The research team, led by Mohamed Darrag of the National Research Institute of Astronomy and Geophysics in Cairo together with Shuanggen Jin of Henan Polytechnic University and colleagues in Spain, North Macedonia, and Egypt, focused on a deceptively simple question: where, exactly, does the tropics end? In cartography the answer is fixed at roughly 23.5 degrees north and south, the lines where the sun can appear directly overhead. In climatology, however, the tropical edge latitudes are dynamic boundaries that migrate with the seasons and respond to climate forcing. Under a warming atmosphere, these edges have been shifting poleward across the globe, a phenomenon known as tropical belt expansion that has been robustly detected using satellites, radiosondes, and reanalysis datasets since the Intergovernmental Panel on Climate Change flagged it in its Fifth Assessment Report.

To pin down the tropical edge over the Mediterranean, the researchers turned to the tropopause, the boundary layer between the churning troposphere below and the stratified stratosphere above. In the tropics the tropopause sits high and cold; toward the poles it drops steeply. The team applied two independent metrics to ERA5 reanalysis data at a quarter-degree resolution. The first, the tropopause drop method, defines the tropical edge as the latitude where tropopause height falls 1.5 kilometers below its tropical average. The second, the tropopause gradient method, locates the latitude of the maximum meridional gradient in tropopause height. Both methods told the same story: the tropical belt has been widening, expanding poleward at approximately 0.14 degrees per decade according to the drop method and 0.27 degrees per decade according to the gradient method, with uncertainty ranges of roughly 0.05 and 0.06 degrees respectively.

Underpinning this expansion is a dramatic rise in the tropopause itself. The lapse rate tropopause height over the Mediterranean climbed by approximately 80.58 meters per decade over the study period, a rate the authors note is higher than global estimates, which have ranged from roughly 39 to 66 meters per decade in earlier work. The explanation lies in the region’s exceptional warming: the Mediterranean has warmed by about 1.40 degrees Celsius since the late nineteenth century, exceeding the global mean rise of 1.10 degrees. As greenhouse gases warm the troposphere and expand it vertically, the tropopause is pushed upward. The study found the strongest tropopause height trends, reaching 266.50 meters per decade, in the eastern Mediterranean near 30 degrees north, a zone the authors attribute partly to the influence of the South Asian monsoon system. Tropopause temperature, meanwhile, fell by 0.12 kelvin per decade, showing a strong negative correlation of minus 0.86 with height, a classic fingerprint of greenhouse-driven change.

The geography of the expansion is strikingly uneven. Both definitions of the tropical edge place the boundary farther poleward in the eastern Mediterranean than in the west, a longitudinal contrast the researchers link to the region’s position between the subtropical high-pressure systems of the Hadley circulation and the mid-latitude westerlies, to stronger land-sea thermal gradients in the east, and to sea surface temperature variability. The eastern Mediterranean also shows more pronounced poleward occurrences of the tropical edge, consistent with its exposure to tropical-extratropical teleconnections. Seasonally, the tropical edge behaves as expected, migrating northward in boreal summer, when the median reached about 38.83 degrees for the drop method and about 41.00 degrees for the gradient method, and retreating equatorward in winter, with a seasonal swing of roughly five to ten degrees of latitude.

To connect these shifting boundaries to the climate people actually experience, the team correlated the tropical edge positions with five key variables: surface temperature, lower tropospheric temperature averaged from the surface to five kilometers, upper tropospheric temperature from five kilometers up to the tropopause, precipitation, and the Standardized Precipitation Evapotranspiration Index, a widely used drought indicator. Surface temperature showed abundant positive correlations with the tropical edge, peaking at about 0.34 in the eastern Mediterranean, meaning warmer surface conditions tend to accompany northward displacement of the tropical boundary. Upper tropospheric temperature correlated even more strongly, with coefficients reaching 0.55, while precipitation showed predominantly negative correlations in the eastern Mediterranean, dynamically consistent with the poleward migration of the Hadley circulation’s descending branch, which pushes subtropical dry zones toward the basin.

The most sophisticated part of the analysis employed singular value decomposition, a statistical technique that extracts dominant coupled patterns of covariability between two spatial fields. The leading mode captured the majority of the shared variability, explaining between 56.48 and 86.32 percent of the covariance depending on the variable, with the strongest temporal correlation of 0.67 found between the tropical edge and upper tropospheric temperature. This identifies the thermal structure of the upper troposphere as the atmospheric component most tightly coupled to tropical belt fluctuations. The second coupled mode, though smaller, revealed something equally important: localized spatial structures showing pronounced positive coupling between the tropical edge and both surface and lower tropospheric temperatures specifically over the eastern Mediterranean, indicating that tropical expansion is associated with enhanced warming concentrated in that subregion.

The trends in the underlying climate variables reinforce the picture of a basin under mounting stress. Monthly average surface temperature over the Mediterranean rose by approximately 0.48 kelvin per decade, with the steepest increases in the east. Lower tropospheric temperature climbed by 0.36 kelvin per decade, while upper tropospheric temperature rose more slowly at 0.09 kelvin per decade. Total precipitation declined by about 0.25 millimeters per decade, and the drought index fell by 0.070 per decade, with the strongest drying signals in the northern Mediterranean between 40 and 50 degrees north. The vertical temperature structure showed warming throughout the troposphere, peaking at 0.50 kelvin per decade near 45 to 50 degrees north, paired with stratospheric cooling exceeding minus 0.50 kelvin per decade, the contrasting thermal responses that scientists regard as a signature fingerprint of human-induced climate change.

What makes the study particularly valuable is its methodological consistency. The two independent definitions of the tropical edge produced nearly identical correlation patterns and coupled modes, suggesting the identified relationships are robust rather than artifacts of how the tropical boundary is measured. The findings arrive amid projections that Mediterranean precipitation could decline by 10 to 30 percent by the end of the century and that the eastern Mediterranean and Middle East are warming roughly twice as fast as the global average. For a region whose waters are already warming four times faster than the global norm for coastal seas, whose agriculture, water resources, and biodiversity face intensifying pressure, and where desertification is driven by falling soil moisture and rising evaporative demand, the message is sobering. The tropics are not merely an abstract latitude line on a map; their expanding edge is now measurably entangled with the temperature, rainfall, and drought patterns of one of the world’s most vulnerable climate hotspots.

Subject of Research: Tropical belt expansion and its linkage to Mediterranean climate variability from 1980 to 2022

Article Title: Tropical belt expansion and its impacts on climate variability in the Mediterranean from 1980 to 2022

Article References: Tropical belt expansion and its impacts on climate variability in the Mediterranean from 1980 to 2022. (n.d.). https://doi.org/10.5194/acp-26-14031-2026

Image Credits: AI Generated

DOI: 10.5194/acp-26-14031-2026

Keywords: tropical belt expansion, Mediterranean climate, tropopause height, tropical edge latitude, Hadley circulation, ERA5 reanalysis, singular value decomposition, surface temperature, precipitation trends, SPEI drought index, climate change hotspot, eastern Mediterranean

The foundation of the work is a carefully quality-controlled dataset of daily precipitation observations from 24 meteorological stations spanning the years 2010 to 2024. Before any modeling could begin, the authors subjected these records to rigorous homogeneity testing, using classical statistical procedures such as the Alexandersson standard normal homogeneity test and the Pettitt change-point test to ensure that the trends they detected were genuine features of the climate rather than artifacts of station relocations or instrument changes. What emerged from this screening was striking: a statistically significant and spatially coherent shift in the precipitation regime centered around the year 2020, with a domain-wide mean annual precipitation anomaly of minus 20.5 percent relative to the baseline decade. In other words, the region has recently entered a markedly drier state, and the drying is not confined to isolated locations but sweeps across the entire coastal domain.

To make sense of the region’s spatial complexity, the researchers turned to unsupervised machine learning. Using K-Means clustering, an algorithm that partitions data points into groups based on their similarity, they divided the study domain into three physically interpretable subregions: Coastal, Inland, and Mountainous. The validity of this partition was assessed with silhouette analysis, a standard diagnostic that measures how well each station fits its assigned cluster compared with neighboring clusters. The resulting zones are not arbitrary statistical constructs; they correspond to real gradients in topography, moisture availability, and storm behavior, with the Taurus range acting as a formidable orographic barrier that shapes how moisture from the Mediterranean is converted into rainfall.

At the heart of the study sits an explainable machine learning classifier built on XGBoost, a gradient-boosted decision tree system that has become a workhorse of modern environmental prediction. The classifier was trained to distinguish extreme precipitation days from ordinary ones, using a rich set of candidate predictors drawn from multiple sources: ERA5-Land reanalysis data, satellite-derived products, and large-scale teleconnection indices from NOAA. Crucially, the model was validated temporally, meaning it was tested on data from periods separate from its training window, a practice that guards against the inflated skill scores that plague many machine learning applications in climate science. The classifier achieved an area under the receiver operating characteristic curve, or AUC-ROC, of 0.835, a strong diagnostic performance that indicates genuine predictive skill rather than memorization.

But the real breakthrough lies in what the model could explain. Using TreeSHAP, a game-theoretic attribution method that quantifies each variable’s contribution to every individual prediction, the authors interrogated the black box and found that near-surface relative humidity is the overwhelmingly dominant thermodynamic trigger for extreme precipitation events, with a mean absolute SHAP value of 0.557. Even more revealing was the shape of the relationship: the model identified a non-linear activation threshold near 65 to 70 percent relative humidity, below which extreme rainfall becomes unlikely regardless of other conditions. This sharp threshold is consistent with Clausius-Clapeyron constraints, the fundamental thermodynamic law dictating that warmer air can hold roughly seven percent more water vapor per degree Celsius of warming, and that heavy precipitation requires a saturated lower atmosphere to draw upon.

The SHAP analysis also uncovered a second, spatially structured insight: the humidity control on extreme precipitation intensifies with elevation. In the mountainous subregion along the Taurus range, the coupling between low-level moisture and extreme rainfall is stronger than along the coast, a signature of orographic enhancement in which moist air masses are forced upward over terrain, cool adiabatically, and release their water as intense, localized downpours. This finding matters for practical reasons as much as scientific ones, because it tells water managers and emergency planners that the same atmospheric moisture can produce very different flood outcomes depending on where it intersects the topography, and that mountain communities face a distinct and amplified exposure.

To quantify how often such extremes can be expected to recur, the authors applied Generalized Extreme Value modeling, the statistical framework that underpins modern flood and rainfall frequency analysis. Rather than relying solely on the relatively short station records, they fitted GEV distributions to a 44-year historical baseline from the CHIRPS satellite-gauge blended precipitation dataset, which provides the long record needed to constrain estimates of rare events. The results reveal a severe concentration of hazard along the eastern inland corridor of the study domain, and a domain-mean 100-year return level of 102.4 millimeters per day. That figure represents the daily rainfall total that, on average, should be exceeded only once per century, and it provides a concrete benchmark for the design capacities of dams, culverts, and urban drainage systems across the region.

The final and perhaps most consequential component of the pipeline looks forward. Drawing on the Coupled Model Intercomparison Project Phase 6, or CMIP6, the authors examined projections under two shared socio-economic pathways: SSP2-4.5, an intermediate emissions scenario, and SSP5-8.5, a high-emissions trajectory. By the period 2041 to 2060, both scenarios indicate robust declines in the frequency of extreme precipitation events, by 19.5 percent under SSP2-4.5 and 12.1 percent under SSP5-8.5. Taken together with the observed drying trend since 2020, these projections point toward a transitional shift in the region’s hydroclimate, one that the authors characterize as a regime of fewer but potentially more intense convective precipitation events.

This apparent paradox, in which total rainfall declines while the most intense downpours persist or even intensify, is one of the most actively debated features of Mediterranean climate change. The Eastern Mediterranean and Middle East have been identified as a prominent climate change hotspot, and previous research has documented how reduced large-scale circulation and diminishing overall precipitation can coexist with a thermodynamic intensification of the heaviest events, which draw on a warmer, moister boundary layer when the right synoptic triggers do arrive. The findings from coastal Türkiye fit squarely within this emerging picture, and they carry a sobering implication: infrastructure designed around historical rainfall frequencies may be simultaneously overbuilt for the new average conditions and underbuilt for the extremes that remain.

What distinguishes this study is less any single result than the architecture that connects them. By weaving together multi-source data fusion, spatial regionalization, explainable classification, extreme value analysis, and scenario-based projection, the authors demonstrate a template that other data-sparse, hazard-exposed regions could readily adopt. The explainability layer is particularly significant for the credibility of machine learning in climate applications, because it transforms the model from an opaque predictor into a scientific instrument that recovers physically meaningful relationships, such as the humidity activation threshold and its orographic amplification, that forecasters and policymakers can actually interrogate and trust. For the coastal communities of Eastern Mediterranean Türkiye, the message is twofold: the climate is already measurably drier than it was a decade ago, and the floods that do arrive will demand respect, because the atmosphere’s capacity to deliver them in concentrated bursts remains fully intact.

Subject of Research: Explainable machine learning and extreme value analysis of extreme precipitation drivers, recurrence, and CMIP6 projections in coastal Eastern Mediterranean Türkiye

Article Title: Explainable machine learning and extreme value analysis for precipitation projections in coastal Eastern Mediterranean Türkiye

Article References: Deniz Cüvitoğlu, F., & Cüvitoğlu, A. (2026). Explainable machine learning and extreme value analysis for precipitation projections in coastal Eastern Mediterranean Türkiye. Theoretical and Applied Climatology, 157(10), Article 637. https://doi.org/10.1007/s00704-026-06560-w

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06560-w

Keywords: extreme precipitation, explainable machine learning, XGBoost, TreeSHAP, Generalized Extreme Value analysis, CMIP6, SSP2-4.5, SSP5-8.5, Eastern Mediterranean, Türkiye, Clausius-Clapeyron, orographic enhancement