The Jarilla fire was ignited by lightning on August 12, 2025, and officially began the following day in Cáceres, northern Extremadura. It spread with extreme behavior across the surface, through the canopy and underground, while flying embers produced secondary spot fires. The fire was declared under control on August 24 and fully extinguished on September 28, although satellite detections of active fire had ceased after August 21. Merged observations from three VIIRS satellites showed a rapid advance from August 13 through 17, a period when the fire traversed most of the ultimately affected area, followed by slower expansion along the eastern flank and in the north-northeastern sector as conditions moderated.

Hot, dry conditions were already established before ignition. Between August 5 and 11, daily maximum temperatures ranged from 35.6 to 38.9°C, minimum relative humidity fell between 14.7% and 21.2%, and maximum vapor pressure deficit, a measure of the atmosphere’s drying power, reached 4.5 to 5.8 kPa. The Fire Weather Index was in the extreme-danger class on every day except August 9, when it was classified as very high. These conditions coincided with a pre-fire Sentinel-2 composite showing mean vegetation vigor, measured by the Normalized Difference Vegetation Index, of 0.53. At the same time, the mean Normalized Difference Infrared Index, used here as an indicator of moisture in living vegetation, was only 0.05 and fell to -0.20 at the fifth percentile. The fire therefore encountered both abundant fuel and severe vegetation water stress.

The episode’s most hazardous phase ran from August 12 through 17. Across those six days, temperature reached 38.8°C, relative humidity dropped to 14.8%, and vapor pressure deficit peaked at 5.9 kPa. The Fire Weather Index remained in its extreme class and reached 70.3 on August 15. From 1 p.m. to 8 p.m. during the active phase, temperature exceeded 30°C and relative humidity remained below 30% in every hour, satisfying two of the three conditions in the “three thirties” rule for extreme fire behavior. The third condition was not met because the maximum hourly wind recorded during August 12–24 was only 15.8 km/h. The weather was therefore extreme primarily through heat and atmospheric desiccation rather than exceptionally strong synoptic wind.

Wind nevertheless played an important organizing role. The hourly circulation had two distinct regimes. North-easterly flow was the most frequent, but it was generally weak and occurred mainly at night. A south-to-south-south-westerly flow dominated the hottest afternoons and the period of greatest fire advance, appearing during approximately 92% of daylight hours from 1 p.m. to 8 p.m. This flow coincided with the lowest humidity and highest vapor pressure deficit and pushed the advancing front toward the northeast, matching the reconstructed southwest-to-northeast progression. The steering direction rotated clockwise as the event continued, helping explain the fire’s later shift toward the eastern flank. Because these data came from one ERA5 reanalysis grid cell at 0.25° resolution, they represent the broader synoptic flow rather than potentially stronger local winds channeled by slopes and valleys.

The terrain was rugged, with elevations spanning 355 to 2,369 meters inside the fire perimeter. Mean slope was 21.2 degrees, the maximum was 78.5 degrees, and slopes of at least 15 degrees covered 72.6% of the burned area. About 36.1% of the perimeter had an aspect favorably aligned with the south-south-westerly wind; combining that alignment with slopes of at least 15 degrees produced 4,778 hectares, or 27.5% of the fire. The researchers used a 5-meter national elevation model to identify propagation corridors, defined as pixels where slope was at least 15 degrees, wind-slope alignment fell within 60 degrees of the source wind, and vegetation vigor exceeded the within-fire median. With the south-south-westerly flow, these corridors covered 2,376 hectares, or 13.7% of the burned area. A northeast-wind version covered 1,924 hectares, or 11.1%.

Post-fire satellite measurements showed that severity was extensive well beyond these corridors. The mean differenced Normalized Burn Ratio, or dNBR, across the perimeter was 545, and 93.6% of the area, or 16,212 hectares, registered some degree of burn. Moderate-high and high severity together covered 10,890 hectares, equivalent to 62.9% of the fire. Inside the south-south-westerly propagation corridors, mean dNBR was 664.6 and 75.0% of the area fell in the combined high-severity classes. Outside them, mean dNBR was 525.4 and 61.0% met the same threshold. The corridors were therefore consistently associated with comparatively severe burning, but they contained only 1,783 hectares, or 16.4%, of all high-severity area. Most of that area—9,107 of 10,890 hectares—was outside the mapped corridors.

The contrast remained stable when the researchers varied the thresholds used to define the corridors. Across combinations of 10-, 15- and 20-degree slopes, wind alignments of plus or minus 45 to 75 degrees, and vegetation-vigor cutoffs at the 40th, 50th or 60th percentile, corridor extent ranged from 1,727 to 2,961 hectares, or 10% to 17.1% of the perimeter. Mean dNBR within the corridors remained between 659 and 669, compared with 521 to 531 outside. The size and precise boundaries of the corridors depended on the chosen thresholds, but their relatively elevated severity did not. Results using the northeast flow were similar, and a progressive filtering exercise showed that adding slope, fuel continuity and wind alignment to the whole perimeter increased the share classified as high severity from 62.9% to 67.3%, 71.7% and 75.0%, respectively.

These findings do not establish that the three factors acted independently, and the study has important limitations. It examines one fire retrospectively, uses a single meteorological grid point, treats the principal driving wind as a static south-south-westerly direction even though it rotated during the event, and infers fire behavior indirectly from post-fire dNBR rather than measuring front speed or intensity. The dNBR severity classes used in the analysis had not been validated with field observations for this fire, and their transferability depends on vegetation, pre-fire conditions, image timing and methodology. The authors also caution that the corridor mapping is a decision-support concept derived from one event, not an operationally validated tool. Nevertheless, within the evidence available, the spatial pattern is consistent with a broader pattern: during an extreme atmospheric drought, dry and connected fuels allowed high severity across most of the landscape, while wind-aligned slopes and fuels locally intensified the burn without determining where severe burning occurred.

Subject of Research: Weather, terrain and fuel controls on the 2025 Jarilla wildfire in western Spain

Article Title: How do weather, topography and fuel condition drive the extreme behavior of a Mediterranean megafire? A case study of the 2025 Jarilla wildfire (western Spain)

Article References: Hernández-Sánchez, L., & Francos, M. (2026). How do weather, topography and fuel condition drive the extreme behavior of a Mediterranean megafire? A case study of the 2025 Jarilla wildfire (western Spain). Frontiers in Forests and Global Change, 9, Article 1953360. https://doi.org/10.3389/ffgc.2026.1953360

Image Credits: AI Generated

DOI: 10.3389/ffgc.2026.1953360

Keywords: Jarilla wildfire, Mediterranean megafire, burn severity, vapor pressure deficit, fire weather index, wind-slope alignment, vegetation fuel continuity, Sentinel-2, ERA5 reanalysis, VIIRS fire detection, weather, topography

Rewilding, a conservation approach that gained its name in the 1980s, aims to restore self-willed ecosystems in which natural processes — including stochastic disturbance and the activity of wild grazers — operate with minimal human control. The classic formulation proposed by Soulé and Noss emphasized large protected cores, connecting corridors, and keystone carnivores, but modern European projects have broadened the idea to include the passive reversion of farmland. At Arger Fen, fields taken out of arable production between 2004 and 2014 were simply left alone: no fertilizer, no livestock during the study period, no active conservation management. Succession was allowed to run its course, converting former cropland into a mosaic of rough grassland and scrub.

The four study fields differed sharply in their terrain. Two were almost perfectly flat, with mean slope gradients of just 0.6 percent, while the other two sloped from very weak to moderately steep, reaching gradients of up to 10.9 percent and a vertical relief of 27 meters. All had been plowed and cropped before 2014, producing maturing grassland swards comparable to other ex-arable rewilding sites in Suffolk. The researchers walked 400-meter W-shaped transects through each field three times between May and August 2021, recording adult Orthoptera both visually and by ear, since stridulating males of most local species call at frequencies within human hearing range.

Six species were recorded, all widespread in Suffolk: the meadow grasshopper Pseudochorthippus parallelus, Roesel’s bush-cricket Roeseliana roeselii, the long-winged conehead Conocephalus fuscus, the field grasshopper Chorthippus brunneus, the lesser marsh grasshopper Chorthippus albomarginatus, and the dark bush-cricket Pholidoptera griseoaptera. Overall density reached 1,221 adult grasshoppers per hectare — more than five times the 234 adults per hectare recorded at Black Bourn Valley, a flatter rewilding site 30 kilometers to the north. The comparison hints that topographic variety itself may boost carrying capacity for these insects.

The statistical patterns were striking. There was strong evidence that C. brunneus, the field grasshopper, was far more abundant on slopes — it made up 27 percent of adult detections in sloping fields but only 1 percent in flat ones. The long-winged conehead showed the opposite pattern, strongly preferring flat ground, where tall coarse grasses such as cock’s-foot grow in the moist soil at the base of slopes. Species diversity, measured with the Shannon-Wiener index, was significantly higher in the sloping fields, and linear regression confirmed that species richness and diversity both increased with slope gradient, with very strong evidence for the diversity relationship.

What makes slopes so attractive to some species? The answer appears to lie partly in the activities of wild lagomorphs. Brown hares and rabbits grazed the sloping fields far more heavily than the flat ones — droppings and burrow excavations were both significantly denser on slopes, and regression showed very strong positive relationships between slope gradient and rabbit excavations. This grazing and digging created patches of exposed soil, which the field grasshopper needs for egg-laying and basking. Bare ground warms quickly in sunshine, offering the hot microclimates that grasshopper eggs and nymphs require for development.

The study also suggests an intriguing movement pattern. Nymphs of all species were more abundant in flat fields, yet adult C. brunneus concentrated on slopes. The authors propose that nymphs hatch on flatter ground and then move uphill as they mature, seeking out the lagomorph-grazed bare soil patches for oviposition — a lifecycle choreography shaped by the interaction between topography and wild grazing. Early-instar grasshoppers are known to favor short grassland near hatching sites before dispersing into taller swards as they develop.

Not every finding pointed the same way. The meadow grasshopper and Roesel’s bush-cricket showed moderate evidence of preferring flat ground, and the two bush-crickets that have expanded their British ranges northward with climate change — R. roeselii and C. fuscus — were early colonists of the flat post-arable grassland, where tall vegetation offers shelter and oviposition sites. Meanwhile, an unexpected player entered the story: ash dieback disease. In Hullback’s Grove, a small stand of ash saplings killed back by the fungus Hymenoscyphus fraxineus maintained an open mosaic of grass and scrub that would otherwise have shaded out as the canopy matured. All six Orthoptera species were detected in this diseased hillside patch, illustrating how stochastic natural disturbances — even devastating ones — can generate habitat heterogeneity that conservation managers would struggle to replicate.

The authors acknowledge limitations. Only two fields of each type were studied, the surveyor’s ear cannot detect the conehead’s ultrasonic 30-kilohertz call without equipment, and dropping counts may have been easier to spot in short grazed vegetation than in tall moist sward. Still, the combined visual-acoustic method detected all six species, and the technique is considerably less time-intensive than automated acoustic detectors for low-frequency callers.

The broader message is one for anyone planning a rewilding scheme: topography matters. Flat ex-arable land tends toward an open layer of fine-leaved grasses with a warm microclimate, but limited coarse grasses for feeding, whereas undulating terrain with slopes creates a patchwork of microclimates, soil drainage regimes, and vegetation structures. The authors postulate that rewilding schemes on arable land may be particularly effective when they incorporate topographic undulations — both flat areas and hillsides — to promote the greatest diversity of Orthoptera. At Arger Fen, the heathy acid grassland of the historic Leavenheath common, enclosed after 1817, appears to be re-establishing on the slopes, with the near-threatened annual common cudweed already returning. If that trajectory continues, the field grasshopper populations there — currently 542 to 700 adults per hectare on slopes — may climb toward the 1,500 to 3,100 adults per hectare seen on long-established heathland, a quiet testament to what happens when the land is simply allowed to be itself, bumps and all.

Subject of Research: Influence of topographic heterogeneity on Orthoptera diversity and abundance in a rewilding scheme on former arable land

Article Title: Topographic heterogeneity influences diversity and abundance of Orthoptera in a rewilding scheme

Article References: Gardiner, T., & Casey, D. (2024). Topographic heterogeneity influences diversity and abundance of Orthoptera in a rewilding scheme. Journal of Orthoptera Research, 33(2), 255-266. https://doi.org/10.3897/jor.33.119897

Image Credits: AI Generated

DOI: 10.3897/jor.33.119897

Keywords: rewilding, Orthoptera, grasshoppers, bush-crickets, topography, slope gradient, Arger Fen, Suffolk, lagomorph grazing, ash dieback, biodiversity, habitat heterogeneity

The setting itself is remarkable. The reserve spans 737,088 hectares of federally protected forest bounded on the east by the Iriri River, a clear-water tributary of the Xingu. No roads or trails reach the study area; access requires roughly two days of navigation along the Xingu and Iriri rivers from Altamira. This remoteness has long kept botanists away, even though recent remote-sensing analyses based on airborne LiDAR data and deep learning had flagged the region as harboring extensive areas of high canopy palm cover. The new field survey confirms that prediction on the ground, and it does so with numbers that would impress any tropical ecologist.

Walking the transect on foot at roughly one kilometer per hour, at least two experienced observers censused a continuous twenty-meter-wide belt, partitioned into one hundred contiguous sampling units of twenty by fifty meters. In total they recorded 1,506 adult palm individuals belonging to eighteen taxa, seventeen identified to species level and one morphospecies to genus. Four species dominated overwhelmingly: Attalea speciosa with 527 individuals across 85 plots, Euterpe longibracteata with 267, Geonoma baculifera with 263, and Euterpe oleracea with 105. Together these four accounted for more than three-quarters of every palm counted. Species accumulation curves and multiple richness estimators, including Chao, Jackknife, and Bootstrap, converged on eighteen species, indicating that the sampling effort captured nearly the entire local palm flora.

Attalea speciosa, the babassu palm, reached an average density of 52.7 individuals per hectare and local peaks of 270 adult individuals per hectare within a single plot. Its hyperdominance is not merely a botanical curiosity. Palms can constitute up to a quarter of stems exceeding ten centimeters in diameter in some tropical forests, and biomass models developed specifically for palms suggest their carbon fixation capacity may be nearly a third higher than estimates based on dicotyledonous trees. In a region flagged by satellite for exceptional palm abundance, documenting which species dominate and where is directly relevant to understanding forest carbon dynamics in the eastern Amazon.

To understand why palms clustered where they did, the researchers extracted environmental data for the centroid of each sampling unit. From the TOPODATA digital elevation model, derived from Shuttle Radar Topography Mission data at thirty-meter resolution, they obtained altitude, slope, relief, exposure, and terrain shape. From HydroSHEDS they calculated the distance to the nearest perennial stream. And from CBERS-4A satellite imagery they derived the normalized difference vegetation index, or NDVI, a proxy for vegetation greenness and forest structure that ranged from 0.597 to 0.662 along the transect. Crucially, the team also recorded in the field the presence or absence of igarapés, the shallow, narrow, slow-moving streams typical of Amazonian environments that are generally invisible in satellite imagery.

The statistical architecture of the study was rigorous. A Redundancy Analysis linked community composition to the continuous environmental variables, with Variance Inflation Factors confirming no problematic multicollinearity. Species richness was modeled with a Gaussian General Linear Model for continuous predictors and analysis of variance for categorical ones, followed by Tukey’s Honestly Significant Difference tests for pairwise comparisons. For the six most abundant species, Bayesian regression models accommodated different response distributions, including zero-inflated count and presence-absence data, quantifying species-specific habitat associations with credible intervals rather than single point estimates.

The results revealed a striking division of labor among environmental factors. Community composition was significantly associated with NDVI, altitude, and distance to streams, which together explained 17.82 percent of the observed variation, with the first constrained axis accounting for 81.84 percent of the constrained variation. Species richness, by contrast, showed no significant association with any continuous variable but responded strongly to the presence of igarapés and to terrain shape. Plots containing igarapés had significantly higher richness than plots without them, with estimated marginal means of 2.07 versus 1.56 species per plot. Terrain shape mattered too: convex, water-divergent areas and concave, water-neutral areas supported higher richness than flat, water-convergent and flat, water-divergent terrains, and the categorical model explained fully half of the observed variation in richness.

The Bayesian models then exposed the ecological personalities of the dominant species. Attalea speciosa showed the strongest associations of all: its expected abundance decreased with increasing NDVI and was lower in plots containing igarapés, indicating a clear preference for relatively open forest patches away from streams. Geonoma baculifera and Euterpe oleracea displayed the opposite pattern, both positively associated with the presence of igarapés and substantially more abundant in riparian plots. Geonoma baculifera formed dense clusters reaching up to 630 individuals per hectare, comparable to densities reported for seasonally flooded sandy soils elsewhere in the eastern Amazon. Euterpe longibracteata responded more to terrain shape than to greenness, favoring flat water-neutral or convex water-convergent topographic positions. Models for the two Astrocaryum species showed lower explanatory power and broad credible intervals, warranting cautious interpretation.

The hyperdominance of Attalea speciosa carries a deeper historical resonance. In the neighboring Rio Iriri reserve on the opposite bank of the river, the same species was found hyperdominant and associated with historical forest disturbance, where archaeological evidence indicates that this disturbance dates to Indigenous occupation during the eighteenth century. The present-day dominance of babassu in the region may therefore reflect a long-term anthropogenic legacy rather than recent extractive activity, although in the newly surveyed area the relative contributions of natural disturbance regimes and historical human influence remain uncertain, and both may have contributed. This possibility ties the palm community to one of the most compelling narratives in Amazonian science: the recognition that many seemingly pristine forests bear the fingerprints of ancient human management.

The richness documented at RESEX Riozinho, seventeen identified species plus one morphospecies, exceeded that of the two other areas previously surveyed along the eastern margin of the Xingu Basin, where ten species were recorded in the Kayapó Indigenous Territory roughly 400 kilometers to the southwest and eleven near Altamira. This pattern fits the broader westward increase in palm diversity across Amazonia, associated with rising rainfall toward the center and west of the basin. Two widespread palms of the Xingu Basin, Socratea exorrhiza, the famous walking palm adapted to seasonally flooded soils through its stilt roots, and Oenocarpus bataua, long associated with Indigenous management and dispersal, both occurred at comparatively low local abundance, showing that regional hyperdominance is not necessarily mirrored at the plot scale. The occurrence of Iriartea deltoidea, among the most abundant Amazonian tree species despite having been recorded in relatively few floristic inventories, extends its documented distribution within the eastern Amazon.

What does this mean for conservation? Several palm species have been proposed as indicators or surrogates of biodiversity, and describing their local environmental associations may improve their application in conservation planning. The findings may also contribute to future ecological studies, restoration initiatives, and agroforestry projects involving native palms. Yet the researchers are careful about scope. Because these patterns were documented along a single continuous transect, they should be interpreted as spatial associations within the surveyed landscape rather than as general ecological relationships for the eastern Amazon. The relatively low proportion of variation in composition explained by the measured variables suggests that additional factors, such as edaphic properties and disturbance history, also shape the community.

Still, the broader lesson is unmistakable. In one of the least-studied corners of Pará, the architecture of the palm community is written in the language of streams, slopes, and forest greenness. Small watercourses that satellites cannot see turn out to matter more for palm diversity than the perennial rivers that they can, a finding that argues powerfully for the continued value of boots-on-the-ground botany in an age of remote sensing. As the Amazon faces intensifying pressures from deforestation corridors barely a hundred kilometers to the north and east, inventories like this one provide the floristic baselines against which all future change will be measured, and they remind us that the forest’s hidden kingdoms still await their cartographers.

Subject of Research: Palm community structure and its associations with topography, hydrography, and forest structure in the eastern Amazon

Article Title: Palm community structure in relation to topography, hydrography, and forest structure in the Iriri River Valley, eastern Amazon

Article References: Salm, R., von Schmalz, K. E., Ruz, E. H., de Souza, D. A., de Oliveira Jr, A. P., & Pereira, C. C. (2026). Palm community structure in relation to topography, hydrography, and forest structure in the Iriri River Valley, eastern Amazon. Neotropical Biology and Conservation, 21(4), 297-320. https://doi.org/10.3897/neotropical.21.e206551

Image Credits: AI Generated

DOI: 10.3897/neotropical.21.e206551

Keywords: Amazon, palm communities, topography, hydrography, NDVI, species distribution, Palm, community, structure, relation, forest, Iriri

Storm tracks, the preferred highways along which extratropical cyclones and their attendant wind, rain and temperature swings travel, are among the most consequential features of the climate system. They regulate weather variability and extremes throughout the midlatitudes of both hemispheres, yet climate models still struggle with stubborn biases in their strength and location, and emerging discrepancies have appeared between simulated and observed storm track trends in some regions. That makes a return to first principles, asking which parts of Earth’s uneven surface actually build the storm tracks we observe, both timely and practical.

The team attacked the problem using MiMA, the Model of an idealized Moist Atmosphere, an intermediate-complexity general circulation model that bridges the gap between stripped-down aquaplanet experiments and fully comprehensive climate models. Crucially, MiMA carries full radiative transfer through the Rapid Radiative Transfer Model, a physically consistent treatment of moisture transport and latent heat release, and a slab ocean with prescribed ocean heat fluxes. That combination allowed the researchers to switch Earth-like land–sea contrast, topography and ocean heat transport on and off in any combination, an experiment that no single comprehensive model could perform cleanly, since in the real world it is difficult to imagine mountains without land or ocean circulation without continents.

The authors ran a suite of eight core configurations, each lasting 38 years after spin-up, beginning with a perfectly zonally symmetric aquaplanet and building up to a realistic ALL3 configuration containing all three surface inhomogeneities. By comparing each partial configuration with the full one, they could isolate both the isolated nonlinear response of a single ingredient, added first onto an aquaplanet, and its full nonlinear response, added last to a world that already had the other two. In parallel, they updated the model’s prescribed albedo profile to match satellite observations from CERES and revised the implied ocean heat transport so that the net flow of heat from the Southern Hemisphere to the Northern Hemisphere reached 0.54 petawatts, in line with observationally derived estimates, up from just 0.24 petawatts in the earlier configuration.

The realism check was encouraging. When all three ingredients were switched on, the model reproduced the observed pattern of storm tracks, with peaks over the North Pacific, the North Atlantic and the Indian-Ocean sector of the Southern Ocean, although the North Pacific came out somewhat too strong, the North Atlantic somewhat too weak, and the finer zonal structure of the Southern Hemisphere storm track was only fully captured at the higher T85 resolution. With the earlier albedo and ocean-flux settings, storm tracks had been 17 percent too weak at T85 and 29 percent too weak at T42; the updated configuration brought that bias down to 7 percent at T42 and essentially eliminated it at T85.

The central result concerns additivity. If the climate system were linear, the storm tracks in the full realistic configuration would equal the sum of the responses to land, mountains and ocean heat transport imposed individually. They do not. The team found substantial non-additivity both in the regional structure of the storm tracks and in the hemispheric asymmetry. Adding all three inhomogeneities reduces transient kinetic energy everywhere, partly because more energy is handed off to stationary waves forced by the uneven surface, and partly because realistic ocean heat transport carries some of the poleward energy load that transient eddies would otherwise shoulder. But the size of that effect depends dramatically on the order of assembly. In most sectors, the impact of the surface inhomogeneities is magnified when they are imposed on an aquaplanet compared with when they are removed from the full configuration, and the regional signature of ocean heat transport flips qualitatively between the two, weakening storm tracks most strongly over Eurasia when added first but over the North Pacific and North Atlantic when added last.

The same story holds for the headline asymmetry: in the full configuration the model’s Southern Hemisphere storm tracks are roughly 48 percent stronger than the north’s when measured with 2-to-8-day filtered transient kinetic energy, and about 25 percent stronger with a sub-monthly filter, broadly consistent with the observed excess of about 23 to 24 percent in the moist static energy framework applied to ERA5 reanalysis. Yet the sum of the isolated responses of the three ingredients accounts for only half of that asymmetry, while the sum of the full nonlinear responses overshoots it by 30 percent. Among the individual ingredients, land–sea contrast emerges as the most important driver of the hemispheric asymmetry, followed by ocean heat transport, with topography a distant third, a ranking that challenges earlier conclusions from comprehensive models in which topography and ocean circulation dominated.

To explain the mechanisms, the authors turn to the atmospheric moist static energy budget, decomposing poleward heat transport into contributions from the ocean, the mean meridional circulation, stationary eddies and transient eddies. In the realistic configuration, the surface energy input term, reflecting the ocean’s preferential delivery of heat to the Northern Hemisphere extratropics, contributes about 15.6 percentage points to the hemispheric asymmetry, while the stationary eddy term contributes 22.4 points, partially offset by a top-of-atmosphere term of minus 5.2 points. A striking simplification emerges when the researchers examined outgoing longwave radiation: across all 21 simulations, the correlation between the hemispheric asymmetry in longwave emission and the asymmetry in surface temperature was 0.99, meaning surface temperature essentially dictates how much energy the planet radiates to space in each hemisphere. Ocean heat transport and topography both preferentially cool the Southern Hemisphere, warming the north and increasing its longwave loss, which partially cancels their own intensifying effect on the asymmetry; land–sea contrast, by contrast, preferentially cools the north, deepening the asymmetry.

Two sensitivity experiments underline how delicate these balances are. Boosting the implied Southern-Ocean-to-North-Atlantic heat transport from 0.54 to 0.74 petawatts, a shift well within observational uncertainty, produced dramatic cancellations: transient eddy heat transport in the north actually increased by 0.34 petawatts rather than decreasing, because the stationary eddy term weakened by nearly the same amount, even as the North Atlantic storm track intensified locally. Likewise, tweaking midlatitude albedo over Northern Hemisphere land and ocean produced compensating changes in absorbed shortwave and emitted longwave radiation, leaving the hemispheric asymmetry nearly untouched despite pronounced regional shifts. The authors caution that MiMA lacks radiatively active clouds, whose treatment differs widely across climate models, and that its overly strong stationary eddy asymmetry may inflate the apparent importance of land–sea contrast. Even so, the message is clear: storm tracks cannot be understood ingredient by ingredient. Each piece of Earth’s patchwork surface sets the background state on which the others act, and that entanglement may be precisely why climate models, with their differing ocean heat transports and cloud biases, still disagree about where and how strongly the planet’s storms will rage in a warming world.

Subject of Research: How land–sea contrast, ocean heat transport and topography shape the localization and hemispheric asymmetry of midlatitude storm tracks

Article Title: Building blocks of localized storm tracks: revisiting asymmetries between the NH and SH in storm track strength

Article References: Garfinkel, C. I., Shaw, T., Keller, B., Gerber, E. P., White, I. P., Jucker, M., Ning, W., Adam, O., & Liu, S. (2026). Building blocks of localized storm tracks: revisiting asymmetries between the NH and SH in storm track strength. Weather and Climate Dynamics, 7(4), 1951-1975. https://doi.org/10.5194/wcd-7-1951-2026

Image Credits: AI Generated

DOI: 10.5194/wcd-7-1951-2026

Keywords: storm tracks, midlatitude cyclones, land-sea contrast, ocean heat transport, topography, stationary waves, transient eddies, moist static energy budget, general circulation model, hemispheric asymmetry, albedo, climate modeling

Atmospheric rivers are long, narrow corridors of concentrated water vapor transport in the atmosphere, often carrying more moisture than the mightiest terrestrial rivers. When they encounter mountain ranges or frontal systems, that vapor is forced upward, cools, and condenses into intense precipitation. In California and western Europe, these systems are famous for delivering both life-giving rain and devastating floods. In the Middle East, they have received less systematic attention, despite events such as the record Middle East floods documented by earlier researchers. The new study set out to close that gap by quantifying, for the first time at national scale, the frequency, intensity, and precipitation contribution of atmospheric rivers affecting Iran over nearly four decades.

The technical backbone of the research is the ERA5 reanalysis dataset, a state-of-the-art product from the European Centre for Medium-Range Weather Forecasts that blends observations with numerical modeling to produce a physically consistent record of the global atmosphere. The team computed Vertically Integrated Vapor Transport, or IVT, a measure of the total flux of water vapor through a column of air, for the rainy months from November through May between 1980 and 2020. IVT is the standard diagnostic for identifying atmospheric rivers because it captures both the humidity and the winds that carry moisture toward land. High IVT values arranged in elongated, coherent structures are the fingerprint of an atmospheric river.

Detecting these structures over Iran posed a distinctive challenge. Many global detection algorithms rely on fixed IVT thresholds tuned to maritime environments, where moisture transport is relatively uniform. Over Iran’s complex topography, which includes the Zagros and Alborz mountain ranges, the high Iranian Plateau, and low-lying southern coastal plains, a single threshold can fragment atmospheric rivers or miss them entirely. To overcome this, the researchers employed a spatially varying IVT threshold designed to preserve the continuity of atmospheric river structures across mountainous terrain, combined with geometric filtering criteria that ensure identified features possess the elongated shape characteristic of true atmospheric rivers. This approach improves the reliability of the climatology in regions where orography strongly modulates moisture flow.

The results reveal that approximately fifteen atmospheric river events affect Iran in a typical year, with activity peaking in March and reaching its minimum in May. That seasonal rhythm reflects the southward retreat of the subtropical jet stream and the strengthening of Mediterranean and Red Sea moisture sources during the heart of the cool season. Perhaps more striking is the geography of their impact. The contribution of atmospheric rivers to precipitation generally decreases from southern to northern regions of the country, and from the windward western slopes toward the arid central interior. This gradient tells a story about orography: when a moisture-laden river of air slams into the Zagros Mountains, the forced ascent wrings out enormous quantities of rain and snow, while regions sheltered behind the ranges receive far less of the transported moisture as precipitation.

To probe how atmospheric rivers behave in climatically anomalous years, the team classified years as wet or dry using the Nietzsche classification and then compared atmospheric river activity between the two groups. The contrast was clear. Wet years averaged about sixteen atmospheric river events annually, while dry years saw only around eleven. During wet years, the influence of atmospheric rivers on precipitation intensified markedly in western and southern Iran, the regions where orographic enhancement is strongest. During dry years, however, something subtler happened: the storm tracks themselves shifted, steering atmospheric rivers toward southern and southeastern Iran, where their maximum influence was observed. In other words, drought years are not simply years with fewer atmospheric rivers; they are years in which the rivers flow along different paths.

The study also uncovered a striking regional asymmetry in how atmospheric rivers relate to climate anomalies. In western Iran, wet and dry years are strongly tied to atmospheric river activity, making these systems a reliable indicator of the region’s hydrological fortunes. Central Iran, by contrast, behaves almost independently of atmospheric rivers, its precipitation anomalies apparently governed by other factors. In the southern stations, the researchers found no significant difference in the contribution of atmospheric rivers to precipitation between wet and dry years, suggesting that in those locations the presence of an atmospheric river does not by itself determine whether a year will be anomalously wet. These nuances matter enormously for anyone attempting to forecast seasonal water availability or anticipate flood risk.

Underlying all of these patterns is the fundamental role of topography. The authors conclude that mountains play a decisive part in converting atmospheric river moisture transport into precipitation, but that this conversion depends on geographical location and local climate. A given atmospheric river may dump torrential rain on the western slopes of the Zagros while leaving the central plateau nearly untouched. The interaction between atmospheric rivers and topography influences wet and dry conditions at individual stations to varying degrees, which helps explain why Iran’s precipitation regime is so spatially heterogeneous. This interplay between large-scale moisture transport and local orographic forcing is precisely the kind of process that global climate models often struggle to capture, making regional climatologies like this one especially valuable.

The practical implications extend to water resource management and flood risk assessment in arid and semi-arid regions worldwide. Iran faces chronic water stress, with declining groundwater reserves, recurrent droughts, and occasional catastrophic floods. Knowing that roughly fifteen atmospheric rivers arrive each year, that they cluster in the late winter and early spring, and that their tracks shift southeastward in dry years gives water managers and forecasters a framework for anticipating when and where heavy precipitation is most likely. As the climate warms, atmospheric rivers are expected to intensify in many regions, raising the stakes for understanding their behavior in the Middle East. This 39-year climatology provides the baseline against which future changes can be measured, and a reminder that even in the driest landscapes, the atmosphere occasionally delivers its water in torrents.

Subject of Research: Climatological analysis of atmospheric rivers and their contribution to precipitation across Iran

Article Title: Climatological analysis of atmospheric rivers and their contribution to precipitation across Iran (1982–2020)

Article References: Pazhouhesh, F., Esfahani, M. A. N., & Ghasemi, A. R. (2026). Climatological analysis of atmospheric rivers and their contribution to precipitation across Iran (1982–2020). Theoretical and Applied Climatology, 157(10), Article 663. https://doi.org/10.1007/s00704-026-06570-8

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06570-8

Keywords: atmospheric rivers, Iran, precipitation, ERA5 reanalysis, integrated vapor transport, arid climate, drought, flooding, topography, water resources, climatology, Middle East meteorology

The research, led by Kazım Kaba of Atatürk University together with colleagues at Manisa Celal Bayar University, DAG, and Çukurova University, addresses a stubborn problem in light pollution science. Satellite instruments such as the Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite, or VIIRS, provide high-resolution measurements of upward radiance from cities and towns, but they do not directly measure the glow that scattered light produces in the sky above an observatory. Ground-based sky quality meters, meanwhile, record actual sky brightness at specific points, but only at those points. Bridging the gap between these two views, one broad but indirect, the other direct but sparse, has long been a methodological challenge, particularly in mountainous regions where light propagation is shaped by complex topography.

To close that gap, the team built and rigorously compared several mapping approaches. Traditional geostatistical techniques, including Ordinary and Universal Kriging, were tested alongside modern machine learning regressors such as support vector regression and a hybrid framework that couples random forest regression with Kriging of its residuals, often called regression Kriging. The inputs combined VIIRS nighttime radiance with extensive in-situ sky quality meter measurements collected around the observatories. The comparison produced a cautionary tale about blindly trusting statistical scores. Ordinary and Universal Kriging, the workhorses of classical spatial interpolation, suffered from smoothing effects and overfitting when confronted with the complex terrain surrounding the sites, washing out real spatial structure.

Support vector regression told a different but equally instructive story. The algorithm achieved impressively high statistical validation scores, yet when asked to extrapolate into data-sparse regions it produced physically implausible predictions, in some cases implying sky brightness values that violate natural limits on how bright an unpolluted sky can actually be. For a field where the difference between a pristine site and a degraded one is measured in magnitudes per square arcsecond, such artifacts are not mere curiosities; they could mislead decisions about where to site future telescopes or how to protect existing ones. The lesson, the authors argue, is that physical consistency must be treated as a hard constraint, not an afterthought.

The random forest regression Kriging model emerged as the clear winner. It achieved robust validation accuracy, with coefficients of determination of 0.74 and 0.80 for the two study regions, while remaining strictly consistent with the natural brightness limits of the night sky. By letting the random forest capture nonlinear relationships between satellite-observed radiance, terrain, and measured sky glow, and then using Kriging to model the spatially structured residual, the hybrid approach preserved fine-grained detail that pure geostatistics smoothed away and avoided the runaway extrapolations of pure machine learning. The resulting maps offer observatory managers a realistic, high-resolution view of where light pollution originates and how it spreads across the landscape.

Beyond the methodology, the temporal analysis uncovered two strikingly different pollution regimes. Around the high-altitude Erzurum plateau, home to DAG, sky brightness follows a pronounced seasonal cycle driven by what researchers call snowglow. When snow blankets the ground, it acts as a vast white reflector, bouncing upward the light emitted by nearby settlements and amplifying human-induced skyglow by more than 1.5 times compared with snow-free conditions. The effect, which has been documented in suburban Europe, is particularly consequential for a mountain observatory, because the very winters that bring stable observing conditions also bring the reflective snowpack that magnifies whatever light leaks from the region’s towns and roads.

The Antalya coast surrounding TUG tells a darker story in a different sense. There, sky brightness has deteriorated monotonically, independent of season, in step with rapid tourism-oriented urbanization along the Mediterranean shoreline. Hotels, resorts, and expanding infrastructure emit light year-round, and the coastal topography channels that glow toward the observatory site. Unlike the seasonal snowglow signal at Erzurum, which at least offers a predictable annual rhythm, the Antalya trend points steadily in one direction, raising concerns about the long-term optical viability of one of Türkiye’s historic observing hubs if lighting practices remain unchanged.

The findings arrive amid a broader global reckoning with light pollution. Previous studies, including the world atlases of artificial night sky brightness and surveys of light pollution indicators at all major astronomical observatories, have shown that ground-based astronomy faces a growing threat from expanding artificial lighting. What the Turkish study adds is a transferable toolkit: a validated, physically constrained machine learning pipeline that fuses free satellite data with inexpensive ground sensors to produce actionable brightness maps. The VIIRS data used in the work are publicly distributed through NASA’s LAADS DAAC service, and the authors note that their sky quality meter measurements can be requested for further research, lowering the barrier for other observatory communities to replicate the approach.

The work was supported by the Scientific and Technological Research Council of Türkiye, TÜBİTAK, through its 3501 Career Development Program under project number 124F297, and the authors declare no competing interests. For DAG, which is moving toward first light with its large optical telescope, and for TUG, which has served Turkish astronomy for decades, the message of the study is double-edged. The new maps provide exactly the quantitative evidence needed to argue for dark-sky protections, shielding ordinances, and lighting curfews in surrounding communities. But they also confirm that the pressures of snow-reflected glow in the east and relentless coastal development in the west are real, measurable, and growing. Whether Türkiye’s flagship observatories keep their dark skies may now depend less on the mountains they sit on than on how the valleys below choose to light the night.

Subject of Research: Machine learning-based mapping of night sky brightness and light pollution dynamics at Türkiye's major astronomical observatories

Article Title: Long-term dynamics and machine learning-based mapping of night sky brightness: snowglow, urbanization, and topography effects at major astronomical observatories in Türkiye

Article References: Kaba, K., Aydın, S., Türkmen, R. B., Polat, F., Aksoy, F., Nasıroğlu, İ., Yeşilyaprak, C., & Kandırmaz, H. M. (2026). Long-term dynamics and machine learning-based mapping of night sky brightness: snowglow, urbanization, and topography effects at major astronomical observatories in Türkiye. Experimental Astronomy, 62(2), Article 16. https://doi.org/10.1007/s10686-026-10076-6

Image Credits: AI Generated

DOI: 10.1007/s10686-026-10076-6

Keywords: light pollution, night sky brightness, snowglow, machine learning, regression Kriging, Suomi NPP VIIRS, sky quality meter, DAG observatory, TÜBİTAK National Observatory, urbanization, topography, Türkiye

The research team, led by Alisha Keprate with D.R. Bhardwaj, Prashant Sharma, and Rushal Dogra, sampled soils across four contrasting land-use systems at two topographic positions — sheltered valley floors and cooler mountain slopes — and at three depths reaching down to 60 centimeters. Their study area, spanning roughly 1,543 to 2,396 meters above sea level in the Lesser Himalayan range, receives about 850 millimeters of annual precipitation, mostly from the southwest monsoon, and its Brown Podzolic soils sit on slopes of 15 to 35 percent. This combination of high rainfall, rugged relief, and intensive smallholder farming makes the region a natural laboratory for studying how land management reshapes one of the planet’s largest terrestrial carbon pools.

Soil organic carbon is not a single substance but a family of fractions that differ sharply in how quickly they turn over. The researchers used a modified Walkley-Black oxidation procedure, applying sulfuric acid at increasing concentrations to separate very labile, labile, less labile, and non-labile carbon pools. The two most easily oxidized fractions together form the active pool, which fuels rapid nutrient cycling, while the more resistant fractions make up the passive pool, the long-term reservoir that locks carbon away for decades or centuries. Alongside these fractions, the team computed the lability index, carbon pool index, and carbon management index — composite metrics that translate raw chemistry into practical measures of soil health and management performance.

The results were striking. Agroforestry plots, in which ten-to-fifteen-year-old apple trees grow alongside annual crops such as peas, beans, rajmash, potatoes, and barley, recorded the highest total organic carbon at 19.83 milligrams per gram of soil — roughly 50 percent more than adjacent agricultural plots growing potatoes, peas, and barley, and more than double the 9.72 milligrams per gram found on barren reference land. Apple monoculture orchards fell in between at 17.71 milligrams per gram. The same hierarchy held for nearly every carbon fraction: the active carbon pool reached 11.26 milligrams per gram under agroforestry compared with just 4.38 on barren land, while the passive pool peaked at 8.57 milligrams per gram in the tree-based system. Soil carbon density followed suit, climbing to 48.59 megagrams per hectare under agroforestry against a meager 25.59 on barren ground.

The carbon management index told an even more compelling story. Relative to the barren reference, the index rose by 137 percent under agroforestry, 114 percent under horticulture, and 44 percent under agriculture. Because this index integrates both the size of the carbon pool and the lability of its constituent fractions, the authors argue it captures a genuine improvement in the quantity and quality of soil carbon under tree-based management. The mechanism, they suggest, is a steady supply of organic matter — leaf litter, pruning residues, root biomass, and root exudates — that feeds microbial communities, promotes stable soil aggregates, and builds organo-mineral associations. Apple leaf litter, rich in phenolic compounds, may further slow decomposition and favor gradual nutrient release, tipping the balance toward carbon stabilization rather than loss.

Topography proved to be a second, independent sculptor of soil carbon. Valley soils, warmer and biologically livelier, held more of the fast-cycling active fractions: very labile carbon reached 5.14 milligrams per gram there, against 3.99 on mountain slopes, and the active pool overall measured 9.08 versus 6.73 milligrams per gram. Mountain soils, by contrast, accumulated more of the recalcitrant material — the passive pool reached 9.04 milligrams per gram on slopes compared with 5.39 in valleys, and non-labile carbon rose to 3.65 milligrams per gram. The researchers attribute this split to cooler slope temperatures that suppress microbial mineralization, strengthen the adsorption of organic matter onto clay minerals, and favor fungal communities that convert labile substrates into stable, microbial-derived organic matter. In effect, valleys recycle carbon quickly while mountains bank it.

Depth added a third dimension to the pattern. Total organic carbon declined steadily from 17.64 milligrams per gram in the surface 0-to-20-centimeter layer to 12.86 at 40-to-60 centimeters, and the active fractions fell in parallel, reflecting the concentration of litter and root inputs near the surface. Yet the non-labile fraction moved in the opposite direction, rising from 2.10 to 3.88 milligrams per gram with depth — a signature of older, more persistent carbon that has escaped rapid decomposition in the subsoil. A principal component analysis confirmed the split, with the first two axes explaining 56.4 percent of total variance and cleanly separating surface, labile, nitrogen-rich soils from deeper horizons dominated by passive fractions.

Nitrogen dynamics mirrored the carbon story. Total nitrogen was highest under agroforestry at 0.092 percent, and soil nitrogen density peaked at 2.27 megagrams per hectare in the tree-crop system, compared with 1.93 under agriculture and 1.94 on barren land. Valley soils again outpaced mountain soils, and all nitrogen measures declined with depth. Ammoniacal nitrogen reached 66.11 milligrams per kilogram under agroforestry, while nitrate nitrogen was highest in horticultural orchards at 61.44 milligrams per kilogram — a difference the authors link to heavy fertilizer inputs and the absence of intercropped plants competing for nitrate uptake in monoculture orchards. Correlation analysis reinforced the coupling of the two nutrient cycles: total organic carbon and total nitrogen were strongly positively correlated, and the carbon management index tracked closely with both carbon lability and nitrogen availability.

Taken together, the findings carry a clear message for the fragile mountains of the Himalayas and beyond: converting conventional annual agriculture to apple-based agroforestry could simultaneously enlarge the soil’s carbon bank, improve its nitrogen capital, and boost the overall carbon management index — a trifecta for climate-resilient mountain farming. The authors caution that their study reflects a single sampling period and that the underlying biological and physicochemical mechanisms were inferred rather than directly measured. Even so, in a region where steep slopes, erodible soils, and shifting land use threaten both livelihoods and carbon stocks, the evidence that mixing trees with crops builds richer, more stable ground adds scientific weight to a strategy many Himalayan farmers have practiced for generations — and gives policymakers a quantified reason to encourage it.

Subject of Research: Effects of land-use type, topographic position, and soil depth on soil organic carbon fractions and nitrogen dynamics in the wet temperate northwestern Himalayas

Article Title: Land-use and topographic effects on soil carbon and nitrogen fractions across contrasting land-use systems in the wet temperate northwestern Himalayas

Article References: Keprate, A., Bhardwaj, D., Sharma, P., & Dogra, R. (2026). Land-use and topographic effects on soil carbon and nitrogen fractions across contrasting land-use systems in the wet temperate northwestern Himalayas. Journal of Agriculture and Food Research, 31, Article 103262. https://doi.org/10.1016/j.jafr.2026.103262

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103262

Keywords: soil organic carbon, agroforestry, carbon fractions, carbon management index, soil nitrogen, northwestern Himalayas, land use change, topography, apple orchards, carbon sequestration, soil depth, climate-resilient agriculture