We welcome contributions addressing one or more of the following themes:
disentangling variability in teleconnections and their influence on regional climate, including their dynamics and predictive potential;
assessing the role of large-scale circulation changes in driving future regional climate change,
understanding discrepancies between simulated and observed climate variability and teleconnections, including potential improvements arising from advances in model resolution, process representation and emulators.
understanding changes in teleconnection patterns arising from strong external forcing.
This session emphasizes the physical interpretability of statistical and modelling results along with the accurate, context-appropriate use of statistical tools in physics-centered climate research. Studies that employ innovative methods to bridge statistical analysis and physical understanding – such as machine learning, causal inference methods, storyline approaches, Bayesian framework, or novel diagnostics for teleconnections – are encouraged.
Orals: Tue, 5 May, 10:45–12:30 | Room 0.96/97
A winter-long or month-long merging of the Atlantic and African jet streams, as occured during Northern Hemisphere winter 2009-10, represents a rare dynamical change in the jet stream, with significant large-scale changes in synoptic storms and the distribution of weather extremes. Previous reanalysis-based studies showed that these rare jet-merging occurred along with anomalously strong tropical-Pacific heating and weak mid-latitude eddies. In idealized models, externally imposed stronger tropical heating and weaker mid-latitude baroclinicity will result in a shift of an eddy-driven jet to a merged-jet. In this talk we examine how this idealized-model picture can be extended to the complex atmosphere, to explain the observed and possible future Atlantic-African jet merging.
Using ERA5 reanalysis and CESM2-LENS large ensemble simulations, we identify a few "external forcing building blocks" that emerge 1-2 months before month-long jet merging during winter. These include Central Pacific and Eastern Pacific El Ninos, and several dynamically linked but distinct recurring large-scale mid-latitude anomaly patterns, which act to weaken the synoptic eddies. These include anomalies in surface temperature, lower tropospheric moisture, upper level geopotential height, and the stratospheric polar vortex.We find several distinct combinations of these external forcing building blocks which lead to jet merging, depending on the type of tropical heating anomaly. We will conclude with discussing possible implications for climate change.
How to cite: Harnik, N. and Suresan, S.: Drivers of Atlantic-African jet merging: A localized-building-blocks view of dynamical regimes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10093, https://doi.org/10.5194/egusphere-egu26-10093, 2026.
Sea surface temperature (SST) trends over the satellite era show a pronounced cooling over the tropical south-eastern Pacific and enhanced warming over the West Pacific warm pool. By contrast, climate models tend to warm across all longitudes in the tropical Pacific. What does this discrepancy mean for climate model trends outside the tropical Pacific? Does capturing the observed pattern of tropical Pacific SST warming help to resolve other trend discrepancies in models? We use two complementary methods to constrain boreal winter SST trends in coupled models: pacemaker experiments, and conditioned near-term climate predictions (hindcasts). We find that the global response to constraining tropical Pacific SST trends resembles the interannual La Niña response. The Pacific SST trend explains 33-39% of the poleward zonal-mean jet shift seen in the models, and is associated with robustly reduced tropical tropospheric warming trends consistent with reanalyses. It also improves surface air temperature and precipitation trends in ENSO-sensitive regions, such as the South Asia, southern Africa, and the Americas. Our results highlight the importance of resolving discrepancies in the tropical Pacific for building confidence in climate model trends globally.
How to cite: Thomas, R., Kang, J., Dunstone, N., Shaw, T., and Woollings, T.: Climate impacts of tropical Pacific SST trends in boreal winter, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9252, https://doi.org/10.5194/egusphere-egu26-9252, 2026.
This study investigates the interference between Indian and Pacific Ocean teleconnections with Southern Africa (SA) during the austral early summer (November-December) of El Niño-Southern Oscillation (ENSO) events. During 1979-2024, reanalysis and observational datasets suggest that ENSO events drive below-average rainfall conditions over SA.
Partial regression analysis shows that the Indian Ocean teleconnection accounts for 38% of the ENSO-related rainfall variability over SA, while the Pacific teleconnection accounts for 62%, evidencing an interference of distinct teleconnection pathways. We reveal two mechanisms driving these anomalies: a) a Matsuno-Gill-like response over the Indian Ocean, related to the Indian Ocean teleconnection; and b) a South Atlantic zonal wavenumber-4 Rossby wave train, associated with the Pacific teleconnection.
The wave train originates from the La Plata sector, where rainfall anomalies generate vorticity tendency through vortex stretching, forming a Rossby wave source. By implementing a Rossby wave ray tracing algorithm, we show that the South Atlantic Rossby wave undergoes wave splitting, with shorter waves refracted toward SA, and longer waves continuing toward the Southern Ocean. A further analysis using a large ensemble of CMIP5/CMIP6 models suggest that the La Plata Rossby wave source is positively correlated to subsidence over SA. Furthermore, models failing to simulate the ENSO-La Plata teleconnection also do not reproduce the South Atlantic Rossby wave train, reinforcing the role of the ENSO-La Plata rainfall link in promoting subsidence over SA.
We further corroborate the observational evidence through ad-hoc sensitivity experiments using the SINTEX-F2 general circulation model. Two experiments are performed: a tropical Pacific experiment, in which Sea Surface Temperatures (SSTs) are allowed to freely evolve over the tropical Pacific, and a tropical Indian Ocean–Maritime Continent experiment, in which SSTs are free over the tropical Indian Ocean and Maritime Continent. Outside these regions, SSTs are strongly nudged toward the control climatology. The model results confirm the potential interference of teleconnections originating from the Pacific and Indian Oceans in driving dry anomalies over SA. In particular, Pacific forcing induces a Southern Atlantic Rossby wave train, whereas Indian Ocean forcing produces a Matsuno–Gill-type response, further conforming observational results.
How to cite: Sabatani, D., Gualdi, S., Behera, S., Morioka, Y., and Richter, I.: Disentangling the interference between Indian and Pacific Ocean teleconnections with Southern Africa during austral early summer , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18346, https://doi.org/10.5194/egusphere-egu26-18346, 2026.
Megadroughts and megapluvials are multi-year dry and wet events of exceptional duration and intensity. There is strong paleoclimate evidence for the existence of such events in various regions of the globe. However, the mechanisms how these anomalies can be sustained for long periods of time have not been clearly elucidated and reproduced in climate models. Here we address this question using large-ensemble simulations with the CESM2 fully-coupled climate model. We argue that, outside ENSO-influenced regions, meteorological megadroughts and megapluvials in the simulations are mainly caused by natural variability in the atmosphere with limited influence from the oceans. We first show that interannual correlations in accumulated precipitation are weak. Multi-year extreme precipitation events therefore arise as a succession of independent yearly events. Secondly, we show that in the simulations anomalous SST patterns do not explain the intensity of dry and wet years contrary to what was postulated for real world megadroughts and megapluvials. These results imply that, outside ENSO-influenced regions, megadroughts and megapluvials in the climate model are caused by the succession of independent dry and wet years and not from the interaction with the slower ocean. However, the intensity and frequency of recorded megadroughts and megapluvials are not compatible with the model result that they arise as a succession of independent years. This strongly suggests that key physical mechanisms are missing in the model to reproduce these peculiar events and advocates for caution in estimating the probability of multi-year dry and wet events from climate model simulations.
How to cite: Noyelle, R., Knutti, R., Fischer, E., and Wernli, H.: Megadroughts and megapluvials in CESM2: can they be explained by oceanic internal variability ?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9989, https://doi.org/10.5194/egusphere-egu26-9989, 2026.
Recent observed trends indicate increasing future precipitation in Northern Europe, yet CMIP6 models show substantial spread in sign and magnitude of both historical and future precipitation trends in the region. This large model spread highlights the difficulty in accurately modelling regional precipitation in global climate models, and the low confidence in future precipitation trends. In this study, we evaluate recent historical winter precipitation trends in selected models of the CMIP6 ensemble by validating the models against reanalysis and observations, and examining how the trends are influenced by sea surface temperatures (SSTs) and the large-scale atmospheric circulation, particularly the North Atlantic storm track. We consider data from CMIP6 historical and AMIP experiments, the latter using prescribed observed SST and sea ice concentration. Additionally, we include a complimentary set of AMIP-style experiments with the Norwegian Earth System Model (NorESM2) where we explore the effect of different time-evolving SST fields.
Results show that models yield consistent precipitation patterns, which enables an assessment of the role of North Atlantic SST in shaping Nordic precipitation trends, when averaging over multiple ensemble members. Differences in Nordic precipitation trends are tied to differences in the North Atlantic SST pattern evolution, with consistent changes in latent heat flux, atmospheric baroclinicity and lower tropospheric zonal wind patterns. Particularly, differences in SST in the North Atlantic warming hole and along the eastern US coast and close to Svalbard, the latter related to rapid warming from Arctic sea ice loss, can influence the precipitation trends. Employing the relationship between North Atlantic SST and precipitation trends in the Nordic region, we can better understand the large precipitation spread among climate models, and thus increase confidence in both historical and future precipitation in the models. Furthermore, while the majority of CMIP6 models provide just a single ensemble member for the AMIP experiment, our results demonstrate that using multiple ensemble members for the AMIP experiments is essential to account for internal variability and to achieve robust results.
How to cite: Rosendahl, A., Gjermundsen, A., Seland Graff, L., and Schulz, M.: Nordic precipitation trends and North Atlantic circulation patterns in CMIP6 models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10875, https://doi.org/10.5194/egusphere-egu26-10875, 2026.
In this study we apply a recently developed, ensemble-based method to track the changes of the Southern Annular Mode (SAM) and its climate impacts under a changing climate. The advantage of this method is that it does not rely on oscillation patterns tacitly assumed to be constant over a given time period, as it is the case with traditional methods based on single time series.
SAM is the leading mode of atmospheric variability of the Southern Hemisphere’s extratropics. One of the traditional definitions of the SAM is that it is the first mode of the empirical orthogonal function (EOF) analysis of mean sea-level pressure (SLP) for 20°S–90°S for a given time period. SAM index time series is then computed by projecting the SLP anomalies on this loading pattern and standardized for the time period. The strength of the linkages associated with SAM can be calculated as correlation coefficients between time series of the SAM index and other meteorological variables.
Studies over the last decades showed a trend of the SAM towards the positive phase. Since the traditional, time series-based definition of SAM calculates the oscillation pattern for a chosen time period, this pattern and the SAM-related correlations are treated as constant for that time period. However, in a changing climate stationarity cannot be assumed. Consequently, positive shift inferred using traditional methods are questionable. Therefore, in this study, using different climate models’ large ensembles, we apply a recently developed method, the snapshot EOF (SEOF) analysis to calculate SAM. This method performs the EOF analysis across the ensemble dimension at each time instant, utilizing the fact that members of a sufficiently large ensemble correctly cover the distribution of the possible climate states at each time instant after a certain convergence time. Instantaneous ensemble-based SEOF loading patterns represent the spatial structure of the SAM that characterizes the potential variability in the climate states of the given time instant, and the corresponding SEOF-based SAM indices reveal the phases in which the ensemble members are in that very moment. In this way, beyond a correct characterization of the SAM at each time instant, the time-dependence of its pattern can also be monitored. Furthermore, instantaneous correlation coefficients between the instantaneous indices and other variables can be computed across the ensemble to reveal the correct instantaneous connection strengths and their time-dependence.
By means of the SEOF analysis, we show that the recent and future positive trend in the SAM for 1950–2100 seen with the traditional methods is the consequence of the change in the ensemble mean SLP field (mean state of the oscillation), with decreasing SLP in Antarctica and increasing SLP at the mid-latitudes. Besides this, SEOF-based SLP regression maps reveal that the absolute value of the typical amplitudes of SAM-related anomalies will decrease at most of the geographical locations, and the explained variance also shows a significant decrease of 5-10%. Correlation coefficients with surface temperature changes even 0.3-0.4 over the 150 years in certain regions.
How to cite: Haszpra, T.: Capturing and interpreting the Southern Annular Mode’s positive shift in large ensembles using the snapshot approach , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-479, https://doi.org/10.5194/egusphere-egu26-479, 2026.
We investigate the interannual variability of the North Pacific Central Mode Water (CMW) under the phase relationship of the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), based on multiple observational datasets. Peaks and troughs of the CMW variability are primarily observed when ENSO and PDO are in phase, but only moderate variation when ENSO and PDO are out of phase. In El Niño spring during positive PDO, extreme CMW ventilation takes place in the central North Pacific (180°–155°W, 30°–40°N), where no local ventilation occurs for other cases. Such extreme CMW ventilation induces stronger temperature anomalies, which persist longer and penetrate deeper. Our results suggest that CMW, representing a long-term ocean memory, may play a more significant role in tropical-extratropical interactions than ever expected.
How to cite: Xu, L., Liu, J., Zheng, X.-T., Wang, K., and Li, J.: Extreme Ventilation of the North Pacific Central Mode Water by El Niño During Positive Phase of the Pacific Decadal Oscillation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16940, https://doi.org/10.5194/egusphere-egu26-16940, 2026.
The Equatorial Pacific Cold Tongue (CT) bias is a systematic sea surface temperature (SST) bias, persisting throughout all generations of comprehensive climate models. Recent works suggested that extratropical SST biases contribute to the CT bias, mediated by the wind-driven ocean overturning circulation in the Pacific. However, as shown here, the northern and southern hemispheric "eastern exchange windows", which are the dominant extratropical sources for water upwelling in the Equatorial Pacific, are not characterized by cold SST biases. Here we explore these links using Lagrangian back trajectory analysis in 32 models participating in phases 5 and 6 of the coupled model intercomparison project (CMIP5/6), and four ocean reanalyses. Consistent with previous works, Equatorial Pacific upwelling is found to be sourced primarily from late-winter subduction in the extratropical eastern exchange windows. We also find that climatological dynamical fields dominate the probability distribution maps linking extratropical subduction with upwelling in the CT. Variations across CMIP5/6 models and between CMIP5/6 models and reanalyses consistently point to poleward shifts of the eastern exchange windows into colder extratropical waters as a likely key contributing factor to the CT bias, which, due to the strong meridional SST gradients in the extratropics, can drive CT biases regardless of extratropical SST biases. Consistent with previous works, cold biases in the northern extratropics, which partially overlap with the north-eastern exchange window, also contribute to the CT bias. Trajectory duration varies considerably across models and between models and reanalyses, but is not consistently related to the CT bias.
How to cite: Adam, O., Ariel, O., Shourky, M., and Gildor, H.: Pacific cold-tongue bias in CMIP5/6 linked to shifts in extratropical subduction zones, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5622, https://doi.org/10.5194/egusphere-egu26-5622, 2026.
Understanding the origins of climate variability (e.g., ENSO and AMV) and their interactions across timescales, as well as assessing model performance in simulating them, relies on robust sea-surface temperature (SST) datasets. Yet, there are numerous instrumental SST products that differ in their bias adjustments and gridding/infilling strategies. These structural choices propagate to key inferences about the climate system such as climate variability indices, the separation of internal and forced components, and teleconnection magnitudes and spatial patterns. Here, we explain why instrumental SST products differ, what these differences imply for climate variability and teleconnection analyses, and which products are best suited for specific applications. We review recent advances in bias adjustment and gridding/infilling of in situ data and assess the implications of these methods for global mean SST evolution and regional variability indices. We find substantial discrepancies in trends during the satellite era among older products, whereas state-of-the-art datasets are much more consistent. State-of-the-art SST datasets are also more consistent with signals from CMIP-class climate models in global mean SST during World War II, Atlantic multidecadal variability indices, and trends in the tropical Pacific zonal gradient — demonstrating the need to carefully choose SST datasets when investigating climate variability. Disagreements persist, however, for early-20th-century warming, which has implications for separating forced response from internal variability, and in data-sparse regions such as the Southern Ocean and Arctic. To support robust, physically interpretable teleconnection diagnostics, we articulate practical principles for dataset selection and highlight the NCAR Climate Data Guide as an evolving resource for updated SST benchmarking.
How to cite: Chan, D., Kent, E. C., Lenssen, N., Deser, C., Merchant, C. J., Ishii, M., Sandford, C., Huang, B., Yin, X., Kennedy, J. J., Cornes, R. C., Huybers, P., and Gebbie, G.: SST Dataset Choice Affects Estimates of Historical Climate Variability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18307, https://doi.org/10.5194/egusphere-egu26-18307, 2026.
How the El Niño-Southern Oscillation (ENSO) will respond to greenhouse warming remains uncertain. Here we present results from an ensemble of greenhouse warming simulations conducted with the AWI-CM3-resolution climate model at 30 km atmosphere and 4-25 km ocean resolution. The model simulates a rapid transition from a moderate-amplitude irregular ENSO regime, as observed in the current climate, to a highly regular oscillation with intensifying amplitude. Using low-order dynamical ENSO models, we demonstrate that this behaviour is mainly due to noise-induced supercriticality. As ENSO intensifies in the AWI-CM3 model, it also synchronizes with other prominent climate modes, such as the North Atlantic Oscillation and the Indian Ocean Dipole, thereby imprinting its regular, predictable variability on them. This process significantly alters the global patterns of climate memory.
How to cite: Timmermann, A., Stuecker, M., Zhao, S., Lee, S.-S., Moon, J., Semmler, T., Ghosh, R., Jung, T., and Jin, F.-F.: Noise-induced ENSO supercriticality due to greenhouse warming and implications for climate memory, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3243, https://doi.org/10.5194/egusphere-egu26-3243, 2026.
The daily to multi-decadal natural variability of large-scale atmospheric circulation makes it challenging to distinguish forced long-term trends and their impact on surface air temperature and precipitation changes. This study disentangles the thermodynamical and circulation-induced, i.e. dynamical, contributions to climate change using idealized model simulations having their large-scale free-troposphere circulation nudged towards either preindustrial or +4°C warmer world winds as previously simulated by the same model without nudging. In both seasons, thermodynamical changes are the primary contributor to the total climate change signals of surface air temperature and precipitation, yet changes in horizontal advection significantly reduce or raise the regional signal. Changes in vertical motion additionally impact precipitation changes, and it was found to be regionally dependent whether changes in horizontal advection or vertical motion are the dominant reason for the observed precipitation change. Quantifying the impact of changes in atmospheric circulation with climate change is therefore a necessity for regional climate change projections.
How to cite: Monfort, E., Sánchez-Benítez, A., Jung, T., and Goessling, H.: Dynamical vs. thermodynamical contributions to climate change: an analysis of idealized nudged model simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1056, https://doi.org/10.5194/egusphere-egu26-1056, 2026.
The North-west Indian Ocean (Arabian Sea) is the second most significant upwelling zone, contributing 90 Tg-Cyr-1 to the atmosphere. This region is oceanographically dynamic with a reversal in summer and winter monsoonal wind direction, resulting in season-specific upwelling and runoff dynamics. For example, the southwest (SW) monsoon drives large-scale upwelling and high productivity in the Western and Northern Arabian Sea, while the Eastern Arabian Sea (EAS) experiences comparatively moderate upwelling (Singh et al., 2011). In contrast, northeast monsoon winds promote convective mixing off central India and contribute to maintaining the strong Oxygen Minimum Zone (OMZ) at ~150-1200 m (Wyrtki, 1973; Naqvi, 1991. Despite its importance, high-fidelity paleoclimate reconstructions from this region are sparse.
This study aims to reconstruct past surface ocean productivity as a function of wind-driven upwelling and or surface runoff, thereby providing new constraints on carbon dynamics in the Eastern Arabian Sea over the last 55-kyr. We used the surface-dwelling planktic foraminifera species Globigerinoides ruber for reconstructing sea surface temperature (Mg/Ca), sea surface salinity (δ18O), surface ocean productivity and nutrient supply (Ba/Ca, Cd/Ca). All samples were reductively cleaned following Boyle & Keigwin (1985), ensuring reliable Cd/Ca and Ba/Ca measurements.
The Mg/Ca-derived SSTs demonstrate ~2–3 °C cooling during the LGM, whereas the earlier stadials are punctuated by modest cooling, consistent with reduced SW monsoon intensity (Elderfield & Ganssen, 2000; Saraswat et al., 2005; Anand et al., 2008). The δ¹⁸Osw derived salinity reaches its maximum during the LGM, reflecting weakened summer monsoon precipitation, enhanced evaporation, and a southward migration of the Intertropical Convergence Zone (ITCZ) (Ivanochko et al., 2005).
Our foraminiferal Cd/Ca ranges from 0.03 to 0.18 µmol/mol, and Ba/Ca from 1.0 to 2.7 µmol/mol, reflecting substantial variability in nutrient supply, freshwater discharge and export productivity over the last 55 kyr. The following interpretations are based on the preliminary observations. Both Cd/Ca and Ba/Ca covary, with pronounced peaks during HS4 and HS5 and more moderate increases during HS2-HS3, consistent with intensified winter monsoon-driven mixing and shoaling of the nutricline (Altabet et al., 2002; Ivanochko et al., 2005). The LGM further combines elevated Cd/Ca with low Ba/Ca and the highest salinities, indicating reduced freshwater discharge and weak SW monsoon rainfall, which lowered dissolved Ba inputs while suppressing upwelling, and limiting export productivity. In contrast, HS1 is characterised by decreasing salinity, elevated Ba/Ca and moderate Cd/Ca values, suggesting enhanced export productivity (Lea & Boyle, 1991) or freshwater discharge despite lower nutrient concentrations than during the LGM. This pattern indicates that HS1 productivity is mediated by mixing-driven nutrient inputs, but in a hydrographic context distinct from the highly saline, nutrient-rich but low-productivity LGM.
Together, this study demonstrates that EAS productivity was profoundly shaped by shifts in monsoon-driven upwelling and freshwater runoff, thereby reflecting the far-reaching influence of high-latitude climate perturbations on tropical ocean processes.
How to cite: Saha, A., Walling, T., Chanakya, I. V. S., and Misra, S.: Productivity Changes in the North-west Indian Ocean (Arabian Sea) over the last 55 kyr: Interplay between Monsoon and Upwelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1279, https://doi.org/10.5194/egusphere-egu26-1279, 2026.
Equatorial Pacific ocean heat content (OHC) variability is a key component of tropical climate dynamics, especially in the evolution of the El Niño–Southern Oscillation (ENSO). Recent work has shown that the strong 2023–2024 El Niño was driven primarily by oceanic processes, independent of the classical positive Bjerknes feedback. Climate models project that such events will become more frequent under continued warming, highlighting the need to better understand the mechanisms regulating equatorial OHC variability. While local air–sea interactions dominate variability on sub-annual timescales, the contribution of ventilated waters from extra-tropical source regions on annual to decadal timescales remains less clearly defined.
This study focuses on the following gaps in our understanding of tropical–extra-tropical ventilation: First, which physical mechanisms regulate the magnitude and variability of subduction fluxes in the extra-tropical source regions? Second, to what extent is the commonly assumed adiabatic transport along isopycnal pathways valid, and how strongly do diapycnal mixing and nonlinear temperature–salinity effects modify water-mass properties during advection? Third, how do these processes together control the contribution of remote ventilation to equatorial Pacific OHC variability?
To address these questions, we employ a Lagrangian framework based on ocean reanalysis data, tracking subducted water parcels from their source regions to the equatorial Pacific. By analyzing the evolution of temperature and salinity along particle trajectories, we assess the relative roles of subduction variability, interior isopycnal transport, and diapycnal mixing in shaping equatorial OHC variability on interannual to decadal timescales.
How to cite: Shourky, M. and Adam, O.: Relation of Tropical–Extra-tropical Ventilation to Equatorial Pacific Ocean Heat Content Variability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5923, https://doi.org/10.5194/egusphere-egu26-5923, 2026.
Interdecadal cycles repeatedly appear in multiple global climate variables such as rainfall, temperature, and major climate modes, yet their origin remains a mystery and is most often attributed to quasi-periodic artefacts of internal climate variability or red-noise processes. Here we identify statistically significant (p < 0.001), coherent 12.9- and 19.9-year cycles in detrended rainfall, surface temperature, and total cloud fraction across ~40% of global land areas using the Gaussian clustering of wavelet amplitude power spectrum (GC-WAPS) method. GC-WAPS enables the aggregation of subtle cyclic signals across extensive spatial networks of climate records, providing robust discrimination from red-noise variability.
The resulting patterns exhibit organised regions of positive and negative phase alignment, forming large-scale teleconnection-like structures rather than isolated local responses. At sites exhibiting significant periodicity, the mean cycle amplitude in total cloud fraction is approximately 2%, corresponding to an estimated ~0.4°C modulation of surface temperature, consistent with estimates derived from longwave cloud radiative effect sensitivity. The cycles contributed an average of 10% to rainfall variance in significant regions, with the strongest signal being detected in eastern Australia, where the timing aligns with extended drought epochs. Regions of positive and negative correlation are mostly balanced, meaning these cycles represent a redistribution of energy rather than an overall heating or cooling effect.
The detected oscillations also align in period and phase with repeating gravitational cycles in Solar Inertial Motion (SIM), driven by the orbital dynamics of the Jovian planets, and consistently lag these dynamics by approximately two years. All five SIM periods shorter than 60 years correspond to cluster peaks in global rainfall within 1% error (12.9-, 19.9-, 29.4-, 35.9- and 45.4-years), though the three longer cycles are interpreted cautiously due to record length of each dataset. The observed phase coherence, amplitude, and cross-variable consistency motivate a tentative mechanism in which gravitational perturbations modulate interplanetary dust influx, leading to downstream changes in cloud cover, radiative balance, and rainfall; further work is required to test this hypothesis. These findings have implications for low-cloud feedback and decadal variability, highlighting a potentially externally timed component of Earth’s climate variability that is not explicitly represented in current CMIP-class models.
How to cite: Selkirk, T., Western, A., and Webb, A.: Coherent interdecadal cycles in global rainfall, temperature, and cloud cover, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6007, https://doi.org/10.5194/egusphere-egu26-6007, 2026.
Multi-year droughts are severe natural hazards that have become more common due to climate change. Their longevity and resulting impact distinguish them from shorter seasonal or sub-annual drought events. This persistence in drought events suggests an important role for memory in the climate system but could also be caused by coincidental alignment of consecutive dry years. Since multi-year droughts are relatively rare and research has mostly focused on individual case studies, general multi-year drought drivers remain poorly understood.
We identified different regional influences from the ocean, atmosphere and land surface correlating with multi-year droughts onset, with lags up to several months in prior to drought onset. Building on this, we here investigate how land-atmosphere and ocean-atmosphere interactions shape multi-year drought frequency, duration, and periodicity on annual to multi-decadal timescales. For this, we have set up a set of global climate model experiments performed with EC-Earth3, designed to selectively enable or suppress land-atmosphere and ocean-atmosphere coupling, both on global and regional scales. This allows us to directly assess the influences of ocean-atmosphere and land-atmosphere coupling, memory in the ocean and land, and the role of climate variability on different drought characteristics from annual to multi-decadal time scales.
By comparing multi-year droughts to shorter drought events across these experiments, we can quantify the extent to which different interactions actively promote the occurrence of multi-year droughts. Our results will provide new insight into the influence of climate memory and variability on multi-year droughts and clarify the potential limits of predictability for multi-year droughts on regional and global scales.
How to cite: van Mourik, J., van der Wiel, K., Hazeleger, W., and Wanders, N.: Disentangling the influence of climate memory on multi-year droughts using model experiments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7843, https://doi.org/10.5194/egusphere-egu26-7843, 2026.
Assessing climate-change impacts solely from local trends may be misleading, as large-scale teleconnections transmit anomalies across regions and may reorganize spatial risk, potentially creating dynamically influential “hot spots.” This study presents a station-based climate-network (“climate grid”) framework to quantify spatiotemporal connectivity and its long term evolution across Türkiye. The network is built from 221 in situ stations operated by the Turkish General Directorate of Meteorology and is based on 1960–2024 average daily temperature and total daily precipitation observations.
All computations are performed in Python environment using equations formulated for climate-grid construction and are parallelized to handle to the full set of pairwise station calculations. Prior to network construction, station time series are deseasonalized and standardized to anomalies to ensure cross-regime comparability across Türkiye’s diverse climatic regimes and topography, in line with standard climate-network methodologies. A Monte Carlo permutation procedure is applied to test link significance and to define objective sparsification thresholds, minimizing spurious connections.
Hot spots are identifies through network centrality analysis, emphasizing degree and its directional components (in-degree/out-degree) to classify stations that mainly drive regional variability (“sources”) from those that mainly respond to it (“sinks”). This is consistent with prior degree-based hot-spot detection that combine degree-based hot-spot mapping with nonparametric trend testing (e.g., Mann–Kendall) to evaluate changes under anthropogenic forcing. Guided by recent network studies on how extremes propagate through networks and how drought conditions synchronize directionally, the framework supports to track spatiotemporal connectivity through time and to identify regions with potential cascading behavior.
The resulting climate grid is separated into two complementary components: (i) a focal-station network that summarizes the links from a station to its surrounding stations, and (ii) a reciprocal network describing the surroundings’ connections back to the focal station. Explicitly representing both outward and inward connectivity provides a directional interpretation of climate coupling and allows stations to be characterized as potential “sources” versus “sinks” of climate influence. Hot spots are then identified using network centrality measures. This allows us to map influential and sensitive locations across Türkiye, assess how connectivity patterns shift over time, and help prioritize monitoring and adaptation actions under increasing climate variability and extremes. The results are presented and discussed in terms of national-scale connectivity patterns, hot-spot persistence, and emerging shifts through time.
Keywords: climate networks; spatiotemporal connectivity; station-based grid; Türkiye; time-lagged dependence; hot spots.
How to cite: Barut, H. and Ünal, Y.: Mapping Climate Connectivity and Hot Spots over Türkiye Using a Station-Based Network Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9043, https://doi.org/10.5194/egusphere-egu26-9043, 2026.
The Northern Hemisphere jet streams exhibit variability on decadal to multidecadal timescales, potentially providing an important source of climate predictability. Compared to reanalysis data, however, global climate models underestimate this low-frequency variability.
While the origin of this missing variability remains unclear, a possible cause might be insufficient ocean-atmosphere coupling. Increasing horizontal model resolution to capture mesoscale frontal processes can enhance this coupling and, consequently, decadal atmospheric circulation variability associated with decadal sea-surface temperature variability.
To characterize decadal circulation variability, we analyze patterns of low-frequency variability of Northern Hemisphere wintertime sea-level pressure and 700 hPa zonal wind using low-frequency component analysis. By comparing ERA5 reanalysis to CESM1 simulations at both a standard 1° and a higher 0.25° atmospheric resolution, we aim to (1) compare model and reanalysis, and (2) investigate the gain of increasing model resolution.
We find that the ratio of low-frequency to total variance in the Northern Hemisphere storm track regions is considerably higher in the reanalysis than the model data for all leading modes of variability. Our analysis also reveals differences in the composition of modes of low-frequency variability between reanalysis and the two model resolutions.
This research advances understanding of how global climate models represent low-frequency circulation variability at different resolutions, which is crucial to improve decadal predictability and climate projections.
How to cite: Glock, E., Müller, J., Xuan, Z., and Jnglin Wills, R.: Decadal circulation variability in storm track regions: a comparison of reanalysis and model data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10757, https://doi.org/10.5194/egusphere-egu26-10757, 2026.
Inter-basin interactions are a pivotal driver of the global climate system. By employing the inter-basin teleconnectivity (IBT) analysis, this study systematically investigates the dominant simultaneous inter-basin linkages across the Pacific, Atlantic, and Indian Oceans in the annual mean sea surface temperature field. We identify 11 distinct inter-basin teleconnections (IBTs), which include two previously recognized patterns, i.e. the boundary current synchronization (BCS) and South Atlantic-South Indian Ocean synchronization (SASI), along with nine new potential IBTs. Two of these new IBTs respectively represent the inter-basin linkages of the Pacific Decadal Oscillation (PDO) and Indian Ocean Basin Mode (IOB) with other ocean basins. We mainly analyze the spatiotemporal characteristics of the remaining IBTs, namely the Bay of Bengal-South Atlantic synchronization (BBSA), Northwest Atlantic-Southeast Indian Ocean seesaw (NASI), Caribbean Sea-Southwest Indian Ocean seesaw (CSSI), Southwest Pacific-Southeast America synchronization (SPSA), North Pacific-South Atlantic seesaw (NPSA), North Tropical Indo-Pacific seesaw (NTIP), and Southern Hemispheric Tripole (SHT). The results demonstrate that these IBTs are statistically relatively independent of some known climate modes and exhibit distinct quasi-periodic characteristics on interannual to decadal timescales. These findings enhance our understanding about inter-basin linkages and interactions.
How to cite: Zhang, D. and Li, J.: Inter-basin Teleconnections in the Annual Mean Sea Surface Temperature Field, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11535, https://doi.org/10.5194/egusphere-egu26-11535, 2026.
Here, we use three variable-resolution, global models to explore storylines of future Arctic and Antarctic climate change previously derived by Levine et al. (2024; 10.5194/esd-15-1161-2024) and Williams et al. (2024; 10.1175/JCLI-D-23-0122.1). The models are the Community Earth System Model (CESM), the ICOsahedral Nonhydrostatic model (ICON), and the Model for Prediction Across Scales (MPAS). The pair of Arctic storylines examined represent 1) weak Arctic amplification combined with strong SST warming in the Barents-Kara Seas and 2) strong Arctic amplification combined with weak SST warming in the Barents-Kara Seas. Over Antarctica, the storylines explored are 1) high Southern Hemisphere (SH) sea-ice loss combined with a shorter delay in SH vortex breakdown, and 2) low SH sea-ice loss combined with a longer delay in SH vortex breakdown.
Sea surface temperatures (SSTs) and sea ice concentrations (SICs) from CMIP6 models that are representative of these storylines were provided to the variable-resolution models to perform a number of AMIP-style experiments. We performed experiments for the recent past and for the future with uniform and refined horizontal resolution over the polar regions. The result is a novel and comprehensive set of experiments based on three different variable-resolution models (CESM, ICON, MPAS), two different SST and SIC forcing fields for the Arctic and two for the Antarctic (from 4 different CMIP6 models), two different resolutions (refined and unrefined), and two different time periods (recent past and future).
We use this experiment set to explore the extent to which results from the variable-resolution experiments resemble the CMIP6 models that have been selected to represent the storylines that the SSTs and SICs are taken from, focusing on near-surface temperature, precipitation, and 850-hPa zonal wind. Furthermore, we quantify the influence of the storyline model, the influence of the variable-resolution model, and the influence of the resolution on the future responses. Results show that the influence of the storyline and the variable-resolution model is larger than the influence of the resolution for all variables and seasons in both the Arctic and Antarctic. In the Antarctic, the storyline influence moreover tends to be larger than the model influence, meaning that the model differences are smaller than the differences associated with the phase of the remote drivers (high/low SH sea-ice loss & short/longshort SH vortex breakdown delay). While we find similar results for near-surface temperature in the Arctic, the storyline and model influence are more comparable for precipitation and zonal wind. Overall, our results suggest that for the large-scale climate change responses considered here, careful selection and sampling of storyline drivers and model structural uncertainty is more critical than increased horizontal resolution in the polar regions.
How to cite: Graff, L. S., Handorf, D., Köhler, R., Levine, X., Wijngaard, R. R., Williams, R. S., and Mooney, P. A.: Quantifying future Arctic and Antarctic climate change from a storyline perspective using global variable-resolution models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13000, https://doi.org/10.5194/egusphere-egu26-13000, 2026.
The surface and subsurface temperatures of the eastern equatorial Pacific (EEP) cold tongue region are closely tied to tropical Pacific dynamics and to the El Niño Southern Oscillation (ENSO). Uncovering the paleoclimate history of the EEP is key to understanding Holocene ENSO change, but reconstructions of EEP variability are often complex and integrate both seasonal and interannual variability. While sub-annually resolved corals may be able to differentiate these components, such records from the EEP are sparse, short, and discontinuous. Ocean sediment records can provide continuous records, but have been limited in their ability to differentiate seasonal and inter-annual variability changes. Here we examine mixed-layer foraminifera to explore whether variations in the trace elemental ratios of closely-related species/morphotypes can address the question of seasonality change and enhance our understanding of the evolution of Holocene ENSO. We analyzed Mg/Ca ratios in EEP foraminifera including the mixed-layer dwelling Globigerinoides ruber (sensu stricto) and the closely related form G. elongatus, which has historically been classified as a morphotype of G. ruber (sensu latu). Evidence suggests G. ruber ss calcification temperatures in the EEP are slightly warmer, commonly interpreted as a shallower calcification environment. However, the geochemical evidence is also consistent with a warm-season bias, which, combined with a potential cold-season preference for G. elongatus / G. ruber sl could provide evidence to reconstruct EEP seasonal change. We find that the Mg/Ca difference between these forms varies through the Holocene, with the smallest difference at mid-Holocene (from 3-6 ka) when reduced tropical Pacific variability is recorded by multiple proxies and simulated in models. We explore whether our data show reduced seasonality or alterations to the upper-water column thermal structure. However, as EEP seasonality and upper-water column structure are both related to tropical Pacific dynamics, the variations observed in our record point toward mid-Holocene alterations to tropical dynamics. These results are put in the context of our current understanding of EEP variability and ENSO changes, and we examine how these insights can enhance our insights into ENSO evolution through the Holocene.
How to cite: Rustic, G.: Holocene tropical Pacific dynamics revealed by trace elemental variations in mixed-layer foraminifera: signs of changing eastern equatorial Pacific seasonality or upper water column structure?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15395, https://doi.org/10.5194/egusphere-egu26-15395, 2026.
Posters virtual: Fri, 8 May, 14:00–18:00 | vPoster spot 4
EGU26-17596 | Posters virtual | VPS7
Impact of Different Initialization Strategies on the Representation of Dominant SST Variability Modes in the NorCPM Coupled Climate ModelFri, 08 May, 14:51–14:54 (CEST) vPoster spot 4
A realistic representation of sea surface temperature (SST) variability in climate models is essential for seasonal-to-interannual forecasting and for understanding large-scale climate oscillations. This study evaluates the impact of three initialization strategies in the NorCPM coupled climate model on the structure and temporal evolution of the leading modes of global SST variability over the 1980–2010 period. The analyzed strategies include a free-running simulation (FREE), ocean data assimilation using an ensemble Kalman filter (ODA), and atmospheric nudging of wind and temperature anomalies (NUDA_UVT). Model results are evaluated against the HadISST observational dataset.
Empirical Orthogonal Function (EOF) analysis is applied to monthly SST anomalies computed over the full globe and using all calendar months, without regional restriction or seasonal stratification. This framework enables a consistent comparison of the dominant large-scale SST variability modes across all datasets. The results indicate that ocean data assimilation (ODA) best reproduces the leading ENSO-related mode, achieving a spatial correlation of 0.98 and the lowest root mean square error in its principal component (RMSE = 1.70). For the second mode, associated with lower-frequency variability, atmospheric nudging (NUDA_UVT) shows improved spatial agreement (correlation = 0.90) compared to ODA. The free-running simulation captures the main spatial structures but displays systematically larger temporal errors.
These findings demonstrate that ocean data assimilation is the most effective strategy for representing ENSO-like variability in NorCPM, while atmospheric nudging provides added value for lower-frequency modes. As a perspective, this work will be extended to investigate the impact of initialization strategies on atmospheric fields, as well as to explore SST variability at specific seasonal and regional scales.
How to cite: Moutachaouiq, K., Bari, D., Omrani, N.-E., and Nafiri, S.: Impact of Different Initialization Strategies on the Representation of Dominant SST Variability Modes in the NorCPM Coupled Climate Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17596, https://doi.org/10.5194/egusphere-egu26-17596, 2026.
EGU26-4441 | ECS | Posters virtual | VPS7
Intensified dominance of El Niño-like convection relevant for global atmospheric circulation variationsFri, 08 May, 14:54–14:57 (CEST) vPoster spot 4
Tropical convectionanomaly could serve as a crucial driver of global atmospheric teleconnections and weather extremes around the world. However, quantifying the dominances of convection anomalies with regional discrepancies, relevant for the variations of global atmospheric circulations, remains challenging. By using a network analysis of observation-based rainfall and ERA5 reanalysis datasets, our study reveals that El Niño-like convection is the most primary rainfall pattern driving the global atmospheric circulation variations. High local concurrences of above-normal rainfall events over equatorial central-eastern Pacific amplify their impacts, even though the most intense rainfall anomalies are observed near the Maritime Continent. Furthermore, we find that the impacts of El Niño- like convection will be tripled by the end of this century, as projected consistently by 23 climate models. Such “rich nodes get richer” phenomenon is probably attributable to the dipolar rainfall changes over theequatorial western-central Pacific. This study highlights the dominant role of El Niño- like convection on the global climate variations, especially under the future changing climate.
How to cite: Lin, S., Cai, F., Gerten, D., Yang, S., Jiang, X., Su, Z., and Kurths, J.: Intensified dominance of El Niño-like convection relevant for global atmospheric circulation variations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4441, https://doi.org/10.5194/egusphere-egu26-4441, 2026.
EGU26-1007 | ECS | Posters virtual | VPS7
Uncovering Causal Pathways of Agricultural Droughts using Climate and Vegetation SignalsFri, 08 May, 15:33–15:36 (CEST) vPoster spot 4
The impacts of climate change are directly visible in the intensification and increasing frequency of extreme climate events, such as floods and droughts. Since droughts result from complex, multivariate, and non-linear land-atmosphere interactions, understanding these relationships is crucial for developing impactful future measures to reduce or mitigate drought impacts. Many studies have performed correlation analysis among these variables, but (1) correlation does not fully resolve causality and complexity of drought occurrence, due to which (2) the nonlinear behavior of drought propagation remains poorly understood. This study applies conditional independence tests, such as the Peter and Clark Momentary Conditional Independence algorithm (PCMCI+), to identify and analyze the causal drivers of drought at different lag periods using multivariate time series data. We investigated the influence of seven important variables for drought incidences on drought-induced vegetation responses in the drought-prone Bundelkhand region of Central India as well as its seven districts (Banda, Chitrakoot, Hamirpur, Jalaun, Jhansi, Lalitpur, Mahoba) separately. We used ERA-5 land monthly data at 0.1˚ spatial resolution for climatic variables, including precipitation, temperature, evaporation, relative humidity, soil moisture, and biophysical variables as Leaf Area Index (LAI) and the Normalized Difference Vegetation Index (NDVI) which measures vegetation health via greenness used as a proxy for drought-induced vegetative stress, were taken from Peking University’s Global Inventory Modelling and Mapping Studies version 1.2 (PKU GIMMS) at 0.0833˚ spatial resolution. The analysis spans 32 years temporally from 1990 to 2021 and is carried out at a monthly scale by temporally aggregating the data through monthly averages.
For each variable, PCMCI+ measures partial correlation as a function of the maximum time delay and the significance threshold applied. Results here are presented for a maximum time lag of 3 months and a significance value of 0.05. At the investigated spatiotemporal scales, precipitation is the primary driver of soil moisture in Bundelkhand given a 3-month lag. Temperature primarily affects LAI with a 1-month lag, while accumulated warmth supports vegetation on longer timescales (3-month lag). Among atmospheric factors, relative humidity emerges as the strongest control on vegetation greenness and canopy development, influencing both NDVI, and LAI. The results also reveal important land-atmosphere feedback. The negative feedback between soil moisture, NDVI, and LAI indicates self-limiting plant growth under water stress 2-3-month lag. Vegetation contributes to surface cooling as expected, reflected in the inverse relationship between LAI and temperature. Furthermore, vegetation regulates evaporation, with NDVI affecting evaporation at a 2-month lag and LAI at a 3-month lag. Spatially, district-level patterns generally mirror the regional findings, except for Lalitpur, where fewer and different causal links were identified. Overall, the study shows that humidity-driven vegetation dynamics and multi-lag feedback between the land surface and atmosphere are central to drought evolution, highlighting the importance of explicitly representing these coupled processes in ecohydrological assessments. Future work should translate these identified causal pathways into next-generation drought monitoring and forecasting systems that incorporate lag-aware vegetation-climate interactions to improve drought early-warning capabilities and anticipatory mitigation planning.
How to cite: Sahu, H., Garg, P. K., Vijay, S., and Dasgupta, A.: Uncovering Causal Pathways of Agricultural Droughts using Climate and Vegetation Signals, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1007, https://doi.org/10.5194/egusphere-egu26-1007, 2026.
