSTs. However, coupled simulations still exhibit large biases, underlining the need for further development of ocean–atmosphere coupling representation. These findings highlight both the potential and the current limitations of storm-resolving models for simulating and projecting persistent weather extremes in a warming climate.
The instability of Rossby waves has been a long–standing topic in dynamical meteorology. The classic theoretical analysis had provided in–depth physical understanding of the problem. However, developing a systematic and quantitative comprehension of wave energy and amplitude evolution remains challenging. With an eye to such issues, this investigation provides a novel and practicable algorithm to solve the wave action conservation equation. Theoretical analysis establishs that wave packet energy evolves through two competing factors: direct proportionality to intrinsic frequency and inverse proportionality to group velocity magnitude. Energy density attains extremal values at turning points where group velocity magnitudes become extremized. To ensure a ray can be reflected by a turning point, zonal phase speed must be smaller than an upper limit determined by the dispersion relation at the turning point. Crucially, a specific zonal phase speed range emerges below this maximum threshold where concurrent transient growth of both wave energy and amplitude occurs when a ray is moving toward the turning point, with the upper limit corresponding to optimal wave development conditions. Numerical experiments on a prototype westerly jet reveal distinct instability mechanisms: substantial transient growth – capable of triggering nonmodal instability – arises when rays moves toward turning points, while exponential amplification characteristic of modal instability develops at inflection points with positive energy growth rate. The derived zonal phase speed thresholds and transient growth metrics form a diagnostic framework applicable to observed atmospheric flows, enabling quantitative evaluation of both modal and nonmodal instability potentials. By unifying wave evolution dynamics with classical instability criteria, this work provides an operational bridge between theoretical predictions and real–world flow diagnostics.
Atmospheric rivers (ARs) play a major role in transporting heat and moisture into the Arctic, yet their thermodynamic structure and regional impacts remain poorly understood. Here, we adopt a combined Eulerian–Lagrangian framework to investigate two intense ARs that penetrated into the central Arctic within one week in April 2020 during the MOSAiC field campaign. This study provides a comprehensive view of their large-scale dynamics, moisture sources, and thermodynamic evolution.The first AR entered the Arctic via the Siberian sector, driven by a highly anomalous quasi-stationary anticyclone over north-central Siberia. The second followed an Atlantic pathway and was associated with an unusually deep and persistent cyclone over Baffin Bay. Despite their distinct origins and pathways, both events produced extreme surface impacts, including widespread warming across Eurasia exceeding 9 °C over a 7 d period and intense precipitation along the Greenland coast and in the central Arctic. The events coincided with a notable decline in sea ice extent along eastern Greenland and in the Barents-Kara Sea, that is highly correlated with the AR-induced warming and rainfall.Backward trajectory analysis of parcels associated with extreme Arctic precipitation reveals distinct pathways and thermodynamic evolution. During both AR events, a subset of air parcels exhibiting classic AR characteristics is identified. These warm, moist, low-pressure airmasses ascend upon arrival and release intense precipitation. Moisture sources, however, differed by pathway: the Atlantic AR drew from the warm Gulf Stream region, while the Eurasian AR was fed by continental Eurasia. These findings highlight the diverse origins and mechanisms of ARs and their capacity to drive rapid Arctic climate and cryospheric changes.
Glacier recession gives rise to changes in land surface type and topography that are poorly represented in atmospheric models but may have important local impacts on climate. Implementing these changes in the Weather Research and Forecasting (WRF) model for the Jostedalsbreen ice cap in western Norway results in warmer and drier regional climate with less snow that can amplify glacier recession through a positive feedback effect. Most of the climatic response to glacier recession is related to the surface lowering associated with ice melt, resulting in reduced orographic lifting of moist air masses and higher surface pressure. The climatic response to glacier recession is largest where the ice melts but is also evident in adjacent valleys several kilometers away from the ice cap. While the warming by glacier recession amplifies effects of global warming, reduced precipitation counteracts the projected regional increase in precipitation. These findings should be included in estimates of glacier mass balance and have implications for agriculture, hydropower, tourism, and biodiversity around glacierised landscapes.
Extreme temperature swings from one day to the next, whether warming or cooling, can significantly impact human health, ecosystems, and the economy. These effects may become more pronounced or attenuated in the future. Part 1 of this research identified the physical processes – advection, as well as adiabatic and diabatic temperature changes – that cause extreme day-to-day temperature (DTDT) fluctuations in the present climate. Extreme DTDT variations are projected to change under future warming; however, how and which processes drive these changes remain poorly understood. This study addresses this question globally by analysing physical processes in Community Earth System Model Large Ensemble (CESM–LE) simulations under a high–emission scenario, employing both Eulerian composite and Lagrangian backwards–trajectory analyses. The projected changes in (extreme) DTDT variations display a seasonal contrast: weakening in mid- to high latitudes and intensification in the tropics during December–February (DJF), while during June–August (JJA), tropical intensification is more widespread, and only some extratropical locations experience reductions in DTDT variations. The spatial pattern of projected changes in the DTDT variations is mostly associated with changes in the standard deviation of daily temperature, whereas changes in temporal autocorrelation give rise to regional variations in magnitude. In the extratropics during DJF, the weakening of DTDT extremes is mainly driven by reduced advection contributions due to Arctic amplification. However, during JJA, reductions in extremes result from changes in advection, diabatic, and adiabatic processes, with differences between events and regions in their relative contributions. Furthermore, changes in diabatic processes play a significant role in the projected intensification of extremes in JJA over land areas in the tropics and subtropics, while the tropical intensification during DJF results from local changes in diabatic and adiabatic processes. Our findings demonstrate that a regional and seasonal perspective that, in addition to the well–established role of advection, also accounts for diabatic and adiabatic heating processes is essential for understanding projected extreme DTDT changes and for developing suitable adaptation strategies.
The Eastern Mediterranean is a water-scarce, climate-sensitive region. Eastern-Mediterranean cyclones (EMCs) are a major contributor to precipitation totals and weather extremes, including heavy precipitation, strong winds, temperature extremes and dust storms, substantially impacting the population and natural environment. Understanding EMCs' variability and their associated impacts is essential for improving their predictability and forecasts. The large case-to-case variability of cyclone development and associated impacts calls for EMC classification that incorporates dynamical insight into EMC large-scale setting, their track characteristics and associated surface weather. Here we classify EMCs based on their associated upper-tropospheric potential vorticity (PV) structures, providing a novel process-based framework for quantifying cyclone-associated surface weather and extremes. Using the self-organising map (SOM) algorithm to categorise ERA5-based PV distributions during EMCs from 1979–2020, six distinct PV patterns highlight different governing large-scale and synoptic settings. Each EMC type involves distinct mean and extreme surface weather signatures. Two clusters with high PV anomalies over the eastern Mediterranean dominate the regional annual precipitation. A strong ridge upstream of the PV trough during Rossby wave breaking leads to enhanced precipitation, compared to a similar PV configuration with a weak ridge upstream. Temperature anomalies during the cyclone passage are strongly linked to upper-level PV patterns, with certain EMC types causing notable near-surface warm and cold temperature extremes. In transition and warm seasons, occasional extreme localised precipitation is found despite the prevalence of shallow thermal lows with weak upper-tropospheric PV anomalies and generally no/low precipitation amounts. While the annual frequency of EMCs exhibits no significant trend, some clusters show contrasting trends. A notable increase in the frequency of non-precipitating EMCs, indicates a potential shift toward drier, but occasionally more extreme conditions in the region. Through this classification approach the link between EMCs large-scale setting and their surface impacts is systematically mapped. These findings provide a framework for the evaluation of cyclones and their prediction, and may improve strategies for managing the societal and environmental impacts of EMCs at weather and climate timescales.
The global monsoon system is a lifeline for two-thirds of the world's population, as it is essential for tropical water security, food, and agriculture. However, its complex multiscale interactions challenge weather and climate models. This study investigates how horizontal grid spacing (80, 40, and 10 km) in the ICOsahedral Non-hydrostatic (ICON) model affects both the mean and the variability of Northern Hemisphere monsoons across diurnal, intraseasonal, and interannual timescales. All simulations show substantial skill in capturing the global monsoon system domain and its mean annual range of precipitation with a pattern correlation of > 0.7 and RMSE < 3 mm d−1. For the key Northern Hemisphere regional monsoons, South Asia (SAsiaM), West Africa (WAfriM) and North America (NAmerM), ICON achieves an accuracy > 80 % in capturing the observed monsoon domain. Crucially, the impact of grid spacing is strongly region-dependent and non-systematic. The finer grid spacing induces higher mean precipitation biases over continental SAsiaM, and WAfriM. Some of these biases are related to the intensity and location of moist monsoonal low-level jets, as well as their sensitivity to grid spacing. Furthermore, the fine grid spacing overestimates monsoon precipitation variability at interannual and intraseasonal scales, including intense precipitation frequency (> 10 mm d−1). This amplification stems primarily from enhanced grid-scale precipitation resulting from efficient microphysical processes, while convective precipitation exhibits limited sensitivity to grid spacing. Over NAmerM, biases are smaller and show minimal sensitivity to model grid spacing. Increased intraseasonal variance (2–30 d band) in the 10 km simulation is linked to more intense low-pressure synoptic systems over SAsiaM and intense African easterly wave activity over WAfriM. All simulations agree on the diurnal precipitation peak timing, with the 10 km simulation marginally performing better over continents. Our results demonstrate that fine grid spacing alone does not uniformly improve monsoon simulations. Some features, such as the precipitation diurnal cycle, are improved while existing biases in mean precipitation and variability are enhanced. This underscores the role of region-dependent sensitivity of grid spacing governing monsoon dynamics.
Atmospheric blocking often triggers extreme events and remains difficult for weather and climate models to represent due to the complex multi-scale processes in its lifecycle. While recent studies highlight the importance of latent heat release in building and maintaining the upper-level anticyclonic anomaly, different perspectives assign varying roles to dry and moist dynamics, and it is still unclear whether their relative roles differ across regions where blocking occurs. This study uses a quasi-Lagrangian potential vorticity (PV) framework applied to ERA5 (1979–2021) to investigate blocking in the North Atlantic–European sector from the perspective of four large-scale blocked weather regimes. We track negative upper-tropospheric PV anomalies (PVAs−) around blocked regime onset and quantify the processes governing their amplitude changes to assess the roles of dry and moist dynamics. Most PVAs−PVAs−PVAs−−−PVAs−PVAs−−
Heavy precipitation events (HPEs) are a precious source of water in the Sahara, but often trigger devastating flooding. These events are strongly associated with surface cyclones, making accurate cyclone forecasting crucial for predicting hazards related to HPEs and their impacts. In this study, we investigate the predictability of HPE-associated cyclones across the Sahara and its drivers. We use ERA5 reanalysis and ECMWF reforecasts initialized between December 2000 and November 2020. Forecast skill on short-, medium-, and extended-range timescales is evaluated based on the overlapping areas of observed and forecasted cyclones over the Sahara. Results show that the lead time of skillful prediction is up to about 10 d. Forecast skill varies strongly with season. At short lead times, skill is higher in winter, whereas at medium to extended lead times, skill is relatively high in summer, albeit with increased false alarm rates. These seasonal differences are also reflected in cyclone location and characteristics: deeper northern Sahara cyclones are predicted better than shallower ones, while in summer, skillful forecasts are found mainly in the southwestern Sahara. Northern Saharan cyclones are better predicted when Rossby wave patterns are persistent, whereas transitions between circulation patterns correspond to reduced forecast skill. These findings suggest that the predictability of HPE-associated cyclones in the Sahara is flow-dependent, and that high predictive skill can extend to subseasonal timescales under favorable flow conditions. Understanding these variations across regions, seasons, and circulation patterns is key to improving the predictability of HPEs and their related impacts.
Stratospheric extreme events during Northern winter and spring have been shown to sometimes enhance the sub-seasonal predictability of large-scale tropospheric circulation patterns such as the North Atlantic oscillation (NAO) and Greenland/European blocking. However, it remains unclear whether event-to-event differences in the observed tropospheric evolution after individual sudden stratospheric warmings (SSWs) represent a robust difference in the tropospheric response to the events, or whether such differences in tropospheric evolutions are simply caused by tropospheric variability. To make progress on this question, we robustly quantify the tropospheric response with an ensemble simulation strategy in a controlled model environment. We construct a model climatology using the ICON global numerical weather prediction (NWP) model, representing a wide range of realistic stratosphere–troposphere evolutions during winter months, but under controlled boundary conditions to exclude confounding factors like teleconnections of tropical origin. The simulations reproduce key aspects of observed stratosphere-troposphere coupling, providing a consistent framework to assess event-specific tropospheric responses. We produce spin-off ensembles for selected SSW events; the corresponding ensemble means help robustly quantify the tropospheric response to these SSWs. We find pronounced and robust event-to-event differences in the tropospheric response to SSWs. We further show that the flow anomalies in the lower stratosphere during the second week are well correlated with the surface response 3–7 weeks after the SSW. Moreover, our results indicate that the formation of wave reflection surfaces within the lower stratosphere may prevent the establishment of persistent lower-stratospheric anomalies. Overall, our controlled model simulations show that individual SSWs may differ significantly in their likelihood to induce a tropospheric response and that this likelihood is mainly determined by the post-SSW flow evolution within the stratosphere. These results may be relevant for sub-seasonal predictability of surface weather, especially given that the stratospheric part of the response to SSWs is highly predictable.
Extratropical cyclones (ETCs) are an important part of the atmospheric circulation, cause most of the day-to-day weather variability, and have societal impacts through strong winds and heavy precipitation in the mid-latitudes. Therefore, from both weather forecasting and climate change perspectives it is crucial to understand how they develop and intensify. In this study we aim to identify which environmental background conditions, here called ETC precursors, have the most control on the intensity of ETCs in the North Atlantic and Europe in the cold season. We apply an ensemble-based statistical method with ERA5 reanalysis data to associate climatologically typical perturbations in multiple ETC precursor fields at genesis time to distributions of five ETC intensity measures at time of maximum ETC intensity. We find that higher ETC wind intensity is associated with a stronger jet stream, especially downstream of the ETC centre, and increased meridional temperature gradients, with an emphasis on warmer upper levels south of the ETC centre. Precipitation is controlled by temperature and moisture throughout the tropospheric column, with higher values associated with more precipitation. We perform the same analysis for four groups of ETCs with different average intensities and show that while differences exist in the controlling precursors among the groups, no clear patterns are observed. Due to the non-linear growth of ETC intensity, the precursor fields at genesis time offer limited explanations about differences in maximum ETC intensity. Through analysing the temporal evolution of the four ETC intensity groups, we conclude that to understand differences in ETC intensity it is necessary to investigate multiple ETC precursor fields and their evolution through time.
Tropical-extratropical cloud bands are elongated cloud structures bridging tropical and midlatitude regions that act as a primary source of regional precipitation. While the role of Rossby wave breaking in the formation of cloud bands is established, the extent to which this dynamic forcing governs cloud band characteristics, their entire lifecycle, their spatial distribution and seasonality has not yet been systematically quantified. In this study, we apply an object-based approach to reanalysis data to investigate how stratospheric potential vorticity (PV) structures, as indicators of Rossby wave breaking, influence cloud band formation and persistence over the South Pacific region. Our climatological analysis confirms a robust statistical link in which cyclonic PV structures steer tropical moisture poleward and eastward, shaping the diagonal orientation of the cloud bands. We also find that cloud band duration is modulated by the properties of PV structures: long-lived cloud bands are distinguished by a systematically higher frequency of upstream PV structures and are sustained by persistent PV structures throughout their lifecycle, which favour a more zonal orientation of the cloud systems. Categorizing by cloud band duration reveals distinct seasonal regimes: while short-lived events occur year-round, persistent cloud bands are strictly confined to the austral warm season. Furthermore, long-lived cloud bands are associated with PV structures that reside significantly farther equatorward prior to genesis compared to those of short-lived events. These findings highlight that breaking Rossby waves create a tropospheric environment favouring not only the formation but also the maintenance of these cloud bands. Consequently, accurately representing Rossby wave dynamics in weather and climate models is critical for simulating cloud band characteristics and their influence on climate variability.
The current pace of climate change challenges the statistical methods used for bounding heatwave intensities, prompting the need for a physics-based upper bound to extreme surface temperatures (Ts). A recently proposed approach for deriving such a bound uses the hypothesis that convective instability limits the development of heat extremes. Here, we show that under this hypothesis, the absolute upper bound for extreme Ts
Cold spells in the Northern Hemisphere mid-latitudes have been linked to Rossby waves. Yet the mechanisms by which these large-scale waves impact cold-spell formation remain unclear. Here we develop novel metrics to separately determine the amplitude and speed of large-scale ridges and troughs, derived from the first five zonal Fourier decompositions of the geopotential height field. This approach allows us to examine the behavior of large-scale ridges and troughs during winter cold spells. These ridges and troughs mainly represent climatological features, which can be regarded as wobbling around their climatological positions due to interactions with background flow. Our findings indicate that while ridges and troughs across the entire mid-latitudes experience significant changes during cold spells, the local ridge and trough near the cold spell's location play a major role in the development of these events. The nearest upstream ridge and downstream trough of the cold-spell region are located in a way that facilitates development of the extreme cold anomaly. This ridge and trough amplify and slow down, enhancing and prolonging southward advection of cold air from the Arctic into the cold-spell region. The slow and amplified upstream ridge and downstream trough occur several days before the region’s minimum temperature, suggesting these local wave anomalies induce cold-spell formation.