We invite contributions on theoretical developments of classification methods as well as on their use in various tasks of atmospheric sciences, such as climate zonation, identification and analysis of circulation and weather types, and synoptic catalogues. Climatological, meteorological, and environmental applications of circulation classifications are particularly welcome.
The session will also include presentations on statistical (empirical) downscaling as a tool for evaluation and reconstruction of historical climate, gap filling in time series, analysis of extremes and non-climatic variables. Also intercomparisons among downscaling methods and their validation belong to this session.
Contributions on teleconnections (modes of low-frequency variability) and circulation regimes are expected to cover particularly their impacts on surface weather, climate, and environment.
The contributions on climatology of cyclones and other pressure formations will include analyses of cyclone tracks, life time and intensity of cyclones, as well as analyses of anticyclones and blockings. We also invite studies on impacts of the pressure formations on the environment and society, their relationships with large scale circulation patterns, as well as analyses of their recent trends and behavior in possible future climates.
The literature provides a wealth of metrics and indices meant to capture large‐scale and synoptic-scale atmospheric circulation features, including jet‐stream characteristics, cyclonic and anticyclonic Rossby wave breaking, atmospheric blocking, atmospheric rivers, fronts and more. Many studies relate these features to the occurrence of surface extremes. Often, separate studies relate different features to the same extremes in the same region. A systematic intercomparison of how strongly each feature relates to specific surface extremes remains largely lacking. Here, we utilise ERA5 reanalysis data to compare how multiple circulation features relate to temperature extremes in Europe. We find that cold spells in a large part of Europe are predominantly associated with high‐latitude blocking, yet that Rossby wave breaking plays an important role for cold spells in South-Eastern Europe. For warm extremes, blocking is the dominant feature in Northern and Southern Europe, wave breaking in Central and Eastern Europe, while different jet‐stream configurations dominate in Western Europe and Iberia. We further analyse the co-occurrence of different circulation features, to account for the fact that more than one may be present when any given surface extreme occurs. Finally, we extend the analysis to precipitation extremes in the global extratropics. Our results highlight that the atmospheric circulation feature(s) which display the strongest statistical connection to surface extremes is highly dependent on the type of extreme and region, and that multiple features should be considered in continental or larger-scale analyses. We also underscore that multiple features often co-occur in conjunction with surface extremes, and that disentangling their individual contributions can be challenging.
How to cite: Messori, G., Stergiou, P., and Segalini, A.: From Atmospheric Circulation Features to Surface Extremes, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-70, https://doi.org/10.5194/ems2026-70, 2026.
Comparison of two different datasets is a common task in climatology. Possible examples include a comparison of two reanalyses; model validation, i.e., a comparison of a climate model output with observed data or a reanalysis; or assessment of future climate change, i.e., a comparison of two model runs for a future and current climate state. Such comparisons may be conducted for a variety of climate elements, including atmospheric circulation. In this contribution, we focus on circulation types as result of a classification of atmospheric circulation patterns.
There are several possible ways of how to conduct the comparison, one of them being a separate and independent classification in either dataset; such a procedure has been used many times.
We take a simple and widely used classification method, k-means clustering, as an example. Two equally long datasets of daily sea level pressure are subjected to k-means clustering, with an equal number of resulting circulation types. Circulation types are then compared between the two datasets. While many types occur in both datasets, there is not a full one-to-one correspondence between the types; i.e., some types occur only in one dataset and some types occur only in the other. The occurrence frequencies of some types substantially differ between the two datasets. Interpretation of some of the identified differences is attempted.
In the next step, we uncover the nature of both datasets: They are subsamples of a single dataset, viz., ERA-5 reanalysis. There is no reason for the two sets of circulation types to differ. All the differences detected (and subsequently interpreted) are artefacts, therefore, not real features. We argue that conducting a classification separately in each dataset is not an appropriate procedure for a fair comparison between two datasets; it is likely to lead to erroneous conclusions. This statement is supported by two other comparison procedures: a single classification applied to both datasets together, and a projection of circulation types identified in one dataset to the other one. They both demonstrate that the circulation types and their frequencies do not in fact differ between the two data subsamples.
How to cite: Huth, R. and Stryhal, J.: (Un)fair comparison of classifications of atmospheric circulation patterns between two datasets, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-355, https://doi.org/10.5194/ems2026-355, 2026.
Water exchange between the Baltic Sea and the North Sea is constrained by narrow straits and substantial freshwater input, resulting in predominantly outflow conditions. Episodic saline inflows are therefore crucial for maintaining the Baltic Sea salt balance, ventilating deep basins, and sustaining ecosystem functioning. These inflows are closely linked to large volume changes (LVCs) and reflect variability in synoptic‑scale atmospheric circulation.
Here, we focus on the characteristic two‑phase evolution of LVCs. A prolonged preconditioning phase, dominated by easterly circulation types, promotes export of water from the Baltic Sea, followed by a forcing phase with strong westerly flow that enables inflow through the Danish Straits. This evolution is clearly manifested in sea surface elevation changes at Landsort: easterly circulation types prevail prior to sea level minima, whereas westerly and northwesterly types dominate prior to maxima, highlighting the asymmetric synoptic structure of LVCs.
We derive objective atmospheric circulation classifications and perform sensitivity experiments that vary the classification method, spatial domain, pressure level, and temporal aggregation. This synoptic‑climatological framework allows us to assess the robustness of circulation–inflow relationships and to identify which methodological choices most strongly influence the detected links.
Our results show that LVCs are not associated with a single synoptic pattern but instead emerge from characteristic sequences of circulation types and their temporal succession, emphasising the importance of cumulative and antecedent atmospheric forcing. Spatially, coherent synoptic‑scale forcing extends across the Baltic Sea region, with similar circulation characteristics over Central Estonia and the Danish Straits. Enhanced cyclonic activity over Central Scandinavia and the Norwegian Sea during LVCs suggests preferred synoptic pathways that strengthen basin‑scale pressure gradients. Finally, circulation anomalies are evident throughout the year preceding LVCs, with particularly strong signals in summer and at mid‑tropospheric levels, underscoring the importance of multilevel and multitemporal analyses in the synoptic climatology of extreme inflow events.
How to cite: Post, P. and Lehmann, A.: Linking Variability in Baltic Sea Volume to Atmospheric Circulation, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-713, https://doi.org/10.5194/ems2026-713, 2026.
Previous research on the energy balance of coral reefs on the Great Barrier Reef (Australia) and the Gulf of Eilat (Aqaba) (GoE, Israel) has shown that synoptic weather patterns that cause light winds, high temperatures and relative humidity, and clear skies increase the risk of high to extreme water temperatures. Here we present results of an automated k-means clustering method that uses ERA5 reanalysis data of mean sea level pressure, relative humidity at 1000 hPa and 850 hPa, winds at 10 m and 500 hPa, air temperature at 2 m and 850 hPa, and atmospheric thickness to identify synoptic weather patterns associated with summer high water temperature (> 29 °C) events for three consecutive days in the GoE. These conditions may trigger thermal coral bleaching events (TCBEs).
Three synoptic circulation patterns (Type 3, 2,1) were identified characterized by the advection of hot and humid air from the eastern Mediterranean toward the GoE beneath a region of atmospheric subsidence. This subsidence contributes further warming while inhibiting cloud development, thereby increasing the potential for strong radiative heating of the coral reefs in the GoE. The three synoptic patterns were found to follow the sequences of Type 3→2→1, Type 3→2 or Type 3→1 for 90% of events, almost always commencing with the Type 3 synoptic circulation pattern. The Type 3 synoptic circulation pattern is characterized by the axis of the Persian Trough running from central Iraq southeast to the United Arab Emirates and Oman. Winds at 10 m are generally light and below 10 ms-1 from the north and northwest over the eastern Mediterranean and north Africa. Air temperatures at 10 m over land are mostly > 35 °C with terrestrial 1000 hPa relative humidity around 30% or less with higher values in the north and south over Ethiopia, South Sudan and the Central African Republic.
Identifying the synoptic meteorology of TCBEs provides essential baseline data to monitor change in the weather patterns we identify. These resemble the previously documented “High to west” synoptic pattern. This pattern is linked to several large-scale global circulations that include the descending limb of the meridional Hadley Circulation and the zonal Walker Circulation which is linked to the Indian monsoon. Future warming and its predicted impact on the Hadley Cell and Walker Cell atmospheric circulations may therefore cause change to the synoptic patterns we have identified and their impact of the thermal environment of coral reefs in the GoE.
How to cite: McGowan, H., Theobald, A., and Lensky, N.: Synoptic typing of atmospheric circulation patterns associated with coral reef high water temperature events, Gulf of Eilat (Aqaba), Israel., EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-11, https://doi.org/10.5194/ems2026-11, 2026.
The Central-Eastern Himalayas (CEH), a key high-altitude barrier on the southern edge of the Tibetan Plateau, experiences concentrated summer rainfall and is a crucial water source for Asian countries. Understanding the interannual variability of summer precipitation across the CEH is essential for guiding efficient water management and supporting socio-economic development in South Asia. Here, we investigated the relationship between the CEH summer precipitation and all kinds of signals from the oceans. Analysis of long-term observations and reanalysis data revealed that the summer North Atlantic Oscillation (SNAO) has driven a positive summer precipitation in the CEH during 1994-2010. The SNAO triggered an anomalous anticyclone over Indian subcontinent during the specific period. The anticyclone directed low-level horizontal winds from North Indian toward the Himalayas’ southern slope. The southern slope forces the abnormal horizontal winds to generate a strong climbing flow component, leading changes in the precipitation distribution of CEH. Experiments with removing the plateau topographic features show that the positive precipitation distribution in the CEH shifts into a dipole-like pattern. The CEH was dominated by negative precipitation distribution after removing the plateau topography. All these results supported that the summer precipitation in the CEH during 1994-2010 was governed by the upstream atmospheric circulation from the Atlantic Ocean. While in other years, SNAO influences on CEH summer precipitation was not clear. This is due to the position shift of the SNAO-driven anticyclone to the south of the CEH. The position of SNAO-driven anticyclone modulates the coupled and decoupled relationship between SNAO and CEH summer precipitation variability. Therefore, understanding the dynamic links between the SNAO and CEH summer precipitation is key to enhancing precipitation prediction accuracy.
How to cite: Chen, X.: Stationary influence of the North Atlantic Oscillation on summer precipitation in the Central-Eastern Himalayas during 1994-2010, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-145, https://doi.org/10.5194/ems2026-145, 2026.
Euro-Atlantic weather regimes (WRs) act as critical drivers of European weather variability and extreme events. While previous research extensively details the correlational impacts of these quasi-stationary large-scale circulation patterns, explicitly predicting ground-level meteorological variables, such as surface temperature and precipitation, directly from WR indices remains an underexplored challenge.
In this contribution, we introduce an AI model that maps Euro-Atlantic WR indices to monthly anomalies in European 2-meter temperature and precipitation, explicitly bridging the circulation–surface link at seasonal time scales. Drawing on ERA5 reanalysis data (1940–2024), we derive seven year-round and four seasonal (DJF/JJA) WRs from 500 hPa geopotential height (Z500) fields using EOF analysis and k-means clustering. A residual neural network then processes these monthly WR indices alongside calendar data to reconstruct the corresponding surface anomaly fields across Europe.
Our model demonstrates high anomaly correlation and low mean absolute error, particularly during the winter months, and significantly outperforms traditional linear WR-composite reconstructions. Furthermore, when driven by WR indices predicted by the bias-corrected ECMWF SEAS5, the AI framework matches or exceeds SEAS5's ensemble mean across most deterministc metrics.
A critical question for operational implementation is the minimum accuracy required in the predicted WR indices for our AI framework to outperform baseline dynamical forecasts. To address this, we perform a sensitivity analysis by incrementally introducing artificial error into the input WR indices, simulating varying levels of forecast skill. By tracking how the AI model's output quality declines as the inputs worsen, we pinpoint the minimum WR forecast accuracy required for our framework to outperform direct ECMWF SEAS5 predictions of European winter and summer anomalies.
Ultimately, our findings reveal that a substantial portion of the spatial structure within European monthly anomalies can be directly inferred from the low-frequency Euro-Atlantic regime state. This research motivates the broader application of AI and hybrid methodologies to enhance regime predictability, ultimately advancing sub-seasonal to seasonal (S2S) forecasts of European weather and associated climate risks.
How to cite: Camilletti, A., Franch, G., Tomasi, E., and Cristoforetti, M.: AI reconstruction of European temperature and precipitation anomalies from Euro-Atlantic weather regimes, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-171, https://doi.org/10.5194/ems2026-171, 2026.
This preliminary study builds on previous work on the climatology of atmospheric fronts over Europe and their relationship with day-to-day near-surface air temperature variability. Earlier analyses have shown that temperature responses to frontal passages exhibit substantial spatial and seasonal variability, suggesting the influence of multiple interacting atmospheric processes.
The present contribution focuses on the role of large-scale circulation in modulating day-to-day temperature differences (DTD) associated with atmospheric fronts. Fronts are identified using an objective detection method applied to ERA5 reanalysis data for the period 1961–2020 over Europe. The synoptic-scale circulation is characterized by the Jenkinson–Collison classification derived from sea level pressure fields and aggregated into a reduced set of circulation types.
The analysis considers both warm and cold fronts during winter and summer seasons. In addition to temperature changes, the relationship between circulation types and frontal occurrence is examined using conditional probabilities, which quantify how strongly individual circulation types favour the occurrence of a given front type relative to its climatological frequency. This framework enables a systematic assessment of the links between frontal passages, temperature variability, and large-scale circulation.
Preliminary results indicate that circulation types may influence both the occurrence of fronts and the associated temperature responses. However, the strength and spatial structure of these relationships vary considerably across Europe and between seasons, pointing to a complex interplay between frontal dynamics and atmospheric circulation.
Overall, this study represents a first step towards a more integrated understanding of temperature variability by combining objective front detection with circulation classification. Further work is needed to better quantify and interpret the identified relationships.
How to cite: Navrátilová, D., Stryhal, J., Huth, R., and Kašpar, M.: Day-to-day temperature variability, atmospheric fronts, and circulation types: How they fit together?, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-367, https://doi.org/10.5194/ems2026-367, 2026.
Scientific evidence shows that climate and meteorological conditions strongly modulate forest CO₂ fluxes measured using Eddy-Covariance method. However few studies have investigated the impact of synoptic-scale circulation on gas exchange variability.
Seasonal estimates of Gross Primary Production (GPP), Net Ecosystem Exchange (NEE) and Ecosystem Respiration (RECO) were derived using linear regression models applied to Eddy Covariance data collected at the Collelongo-Selva Piana LTER-Italy site (3000 ha beech forest) from 1996 to 2014. Circulation Weather Types (CWTs) derived from ERA5 MSLP and HGT500 (used individually and combined) are generated via principal methods available in the used software (Simulated Annealing, Leader, Principal Component Analysis, Threshold methods).
We use COST Action 733 software to construct and compare multiple CWT classifications over a fixed Italian domain, selecting the optimal classification for explaining CO₂ flux variability.
Classifications are ranked by minimizing intraclass and maximizing interclass variance of GPP, NEE and RECO. This approach identifies the CWT classification that best discriminates flux regimes driven by synoptic patterns (uptake under westerlies vs. emissions under blocking).
The optimized Italian CWT enables diagnostic attribution of observed CO₂ anomalies to specific circulation drivers, helping to clarify Collelongo beech forest ecosystem processes.
In addition, the CO₂‑optimized CWT classification could be applied in CORDEX climate scenarios to quantify the future impacts of changing circulation frequencies on forest ecosystem activities.
Hence, understanding how CWTs influence natural ecosystem fluxes — and how these circulation patterns may evolve under future scenarios — could provide valuable guidance for forest management. This includes strategic species selection for adaptive silvicultural practices, supporting decision makers in climate-resilient forestry planning.
How to cite: Rossi, M., Costafreda-Aumedes, S., Giusti, R., Gozzini, B., Iannuccilli, M., Mazzenga, F., Messeri, A., Messeri, G., Matteucci, G., and Vallorani, R.: Optimizing COST Action 733 Weather Type Classifications over Eddy Covariance Fluxes at Collelongo Beech Forest eLTER site (Italy), EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-86, https://doi.org/10.5194/ems2026-86, 2026.
New generations of climate scientists get involved in downscaling global climate models, and the scientific community is increasingly being populated by scholars with a diversity of backgrounds and come from various scientific cultures. In particular, there is a renewed drive buoyed by an optimism in artificial intelligence and machine learning (AI/ML), which involves cohorts from the field of computation with different experiences to those with a background of meteorology or climatology. Many of the AI/ML papers on downscaling have ignored lessons learned from 30 years of progress within empirical-statistical downscaling, despite there being attempts with AI/ML starting already in the 1990s. There are also different opinions about downscaling within the CORDEX community which may enrich the scientific discourse within synoptic climatology. It is therefore useful to review and discuss what is established, what are the knowledge gaps, and what are the challenges. In this context, a number of questions are revisited that are relevant for the synoptic and mesoscales. They include: What are the models’ minimum skilful scale? What is the difference between downscaling, bias-correction, and interpolation? Should we regard the (1) downscaling of each data point (“downscaling weather”) or (2) downscaling of information about the curve of statistical distributions, the parameters that determine their shape (“downscaling climate”) as different branches? And what about AI/ML? Caveats concerning non-stationarity still pose a serious problem, and the question of how representative the training data is for a changed future climate is particularly relevant for AI/ML. This is especially important for multi-variable predictors. Some downscaling approaches emphasise the data while others may lean on mathematical theory or physics. A question is how to design tests and evaluations that are fit for purpose when it comes to downscaling global climate models to provide future projections.
How to cite: Benestad, R.: Reflections about regional climate modelling and synoptic scales based on progress over the past 25 years, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-445, https://doi.org/10.5194/ems2026-445, 2026.
The Jenkinson–Collison classification is among the most widely used methods for classifying synoptic-scale sea-level pressure fields and examining their links to surface weather. Its principal advantage, compared with approaches such as self-organizing maps or cluster analysis, is that it predefines circulation patterns based on simple and easily interpretable circulation indices (geostrophic wind speed, direction, and vorticity). Because the method was originally designed to objectively reproduce the manual Lamb weather types for the British Isles, the thresholds governing the assignment of fields to circulation types were chosen accordingly. When applied to markedly different climates with distinct circulation regimes and synoptic relationships, however, the default thresholds are likely to yield suboptimal or even misleading results.
One recent development of the Jenkinson–Collison methodology is its simultaneous application to an array of spatially overlapping (sliding) domains, producing “sliding classifications” that address a key limitation of circulation classifications—their restricted spatial validity. However, particularly at hemispheric or global scales, sliding classifications are highly sensitive to the choice of circulation indices and threshold values, and thus strongly affected by suboptimal parameter settings.
In this contribution, we test a wide range (~10,000) of threshold combinations across multiple Northern Hemisphere extratropical regions to (1) evaluate whether the default thresholds produce meaningful and useful classifications and (2) identify regions where alternative threshold sets improve classification utility. Because the quality and usefulness of a classification depend strongly on the evaluation criteria and research objectives, we employ several metrics and applications to assess performance. These include the tendency toward “snowballing” (i.e., the formation of one dominant class alongside many small ones) and the ability of classifications to explain variability in surface weather elements such as daily mean and maximum temperature, daily maximum wind gust, and daily precipitation totals.
How to cite: Stryhal, J.: Threshold values in spatially sliding Jenkinson–Collison–Lamb circulation classifications, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-230, https://doi.org/10.5194/ems2026-230, 2026.
Supporters & sponsors
