The study area stretches roughly from 13 to 23 degrees east longitude and between 48 and 51 degrees north, encompassing an arc of mountains that begins with the Krušné hory and the Bohemian Forest in the west, passes through the Giant Mountains, Hrubý Jeseník and the Moravian-Silesian Beskids, and continues eastward across the Little and Great Fatra, the Low Tatras, the Tatras themselves and finally the East Slovak Mountains. All of the analysed terrain lies above 800 metres above sea level. The highest average elevation belongs to the Tatras at 1519.2 metres, while the Low Tatras cover the largest area at 1168 square kilometres. This west-to-east transect proved crucial, because it allowed the researchers to detect a striking spatial pattern in how quickly different ranges have warmed.

The data underpinning the analysis are formidable. Daily mean temperatures came from station measurements of the Czech and Slovak Hydrometeorological Institutes, which were subjected to rigorous quality control, homogenisation and gap-filling before being interpolated onto a 500 by 500 metre grid using regression kriging. Terrain variables such as altitude, slope orientation, roughness and convexity served as predictors, ensuring that the gridded temperatures reflected the complex topography of mountain landscapes. To characterise atmospheric circulation, the team turned to hourly geopotential height fields at the 850 hectopascal pressure level from the ERA5 reanalysis, aggregated into daily averages and classified into 27 distinct circulation types using an objective scheme based on flow strength, direction and vorticity.

The headline finding is unambiguous: every one of the ten mountain ranges has warmed significantly. Annual mean temperatures rose at rates between 0.28 degrees Celsius per decade in the Bohemian Forest and 0.44 degrees per decade in the East Slovak Mountains, with a pronounced west-east gradient in warming intensity. Seasonally, summer emerged as the fastest-warming season, with the Tatras recording 0.59 degrees per decade, while autumn showed the weakest trends. Comparing the periods 1961 to 1990 and 1991 to 2025, the difference in mean annual temperature ranged from 0.72 degrees in the Bohemian Forest to 1.36 degrees in the East Slovak Mountains, and a strong Spearman rank correlation of 0.85 confirmed that this eastward intensification of warming is statistically robust.

That longitudinal gradient is not an isolated curiosity. It aligns with broader evidence that northeastern Europe is warming faster than the southwest, and that inland and continental regions outpace coastal ones, a pattern the IPCC has documented at the global scale. The authors suggest that increasing thermal continentality may be at work, and that shifts in the position of cyclonic and anticyclonic dominance over Europe modulate the advection of maritime versus continental air masses. In practical terms, the mountains of eastern Slovakia are now living with a climate that is changing roughly twice as fast, in some measures, as that of their western Czech counterparts, with consequences for snow cover, growing seasons and the upper forest line that differ accordingly.

Circulation itself has not stood still. The classification revealed that anticyclonic types, the high-pressure regimes associated with sinking air, clear skies and persistent weather, have become more frequent, while cyclonic types have declined, particularly during spring and summer. Anticyclonic circulation increased significantly by 5.93 percent in winter and 4.81 percent in summer, driven largely by the AW type in winter and the A and ASE types in summer. Cyclonic types fell by 6.41 percent in spring, with the CSE and CS types showing the largest decreases. This shift toward high-pressure dominance is consistent with documented changes in North Atlantic-European circulation, including altered blocking activity and jet-stream behaviour, and may reflect the poleward expansion of the subtropical circulation belt.

To define extremes, the researchers calculated daily temperature anomalies relative to the climatological mean for each calendar day, removing the seasonal cycle. Extremely warm days were those exceeding the 95th percentile of anomalies, extremely cold days those falling below the 5th percentile, with thresholds fixed separately for each mountain range and season. Between the two periods, extremely warm days increased by roughly 2 to 5 percent across all ranges, with the largest relative increases in the Great Fatra, Little Fatra and Low Tatras, while extremely cold days declined by about 1 to 3 percent, most sharply in the Little Fatra and East Slovak Mountains. Every one of these changes was statistically significant.

The most innovative part of the study is its decomposition framework. The probability of an extreme event was expressed as the sum, over all circulation types, of the frequency of each type multiplied by the conditional probability of an extreme given that type. Changes between the two periods were then split into a dynamic effect, arising from shifts in how often each circulation type occurs, and a thermodynamic effect, arising from changes in how warm a given type tends to be. The result was decisive: for both warm and cold extremes, and in nearly every season and mountain range, the within-type thermodynamic effect dominated. The same weather patterns that once brought cold days now bring fewer of them, and the same patterns that once brought occasional heat now deliver warm extremes far more often.

The physical mechanisms behind this thermodynamic dominance are well understood. Under anticyclonic conditions, especially during blocking events and persistent ridging, clear skies and enhanced radiative forcing favour the development of extremely warm days, while warm-air advection plays a secondary role. Over land, these conditions are amplified by soil-moisture deficits, as persistent anticyclones promote precipitation shortfalls and enhanced evapotranspiration, further heating the surface. In winter and spring, the decline in extremely cold days has been linked to warming within anticyclonic and easterly types, plausibly connected to shrinking snow cover, where the snow-albedo feedback accelerates near-surface warming. Meanwhile, the significant summer increase in anticyclonic frequency likely contributed to warm extremes, even if its overall contribution remained secondary to the thermodynamic signal.

For the mountains themselves, the stakes are high. These ranges harbour rich biodiversity vulnerable to heatwaves, and previous research has tied extreme warmth to high-mountain rockfall in the Alps and to shifts in vertical climatic belts in the Tatras. The new findings suggest that future changes in temperature extremes will depend not only on how circulation evolves, which remains deeply uncertain in climate projections, but on continued warming within existing circulation regimes. The message from sixty-five years of Central European mountain data is stark and viral in its simplicity: it is not primarily the weather map that has changed, but the climate within which the weather map plays out, and thermodynamic warming has now overtaken circulation change as the dominant driver of temperature extremes in these iconic landscapes.

Subject of Research: Influence of atmospheric circulation on temperature extremes in Central European mountain ranges from 1961 to 2025

Article Title: Influence of atmospheric circulation on temperature extremes in mountainous regions of Central Europe during 1961–2025

Article References: Tichopád, D., Řehoř, J., Dolák, L., Láska, K., Zahradníček, P., & Štěpánek, P. (2026). Influence of atmospheric circulation on temperature extremes in mountainous regions of Central Europe during 1961–2025. Theoretical and Applied Climatology, 157(11), Article 695. https://doi.org/10.1007/s00704-026-06605-0

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06605-0

Keywords: atmospheric circulation, temperature extremes, Central Europe, mountain climate, climate change, anticyclonic circulation, ERA5 reanalysis, thermodynamic warming, Tatras, heatwaves, circulation types, warming trends

The research, led by Melek Candan İpek Şenbek of the General Directorate of State Hydraulic Works and Istanbul Technical University, together with Mikdat Kadıoğlu and Elçin Tan, examined thirty years of extreme precipitation events between 1995 and 2024. Using the ERA5 reanalysis dataset produced by the Copernicus Climate Change Service, the team identified 637 days on which rainfall exceeded the 90th-percentile threshold, a statistical marker that separates genuinely extreme days from ordinary wet weather. Every one of those days was then assigned to a circulation class through an objective, machine-learning-driven classification rather than subjective judgment.

The method rested on two well-established statistical techniques working in tandem. First, principal component analysis compressed a suite of dynamic atmospheric variables, including mean sea-level pressure, 500-hPa geopotential height, and wind components at both the 850-hPa and 500-hPa levels, into a small number of orthogonal patterns. By deliberately excluding thermodynamic fields such as temperature and humidity from the clustering input, the authors reduced the influence of seasonal heating cycles and forced the algorithm to focus on the shape of the circulation itself. The K-means algorithm was then applied to the principal component scores, partitioning the 637 extreme days into groups of meteorologically similar situations.

Choosing the right number of clusters is the central judgment call in any such classification, and the authors retained a five-cluster solution after weighing statistical metrics, the robustness of the result to different initializations, and, crucially, whether each cluster could be interpreted as a coherent physical mechanism. The payoff was a set of five regimes that read like a field guide to Black Sea flooding: a Dynamic Convective regime, a Thermal Convective regime, a Northerly Orographic regime, a Cyclonic-Frontal regime, and a Southwesterly Orographic regime.

The standout performer was Cluster 4, the Dynamic Convective regime. It was the most frequent class, produced the highest mean precipitation intensity at 9.59 millimeters per day, and delivered the single wettest event in the entire record at 37.29 millimeters per day. Its events clustered overwhelmingly in summer and autumn, when strong dynamic lifting combined with the region’s abundant moisture supply to squeeze extraordinary volumes of water from the air. The August 2021 floods that devastated parts of the Western Black Sea region, examined in earlier atmospheric studies, fall squarely within the kind of warm-season, dynamically driven environment this regime represents.

Close behind in intensity was Cluster 3, the Thermal Convective regime, with a mean of 9.26 millimeters per day and a similar concentration in the warm season. What set this class apart was its thermodynamic character: enhanced moisture availability and relatively high convective available potential energy, or CAPE, the measure of the fuel available to rising air parcels. Notably, the authors found that the highest CAPE values were spatially confined rather than representative of the whole domain, a reminder that convective instability in this region can be a localized phenomenon, igniting over warm coastal waters or heated inland terrain while the broader atmosphere remains comparatively modest.

The remaining three regimes demonstrate a finding with real consequences for flood forecasting: extreme rainfall does not require an unstable atmosphere. Cluster 1, the Northerly Orographic regime, averaged 8.57 millimeters per day and peaked in autumn, when moist northerly flow off the Black Sea collided with the coastal topography and was forced upward. Cluster 5, the Southwesterly Orographic regime, operated on the same principle from the opposite direction, transporting moisture on southwesterly winds during autumn and winter and wringing it out through terrain-induced ascent. Cluster 2, the Cyclonic-Frontal regime, was the weakest at 7.83 millimeters per day and concentrated in winter and spring, with large-scale ascent and frontal lifting doing the work that convection performs in summer. In all three, persistent moisture supply combined with mechanical or synoptic lifting proved sufficient to generate extremes even under weakly unstable conditions.

Statistical testing confirmed that these differences were not noise. Precipitation intensity differed significantly among the five clusters, with a Kruskal-Wallis H statistic of 28.20 and a p-value below 0.001. Yet when the authors examined the year-to-year frequency of each regime across the full 1995 to 2024 period, they found considerable interannual variability but no statistically significant long-term trend in any of the five classes. In other words, the atmospheric recipes for Black Sea extremes have remained broadly stable in their occurrence over three decades, even as individual events have continued to strike with damaging force.

That stability finding carries an important caveat for climate interpretation. The absence of a trend in regime frequency does not mean the hazards themselves are frozen in place; a warmer atmosphere holds more water vapor, and the intensity of rainfall within a given regime can change even if the regime appears just as often. The authors argue that their results should guide how regional climate projections are read: rather than treating extreme precipitation as a single aggregate variable, projections and seasonal assessments should consider each regime’s contrasting physical mechanisms separately, because a future with more frequent Dynamic Convective setups would pose very different risks than one with more Cyclonic-Frontal events.

For disaster-risk managers in one of Türkiye’s most flood-prone regions, the practical message is that the season and the synoptic signature together tell you what kind of threat is coming. A summer event flagged by high CAPE and dynamic lifting demands rapid-response flash-flood warning systems for steep catchments; an autumn northerly flow regime points to orographic enhancement along the coast and prolonged orographic rainfall on windward slopes; a winter frontal regime suggests broader-scale, longer-duration accumulation. By converting three decades of chaotic weather into five physically interpretable archetypes, the study offers forecasters and planners a structured vocabulary for a hazard that has too often seemed to arrive out of nowhere, and it demonstrates how objective clustering of reanalysis data can turn decades of atmospheric history into actionable knowledge.

Subject of Research: Synoptic classification of extreme precipitation events in the Western Black Sea Region of Türkiye

Article Title: Synoptic drivers of extreme precipitation in the western black Sea Region: a cluster-based classification (1995–2024)

Article References: İpek Şenbek, M. C., Kadıoğlu, M., & Tan, E. (2026). Synoptic drivers of extreme precipitation in the western black Sea Region: a cluster-based classification (1995–2024). Theoretical and Applied Climatology, 157(9), Article 598. https://doi.org/10.1007/s00704-026-06527-x

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06527-x

Keywords: extreme precipitation, Black Sea, synoptic climatology, K-means clustering, ERA5 reanalysis, orographic rainfall, convective storms, flood risk, Türkiye, climate variability, principal component analysis, atmospheric circulation

The researchers, led by Arnau Garcia Mesa, focused on six locations chosen to span a wide range of climatic behavior: Córdoba in southern Spain, Marrakech in Morocco, Lyon in France, Hannover in Germany, Belgrade in Serbia, and Stockholm in Sweden. These sites run the gamut from water-limited regimes, where soils are almost always dry in summer, to energy-limited regimes, where abundant moisture means the land surface and atmosphere interact very differently. For each location, the team assembled more than seven decades of data from the ERA5 and ERA5-Land reanalyses, covering daily maximum temperatures, large-scale atmospheric circulation fields, soil moisture at three depth levels, and seasonal carbon dioxide concentrations measured at NOAA’s Mauna Loa Observatory.

The machine learning framework at the heart of the study is a hybrid architecture the authors call the CombinedModel. Atmospheric data, which arrives as spatial maps of geopotential height at 500 and 200 hectopascals and sea-level pressure, is processed by a ConvNeXt convolutional neural network, a modern image-recognition architecture that had not previously been applied to driver quantification in this context. Local land-surface data and carbon dioxide values, which arrive as simple time series, are handled by a multilayer perceptron. The outputs of both branches are merged in a final classification network that decides, day by day, whether conditions resemble a hot extreme, defined as a daily maximum temperature exceeding the 90th percentile of the 1950–2000 climatology. Because extreme days are rare, the team used a weighted loss function to prevent the model from simply defaulting to predicting ordinary weather, and they trained an ensemble of twenty members to tame the randomness of network initialization.

But prediction alone was not the goal. The real innovation lies in the interpretability layer. Using SHAP values, short for SHapley Additive exPlanations, the researchers borrowed a technique from game theory that assigns each input feature a precise, additive share of the model’s output. Positive SHAP values push the model toward predicting an extreme; negative values push it away. Because the values are additive, they can be summed across grid points and variables to produce a global accounting of driver importance. The team computed these explanations only for the fifty percent most confident extreme predictions in the 2014–2024 test period, ensuring the attribution rested on predictions the network itself trusted.

The headline result is strikingly consistent: atmospheric circulation dominates everywhere. Across all six locations, circulation features accounted for 66 to 86 percent of the total explanatory power, with the geopotential at 500 hectopascals, the mid-tropospheric field that meteorologists use to spot blocking highs and ridges, contributing the most by a wide margin. This aligns with a growing body of work linking European heatwaves to persistent double jets over Eurasia, deep North Atlantic depressions, and Saharan warm-air intrusions, and it echoes a 2025 global analysis finding that 500-hectopascal geopotential is the dominant heat-extreme driver over most of the world’s land area. In other words, the large-scale shape of the atmosphere is the primary engine of a hot day, almost regardless of where you are.

The land surface, by contrast, tells a sharply regional story. Soil moisture’s share of the explanation follows a clear northward gradient: a negligible 0.2 percent in Marrakech, a moderate 9.4 percent in Córdoba, and a substantial 15.4 percent in Lyon, with similarly elevated values in the temperate and northern sites. The pattern makes physical sense. In already-arid Marrakech, summer soils are so consistently dry that year-to-year variability is small, leaving little for the land surface to modulate. In wetter transitional climates, however, a dry soil anomaly can dramatically amplify a heatwave by suppressing evaporation and shifting the surface energy balance toward sensible heating. The SHAP analysis captured this mechanism directly: for the shallowest soil layer, negative moisture anomalies were consistently associated with positive contributions to extreme-heat predictions, while deeper layers showed weaker and less robust signals, likely because neighboring soil layers are so strongly correlated that the model cannot cleanly separate their effects.

Carbon dioxide emerged as the third actor, and its role was revealing. The CO2 feature carried more than ten percent of the explanatory weight at most sites, and its importance was highest precisely where the yearly count of extreme days showed the strongest warming trend. By including CO2 explicitly, the framework controlled for the long-term anthropogenic signal without having to detrend the data, allowing a cleaner attribution of the physical drivers operating on daily timescales. The researchers stress that the explainability outputs represent the model’s interpretation rather than a direct measurement of reality, but the fact that the identified contributions reproduce well-established physical relationships lends the approach considerable credibility.

Robustness checks formed a major part of the study. When the team redefined extremes using the 80th percentile threshold, the same architecture recovered the same picture: circulation still dominated at 64 to 84 percent, and the northward gradient in land importance persisted, though soil moisture’s relative share shrank, suggesting that land-atmosphere feedbacks are not fully activated in milder heat events. A 95th-percentile model, hampered by too few extreme samples, proved unreliable and was set aside. The team also swapped reanalysis data for observations, using the E-OBS gridded temperature dataset and drought indices computed from it as soil-moisture proxies. The Standardized Precipitation Evapotranspiration Index, which incorporates evapotranspiration and thus better represents the surface water balance, reproduced the original results closely, while the precipitation-only Standardized Precipitation Index captured less of the land signal, a finding with practical implications for applying the framework to climate models, where soil layer definitions differ.

Two case studies brought the method down to the scale of individual disasters. For the August 2021 heatwave that pushed temperatures in Córdoba province to a scorching 47.6 degrees Celsius, the model attributed the event overwhelmingly to circulation, with positive SHAP values appearing precisely over the Iberian Peninsula where positive 500-hectopascal geopotential anomalies were located, a remarkable demonstration of spatial locality in the network’s reasoning. Intriguingly, CO2 ranked as the second most important feature even for this single event, hinting at a detectable anthropogenic fingerprint in an individual heatwave. The July and August 2018 heatwave in Hannover told a different story: the shallow soil-moisture layer played a much larger role, with SHAP values at times rivaling the circulation signal, consistent with the wet transitional regime of northern Germany, where the exceptional 2018 drought turned abundant soils into amplifiers of extreme heat.

The authors see their framework as more than an attribution exercise. Because it is data-driven yet physically interpretable, it could be applied to climate model output, to subseasonal-to-seasonal prediction systems, or to new regions, helping to diagnose where models capture or miss key feedbacks and to target climate risk assessments where they matter most. Future work, they note, should test whether the results hold across different network architectures and whether adding humidity fluxes or aerosol information sharpens the picture further. For now, the study offers a compelling demonstration that artificial intelligence, when forced to explain itself, can do more than forecast the weather; it can tell us, in numbers, why the weather turned deadly.

Subject of Research: Drivers of summer heat extremes in Europe and North Africa quantified with explainable machine learning

Article Title: Quantifying atmospheric and land drivers of hot temperature extremes through explainable Artificial Intelligence

Article References: Garcia Mesa, A., Palma, L., Donat, M., Materia, S., Gràvalos Talló, B., & Marcos Matamoros, R. (2026). Quantifying atmospheric and land drivers of hot temperature extremes through explainable Artificial Intelligence. Weather and Climate Dynamics, 7(3), 1709-1731. https://doi.org/10.5194/wcd-7-1709-2026

Image Credits: AI Generated

DOI: 10.5194/wcd-7-1709-2026

Keywords: heatwaves, explainable AI, SHAP values, atmospheric circulation, soil moisture, land-atmosphere coupling, climate change, CO2, machine learning, temperature extremes, ERA5, Europe

The research team confronted a long-standing puzzle. Central Europe sits in a climatological transition zone, wedged between the drying Mediterranean and the wetting Nordic countries, and different studies have reached contradictory conclusions about whether the region is becoming wetter or drier. Part of the disagreement stems from the metrics used. The researchers tackled this by employing two complementary drought indices computed over three-month accumulation windows: the Standardized Precipitation Index, which considers rainfall alone, and the Standardized Precipitation Evapotranspiration Index, which also accounts for atmospheric evaporative demand, the combined thirst of the atmosphere for water from soil and vegetation. The gap between these two measures turned out to be the key to the entire story.

To extend the record back to the pre-industrial era, the team harnessed three independent reanalysis datasets, each blending numerical weather models with historical observations. ERA5, the most modern and high-resolution product, assimilates satellites, aircraft, ships and station data but only reaches back to 1940. The Twentieth Century Reanalysis version 3 relies primarily on surface pressure observations and offers temporal consistency from 1836 onward, while the Modern Era Reanalysis incorporates proxy records, documentary sources and early instrumental measurements. Before trusting any of them, the researchers rigorously evaluated each dataset against century-long weather station records from De Bilt, Frankfurt am Main, Paris-Le Bourget and Uccle, using moving-window error metrics and correlation coefficients to identify the periods where each reanalysis could be considered reliable.

The evaluation revealed telling weaknesses. ERA5 showed spurious dryness in its earliest years, likely because upper-air temperature observations were scarce before 1946, while the Twentieth Century Reanalysis displayed excessive wetness before the late 1910s, when the number of assimilated Northern Hemisphere observations jumped sharply. ModE-RA proved dependable from 1844 onward. The final analysis therefore combined reliable windows from each dataset: 1947 to 2023 for ERA5, 1918 to 2015 for the Twentieth Century Reanalysis, and 1844 to 2008 for ModE-RA. Encouragingly, the datasets agreed well with one another, with correlation coefficients for drought-event identification reaching 0.79 between ERA5 and ModE-RA.

The historical perspective delivered some surprising verdicts. The most severe drought in the 180-year record was not the celebrated disaster of 2018 but the great drought of 1921, which persisted for an extraordinary fourteen months in the ModE-RA reconstruction, producing a severity more than double the threshold defining the worst ten percent of events. Comparable clusters of successive dry years to the 2011-2023 period occurred during 1857-1874 and 1947-1960, separated by conspicuously wet intervals in 1912-1920 and 1977-1988. This pronounced multidecadal oscillation means that any assessment of recent trends must reckon with the phase of natural variability, a caution the authors emphasize throughout.

Yet one finding stood out with unsettling clarity. When evaporative demand was included, the 2010s emerged as the driest decade since the pre-industrial era, with 35 drought months in the ERA5 record, nearly a third of the decade, and western Germany locally exceeding 40 drought months. When only precipitation was considered, that same decade looked entirely unremarkable, with just 21 drought months. This divergence is the fingerprint of warming. Since the 1990s, western Central Europe has warmed at 0.42 degrees Celsius per decade, faster than the global average, and the resulting rise in atmospheric evaporative demand has progressively offset the region’s increasing precipitation. In practical terms, droughts that once required a rainfall deficit now can be manufactured, at least in part, by heat alone.

The seasonal anatomy of this shift is equally revealing. Winter and autumn have become wetter, as robust precipitation increases outpace the modest warming-driven rise in evaporative demand during the energy-limited cold season. Summer, by contrast, shows the strongest increase in evaporative demand, which largely cancels out rainfall gains and produces drying in the water-balance index. Most strikingly, spring, historically an intermediate season, has recently tipped toward drying as well, with precipitation rising far below the roughly seven percent per degree expected from basic thermodynamic scaling while evaporative demand climbed more than twice as fast. Spring drying, the analysis shows, is a distinctly recent development, absent from the longer historical record.

To explain these patterns dynamically, the researchers turned to the atmosphere itself. They applied a k-means clustering algorithm to seasonal anomalies of 500 hectopascal geopotential height, the height of the pressure surface roughly five to six kilometers aloft, for every drought event across the Euro-Atlantic sector. Four recurrent circulation patterns emerged: a Baltic High, a British Isles High, a North-South Dipole combining high pressure over Northern Europe with low pressure to the south, and a European High centered directly over the study region. Each carries a distinct hydroclimatic signature. The Baltic High draws warm continental air from the southeast, inflating evaporative demand, while the British Isles High brings cool northerly flow and its droughts are driven almost purely by rainfall deficits. The North-South Dipole dominates winter droughts and, linked to cold easterly air masses, produces the weakest events.

The European High is the villain of the modern chapter. Droughts associated with this pattern, which combines strong anticyclonic subsidence, reduced cloud cover and the largest positive evaporative demand anomalies, are the most intense in the record, particularly over western Belgium and northern France, and they occur predominantly in spring. Crucially, the fraction of droughts tied to the European High has been rising across all reanalyses and both indices, with moderate to high statistical confidence, while associations with the British Isles High and the North-South Dipole have declined since 1947. This dynamical shift dovetails neatly with the observed hydroclimatic trends: the fading winter dipole aligns with winter wetting under increasingly positive North Atlantic Oscillation phases, and the ascending European High provides a coherent explanation for the emergence of spring drying.

The broader implication is that western Central Europe’s droughts are entering a new regime. Severity alone no longer tells the full story, because the 1921 benchmark can still be matched or exceeded by persistence, while the character of droughts, increasingly hot, evaporative and spring-rooted, has shifted beneath the apparent stability of the long-term water balance. The authors note that compound hot and dry conditions, which inflict impacts exceeding either hazard alone, are becoming the regional norm, and that multi-year droughts of the kind seen in 2018 are projected to intensify further as evaporative demand continues to climb. For the roughly 100 million people who live in this economic heartland of Europe, and for the croplands, grasslands and forests it supports, the message of the past 180 years is clear: the droughts of the future will not simply be repeats of the past, and monitoring systems that ignore the atmosphere’s growing thirst risk underestimating the threat.

Subject of Research: Long-term drought variability and associated atmospheric circulation patterns in western Central Europe since 1844

Article Title: Droughts in western Central Europe and associated atmospheric circulation patterns since 1844

Article References: Neimry, E., Goosse, H., & Jonard, M. (2026). Droughts in western Central Europe and associated atmospheric circulation patterns since 1844. Weather and Climate Dynamics, 7(3), 1759-1778. https://doi.org/10.5194/wcd-7-1759-2026

Image Credits: AI Generated

DOI: 10.5194/wcd-7-1759-2026

Keywords: drought, western Central Europe, atmospheric circulation, evaporative demand, climate change, reanalysis, SPEI, anticyclone, European High, multidecadal variability, spring drying, hydroclimate

The focus of the study is the North Pacific westerly jet, a narrow band of strong winds that blows from west to east in the upper troposphere at midlatitudes. The jet is not merely a curiosity of atmospheric dynamics; it acts as a guiding current for weather systems, steering storm tracks, shaping the position of surface pressure patterns, and influencing temperature and precipitation across East Asia, including Japan. When the jet sits in its correct position, the models that depend on it can represent regional climate with reasonable skill. When it drifts, the errors propagate. A jet displaced to the south or north of its observed position can shift storm tracks, alter the transport of heat and moisture, and distort the simulated response of East Asian climate to greenhouse gas forcing. Understanding what pushes the jet out of place is therefore a matter of practical consequence for anyone who relies on model projections in this densely populated region.

The research team approached the problem by exploiting a distinctive feature of the Coupled Model Intercomparison Project Phase 6, or CMIP6, the international framework through which research institutions around the world contribute coordinated climate model experiments. CMIP6 includes two families of simulations that are directly relevant here. In the first, fully coupled simulations, the atmosphere and ocean evolve together, and the sea surface temperature emerges from the model’s own physics. In the second, atmosphere-only simulations, the ocean is not free to evolve; instead, the atmosphere is driven by observed sea surface temperatures prescribed from historical records. By comparing the position of the westerly jet across these two types of experiments, the researchers could isolate the influence of the sea surface itself, because the atmospheric models and their physics remain the same while the treatment of the ocean surface changes.

The comparison produced a strikingly consistent result. In 34 of the 35 models examined, the westerly jet over the North Pacific sat farther south in the coupled simulations, where sea surface temperature was generated by the models themselves, than in the atmosphere-only simulations, where observed sea surface temperatures were prescribed. This near-unanimous pattern across a diverse international ensemble is significant because it suggests a shared, structural problem rather than a quirk of any individual model. If only a handful of models showed the displacement, it might be attributed to idiosyncratic parameter choices or numerical schemes. The fact that virtually the entire ensemble shifts the jet southward when the ocean is simulated points to a common source, and the most obvious candidate is the systematic sea surface temperature bias that coupled models share.

Establishing a correlation between simulated sea surface temperatures and jet position was only the first step. To demonstrate that the temperature biases actually cause the southward displacement, the researchers turned to targeted atmospheric model experiments. In these experiments, the biases in sea surface temperature diagnosed from the coupled climate models were added directly onto the observed sea surface temperatures, and the atmospheric model was then run with this artificially biased ocean surface. The result was decisive: the experiments reproduced the southward shift of the westerly jet. This is a clean causal demonstration. The atmospheric model, its physics, and its initialization were held fixed, and the only change was the pattern of sea surface temperature. When the biases were imposed, the jet moved. When they were absent, it stayed where observations say it should be.

The team then refined the analysis by asking where, geographically, the responsible biases reside. The sea surface temperature errors in climate models are not uniform across the basin; they vary in sign and magnitude from one region to another, with some areas running too cold relative to observations and others too warm. By imposing the biases separately in different regions, the researchers could test the contribution of each. These regional experiments revealed that biases in the northwestern Pacific play a particularly important role in shifting the westerly jet southward. This finding is physically meaningful, because the northwestern Pacific lies upstream of and adjacent to the jet’s entrance region over East Asia, where the atmosphere is especially sensitive to the thermal contrast between the ocean surface and the continent. Errors in the surface temperature field in this sensitive zone can reshape the large-scale temperature gradients that the jet depends on for its position and strength.

The mechanism connecting sea surface temperature to jet position runs through the atmosphere’s fundamental dynamics. The midlatitude westerly jets are thermally driven winds, sustained by the meridional temperature gradient between the warm tropics and the cold pole. Anything that alters the distribution of temperature in the lower atmosphere alters that gradient, and with it the vertical wind shear and the latitude at which the jet core settles. A sea surface temperature bias in the northwestern Pacific changes the heating of the air column above it, modifies the temperature gradient, and through the response of the atmospheric circulation nudges the jet away from its observed latitude. Because the jet then organizes storm tracks and eddy activity around itself, the displacement is not a transient perturbation but a self-consistent rearrangement of the circulation that persists for as long as the underlying bias does.

The implications extend well beyond the North Pacific. The westerly jet is closely tied to weather and climate in East Asia, including Japan, where it modulates the East Asian winter monsoon, the passage of extratropical cyclones, and the distribution of precipitation through the year. A model whose jet is systematically displaced southward will tend to place weather systems in the wrong places, and those placement errors will be baked into projections of how the region’s climate changes over the coming decades. The study’s central conclusion is that sea surface temperature biases play an important role in biases in the position of the North Pacific westerly jet, which means that a substantial fraction of the circulation error in these models traces back to the ocean surface rather than to the atmospheric physics itself.

This attribution carries a practical message for the modeling community. Improving the representation of sea surface temperature in climate models, whether through better simulation of ocean currents, mixed-layer processes, air-sea heat exchange, or the cloud fields that control the surface energy balance, could therefore lead to a more accurate representation of the atmospheric circulation affecting Japan and East Asia. In an era when regional climate information is increasingly demanded by governments, insurers, and infrastructure planners, narrowing the gap between simulated and observed circulation is one of the most direct routes to more reliable projections. The study also illustrates the value of the CMIP6 experimental design itself: the pairing of coupled and atmosphere-only simulations, combined with targeted sensitivity experiments, gives scientists a powerful diagnostic toolkit for tracing model errors to their sources.

More broadly, the work is a reminder that the reliability of climate projections is built from the ground up, one bias at a time. A temperature error of a degree or two at the ocean surface may seem trivial against the scale of the Pacific, but the atmosphere integrates such errors, amplifies them through circulation dynamics, and expresses them as displaced jet streams and shifted storm tracks. By demonstrating that 34 of 35 CMIP6 models share this vulnerability, and by pinpointing the northwestern Pacific as the critical region, the Ehime University team has given model developers a concrete target and given users of climate projections a clearer sense of where uncertainty in East Asian circulation originates. The path to trustworthy future climate scenarios runs through the present-day simulation, and studies of this kind map that path with increasing precision.

Subject of Research: The influence of sea surface temperature biases on the position of the North Pacific westerly jet in CMIP6 climate models

Article Title: Can errors in sea surface temperature shift the westerly jet?

Article References: Can errors in sea surface temperature shift the westerly jet?. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: sea surface temperature, climate models, westerly jet, North Pacific, CMIP6, model bias, atmospheric circulation, East Asia, Japan, Geophysical Research Letters, Ehime University, storm tracks

The research, published in Atmospheric and Oceanic Science Letters, examined more than six decades of records, drawing on observations and atmospheric reanalysis data spanning 1961 to 2024. Rather than treating all heatwaves as a single category, the team separated them into three types: events that only push daytime temperatures to extremes, events that only produce anomalously hot nights, and the compound events in which both days and nights remain dangerously hot. Comparing the three across China, the researchers found that compound events are particularly concentrated over the Yangtze River Basin, the densely populated and agriculturally vital region that follows the country’s longest river.

One of the study’s most striking findings concerns rhythm. Compound heatwaves over the basin, the analysis showed, display a pronounced 10–30-day periodicity, a subseasonal cycle often referred to in atmospheric science as quasi-biweekly variability. Daytime-only and nighttime-only heatwaves are less tightly coupled to this rhythm. In other words, the events that deny residents any nighttime relief are not random occurrences scattered through summer; they tend to arrive on a recognizable subseasonal clock, driven by slowly evolving patterns in the large-scale atmospheric circulation.

That rhythmic structure matters for forecasting. Variability on the 10–30-day scale sits in the sweet spot of subseasonal-to-seasonal prediction, the forecast range that lies beyond the two-week limit of reliable weather prediction but shorter than seasonal outlooks. If forecasters can identify the precursors of the compound-heatwave cycle, they may gain a valuable head start in warning hospitals, power grid operators, and agricultural planners that a multi-day stretch of unrelenting heat is becoming more likely.

The study goes beyond identifying the rhythm and reconstructs the physical sequence that produces it. The researchers describe a two-stage process. In the first stage, about a week before a compound heatwave strikes, the region experiences increased upward motion and rainfall. That may sound counterintuitive for a heat event, but the wetter soils left behind by this pre-heatwave precipitation turn out to be a crucial ingredient. Moisture stored in the ground becomes fuel for the atmosphere in the days that follow.

In the second stage, as the event approaches, an atmospheric wave pattern propagates eastward toward the basin. This wave favors anticyclonic conditions over the Yangtze region, the kind of large-scale sinking motion that suppresses cloud formation. With fewer clouds overhead, more solar radiation reaches the surface, intensifying daytime heating. At the same time, the wetter soil supports stronger evapotranspiration, the process by which plants and soil release water vapor into the air. Southwesterly winds add a third ingredient, transporting warm and moist air into the region from lower latitudes.

The combined effect is a lower atmosphere that is simultaneously warm and humid, a state that sustains extreme heat through both halves of the day. During daylight hours, strong incoming solar radiation drives surface temperatures upward. After sunset, the abundant water vapor in the boundary layer, supplied by local evapotranspiration and by moisture transported on southwesterly flow, traps heat near the ground and slows radiative cooling, keeping nighttime temperatures anomalously high. Humid air also raises the heat index, making hot nights feel even more oppressive and dangerous to human health than dry heat of the same temperature.

“Compound heatwaves are not simply daytime heat continuing into the night,” said Prof. Yitian Qian, corresponding author of the study. “They result from the coordinated evolution of atmospheric circulation, radiation, soil moisture and moisture transport over a period of several days.” That framing represents a shift in how scientists think about these events. Rather than viewing a compound heatwave as a daytime extreme that merely lingers, the study presents it as the end product of a multi-day coupling between the sky and the land, in which rainfall a week earlier helps set the stage for humid, sleepless nights to come.

The Yangtze River Basin is a particularly consequential place for this kind of research. Home to hundreds of millions of people and a cornerstone of China’s rice production, the region has repeatedly experienced severe summer heat in recent years, including episodes that strained power supplies and threatened crops. Because compound heatwaves concentrate there more than elsewhere in China, according to the new analysis, understanding their subseasonal precursors carries direct implications for protecting both urban populations and food systems in one of the world’s most economically important river valleys.

The practical payoff of the study lies in early warning. The researchers note that changes in rainfall, soil moisture and large-scale circulation before heatwave onset may provide useful early signals of compound heat extremes. A week of unusually wet weather followed by the arrival of an eastward-moving wave pattern and building anticyclonic conditions could, in principle, be recognized in forecast models as a compound-heatwave signature well before the first extreme day arrives. Soil moisture observations, satellite estimates of evapotranspiration, and monitoring of quasi-biweekly circulation anomalies could all feed into such an early-detection framework.

There is also a broader scientific agenda ahead. The authors indicate that future work will examine how tropical and midlatitude atmospheric variability contribute to these events, and whether the precursor signals identified here can genuinely improve subseasonal prediction skill. If they can, the payoff would extend beyond the Yangtze: many of the world’s major heatwave-prone regions feature similar interactions between soil moisture, moisture transport and slowly evolving circulation patterns. For now, the study offers a clear message about the anatomy of sleepless heat. The nights that offer no relief are not accidents of a single hot afternoon, but the culmination of a week-long collaboration between rain-soaked ground, clearing skies, and rivers of warm, wet air converging over the basin.

Subject of Research: Subseasonal mechanisms sustaining day–night compound heatwaves over the Yangtze River Basin

Article Title: Why do some heatwaves last through the night in the Yangtze River Basin?

Article References: Why do some heatwaves last through the night in the Yangtze River Basin?. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: compound heatwaves, Yangtze River Basin, subseasonal variability, quasi-biweekly oscillation, soil moisture, evapotranspiration, anticyclone, moisture transport, atmospheric circulation, nighttime heat, early warning, Atmospheric and Oceanic Science Letters

The urgency of the problem was underscored during the pre-monsoon season of 2026, when temperatures climbed above 46 degrees Celsius across many parts of India. Northern and central regions of the country endured prolonged and intense heat waves, while compound heatwave-PM2.5 pollution events during the pre-monsoon season became increasingly frequent. The convergence of scorching temperatures and elevated particle concentrations during this period drew renewed attention from public health authorities and atmospheric scientists alike, raising a fundamental question: why are these compound extreme events becoming more common, and what mechanisms are driving their formation?

To answer that question, the research team, led by Professor Meng Gao of the Department of Geography at Hong Kong Baptist University, examined pre-monsoon heat-PM2.5 compound extreme events across India between 2017 and 2024. The study combined three complementary lines of evidence: ground-based observations, satellite measurements, and atmospheric chemistry simulations. This integrated approach allowed the researchers to track not only when and where heat and pollution overlapped, but also the physical and chemical processes that linked them. Their analysis revealed that the frequency of compound extreme events increased markedly after 2020, a shift that stands out clearly against the baseline of the preceding years.

The scale of the overlap during individual episodes is striking. In April 2022, more than 70 percent of severe PM2.5 pollution episodes across northern India occurred simultaneously with heat waves. That figure illustrates how tightly the two hazards have become coupled in the region. Rather than alternating between a heat crisis and an air quality crisis, populations in northern India increasingly face both at once, a pattern that public health researchers consider substantially more dangerous because extreme heat amplifies the physiological stress imposed by polluted air, stressing cardiovascular and respiratory systems simultaneously.

At the heart of the new findings is the role of a specific large-scale circulation feature: an anomalous anticyclonic circulation over northern India. Anticyclones, characterized by sinking air and suppressed vertical mixing, are well known for trapping heat near the surface and clearing skies of clouds, which allows more solar radiation to reach the ground and drives temperatures even higher. The study found that this anomalous anticyclone strengthened heat conditions over northern India while simultaneously generating anomalous southeasterly winds that transported additional pollution precursors into the region. In other words, a single meteorological pattern was working on both sides of the compound-extreme equation at once, intensifying the heat while feeding the chemical ingredients needed to build particle pollution.

The chemical consequences of these conditions proved to be just as important as the meteorological ones. The combination of extreme heat and an influx of pollution precursors accelerated atmospheric chemical processes, substantially enhancing the formation of secondary organic aerosols, or SOA, a major component of PM2.5. Unlike primary particles emitted directly from vehicles, industry, or biomass burning, secondary aerosols are manufactured in the atmosphere itself, as gaseous precursor compounds undergo chemical reactions and condense into particulate form. The atmospheric chemistry simulations conducted by the team showed that SOA production increased by approximately 2.3 times during compound events, contributing significantly to the elevated particle concentrations observed under extreme heat.

This finding carries significant implications for how scientists and policymakers understand air quality in a warming world. Secondary organic aerosol formation is highly sensitive to temperature, radiation, and the availability of reactive precursor gases, all of which are modulated by the large-scale circulation patterns described in the study. As heat waves intensify under climate change, the chemical environment of the boundary layer changes in ways that can amplify particle production even if emissions of primary pollutants remain constant. The Indian case demonstrates that climate variability can influence air quality through this pathway, meaning that emission control strategies alone may not fully capture the future trajectory of pollution extremes in densely populated regions.

Lead author Huibin Dai emphasized that the study reframes how compound extremes should be investigated. Most studies have focused on heat waves and air pollution separately, Dai noted, but this research shows that large-scale atmospheric circulation can simultaneously intensify heat and promote secondary aerosol formation, creating favorable conditions for compound heat-PM2.5 extremes. According to Dai, the results highlight an important pathway through which climate variability can influence both weather extremes and air quality, linking two research communities that have often worked along parallel but separate tracks.

The broader context makes these findings particularly consequential for India. The country is home to some of the world’s most densely populated urban corridors, and its pre-monsoon season has historically been associated with severe heat stress on agriculture, water resources, and human health. The demonstration that the same circulation anomalies that drive dangerous heat can also supercharge the atmospheric chemistry that produces PM2.5 suggests that the health burden of future warming may be compounded in ways that standard heat wave or air quality forecasts do not capture. As climate warming is expected to increase the occurrence of extreme heat, these coupled meteorological and chemical processes may further raise the risk of compound environmental extremes across South Asia.

Looking ahead, the research team plans to extend its analysis into the future. The next step, Dai said, is to investigate how compound heat-PM2.5 extremes will evolve under future climate change and to quantify their impacts on human health. The ultimate goal of the work, according to the researchers, is to better understand the mechanisms behind these compound events and to provide scientific evidence that can support early prevention, risk reduction, and climate adaptation strategies. The study was supported by grants from the National Natural Science Foundation of China and the Research Grants Council of the Hong Kong Special Administrative Region, China, and its findings arrive at a moment when the overlap of heat and pollution is emerging as one of the defining environmental health challenges of a rapidly warming century.

Subject of Research: Compound heatwave and PM2.5 pollution extremes driven by atmospheric circulation over India

Article Title: Climate-driven atmospheric circulation fuels dangerous heat-PM2.5 extremes over India

Article References: Climate-driven atmospheric circulation fuels dangerous heat-PM2.5 extremes over India. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: India, heat waves, PM2.5, compound extremes, atmospheric circulation, anticyclone, secondary organic aerosols, air pollution, climate change, pre-monsoon, atmospheric chemistry, public health

The motivation for the work lies in one of the most persistent puzzles in climate science. Observations show that since 1979 the Arctic has warmed nearly four times faster than the global average, a rate so extreme that it has reshaped the temperature contrast between the pole and the equator. Because that temperature gradient is the engine that drives the midlatitude jet stream, the fast-moving river of air that steers storms and separates cold polar air from warmer subtropical air, many scientists have suspected that Arctic amplification must be altering the position, strength, and waviness of the jet. Yet the evidence linking the two has remained contested, with some studies pointing to connections with extreme cold outbreaks and prolonged droughts, and others finding the signals too weak or too model-dependent to be meaningful.

Part of the difficulty is that Arctic amplification is not driven by a single cause. Rising sea surface temperatures warm the planet broadly, while the loss of reflective sea ice exposes dark ocean water that absorbs sunlight and warms the Arctic locally. Previous work has shown that sea ice loss plays a central role in polar warming, but disentangling its effects from those of simultaneous ocean warming requires experiments in which each factor is varied in isolation. That is precisely what Saurral and Kucharski set out to do. Using an intermediate-complexity atmospheric model, a class of models that strips away some of the computational complexity of full climate models while retaining the essential physics of the atmosphere, they ran a suite of simulations in which sea surface temperatures and sea ice concentrations were modified separately and together, allowing them to isolate the fingerprint of each forcing.

The results reveal a striking division of labor between the two drivers. Warming sea surface temperatures dominate the temperature response at low and midlatitudes, spreading warmth across the subtropics and temperate zones, while the loss of sea ice is the primary control on how much the Arctic itself warms. In other words, the global ocean sets the background of the warming world, and the cryosphere determines how extreme the polar amplification becomes on top of it. Neither factor alone can reproduce the observed magnitude of polar amplification: when the researchers imposed sea ice loss on its own, the model overestimated Arctic warming, and when they imposed sea surface temperature changes on their own, the model underestimated it. Only when both forcings were applied together did the simulation produce a realistic picture of the amplified Arctic that observations describe.

Perhaps the most consequential finding concerns the jet stream. The two forcings produced circulation responses that push in opposite directions. Changes in sea surface temperatures drove a poleward shift of the atmospheric jet, consistent with the widening of the tropical circulation and the expansion of the Hadley cell that many studies have documented under global warming. Sea ice loss, by contrast, induced changes in the jet that ran counter to that shift. When the two forcings were combined in a single experiment, their interaction produced a reduced and less robust atmospheric response than either forcing alone, suggesting that the competing influences partially cancel each other out. This cancellation helps explain why different modeling studies, which may weight these forcings differently, have reached such different conclusions about how the midlatitude circulation responds to Arctic change.

The physical logic behind the opposing responses is rooted in how each forcing alters the temperature gradient that sustains the jet. Broad ocean warming raises temperatures most strongly in the tropics and subtropics, steepening the equator-to-pole contrast in the upper troposphere and encouraging the storm tracks and the jet to migrate poleward. Sea ice loss does the opposite at the polar end of the gradient: by warming the lower Arctic atmosphere, it weakens the contrast between the pole and the midlatitudes near the surface, a change that tends to pull the circulation in the other direction. The new experiments show that in a medium-complexity model these two effects do not simply add up, and that their interference is a genuine feature of the coupled response rather than noise.

These findings arrive in the middle of a long-running scientific controversy. An influential hypothesis proposed in 2012 suggested that Arctic amplification would make the jet stream wavier, producing more persistent weather patterns and more frequent extremes such as cold winters and heat waves in the midlatitudes. Subsequent research, including large coordinated model intercomparisons under the Polar Amplification Model Intercomparison Project, has generally found the circulation response to sea ice loss to be robust but weak, and several studies have concluded that Arctic amplification has little influence on midlatitude climate variability. The new work does not settle that debate, but it offers a physical framework for interpreting it: the midlatitude response to climate change reflects the combined effect of global processes, carried by ocean warming, and regional processes, carried by sea ice loss, and the two can work against each other.

The study also carries a methodological message. In an era when climate science increasingly relies on enormous high-resolution simulations, Saurral and Kucharski demonstrate the continuing value of medium-complexity models. Because such models are computationally inexpensive, researchers can run large ensembles of targeted experiments, varying one boundary condition at a time, and thereby isolate mechanisms that would be difficult to separate in comprehensive coupled models where ocean, ice, and atmosphere evolve together. The authors argue that this experimental clarity is exactly what is needed to interpret polar amplification as the joint product of global and regional processes, and to understand why the atmospheric response to Arctic change has proven so elusive in more complex systems.

The implications extend to how scientists project the future. If sea surface temperature changes and sea ice loss produce opposing circulation fingerprints, then the net response of the jet stream and the storm tracks will depend on the balance between them, and that balance may shift as the climate continues to warm. Observations have already documented trends in the jet streams that some researchers have linked to tropical warming, and the new results suggest that any such trend represents the residual of competing influences rather than the effect of a single driver. For regions such as the Mediterranean, where earlier work by some of the same authors has connected sea ice loss to drought conditions, understanding this balance could sharpen assessments of regional climate risk.

What the study ultimately provides is a cleaner conceptual map of a tangled problem. Arctic amplification emerges only when global ocean warming and regional sea ice loss act together, the two leave distinct and partly opposing marks on the midlatitude circulation, and their interaction dampens the overall atmospheric response. As the Arctic continues to transform, experiments of this kind, run in deliberately simplified models where every forcing can be switched on and off at will, may prove to be among the most powerful tools for reading the fingerprints that a changing pole is leaving on the weather of the middle latitudes.

Subject of Research: The separate and combined effects of sea surface temperature warming and Arctic sea ice loss on midlatitude atmospheric circulation in an intermediate-complexity global atmospheric model

Article Title: Arctic amplification fingerprints on the midlatitude circulation in a medium-complexity global atmospheric model

Article References: Saurral, R. I., & Kucharski, F. (2026). Arctic amplification fingerprints on the midlatitude circulation in a medium-complexity global atmospheric model. Climate Dynamics, 64(10), Article 415. https://doi.org/10.1007/s00382-026-08373-z

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08373-z

Keywords: Arctic amplification, sea ice loss, sea surface temperatures, jet stream, midlatitude circulation, climate dynamics, medium-complexity model, polar warming, Hadley cell, storm tracks, climate modeling, atmospheric circulation

The research examined the summers of 1980 through 2025, a 46-year window long enough to capture both year-to-year variability and slower structural change. Diem applied principal component analysis to sea-level pressure fields from the ERA5 global reanalysis, a state-of-the-art dataset produced by the European Centre for Medium-Range Weather Forecasts that blends millions of observations with a physical model of the atmosphere. Principal component analysis is a statistical technique that compresses many correlated variables, in this case pressure values across a grid of locations, into a small number of independent patterns that explain most of the variance. The result is a set of circulation modes that describe how the subtropical high strengthens, weakens, and shifts from one summer to the next.

What makes this study distinctive is its treatment of the high’s western edge. Earlier work often summarized the WNASH with a single metric, such as the longitude of its westernmost ridge or its overall intensity averaged across the basin. But the anticyclone is not a smooth, symmetrical blob. It frequently breaks into multiple ridges, with separate lobes of high pressure over the western Atlantic and the Gulf of Mexico. Diem constructed indices specifically designed to track the positions and separation of these western ridges, then tested how well each representation of the circulation explained precipitation recorded at 1,747 rain gauges scattered across the eastern and central United States.

The answer was unambiguous: the structure of the western ridges matters more than the coarse basin-wide picture. Distinct modes of WNASH and western-ridge variability produced contrasting, regionally heterogeneous precipitation responses, with the strongest and most spatially coherent relationships appearing across the Southeast and portions of the Atlantic seaboard. This makes physical sense. The western flank of the subtropical high is where the clockwise circulation around the anticyclone funnels warm, moist Atlantic and Gulf air toward the continent, feeding the thunderstorm complexes that deliver much of the region’s summer rain. When the ridge positions shift, the moisture conveyor shifts with them, and the gauges record the consequences.

The mechanics of that conveyor are well established in the literature. The Great Plains low-level jet, a river of air a few hundred meters above the ground that surges northward at night, draws its strength partly from the pressure gradient established by the Atlantic anticyclone. Mesoscale convective systems, the organized clusters of thunderstorms that can span several states, depend on that moisture supply. Sea-breeze circulations along the Carolina and Florida coasts, which can trigger afternoon downpours, are also modulated by the position of the high. By reshaping all of these processes, the western ridges of the WNASH act as a kind of hidden thermostat on summertime hydroclimate, one that conventional indices had blurred into the background.

Perhaps the most striking finding is that the high itself has been reorganizing. Over the 1980 to 2025 period, Diem documented a structural change characterized by decreasing separation between the western Atlantic and Gulf of Mexico ridge positions. In other words, the two lobes of the anticyclone have been drifting closer together, altering the geometry of the moisture pathways into the continent. This kind of reorganization is exactly the sort of response climate scientists expect from a warming world, since subtropical anticyclones respond to greenhouse forcing and sea-surface warming in ways that can differ between ocean basins. The study’s trend analyses and comparisons between different epochs of the record allowed these slow structural shifts to be separated from ordinary year-to-year noise.

Crucially, the western-ridge indices outperformed the broader circulation modes when it came to explaining recent precipitation increases across portions of the Southeast. That is a practical result with real forecasting implications. If the geometry of the ridges tracks summer rainfall better than traditional measures, then seasonal outlooks and climate model diagnostics could be sharpened simply by changing how the circulation is described. It also refines the interpretation of earlier studies that linked southeastern rainfall variability to the high’s westward displacement, suggesting that those relationships were real but incompletely characterized, because a single ridge position cannot capture the behavior of a multi-lobed anticyclone.

Yet the study delivers an equally important caution. Substantial residual precipitation increases across the Midwest and Northeast remained unexplained after accounting for WNASH variability, indicating that recent hydroclimatic change across the eastern and central United States cannot be attributed to the Atlantic high alone. The Midwest’s summer rainfall is heavily influenced by soil-moisture feedbacks, convective systems rooted in local land-atmosphere coupling, and moisture streaming in from the Gulf of Mexico and beyond, processes only partially governed by Atlantic circulation. A warming atmosphere also holds more water vapor, roughly seven percent more per degree Celsius, which intensifies heavy rainfall regardless of where the high pressure sits. Disentangling the circulation contribution from the thermodynamic one is one of the central challenges of modern hydroclimate science, and this study draws a clearer boundary around what the WNASH can and cannot explain.

The methodological approach deserves attention as well. Combining rotated principal component analysis of pressure fields, which isolates physically meaningful circulation patterns, with targeted ridge indices and a dense network of ground-based gauges gives the analysis both dynamical rigor and observational grounding. Multiple linear regression modeling allowed the contributions of different circulation modes to be weighed against one another, while inter-epochal comparisons revealed how those relationships have themselves evolved over the decades. The precipitation data used in the study are publicly archived, and the reanalysis products are freely available, making the work reproducible and extensible by other research groups.

The broader significance extends beyond the United States. Subtropical anticyclones shape the climates of every continent bordering the great ocean basins, from the Azores High over Europe to the systems governing the Mediterranean, China, and the West African monsoon. Understanding how their internal structure, not just their average strength, controls regional rainfall is a step toward better projections of where water will be plentiful and where it will become scarce as the planet warms. For the tens of millions of Americans living from the Gulf Coast to the Great Lakes, the message of this research is that the summer rain on their roofs is choreographed, in large part, by the shifting geometry of a high-pressure dome a thousand kilometers out at sea, and that learning to read that geometry more precisely may be one of the keys to anticipating the water cycle of the coming decades.

Subject of Research: Influence of western North Atlantic subtropical high variability on summer precipitation in the eastern and central United States

Article Title: The western North Atlantic subtropical high and summer precipitation across the eastern and central United States

Article References: Diem, J. E. (2026). The western North Atlantic subtropical high and summer precipitation across the eastern and central United States. Climate Dynamics, 64(10), Article 436. https://doi.org/10.1007/s00382-026-08400-z

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08400-z

Keywords: North Atlantic subtropical high, summer precipitation, climate variability, ERA5 reanalysis, sea-level pressure, southeastern United States, Great Plains low-level jet, hydroclimate, Climate Dynamics, atmospheric circulation, precipitation trends, western ridge

The central question motivating the study was deceptively simple. China and India lie in different climate regimes, separated by the Tibetan Plateau and governed by distinct monsoon and circulation systems. Does greening in these two regions produce similar climate effects? And when both regions green at the same time, is the combined response simply the sum of two independent effects? The answer to both questions, according to the simulations, is no. Greening in China generally cools the local climate and brings more rainfall to southern and northeastern China, while greening in India tends to produce warming and reduced rainfall. When the two greening signals are imposed together, the resulting climate feedbacks spread across more than half of the global land surface, producing cooler and wetter conditions in southern China, cooler conditions in western Eurasia, and warmer conditions in northern North America.

“Greening does not necessarily produce the same climate response everywhere,” said corresponding author Miao Yu, Professor at Nanjing University of Information Science and Technology. “What matters is not only how much water vegetation releases into the atmosphere, but also where that moisture goes and how it changes clouds and surface heating.” This distinction lies at the heart of the study. Plants exchange water with the atmosphere through transpiration, and when leaf area increases, the total flux of moisture from land to air rises. But the fate of that moisture—whether it condenses into clouds above the source region, falls as local rain, or is swept away by prevailing winds—determines whether the net effect is cooling or warming, wetter or drier.

In the simulations of Chinese greening, the increased vegetation enhances the transfer of water from the land surface into the boundary layer of the atmosphere. Over southern China, this additional moisture favors cloud formation. The clouds act as a radiative shield, reflecting and absorbing incoming solar energy before it reaches the ground. The reduced surface energy input helps cool the air near the ground, while the same moisture supply supports increased rainfall. In other words, the greening sets off a self-reinforcing loop in which more vegetation means more atmospheric moisture, more moisture means more clouds, and more clouds mean both cooler temperatures and more precipitation—a pathway that amplifies the climate benefits of restoration in that region.

India follows a fundamentally different pathway. Although vegetation there also releases more moisture into the atmosphere, much of that water vapor is transported away by the large-scale circulation instead of condensing into clouds and rain over the subcontinent itself. With fewer clouds forming overhead, more solar energy reaches the surface, temperatures rise, and rainfall decreases. The contrast illustrates a crucial principle of land-atmosphere interaction: the same biophysical process—enhanced evapotranspiration—can yield opposite climate outcomes depending on how regional atmospheric dynamics handle the moisture. In one regime the added water vapor becomes clouds and rain; in another it becomes an export commodity, leaving the source region drier and hotter than before.

The most intriguing results emerged when the researchers simulated simultaneous greening in both countries. Rather than producing a simple additive effect, the combined greening yielded responses that differ qualitatively from either region acting alone. Southern China became more consistently cooler and wetter, while western Eurasia experienced cooling. These remote effects arise because vegetation changes alter not only local energy and moisture budgets but also the large-scale atmospheric circulation. Changes in atmospheric heating can reshape winds high above the surface and influence planetary-scale atmospheric waves that carry climate signals across entire continents. In the simulations, simultaneous greening modified the East Asian and Central Asian jet streams and favored the movement of colder polar air toward Eurasia, providing a physical mechanism for the distant cooling.

“The atmosphere connects regions that may appear far apart,” said lead author Min Xiao, a graduate student working with Professor Miao Yu at Nanjing University of Information Science and Technology. “Vegetation change in one region can reinforce, weaken, or even reverse the climate effects caused by vegetation change elsewhere.” This finding carries significant implications for how scientists and policymakers evaluate restoration projects. If the climate impact of greening in China depends in part on whether India is greening at the same time, then assessments that consider each region in isolation may misestimate the true consequences of ongoing and planned land-use change.

The nonlinearity identified in the study is particularly important. Moisture transport, cloud feedbacks, and atmospheric circulation interact in complex ways, so the climate response to simultaneous greening is not simply the sum of two independent effects. Feedbacks that amplify each other in one configuration can cancel out in another, and circulation changes triggered by one greening region can redirect moisture pathways from the other. This means that the rapidly greening landscapes of Asia—changing concurrently under coordinated policy and agricultural expansion—may be producing climate fingerprints today that no single-region analysis would predict. The study’s simulations suggest these combined fingerprints already extend across more than half of the global land area.

The findings highlight a broader lesson for large-scale ecological restoration and land management. Greening can influence far more than carbon storage or the climate directly above the restored land. Its effects travel through the atmosphere, redistributing energy and moisture and reshaping climate in regions that may be thousands of kilometers from the nearest newly planted tree. For governments investing billions in afforestation and vegetation restoration, the message is that such projects are, in effect, climate interventions whose reach extends well beyond national borders and whose sign—cooling or warming, wetting or drying—depends on regional atmospheric context.

The authors are careful to note the limitations of their work. The study relies mainly on a single land-atmosphere climate model, and model-dependent representations of convection, cloud processes, and circulation dynamics could influence the simulated remote responses. Further studies using multiple models will be important for confirming the teleconnection patterns and quantifying their uncertainty. Even so, the research marks a meaningful step toward understanding how the planet’s two largest greening regions interact with the climate system—and it underscores that in an atmosphere without borders, the climate consequences of changing the land surface are genuinely global in scope.

Subject of Research: Climate responses to vegetation greening in China and India simulated with a land-atmosphere climate model

Article Title: Greening in China and India reshapes climate both locally and far away

Article References: Greening in China and India reshapes climate both locally and far away. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: vegetation greening, China, India, land-atmosphere interactions, evapotranspiration, cloud feedbacks, jet streams, atmospheric circulation, afforestation, climate modeling, teleconnections, Advances in Atmospheric Sciences