Ectothermic animals, including reptiles, amphibians, and most invertebrates, cannot generate enough metabolic heat to regulate their internal temperature. Instead, they depend on external heat sources to reach the body temperatures needed to sustain their physiological and ecological processes. Species fall along a continuum between two extremes: thermoconformers, whose body temperature closely tracks their immediate surroundings, and thermoregulators, which actively maintain body temperature within a narrower preferred range by exploiting spatial and temporal thermal variation through behavior. Distinguishing between these strategies is fundamental to understanding a species’ thermal ecology and its potential vulnerability to climate change.

Lizards draw on several distinct physical pathways to gather heat. Solar radiation in the ultraviolet, visible, and shortwave-infrared spectra is generally the primary heat source for diurnal lizards, transferred by radiation. Substrate temperature, the temperature of the soil, rock, sand, or leaf litter in direct contact with the animal, transfers heat by conduction. Air temperature influences body temperature mainly through convective exchange. Lizards that raise body temperature primarily by basking in sunlight are classified as heliotherms, whereas those relying mainly on conductive exchange with warm substrates are thigmotherms. Many species combine both strategies, and wind can further modify heat balance by enhancing convective heat loss when body temperature exceeds air temperature.

Because these heat sources vary at very fine spatial scales, macroclimatic data such as weather-station air temperatures or gridded climate surfaces are often poor proxies for the temperatures ectotherms actually experience. Vegetation cover, rock crevices, orientation, slope, and substrate type create fine-scale thermal mosaics that provide opportunities for behavioral thermoregulation. By selecting favorable microhabitats, lizards can maintain body temperature near their preferred range even when macroclimatic conditions would predict otherwise, a phenomenon known as the Bogert effect, in which behavioral buffering of the thermal environment may slow the pace of physiological evolution and mask a species’ climatic vulnerability.

The Anatolian rock lizard is a small diurnal lacertid endemic to western Anatolia, distributed from north of the Büyük Menderes River to Bursa and extending eastward into Central Anatolia at elevations up to roughly 1,600 meters. The species typically inhabits rocky areas with dense vegetation and proximity to moisture, and is frequently found under stones at ambient temperatures of 25 to 30 degrees Celsius. Previous work reported a preferred body temperature of approximately 34.5 degrees Celsius in adults, but data on how individuals in natural populations integrate solar radiation, substrate temperature, air temperature, and wind at the microhabitat scale remained scarce. Bioclimatic modeling predicts a northward contraction of suitable habitat for the genus under future climate scenarios, making the question urgent.

To address this gap, researchers conducted field surveys on Mount Spil between April and October 2025, capturing 125 lizards and measuring cloacal body temperature within ten seconds of capture using a fast-response thermocouple, alongside simultaneous measurements of surface temperature, air temperature one centimeter above the ground, solar radiation with a pyranometer, and wind speed at the lizard’s own height. Of these, 89 individuals had complete records and were retained for statistical analysis. Sex was determined in the field, and adults were distinguished from juveniles by snout-vent length.

The results were striking. Mean field body temperature was 32.32 plus or minus 4.53 degrees Celsius, significantly higher than both mean surface temperature of 30.6 degrees and mean air temperature of 28.1 degrees, confirming that the population behaves as an active thermoregulator rather than a passive thermoconformer. Multiple regression analysis showed that surface temperature and solar radiation were the strongest positive predictors of body temperature, with air temperature also significant, while wind speed was not significant at the conventional threshold. The full model explained 67.4 percent of the variance in body temperature, and a reduced model containing only surface temperature and solar radiation still accounted for 60.2 percent of the variance, underscoring how tightly body temperature is coupled to the radiative-thermal environment.

Principal component analysis added a compelling layer to the story. Two components jointly explained approximately 76 percent of the total variance. The first axis represented a combined thermal-radiative gradient with high loadings from body temperature, surface temperature, solar radiation, and air temperature. The second axis was dominated almost entirely by wind speed, contributing 91.96 percent to that component, and was essentially orthogonal to the first. This statistical decoupling suggests that the lizards buffer convective cooling through strategic microhabitat selection, such as using rock crevices and the base of vegetation, effectively neutralizing wind as a determinant of their thermal balance while managing heat gain primarily through solar radiation and substrate temperature.

The study also uncovered a surprising sex difference. Despite the absence of detectable differences in body size between adult males and females, females maintained significantly higher field body temperatures than males, 33.59 versus 31.44 degrees Celsius, with a moderate effect size. Neither snout-vent length nor body mass predicted field body temperature in adults, making a thermal inertia explanation unlikely. The researchers suggest that sex-specific differences in thermoregulatory behavior or microhabitat use, possibly linked to the elevated thermoregulatory demands of vitellogenesis and gestation, warrant further investigation.

The broader implications are clear. The Mount Spil population combines heliothermy with a component of thigmothermy, with solar radiation acting as the ultimate heat source, and relies on microhabitat-scale thermal heterogeneity to stabilize its thermal safety margins. As climate change reshapes thermal landscapes, the authors argue that conservation assessments should prioritize the continuity of thermal refugia and fine-scale habitat heterogeneity over macroclimatic averages. For a species whose suitable habitat is projected to contract northward, the sheltered crevice or sun-warmed rock may matter far more than any regional temperature forecast, and future work quantifying preferred and operative temperatures will be essential to refine projections of its fate under a changing climate.

Subject of Research: Thermal ecology and microhabitat thermoregulation of the Anatolian rock lizard

Article Title: Microhabitat-scale thermal determinants of body temperature in Anatololacerta anatolica from Mount Spil, Western Anatolia

Article References: Çelik, Ç., Afsar, M., & Şahin, M. K. (2026). Microhabitat-scale thermal determinants of body temperature in Anatololacerta anatolica from Mount Spil, Western Anatolia. Herpetozoa, 39, 281-290. https://doi.org/10.3897/herpetozoa.39.e188838

Image Credits: AI Generated

DOI: 10.3897/herpetozoa.39.e188838

Keywords: thermoregulation, Anatololacerta anatolica, ectotherms, microhabitat, solar radiation, Bogert effect, heliothermy, thigmothermy, climate change, lizard ecology, Mount Spil, thermal refugia

The core insight is deceptively simple. Solar radiation does not fall evenly across a landscape. A north-facing slope in the Northern Hemisphere receives less direct beam radiation than a south-facing one; steep gullies sit in shadow for much of the day; and the interplay of slope, aspect and solar geometry produces a patchwork of microclimates that can differ by many degrees within a few dozen meters. Ecologists have long recognized these topoclimates as potential refugia, but most large-scale models of species’ responses to climate change still rely on coarse climate surfaces that smooth this heterogeneity away. Adams and Riddell set out to quantify what that smoothing costs in biological terms, using a mechanistic framework that translates the physical environment into the currency that ultimately matters for survival: energy.

The technical machinery behind the study is considerable. The researchers assembled climate and elevation data from WorldClim version 2.1, slope information from the EarthEnv topography dataset, mountain range delineations from the Global Mountain Biodiversity Assessment Mountain Inventory version 2, and soil properties from SoilGrids 2.0, validating their soil temperature predictions against empirical records from the Soil Climate Analysis Network. On top of these layers they built solar radiation calculations that account for the position of the sun through the day and the year, the tilt and orientation of every grid cell, and the shading cast by surrounding terrain. The result is a continental-scale map of the actual radiative environment experienced at the ground surface across North American mountains, rather than the idealized flat-plate irradiance that standard climate rasters imply.

Into this physical landscape they placed two model organisms that sit at opposite ends of the activity spectrum. The western fence lizard, Sceloporus occidentalis, is a diurnal ectotherm whose body temperature, metabolism and foraging opportunities are governed by the sun. The southern Appalachian salamander Plethodon metcalfi, by contrast, is nocturnal and lungless, active when the sun is down and constrained as much by moisture as by heat. Using bioenergetic models of the kind increasingly favored in biophysical ecology, the team simulated annual energy expenditure and activity budgets for both animals under current and future climate conditions, first without topographic shading and then with it included. The difference between those two runs is the study’s central measurement: the biological value of a shadow.

For the diurnal lizard, that value proved enormous. Incorporating topographic shading reduced predicted annual energy expenditure by up to 20.8 percent, a margin comparable to some of the direct physiological costs of warming itself. More striking still, shading increased the buffering benefit of shifting elevation by 82.1 percent. In other words, when an animal can move both uphill and into shaded aspects, the terrain multiplies the relief it obtains from warming. A lizard that simply climbs a mountain gains the adiabatic cooling of altitude; a lizard that also settles on a cool, shaded slope gains a second, terrain-driven discount on its thermal burden. Models that ignore shading therefore systematically underestimate the refuge value of complex mountains for daytime ectotherms, and may misjudge which populations can persist without range shifts at all.

The nocturnal salamander told a different story. Because it is active at night, when direct solar radiation has vanished and air temperatures converge across aspects, topographic shading provided little buffering of its thermal environment. This asymmetry carries a sobering implication: the same mountain that functions as a climate refuge for a sun-basking lizard may offer a nocturnal, moisture-dependent animal almost no protection at all. Conservation strategies that treat topographic complexity as a universal buffer may be protecting some species while leaving others exposed. The study’s extended analyses also showed that shading produces aspect-specific shifts in the timing of activity and metabolic cost across the hours of the day and the months of the year, meaning terrain reshapes not just how much energy an animal spends but when in the daily and seasonal cycle those costs fall.

Elevation itself emerged as a sharpening fault line. Warming increased energetic costs most at low elevations, widening the gap between the energetic lives of lowland and highland populations. Under future conditions, metabolic expenditure declined more steeply with elevation than it does today for both species, while activity patterns diverged: the lizard’s activity decreased with elevation, whereas the salamander’s increased. The practical consequence is that climate change is not merely pushing thermal stress upward in a uniform wave; it is intensifying the energetic stratification of mountains, concentrating the worst cost-of-living pressures on the low-elevation margins where many species already live near their physiological limits.

Perhaps the most geopolitically resonant finding is continental in scope. Across North America, the researchers found that 48.9 percent of mountain ranges are depleted in the topographic features that buffer the effects of warming. Whether a range can offer its residents shaded refugia is not an accident of the moment but a legacy of deep time: tectonic history shapes present-day terrain-driven microclimates. Ranges forged by different geological processes carry different endowments of steep slopes, contrasting aspects and shadowed valleys. Two mountains with identical summit elevations and identical climate projections can therefore present entirely different futures to the animals living on them. This reframes mountain biodiversity vulnerability as a problem in geology as much as climatology, and suggests that global vulnerability maps built on elevation alone miss half the story.

The study arrives amid a broader correction in climate-change ecology. Earlier work has shown that microclimatic buffering reduces extinction risk, that forest canopies cool the air beneath them by several degrees globally, and that microclimates can slow or even redirect the velocity of climate change through tropical forests. Field studies have repeatedly documented that organisms partition themselves between north- and south-facing slopes, from reptiles and arthropods to salamanders and rodents. What Adams and Riddell add is a quantitative, continent-wide translation of that heterogeneity into energy budgets, the physiological ledger that connects environment to fitness. Recent work on desert lizards has described a cost-of-living squeeze under warming; this study shows that the squeeze is partly negotiable, and that the terms of the negotiation are written into the bedrock.

The implications ripple outward in several directions. For species distribution models, the message is that shading is not a refinement but a first-order variable for diurnal ectotherms, and that omitting it can bias predictions of range shifts, refugia and extinction risk in ways that are now measurable. For conservation planners, the results argue for prioritizing rugged, topographically diverse landscapes, and for recognizing that nearly half of North America’s mountain ranges lack the terrain features that would let shading do its protective work. The authors’ data and code are openly available through Zenodo, inviting other researchers to extend the approach to endotherms, to other continents and to finer spatial scales. As warming accelerates, the study suggests that the fate of mountain life may depend not only on how high the mercury climbs, but on where the shadows fall.

Subject of Research: How topographic shading and terrain-driven microclimates mediate the energetic and physiological responses of ectotherms to climate warming across North American mountain landscapes

Article Title: Topographic variation shapes organismal responses across mountain landscapes

Article References: Adams, D. R., & Riddell, E. A. (2026). Topographic variation shapes organismal responses across mountain landscapes. Nature Climate Change. https://doi.org/10.1038/s41558-026-02773-z

Image Credits: AI Generated

DOI: 10.1038/s41558-026-02773-z

Keywords: topographic shading, microclimate, mountain ecology, climate change, ectotherms, bioenergetic modelling, elevation, solar radiation, lizards, salamanders, refugia, tectonic history

The most pointed critique of vertical farms comes from comparisons with high-tech greenhouse horticulture, which is arguably the fairest benchmark since both technologies target the same market: high-value crops that demand consistent quality, uniformity, and year-round supply. In that comparison, greenhouses enjoy a decisive structural advantage. They harvest natural sunlight directly, and although they still require cooling, ventilation, shading, and CO2 management to hold optimal growing conditions, their electricity demands are far lower than those of a fully artificial-light facility. Work by Stanghellini and Katzin, cited in the commentary, drives the point home with a stark example: when lettuce is produced in a vertical farm in Northern Europe, its carbon footprint exceeds that of lettuce shipped from Southern Europe, even after accounting for long-distance transport. On that reading, hydroponic greenhouses already deliver many of the benefits marketed as unique to vertical farming, including high productivity, controlled environments, reduced water use, and lower pesticide demand, without the crushing electricity bill.

The numbers behind that efficiency gap are sobering. Reviewing the available literature, Orsini notes that vertical farms achieve an energy productivity of roughly 0.08 to 0.13 kilograms of fresh weight per kilowatt-hour, a figure that reflects the fundamental thermodynamics of converting electricity into photosynthetically useful light and then into edible biomass. Enthusiasm for applying vertical farming to staple crops has therefore run into hard limits: the energy required per unit of edible biomass for grain crops is enormous, and powering such facilities with renewables would itself demand vast tracts of land, partially erasing the land-sparing benefits that make indoor farming attractive in the first place. This is why, in practice, the vertical farming industry has concentrated on fresh-cut leafy vegetables and microgreens, crops with high market value, a high harvest index, small physical size, and short production cycles that suit stacked, tightly controlled environments.

Yet the same body of literature contains a second, more optimistic reading, and the difference lies in the analytical boundaries. When assessments extend beyond direct electricity consumption to include water-use efficiency, land-use efficiency, transport distances, post-harvest losses, and urban integration, the balance shifts. Vertical farms reach extraordinary productivity, up to 350 kilograms of fresh weight per square meter per year in commercial facilities, and their water-use efficiency, at about 140 grams of fresh weight per liter of water, is roughly double that of high-tech greenhouses. Shorter supply chains and reduced processing requirements can also cut post-harvest losses, an often-overlooked source of waste in conventional horticulture. None of this overturns the energy penalty, but it reframes the question: a technology that is inefficient in kilowatt-hours may still be efficient in land, water, and food actually delivered to consumers.

Context, the commentary argues, is what determines whether that reframing matters. In Northern European greenhouses, supplemental heating and lighting already account for a substantial share of production energy, which narrows the gap with indoor farms. In dense urban districts, vertical farms can in principle recapture waste heat, CO2, and water from surrounding buildings and infrastructure, improving resource circularity at the neighborhood scale; pilot work in Amsterdam has even explored recovering nutrients from urine wastewater for building-integrated agriculture. Where the electricity grid is dominated by renewable energy, the carbon cost of artificial lighting falls dramatically, further tilting the comparison. The same vertical farm that is difficult to justify in a sunny region with low-carbon power and established greenhouse production may become genuinely valuable where conventional controlled-environment agriculture requires heavy heating, cooling, or long-distance distribution.

Orsini also highlights a hybrid model that sidesteps the either-or framing altogether: using vertical farms for seedling propagation and early-stage crop growth before transplanting into greenhouses. Seedlings and young transplants are small, sensitive, and short-cycle, making them ideal candidates for the precise environmental control that indoor facilities provide, while the energy-intensive indoor phase is kept brief. The mature crop then finishes under sunlight in the greenhouse, capturing solar energy where it counts most. This division of labor, along with vertical farming’s demonstrated potential for herbs, medicinal plants, and vegetable transplants, suggests the technology’s strongest role may be as a specialized component within production chains rather than a standalone replacement for them.

The commentary situates these findings within the concept of City-Region Food Systems, in which urban and peri-urban production are integrated through shorter supply chains, resource circularity, and tighter links between food, energy, and waste-management infrastructure. In that framing, vertical farming is not a competitor to greenhouses but a complementary technology whose value depends on place, crop, and system design. Electricity mix, climate, water availability, transport infrastructure, opportunities for waste-heat and CO2 recovery, and proximity to consumers all alter the relative performance of the two systems. A single performance indicator, Orsini warns, cannot settle the question, and comparisons against horticulture in general, rather than against functionally equivalent high-tech production, produce misleading conclusions.

The commercial turbulence of the industry reinforces the point that technical performance alone does not guarantee sustainability. InFarm, a German vertical farming company that raised around 500 million dollars, collapsed into bankruptcy in 2023, and 80 Acres Farms, despite operating an extensive indoor-farming network and supplying a large retail market, recently decided to cease operations. Orsini is careful not to read these failures as proof that vertical farming is inherently unsustainable. Instead, he treats them as reminders that financial resilience, capital requirements, market structure, and operational scalability must be evaluated alongside resource-use efficiency. A system can be agronomically elegant and still fail economically if the business model assumes universal applicability rather than a defensible niche.

The upshot is a deliberately modest but actionable conclusion. Vertical farming will never outperform sunlight-driven production on raw energy efficiency, and in some contexts the honest answer to whether it makes sense will remain no. But in renewable-powered urban systems, in northern climates where greenhouse energy demand is already high, in hybrid production chains, and in the cultivation of high-value or quality-sensitive crops, it may prove a valuable complement to greenhouses rather than a rival. The productive question, Orsini argues, is not whether vertical farming is sustainable in the abstract, but under what circumstances, and for which crops, it delivers a measurable system-level advantage. The challenge for research and policy is not to crown a winner between vertical farms and greenhouses, but to map the niches where each technology contributes most effectively to sustainable food systems.

For a field that has swung between hype and backlash, that message amounts to a call for analytical discipline. Sustainability assessments, the commentary suggests, should state their system boundaries explicitly, compare vertical farms only with functionally comparable production systems, and incorporate water, land, circularity, transport, and CO2 supply considerations alongside energy metrics. Only then can growers, investors, and policymakers distinguish the configurations of vertical farming that genuinely improve food-system performance from those that merely relocate environmental burdens from the farm to the power plant.

Subject of Research: Comparative sustainability of vertical farming and greenhouse horticulture

Article Title: Efficiency and opportunities in vertical farming and greenhouse horticulture

Article References: Orsini, F. (2026). Efficiency and opportunities in vertical farming and greenhouse horticulture. npj Sustainable Agriculture, 4(1), Article 85. https://doi.org/10.1038/s44264-026-00197-y

Image Credits: AI Generated

DOI: 10.1038/s44264-026-00197-y

Keywords: vertical farming, greenhouse horticulture, controlled-environment agriculture, energy efficiency, urban agriculture, resource circularity, water-use efficiency, land-use efficiency, hybrid production systems, city-region food systems, LED lighting, sustainable food systems

The problem the team set out to solve is one that plagues cave temples worldwide. Many grottoes were originally carved with wooden eaves, galleries, or front halls that shielded the carved surfaces from direct sun, driving rain, and temperature swings. Over centuries, fires, wars, and decay stripped many of these structures away, exposing the fragile interiors to climatic disturbances. Restoring them seems obviously beneficial, yet the environmental consequences of different restoration designs have rarely been quantified. A shelter that blocks sunlight may also trap moisture; a structure that buffers heat may strangle airflow. Until now, conservators have lacked a rigorous, transferable method for comparing these trade-offs before committing stone, timber, and money to a particular design.

The researchers chose Cave 1280 at Longmen as their test case, a semi-open grotto whose conditions could be measured and modeled under three contrasting scenarios: no protective structure at all, a gallery-eave-type scheme that shades the cave front while leaving it largely open to the air, and a hall-type scheme that encloses the cave more completely. This scenario-based comparison is the heart of the study’s framework. Rather than asking whether a shelter helps, the method asks how each specific shelter reshapes the cave’s microclimate—temperature, relative humidity, solar radiation, and air movement—and whether those changes push the cave environment toward or away from stability.

Field monitoring first established the baseline physics of the cave. The measurements revealed pronounced seasonal vertical gradients in both temperature and relative humidity, meaning that conditions at the floor of the cave can differ substantially from conditions near the ceiling or entrance. Such stratification matters because moisture and heat do not act uniformly on carved stone; gradients drive condensation patterns, salt migration, and differential weathering that can damage one zone of a cave while leaving another untouched. Any restoration scheme, the study implies, must be judged by how it reshapes these vertical profiles, not just by average conditions at a single sensor.

The simulation results delivered a genuinely counterintuitive finding. The hall-type scheme, with its fuller enclosure, did exactly what its advocates would expect: it provided stronger thermal buffering, damping the daily and seasonal temperature swings that stress the stone, and it cut incoming solar radiation by an impressive 82 to 97 percent. On paper, those numbers look like a conservation triumph. But the same enclosure that blocks heat and light also restricts air exchange with the outside atmosphere. The hall-type scheme expanded zones of low air velocity inside the cave—pockets where the air barely moves—and this stagnation increased the cave’s sensitivity to moisture retention. In other words, the most protective-looking design created conditions under which dampness, once introduced, lingers longest against the carved surfaces.

This is where the resilience framing earns its keep. Traditional conservation assessment tends to reward structures that minimize fluctuations, treating stability as the sole goal. The resilience-based approach instead evaluates whether a cave environment can absorb and recover from climatic disturbances—rainy seasons, heat waves, visitor-driven humidity spikes—without crossing thresholds that trigger deterioration. A cave that is thermally serene but poorly ventilated may be less resilient than one that experiences wider swings but flushes moisture efficiently. The study’s multi-indicator evaluation captures this tension explicitly, weighing thermal buffering against airflow continuity, spatial openness, reversibility of the intervention, and compatibility with the surrounding landscape.

When all of these criteria were integrated, the gallery-eave-type scheme emerged as the favored option. It provides weaker thermal buffering than the hall-type design, to be sure, and it shields less of the cave from the sky. But it maintains better airflow continuity, preserving the natural ventilation that carries moisture out of the cave, and it keeps the spatial openness that matters both for the cave’s internal climate and for its visual relationship with the cliff face. The gallery-eave design is also more reversible—a crucial consideration in heritage practice, where today’s restoration may need to be revised by tomorrow’s conservators—and it sits more comfortably within the historic landscape of the grottoes.

The broader lesson, as the authors put it, is that greater enclosure does not necessarily ensure better conservation. This principle has implications far beyond a single cave in Henan Province. Semi-open grottoes—caves with large openings that are neither fully sealed chambers nor fully exposed niches—represent one of the most common and most vulnerable categories of rock-cut heritage, from the Buddhist caves of Central and East Asia to rock-hewn churches and tombs on other continents. For such sites, the study offers a transferable framework: reconstruct the historical protective architecture, monitor the actual microclimate, simulate candidate interventions under matched conditions, and evaluate the results with a multi-indicator, resilience-oriented scorecard before any physical construction begins.

The methodological machinery behind this framework deserves attention in its own right. Microclimate simulation allows conservators to test designs digitally, comparing how a gallery eave versus a full hall alters radiation loads and airflow fields across an entire annual cycle, something that would take years to measure empirically for even one design. Solar-radiation modeling quantifies the light and heat reaching carved surfaces, which matters not only for thermal stress but also for photochemical degradation and the biological growth that sunlight and dampness can jointly encourage. By anchoring these simulations in real field monitoring data, the team ensured that the modeled scenarios reflect the genuine behavior of the cave rather than idealized assumptions. The combination of measurement and modeling, evaluated through multiple indicators rather than a single metric, is what allows the framework to produce defensible, site-specific recommendations.

For the managers of Longmen—a UNESCO World Heritage site visited by millions—the findings arrive at a practical moment, offering an evidence-based path for deciding which caves receive which kind of protective architecture. For the wider heritage community, the study is a reminder that conservation is a systems problem, not a shelter problem. The carved stone at Longmen has survived fourteen centuries because of a delicate balance of shade, airflow, and moisture that the original builders understood intuitively. Modern restoration, this research suggests, succeeds best when it respects that balance rather than simply maximizing protection. Sometimes the wisest roof over an ancient Buddha’s head is the lightest one. The work was supported by the National Natural Science Foundation of China, and the team included researchers from Xi’an University of Architecture and Technology, the Leshan Giant Buddha Grottoes Research Institute, Henan University of Science and Technology, and the Longmen Research Institute, reflecting the collaboration between academic modeling and on-site stewardship that such decisions increasingly demand.

Subject of Research: Resilience-based assessment of architectural restoration schemes for the microclimate of semi-open rock-cut cave temples at the Longmen Grottoes, China

Article Title: Assessing architectural interventions in rock-cut heritage: a resilience-based restoration approach at Longmen Grottoes, China

Article References: Liu, Y., Yan, Z., Wang, C., Peng, J., Wang, J., Ma, C., Lei, F., Yue, Y., Zhang, D., & Ni, P. (2026). Assessing architectural interventions in rock-cut heritage: a resilience-based restoration approach at Longmen Grottoes, China. npj Heritage Science. https://doi.org/10.1038/s40494-026-03032-2

Image Credits: AI Generated

DOI: 10.1038/s40494-026-03032-2

Keywords: Longmen Grottoes, cave temples, rock-cut heritage, microclimate, restoration, protective architecture, thermal buffering, solar radiation, ventilation, resilience, heritage conservation, npj Heritage Science

The central challenge facing any long-endurance airship is brutally simple: it must generate enough electricity during the day to power its propulsion, its payload, and its housekeeping systems, while simultaneously storing enough surplus energy in batteries to keep flying through the long hours of darkness. Unlike an aircraft that can land and refuel, a stratospheric airship is expected to remain on station indefinitely, making its energy budget a matter of survival. Undersize the solar array or the battery pack, and the vehicle loses altitude as its batteries drain, eventually descending into denser air, higher winds, and mission failure. Oversize them, and the added weight demands more lift, more structure, and more power just to carry the energy system itself, a self-defeating spiral that designers must carefully avoid.

To untangle this problem, the research team built a comprehensive energy system model that captures the full chain of energy conversion aboard the airship. At the front end of the chain sits the solar radiation environment itself, which varies with the sun’s angle, the day of the year, and the airship’s operating latitude. That incoming radiation feeds the photovoltaic array draped over the airship’s upper surface, whose output depends on the incidence angle of sunlight on the curved envelope and on thermal effects that alter cell efficiency. The generated power then splits between the loads that must be served continuously, principally propulsion to hold position against stratospheric winds and the payload’s instruments, and the battery bank that absorbs surplus energy by day and releases it by night. The researchers formulated the energy balance constraints that tie all of these elements together, ensuring that over every charge-discharge cycle the books balance exactly.

What makes the new work distinctive is its treatment of energy management strategies as a first-order design variable rather than an afterthought. How an airship spends and stores its energy, the authors show, fundamentally reshapes the design space. The team considered multiple strategies, including a maneuverable wind resistance approach, a Position Energy Storage strategy, a Position Potential strategy, and a fixed-speed approach, each representing a different philosophy for how the vehicle should respond to the daily and seasonal rhythm of solar input. For each strategy, they systematically analyzed the feasible combinations of photovoltaic area and battery capacity, extracting the feasibility boundaries that separate workable designs from those that will inevitably run out of energy.

The results reveal a clear and quantifiable trade-off at the heart of airship design. Increasing the photovoltaic area reduces the battery capacity required for overnight operation, because more sunlight is harvested during daylight hours. But the relationship is not linear: the marginal benefit of each additional square meter of solar cells diminishes as the array grows. Beyond a certain point, adding panel area yields only modest savings in battery mass, while the panels themselves add weight and drag. This diminishing-returns curve gives designers a rational basis for choosing a balanced point on the trade-off surface rather than simply maximizing one component or the other. The feasibility maps produced in the study effectively serve as a design chart, allowing engineers to read off which combinations of solar area and battery capacity will keep a given airship aloft under specified conditions.

Perhaps the most striking finding is how dramatically the choice of energy management strategy alters the shape of the feasibility boundary itself. Under the maneuverable wind resistance strategy and the Position Energy Storage strategy, the boundary curves exhibit steep slopes in the region of small photovoltaic areas, along with noticeable curvature variations and inflection characteristics over certain ranges. In practical terms, this means that for airships with modest solar arrays, these strategies impose sharply rising battery requirements, making the design highly sensitive to small changes in panel area. By contrast, the Position Potential and fixed-speed strategies produce smoother, approximately linear boundaries, offering more forgiving and predictable design margins. The implication is significant: the software and control logic that govern how an airship manages its power are not merely operational details but structural constraints that should be fixed early in the design process, because they determine where the feasible region lies.

The study also delivers a sobering message about geography and the calendar. Seasonal and latitudinal conditions exert a powerful influence on energy availability, and therefore on the entire sizing problem. At higher latitudes and during winter, reduced solar radiation drives a notable increase in the battery capacity needed to survive the longer nights and weaker sun. An airship sized for a comfortable summer deployment at mid-latitudes could find itself energy-starved if redeployed northward in January. Conversely, spring, summer, and autumn conditions at mid-latitudes offer the broadest feasible capacity region, giving designers the most freedom and the lightest energy systems. For mission planners, this means that the operating envelope of a stratospheric airship cannot be specified independently of its energy hardware; the two must be co-designed with the intended deployment season and location firmly in view.

These findings arrive at a moment of renewed global interest in the stratosphere as an operational domain. Sitting between conventional aviation and orbital spaceflight, the stratosphere offers persistent surveillance, telecommunications relay, and Earth observation capabilities at a fraction of the cost of satellites, with the added advantage that payloads can be recovered, upgraded, and relaunched. Yet the history of stratospheric airship development is littered with programs that stalled on precisely the kind of coupled problem this study addresses: vehicles that were heavy enough to be robust but too heavy to fly, or efficient enough by day but helpless by night. By providing a rigorous, quantitative framework that links energy management strategy, component sizing, and environmental conditions, the Shanghai Jiao Tong team has given the field a tool for avoiding those classic failure modes.

The methodology itself is also noteworthy for its generality. Because the model spans the full energy pathway, from solar radiation through photovoltaic conversion to propulsion, payload consumption, and battery storage, it can be adapted to different airship geometries, different mission profiles, and different hardware assumptions. The energy balance constraints and feasibility boundaries are extracted systematically rather than through ad hoc case studies, meaning the approach can be reused as a standard sizing procedure as designs evolve. As battery chemistries improve and flexible thin-film photovoltaics push conversion efficiencies higher, the same framework can be re-run to reveal how technological progress enlarges the feasible design space and pushes long-endurance missions toward higher latitudes and harsher seasons.

For now, the study’s practical takeaway is a disciplined one. There is no single correct size for an airship’s energy system; there is only a feasible region whose shape depends on how the vehicle will fly, where it will operate, and when. Designers who ignore the coupling between energy management strategy and capacity allocation risk building vehicles that work beautifully in simulation and fail in the thin, cold air of the stratosphere. By charting that feasible region with care, Zhang, Zhang, and Zhou have turned one of aerospace engineering’s most persistent sizing puzzles into a solvable design problem, bringing the prospect of solar-powered airships that never need to come home one step closer to reality.

Subject of Research: Capacity sizing and feasibility analysis of solar-powered energy systems for long-endurance stratospheric airships under multiple energy management strategies

Article Title: Capacity sizing and feasibility analysis of stratospheric airship energy systems under multiple energy management strategies

Article References: Zhang, L., Zhang, Y., & Zhou, P. (2026). Capacity sizing and feasibility analysis of stratospheric airship energy systems under multiple energy management strategies. Aerospace Systems. https://doi.org/10.1007/s42401-026-00550-6

Image Credits: AI Generated

DOI: 10.1007/s42401-026-00550-6

Keywords: stratospheric airship, photovoltaics, battery capacity, energy management strategy, energy balance, solar radiation, capacity allocation, long-endurance flight, feasibility boundary, latitude effects, seasonal variation, aerospace engineering

The reason such an effort is needed lies in the nature of the observing network itself. Surface meteorological stations are the workhorses of climate-change detection, attribution, and impact studies, and they also serve as the yardsticks against which satellite remote-sensing retrievals and climate model simulations are evaluated. But these stations are not pristine instruments floating above history. Observing instruments are continuously upgraded and replaced, and different instruments carry different biases. When a thermometer design changes or a humidity sensor is swapped for a newer model, the recorded values can shift for reasons that have nothing to do with the atmosphere. These artificial changes, known as inhomogeneities, contaminate the very records scientists rely on to detect long-term climate signals.

In principle, observational data are expected to represent large-scale climate-change signals on the order of 100 kilometers or more. Yet changes in the local environment surrounding a station, most notably urbanization, can be superimposed on those large-scale signals. To accurately detect and attribute climate change, the effects of non-climatic factors and local environmental changes must be removed as much as possible. Some of these effects are comparatively easy to handle. Abrupt changes caused by station relocations and instrument replacements tend to be large and can usually be detected and corrected through conventional homogenization techniques. The harder problem is the slow one: changes in the observing environment around a station are often gradual, and each individual change has only a small effect on the observations, making it extremely difficult to identify and correct. Over decades, however, these small effects accumulate into systematic biases that can significantly distort estimates of climate-change trends and even undermine the reliability of detection and attribution studies.

Traditional homogenization methods generally rely on comparisons with neighboring stations. A set of reference stations with similar elevation and reliable data quality is selected around a target station, and possible inhomogeneities are identified by comparing their time series. The logic is sound when the neighbors are clean. But when many stations in a region are simultaneously affected by instrument sensitivity drift, instrument replacement, urbanization, and other factors, the reference stations themselves may contain inhomogeneities. In that case, the method can miss the very signals it is designed to find, and its ability to detect both gradual and abrupt inhomogeneities becomes limited. This is precisely the situation across much of China, where the national station network has undergone sweeping technological and environmental change over the past sixty years.

To break this deadlock, Wang’s team spent more than a decade developing a homogenization method based on same-station comparison. Instead of leaning on neighboring stations that may share the same hidden biases, the approach overcomes key difficulties in detecting and correcting gradual inhomogeneities, and it enables the detection and correction of both gradual and abrupt inhomogeneities in China’s land-surface climate observations. The variables it covers are the essential ones for climate monitoring: surface solar radiation, wind speed, relative humidity, air temperature, ground temperature, and precipitation. The method provides the technical backbone for building high-quality climate datasets for China, and HCD01 is the first major product of that backbone.

The corrections the team uncovered are striking, and they change how several well-known features of China’s climate record should be interpreted. Before 1990, strict calibration instruments and procedures were lacking, and gradual inhomogeneity caused by instrument sensitivity drift crept into China’s surface solar radiation observations. The consequence is significant: the widely reported decreasing trend in surface solar radiation during 1960 to 1990 was seriously overestimated. Then, during 1990 to 1993, instrument updates caused a sudden increase in the observations, an artificial step that had nothing to do with the sun or the clouds. In other words, part of the famous global dimming and brightening story as recorded over China was an artifact of the instruments rather than the atmosphere.

The twenty-first century brought a different kind of discontinuity. China’s meteorological observations began shifting from manual to automatic observation, and the greatest impact fell on relative humidity. Under conditions of low near-surface wind speed, the dry- and wet-bulb thermometers used in manual observations tended to overestimate relative humidity, whereas the capacitive sensors used in automatic observations did not have this problem. The transition between the two methods therefore produced a false decreasing trend in relative humidity observations in the twenty-first century, a trend that reflects changing hardware rather than a drying atmosphere. Correcting this bias matters enormously, because relative humidity feeds directly into calculations of evaporation, heat stress, and the behavior of the hydrological cycle.

Urbanization left its own fingerprints on the record. The growth of cities around meteorological stations amplified the observed warming trend of daily minimum temperature, since urban surfaces store and release heat differently than the rural landscapes that once surrounded the stations. Urbanization also increased surface roughness, which reduced near-surface wind speed as measured at those sites. Meanwhile, relocations of meteorological stations from urban to rural areas caused abrupt increases in observed wind speed, the opposite artifact. The team notes that although the decline in station-observed near-surface wind speed does not represent large-scale change, it does reflect real changes in near-surface wind speed at the observing sites themselves, and it affects station precipitation observations, since wind influences how effectively rain gauges catch falling precipitation.

Cleaning the station records, however, is only half the battle. Homogenized station observations alone remain insufficient for climate-change research because observing stations are sparse and unevenly distributed across China, and because observation periods differ among stations. That makes direct spatiotemporal analysis at the national scale difficult. To solve this, the team merged the homogenized station observations with ERA5-Land reanalysis data to construct HCD01, providing complete spatial coverage at a daily, 0.1-degree resolution for 1961 through 2022. The results show that HCD01 clearly improves the representation of long-term trends compared with both reanalysis data alone and raw observations, offering a high-quality data basis for studies of regional climate change and its impacts across China.

The study was led by Professor Kaicun Wang, who served as first author and corresponding author. The research team included current graduate students Hongze Cai, Yun Li, Hanmeng Xia, and Changjian Yin from Wang’s group, along with former graduate students including Professor Chunlue Zhou and Associate Professor Yanyi He, both of Sun Yat-sen University, Young Researcher Zhengtai Zhang of Lanzhou University, and Dr. Runze Zhao of the National Satellite Meteorological Center of the China Meteorological Administration. The work was supported by the National Key Research and Development Program of China and the Science and Technology Program of Guizhou Province. With HCD01 now openly available, researchers studying everything from agricultural water demand to solar energy potential in China have access to a climate record in which the instruments, the cities, and the station moves have been carefully accounted for, leaving the climate signal standing on its own.

Subject of Research: Homogenization of Chinese meteorological station records and construction of a gridded climate dataset

Article Title: Peking University team releases homogenized gridded climate dataset for China

Article References: Peking University team releases homogenized gridded climate dataset for China. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: climate dataset, homogenization, China, meteorological stations, solar radiation, relative humidity, urbanization, ERA5-Land, reanalysis, climate change detection, Peking University, Science China Earth Sciences

Reference evapotranspiration, abbreviated ETo, represents the water loss from a standardized grass surface under given weather conditions. Because directly measuring evapotranspiration with lysimeters or micrometeorological towers is expensive and technically demanding, hydrologists and agronomists rely on ETo as a proxy for atmospheric demand. The internationally accepted way to compute it is the Penman–Monteith equation as standardized by FAO-56, a physically based formula that combines an energy term, driven by net radiation, with an aerodynamic term, driven by wind speed and the vapor pressure deficit between the surface and the air. The equation’s multivariate structure is its strength, but it also raises a critical question: which of these meteorological ingredients matters most, and does the answer change from place to place and season to season?

That question motivated a team led by Lucas da Costa Santos of the Federal University of the Jequitinhonha and Mucuri Valleys. The researchers assembled thirty years of daily meteorological records, from 1990 to 2019, for six Brazilian municipalities chosen to represent sharply contrasting climate typologies under the Köppen–Geiger classification: Belém in the Amazon with an equatorial monsoon climate, Salvador with a tropical rainforest regime, Petrolina in the hot semi-arid northeast, Pirenópolis with a tropical savanna climate, and Franca and São Luiz Gonzaga in the humid subtropical south. The sites span a remarkable range, from mean annual temperatures of about 21.4 degrees Celsius in São Luiz Gonzaga to 27.7 degrees in Belém, and from mean solar radiation of 16.69 megajoules per square meter per day in the subtropical south to 23.19 in Petrolina.

To disentangle the influences, the team turned to path analysis, a statistical technique that decomposes simple correlations between weather variables and ETo into direct and indirect effects. Direct effects capture the independent contribution of each variable, while indirect effects reveal how variables interact with one another through their mutual correlations. The researchers first checked for multicollinearity among predictors using variance inflation factors, retaining mean air temperature as the thermal variable because maximum and minimum temperatures introduced redundancy that destabilized the regression models. They also ran Mann–Kendall trend tests to check whether the predictor variables themselves were changing over the study period, finding significant long-term trends in at least one variable at five of the six locations.

The results were striking in their consistency and their variability at the same time. The path models explained between 97.7 and 99.5 percent of the annual variability in ETo across all six locations, an extraordinarily high proportion. Yet the identity of the dominant driver shifted from site to site. In São Luiz Gonzaga, Franca, Salvador, and Belém, solar radiation carried the largest direct effect, with standardized coefficients reaching 0.812 in Franca, indicating that in these places evaporative demand is primarily limited by the energy available at the surface. In Pirenópolis and Petrolina, by contrast, wind speed took the lead, with a coefficient of 0.711 in the semi-arid Petrolina, pointing to a regime in which the aerodynamic removal of vapor, rather than energy supply, sets the pace of evaporation.

The decomposition of indirect effects added a layer of nuance that simple correlation studies miss entirely. In Franca, the seemingly dominant direct effects of radiation and wind were substantially offset by negative indirect pathways, cutting their total effects to a fraction of their direct coefficients. In humid Belém, the positive direct effect of wind speed was overwhelmed by a strong negative indirect effect mediated through solar radiation, so that wind’s net association with ETo actually turned negative. In Petrolina, the opposite occurred: positive indirect effects reinforced the direct dominance of wind, pushing its total effect to 0.837. In other words, the same meteorological variable can be amplified, muted, or even reversed in its apparent influence depending on the interaction structure of the local atmosphere.

Seasonality compounded the picture. When the team repeated the analysis for each meteorological season of the Southern Hemisphere, the hierarchy of controls reconfigured systematically through the year. Solar radiation ranked among the top drivers during the high-insolation summer and spring months, while wind speed gained prominence during autumn and especially winter, when energy availability declines but atmospheric ventilation remains strong, particularly at inland and semi-arid sites. Relative humidity, meanwhile, displayed negative direct effects at every location and in every season, a physically coherent signal of the vapor pressure deficit that governs the aerodynamic term of the Penman–Monteith equation. Drier air pulls water from the surface more aggressively, and the humidity coefficients, reaching −0.469 in São Luiz Gonzaga and −0.374 in Petrolina, quantify that pull.

Perhaps the most consequential finding concerns what did not dominate: temperature. Mean air temperature ranked among the three strongest drivers at only half of the locations at the annual scale, and even there its coefficients were systematically smaller than those of radiation or wind. This challenges the widespread reliance on temperature-based empirical methods such as Hargreaves–Samani, which implicitly assume that thermal proxies can capture evaporative demand. The authors argue that temperature functions mainly as a thermodynamic state variable, signaling the energy content of the atmosphere, while the actual fluxes of vapor depend on radiation balance, humidity gradients, and wind. In regions with strong ventilation or high radiative variability, temperature-only models risk systematic underestimation of water demand, with tangible consequences for irrigation scheduling and water resource planning.

The practical implications extend into a warming future. As global temperatures rise, the atmosphere’s water-holding capacity increases, and vapor pressure deficit tends to grow disproportionately, intensifying evaporative demand in ways that temperature records alone do not reveal. The study’s authors are careful to note the limitations of their approach: ETo is not an independently observed quantity but a deterministic product of the same variables used as predictors, so the path coefficients should be read as indicators of relative contributions within the FAO-56 framework rather than as evidence of independent causation. Solar radiation was estimated from sunshine duration rather than measured directly, each municipality was represented by a single weather station, and the significant long-term trends in several predictors mean the reported hierarchies describe dominant tendencies over the study period rather than fixed relationships.

Even with those caveats, the diagnosis is clear and actionable. There is no universal driver of evaporative demand; the balance between radiative and aerodynamic control is a property of each climate and each season. For water managers in aerodynamically dominated environments like Petrolina, monitoring wind speed and humidity is essential, and neglecting them can mean underestimating irrigation requirements during dry periods. In radiatively controlled regions such as Belém, Salvador, Franca, and São Luiz Gonzaga, cloud cover and seasonal insolation set the agenda, and models that ignore radiation do so at their peril. The study makes a strong case that the era of one-size-fits-all, temperature-based evaporation estimates should give way to multivariate, physically consistent approaches capable of tracking how the atmosphere’s thirst is truly regulated across a changing planet.

Subject of Research: Meteorological controls on reference evapotranspiration across contrasting Brazilian climate typologies

Article Title: Energy versus aerodynamic controls of reference evapotranspiration: a multi-regional assessment across Brazilian climate typologies

Article References: da Costa Santos, L., Capuchinho, F. F., do Patrocínio Figueiró, L. S., José, J. V., dos Reis, E. F., Bonfá, C. S., Araujo, J. E., & Nhongo, E. J. S. (2026). Energy versus aerodynamic controls of reference evapotranspiration: a multi-regional assessment across Brazilian climate typologies. Theoretical and Applied Climatology, 157(10), Article 646. https://doi.org/10.1007/s00704-026-06580-6

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06580-6

Keywords: reference evapotranspiration, Penman–Monteith, solar radiation, wind speed, relative humidity, vapor pressure deficit, path analysis, Brazil, climate typologies, irrigation management, FAO-56, hydrology

The Ångström–Prescott model, extended to practical use by John Prescott in 1940, estimates global solar radiation, the total shortwave energy arriving at the surface, from the ratio of actual bright sunshine hours to the maximum possible daylight hours. Its two coefficients, conventionally labelled a and b, translate the fraction of clear-sky sunshine into a fraction of extraterrestrial radiation. The Food and Agriculture Organization’s influential FAO-56 handbook, which underpins crop water requirement calculations worldwide, suggests default values that assume a relatively clean, stable atmosphere. India’s atmosphere, as the new study demonstrates, is anything but that.

Led by Ashutosh Kumar Misra of the India Meteorological Department in Pune, with colleagues from the department’s regional centres in Guwahati and Chennai, the team derived station-specific coefficients from collocated daily radiation and sunshine-duration records. The network-wide means came out at a = 0.336 with a standard deviation of 0.079, and b = 0.364 with a standard deviation of 0.122. Those averages alone would not be alarming, but the spatial pattern is striking: the largest departures from FAO-56 defaults occurred precisely at stations burdened with heavy aerosol loading across the Indo-Gangetic Plain, Rajasthan, and the western coast, where dust, smoke, and industrial pollution scatter and absorb incoming sunlight in ways the default coefficients never anticipated.

To judge how well the calibrated model performed, the authors deployed a demanding seven-metric evaluation framework rather than relying on a single goodness-of-fit statistic. They computed the coefficient of determination, mean absolute error, root mean square error, normalised RMSE, Willmott’s index of agreement, mean bias error, and the Kolmogorov–Smirnov integral, then synthesised all seven into a Global Performance Index. This composite approach matters because different metrics capture different failure modes: a model can correlate well with observations yet carry a systematic bias, or track the shape of the seasonal cycle while missing its amplitude. Collapsing the picture into one number risks hiding exactly the flaws that matter for irrigation scheduling or solar farm siting.

The headline numbers are respectable. Across the network, the calibrated model achieved a mean coefficient of determination of 0.75, a root mean square error of 1.75 megajoules per square metre per day, a normalised RMSE of 9.95 percent, and Willmott’s index of agreement of 0.92, a value close to the theoretical maximum of one. For a model that requires nothing more than a sunshine recorder and a table of extraterrestrial radiation, that level of skill explains why the Ångström–Prescott formulation has survived a hundred years of competition from far more elaborate schemes, including neural networks and satellite retrievals.

But the seasonal breakdown tells a more nuanced story, and it is here that the study becomes genuinely useful for practitioners. The pre-monsoon months of March through May produced the weakest correlations, with a network-mean R² of just 0.50, even though the RMSE of 1.75 megajoules per square metre per day matched the annual figure. The culprit is day-to-day aerosol variability superimposed on transient convective cloud development. In the hot dry season, dust storms, crop residue burning, and the first thunderstorms of the year can transform the atmospheric transmission of sunlight within hours, decoupling the sunshine-duration record from the radiation actually measured at the surface. A pyranometer responds to every attenuating process; a sunshine recorder, by contrast, only registers when direct beam irradiance exceeds a threshold, so the two instruments can disagree most dramatically exactly when the atmosphere is most turbulent.

The monsoon season posed a different problem. There the model recorded its largest root mean square error, 2.02 megajoules per square metre per day, alongside a systematic positive bias of 0.88 megajoules per square metre per day, meaning the model overestimated the radiation reaching the ground. During the southwest monsoon, thick stratiform and cumuliform cloud decks, elevated humidity, and aerosol-cloud interactions suppress surface radiation far below what the sunshine fraction alone would suggest. For hydrologists computing evapotranspiration during the very season when Indian agriculture depends most critically on accurate water balance estimates, that bias is not a statistical curiosity but a potential source of systematic error in crop water demand calculations.

Beyond calibration, the study turned its attention to the long-term trajectory of surface solar radiation itself, applying the Mann–Kendall nonparametric trend test to annual mean values at each qualifying station. The verdict was sobering: statistically significant downward trends emerged at the majority of stations examined. This finding aligns India with the broader global phenomenon of solar dimming documented in the early 2000s, when researchers first showed that declining surface radiation across many continents was linked to increasing anthropogenic aerosols. Over the Indo-Gangetic Plain, where aerosol optical depths are among the highest in the world and continue to be fed by urbanisation, industrial emissions, and seasonal biomass burning, the dimming signal appears firmly entrenched in the observational record.

The implications ripple outward across several domains. Agricultural water management in India relies heavily on FAO-56 evapotranspiration methods, which use solar radiation as a key input; using uncalibrated default coefficients in aerosol-laden regions risks misestimating irrigation demand by meaningful margins. Solar energy resource assessment, a sector expanding rapidly as India pursues ambitious photovoltaic deployment targets, likewise depends on accurate historical radiation records to rank candidate sites and forecast plant output. And climate modellers have long noted that global models tend to underestimate the direct radiative effects of aerosols over India, a discrepancy that ground-based calibration studies like this one help to quantify and ultimately correct.

What makes the study particularly valuable is its provenance. The data come from the India Meteorological Department’s own operational network, the same institution whose 150-year history of observation underpins much of South Asian climatology, and the daily radiation records are available through the department’s data service portal in Pune for researchers who follow the prescribed procurement procedure. By grounding a century-old empirical relationship in four decades of modern measurements and testing it with a rigorous multi-metric framework, the authors have delivered both a practical toolkit, regionally tuned coefficients that any Indian water manager or solar planner can adopt, and a warning written in the language of statistics: the sunlight reaching India’s surface is fading at many stations, and the models we use to track it must be recalibrated to see that clearly.

Subject of Research: Calibration of the Ångström–Prescott solar radiation model and long-term surface solar radiation trends across India

Article Title: Calibration and long-term trends of the Ångström-Prescott model for surface solar radiation across India

Article References: Misra, A. K., Ghosh, K., Karale, M., & Kumar, A. (2026). Calibration and long-term trends of the Ångström-Prescott model for surface solar radiation across India. Theoretical and Applied Climatology, 157(10), Article 639. https://doi.org/10.1007/s00704-026-06567-3

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06567-3

Keywords: Ångström–Prescott model, solar radiation, India, sunshine duration, aerosols, solar dimming, FAO-56, Mann–Kendall trend test, India Meteorological Department, evapotranspiration, Indo-Gangetic Plain, Global Performance Index

The research, conducted by Mónica F. Cisternas, an independent researcher based in Stephenville, Texas, and Ernesto Gianoli of the Department of Biological Sciences at Tarleton State University, took advantage of a rare opportunity to measure thermal biology where it actually happens: in the field, under natural sunlight, wind, and fluctuating temperatures, rather than in the controlled conditions of a laboratory. The team compared solitary and grouped caterpillars of the gregarious butterfly species, asking a deceptively simple question: how does the difference between a caterpillar’s body temperature and the surrounding air temperature change as air temperature changes? The answer, it turns out, depends strongly on whether the larva lives alone or in a group.

The core metric the researchers examined is known as the body–air temperature differential, essentially the gap between how hot or cold an animal’s body is and how hot or cold the air is. For ectotherms like caterpillars, this differential is shaped by a tug-of-war between heat gained from solar radiation, heat exchanged with the surrounding air, and heat generated or absorbed through metabolism and evaporative water loss. When the differential is positive, the animal is warmer than its environment, which can be beneficial on a cool morning but dangerous during a heat spike. When it is negative, the animal is cooler than the air, a state that may protect tissues from thermal stress. The researchers measured this differential across a natural gradient of air temperatures for both solitary larvae and members of aggregations, then analyzed how the two groups differed.

The results were striking in their asymmetry. Grouped caterpillars showed an overall relationship between their body–air temperature differential and air temperature, meaning their thermal status relative to the environment shifted systematically as conditions warmed. Solitary caterpillars, by contrast, showed no such overall association. Most notably, gregarious caterpillars registered significantly lower temperatures than the surrounding environment in the warmer regions of the temperature gradient. In other words, when the day heated up, the larvae in groups were literally cooler than the air around them, a relative cooling effect that solitary individuals did not display. The researchers note that the evidence for the opposite pattern, grouped caterpillars exceeding air temperature under cooler conditions, was comparatively weak in their dataset, hinting that the cooling benefit of aggregation may be more pronounced in the field than the warming benefit.

Digging deeper into the structure of the aggregations themselves, the team ran an analysis incorporating the number of larvae in each group, and here the story became even more interesting. The interaction between group size and air temperature was statistically significant even after accounting for population-level differences and the intensity of solar radiation at each microsite. The direction of the effect was clear: as air temperature increased, the thermal excess, the amount by which a caterpillar’s body temperature surpassed air temperature, declined more steeply in larger groups. Bigger aggregations, in other words, shed their relative warmth faster as the environment heated up. This suggests that the collective thermal properties of a group, such as the way many bodies alter airflow, shading, and evaporative surfaces, scale with the number of participants, amplifying the cooling effect precisely when it matters most.

Solar radiation at the microsites the caterpillars occupied also emerged as a significant predictor of thermal excess, a reminder that body temperature in small ectotherms is never determined by air temperature alone. A caterpillar basking in direct sun can be many degrees warmer than the air, while one sheltered in shade may be cooler. By including radiation in their models, the researchers could separate the genuine effect of grouping from the simple fact that groups might occupy sunnier or shadier spots. The persistence of the group-size effect after this adjustment strengthens the case that aggregation itself, not just microsite selection, drives the relative cooling. Still, the authors caution that the mechanistic basis of the pattern remains to be worked out, whether it stems from reduced convective heat exchange within clusters, shared shading, evaporative cooling, or some combination of these physical processes.

Perhaps the most conceptually intriguing result concerns the solitary caterpillars. The analysis showed that solitary individuals, but not grouped ones, behaved as thermoconformers, meaning their body temperatures closely tracked ambient temperature with little deviation. Thermoconformity is often considered the default state for small ectotherms lacking physiological or behavioral means of temperature control, but the gregarious larvae broke free of it. By clustering, they effectively decoupled their body temperatures from the ambient thermal environment, gaining a degree of thermal autonomy that a lone larva cannot achieve. From an adaptive standpoint, this decoupling could matter enormously, because enzyme function, growth rates, feeding behavior, and survival in insects are all tightly temperature dependent, and staying within a favorable thermal window can be the difference between thriving and wilting on a hot afternoon.

The study situates itself within a rich literature on the thermal ecology of social caterpillars. Earlier work on eastern tent caterpillars documented synchronized group foraging and tent-based thermoregulation tied to microclimate, while research on emperor moth caterpillars assessed the thermal and water-relations benefits of aggregation. Studies of forest tent caterpillars and processionary moths have explored how colony size shapes larval performance, and comparative work on nettle-feeding nymphalid butterflies contrasted the thermal ecologies of gregarious and solitary larvae. What sets the new study apart is its explicit field test of the cooling hypothesis. As the authors point out, prior evidence showed that aggregation in caterpillars may enhance heat gain under cool conditions, but whether it also facilitates cooling under warm conditions had remained unknown. Their data now supply that missing half of the picture, and they do so under authentic field conditions rather than in artificial settings.

The implications extend beyond one butterfly species. Larval gregariousness is widespread in the swallowtail family, Papilionidae, and previous work by the same team has shown that this lifestyle is more prevalent outside the tropics and influences traits such as larval melanism and defensive reactions. If grouping provides a two-way thermal buffer, warming cold bodies and cooling warm ones, it could help explain why gregarious living has evolved repeatedly across Lepidoptera and why it persists even when it carries costs, such as making clusters more conspicuous to predators. In an era of increasing climatic variability, a behavior that moderates thermal extremes could carry real fitness consequences, a possibility the authors flag as a priority for future research, alongside the need to evaluate how the observed cooling translates into caterpillar performance and survival.

For now, the study stands as a vivid reminder that even the humblest animals employ sophisticated physical strategies to manage their body temperatures, and that some of those strategies only make sense when many bodies act together. A single caterpillar sweltering on a leaf has few options beyond conforming to the heat. A cluster of them, by contrast, builds a collective thermal microenvironment, one that grows more effective at shedding excess heat as it grows larger. The next time a cluster of striped larvae pulses gently on a sunlit stem, consider that they may not be huddling for warmth at all. They may be air-conditioning themselves, together, one body at a time.

Subject of Research: Field evidence that larval aggregation provides relative cooling under warm conditions in gregarious caterpillars.

Article Title: Field evidence of relative cooling under warm conditions in grouped caterpillars

Article References: Cisternas, M. F., & Gianoli, E. (2026). Field evidence of relative cooling under warm conditions in grouped caterpillars. The Science of Nature, 113(5), Article 117. https://doi.org/10.1007/s00114-026-02169-1

Image Credits: AI Generated

DOI: 10.1007/s00114-026-02169-1

Keywords: caterpillars, thermoregulation, aggregation, gregariousness, Lepidoptera, body temperature, ectotherms, thermal ecology, group living, swallowtail butterfly, solar radiation, field study

The study, conducted by Hüdaverdi Gürkan of the University of Florida, the Turkish State Meteorological Service, and Adana Alparslan Turkes Science and Technology University, together with Gerrit Hoogenboom of the University of Florida’s Global Food Systems Institute, set out to answer a deceptively simple question: when NASA POWER says it rained, or reports yesterday’s maximum temperature, how closely does that match what actually happened on the ground? The answer, the researchers found, depends heavily on which variable you care about and where the point of interest sits on the map. For temperature and solar radiation, the news is overwhelmingly positive. For humidity, wind, and precipitation, geography matters enormously, and the dataset’s reliability can degrade sharply along coastlines and in mountainous terrain.

The statistical evidence for temperature is striking. Maximum daily temperature records from NASA POWER explained between 87 and 98 percent of the variance in ground observations, with root mean square errors ranging from 1.50 to 6.89 degrees Celsius. Minimum temperatures performed nearly as well, with R-squared values between 0.78 and 0.97 and errors from 1.23 to 8.37 degrees Celsius. Solar radiation estimates tracked ground measurements with R-squared values from 0.76 to 0.97 and root mean square errors between 1.73 and 3.84 megajoules per square meter. Across all temperature and radiation variables, the study reports overall R-squared values between 0.76 and 0.98, a level of agreement that the authors say establishes NASA POWER as a dependable foundation for climate modeling and agricultural decision support in most settings.

The implications for crop modeling are significant. Crop simulation models, which are used worldwide to forecast yields, evaluate irrigation strategies, and assess climate change impacts, are notoriously sensitive to input weather data. Small biases in daily minimum temperature can alter calculations of growing degree days and chilling requirements, while errors in solar radiation propagate directly into photosynthesis and evapotranspiration estimates. Previous work by Hoogenboom and colleagues, including earlier evaluations of NASA satellite-derived temperature and radiation data over the continental United States, laid the groundwork for using such datasets in agricultural applications. The new study extends that legacy by testing the modern POWER product across a far broader range of topographic and climatic settings, from the humid subtropics of Florida to the complex mountain terrain of Türkiye.

That topographic diversity is precisely where the study’s cautionary findings emerge. The researchers found that the dataset’s performance for relative humidity, wind speed, and precipitation is strongly controlled by local geography. In coastal areas, land-sea breeze circulations and marine atmospheric layers introduce discrepancies that the gridded satellite and reanalysis data struggle to capture. NASA POWER produces values on a grid, essentially averaging conditions over cells of finite size, and these spatial averages smooth over the sharp gradients that occur where land meets ocean. A weather station a few hundred meters from the shoreline can experience humidity and wind regimes that differ substantially from the grid-cell average, producing errors that would surprise a user relying on the dataset without checking it first.

High-relief terrain presents a parallel problem that atmospheric scientists call topographic smoothing. When elevation changes dramatically within a single grid cell, as it does across the mountain ranges of Anatolia or the slopes of Washington State’s Cascades, a single gridded value cannot represent the true spread of conditions from valley floor to ridge crest. The dataset’s estimates regress toward the mean of the cell, underestimating the extremes that stations actually record. This phenomenon, well documented in studies of gridded precipitation in complex terrain, means that hydrologists and agronomists working in mountainous regions should treat NASA POWER outputs for precipitation, humidity, and wind with particular skepticism, or apply bias correction before feeding them into models.

The practical value of the study lies in the regional performance thresholds it establishes. Rather than issuing a blanket verdict on the dataset, the authors provide what amounts to a decision guide: researchers can look up their variable of interest and their terrain type, and determine in advance whether raw NASA POWER data is adequate or whether bias correction is necessary. This distinction matters because bias correction is not free. It requires access to local observations, adds processing steps, and introduces its own uncertainties. Knowing that temperature and radiation can typically be used as-is, while coastal precipitation may demand correction, saves both computational effort and scientific risk. In an era when open-access geospatial datasets are increasingly substituted for sparse station networks, such interoperability benchmarks become essential infrastructure for environmental monitoring.

The validation design itself reflects a growing awareness that dataset quality assessments must span decades, not just single seasons. By drawing on records of 15 to 43 years from networks including the Florida Automated Weather Network, the Georgia Automated Environmental Monitoring Network, Washington State University’s AgWeatherNet, and the Turkish State Meteorological Service, the study captures the full range of interannual variability, El Niño and La Niña cycles, heat waves, and drought years that any operational dataset must handle. A dataset that performs well only in average years is of limited use for the extreme events that matter most to farmers and water managers. The multi-decadal approach also guards against the possibility of agreement arising by coincidence in a short window of unusually stable weather.

The research also situates NASA POWER within a crowded field of gridded climate products, including ERA5, MERRA-2, CRU TS, and CHIRPS, each with its own strengths and known weaknesses. What distinguishes POWER is its accessibility: it is free, requires no registration, and delivers daily agroclimatic variables in formats that plug directly into widely used crop models. The authors’ benchmark gives the global community of agricultural modelers, many of whom work in data-sparse regions of Africa, Central Asia, and South America, a defensible basis for choosing POWER, and a clear-eyed understanding of where it will need help. As climate change intensifies the demand for reliable weather information in agriculture, studies like this one transform a free dataset from a convenient substitute into a rigorously characterized scientific instrument.

Subject of Research: Multi-decadal validation of the NASA POWER gridded meteorological dataset against ground weather stations in the United States and Türkiye for climatology and agricultural modeling applications

Article Title: Validating NASA POWER meteorological data for applied climatology and agricultural modeling: a multi-decadal assessment across diverse topographies in the US and Türkiye

Article References: Gürkan, H., & Hoogenboom, G. (2026). Validating NASA POWER meteorological data for applied climatology and agricultural modeling: a multi-decadal assessment across diverse topographies in the US and Türkiye. Theoretical and Applied Climatology, 157(10), Article 621. https://doi.org/10.1007/s00704-026-06532-0

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06532-0

Keywords: NASA POWER, gridded meteorological data, weather station validation, applied climatology, agricultural modeling, crop simulation, solar radiation, temperature data, precipitation accuracy, topographic effects, bias correction, Türkiye