Thermal Variability Research Articles

An evaluation of intra-university campus temperature variability under variable synoptic weather conditions using mobile transects.

Intensive observations were collected in a wide range of synoptic weather conditions to evaluate variability in the intra-urban heat island on the campus of the University of North Carolina at Charlotte between February 2023 and June 2023. An easily reproducible bicycle-based mobile transit route around the university was traversed during 20 afternoon and 20 evening periods. The magnitude of observed temperature range from an individual data collection period is defined as the campus urban heat island intensity, with areas having more anthropogenic modification also having higher temperatures. While other papers have examined the relationship between the city-scale urban heat island intensity and the present weather conditions, this paper aims to disentangle the relationship between present weather conditions and the magnitude of thermal variability across a small intra-urban campus with diverse land use and land cover characteristics. This will contribute to a better understanding of intra-urban heat islands, particularly identifying days where conditions will be highly dangerous in more developed areas, and not in more natural environments. When comparing the standardized mobile-transit observations to the regionally present weather conditions it is evident that clear and calm conditions often enhance both city-scale and campus-scale heat islands, increasing temperature disparities. While the spatial distribution of warm and cool areas across campus remains relatively constant, the campus-scale heat island is significantly modulated by the present weather conditions.

Greater plasticity in CTmax with increased climate variability among populations of tailed frogs.

Temporally variable climates are expected to drive the evolution of thermal physiological traits that enable performance across a wider range of temperatures (i.e. climate variability hypothesis, CVH). Spatial thermal variability, however, may mediate this relationship by providing ectotherms with the opportunity to behaviourally select preferred temperatures (i.e. the Bogert effect). These antagonistic forces on thermal physiological traits may explain the mixed support for the CVH within species despite strong support among species at larger geographical scales. Here, we test the CVH as it relates to plasticity in physiological upper thermal limits (critical thermal maximum-CTmax) among populations of coastal tailed frogs (Ascaphus truei). We targeted populations that inhabit spatially homogeneous environments, reducing the potentially confounding effects of behavioural thermoregulation. We found that populations experiencing greater temporal thermal variability exhibited greater plasticity in CTmax, supporting the CVH. Interestingly, we identified only one site with spatial temperature variability and tadpoles from this site demonstrated greater plasticity than expected, suggesting the opportunity for behavioural thermoregulation can reduce support for the CVH. Overall, our results demonstrate one role of climate variability in shaping thermal plasticity among populations and provide a baseline understanding of the impact of the CVH in spatially homogeneous thermal landscapes.

Differential production of mitochondrial reactive oxygen species between mouse (Mus musculus) and crucian carp (Carassius carassius).

In most vertebrates, oxygen deprivation and subsequent re-oxygenation are associated with mitochondrial impairment and excess production of reactive oxygen species (ROS) like hydrogen peroxide (H2O2). This in turn triggers a cascade of cell-damaging events in a temperature-dependent manner. The crucian carp (Carassius carassius) is one of few vertebrates that survives months without oxygen at cold temperatures and overcomes oxidative damage during re-oxygenation periods. Mitochondria of this anoxia-tolerant species therefore serve as an excellent model in translational research to study adaptation and resilience to low oxygen conditions and thermal variability. Here, we used high-resolution respirometry on isolated mitochondria from hearts of crucian carp and the anoxia-intolerant mouse (Mus musculus), at 37 and 8°C; two temperatures relevant for transplantation medicine (i.e., graft preservation and subsequent rewarming). We find: (1) a striking difference in H2O2 release between the two species at 37°C despite comparable mitochondrial efficiency and capacity, (2) a massive H2O2 release after inhibition of complex V in mouse at 37°C that is absent in crucian carp, and prevented in mouse by incubation at 8°C or uncoupling with a protonophore at 37°C, and (3) indications that differences in mitochondrial complex I and II capacity and thermal sensitivity influence the release of mitochondrial H2O2 relative to respiration. Our findings provide comparative insights into a spectrum of mitochondrial adaptations in vertebrates and the importance of thermal variability. Furthermore, the species- and temperature-related changes associated with mitochondria highlighted in this study may help identify mitochondria-based targets for translational medicine.

Coordinated Planning for Multiarea Wind-Solar-Energy Storage Systems That Considers Multiple Uncertainties

As the scale of renewable energy sources (RESs) expands, it is essential to optimize the configuration of wind, solar, and storage resources across different areas. Nevertheless, the unavoidable uncertainties associated with both energy supply and demand present significant challenges for planners. This study aims to address the challenge of coordinated planning for multiarea wind-solar-energy storage systems considering multiple uncertainties. First, uncertainties related to future peak demand, thermal generation output boundaries, demand variability, and stochastic unit production are analyzed and modeled on the basis of robust optimization and stochastic programming techniques. Then, a hierarchical coordinated planning model that incorporates both system-wide (SW) and local area (LA) planning models is proposed. The SW planning model is designed to manage the optimal capacity configuration of RESs and energy storage systems (ESSs) within each LA, as well as the operational boundary of LAs. The LA planning models aim to further optimize the capacities of RESs and ESSs and minimize the economic cost within each LA on the basis of local resource characteristics. To achieve the optimal solution, the analytical target cascading (ATC) algorithm is integrated with the column-and-constraint generation (C&CG) algorithm. The simulation results validate the effectiveness and reasonableness of the proposed coordinated planning model, which not only outperforms independent planning approaches but also effectively manages the uncertainties.

Reconstructing and Hindcasting Sea Ice Conditions in Hudson Bay Using a Thermal Variability Framework

The Hudson Bay seasonal sea ice record has been well known since the advent of satellite reconnaissance, with a continuous record since 1971. To extend the record to earlier decades, a thermal variability framework is used with the surface temperature climatological records from four climate stations along the Hudson Bay shoreline: Churchill, Manitoba; Kuujjurapik, Quebec; Inukjuak, Quebec; and Coral Harbour, Nunavut. The day-to-day surface temperature variation for the minimum temperature of the day was found to be well correlated to the known seasonal sea ice distribution in the Bay. The sea ice/thermal variability relationship was able to reproduce the existing sea ice record (the average breakup and freeze-up dates for the Bay) largely within the error limits of the sea ice data (1 week), as well as filling in some gaps in the existing sea ice record. The breakup dates, freeze-up dates, and ice-free season lengths were generated for the period of 1922 to 1970, with varying degrees of confidence, adding close to 50 years to the sea ice record. Key periods in the spring and fall were found to be critical, signaling the time when the changes in the sea conditions are first notable in the temperature variability record, often well in advance of the 5/10th ice coverage used for the sea ice record derived from ice charts. These key periods in advance of the breakup and freeze-up could be potentially used, in season, as a predictor for navigation. The results are suggestive of a fundamental change in the nature of the breakup (faster) and freeze-up (longer) in recent years.

An Ocean Memory Perspective: Disentangling Atmospheric Control of Decadal Variability in the North Atlantic Ocean

AbstractAn ocean memory framework is proposed to reveal the atmosphere's influence on ocean temperatures. Anomalous atmospheric forcing alters the ocean state through two mechanisms: short‐term, local effects involving airsea heat fluxes and Ekman circulation, and long‐term, far‐field effects involving changes from overturning and gyre circulations. The framework employs the Green function's method to incorporate both effects, enabling the quantification of ocean memory and the contribution of atmospheric forcing to ocean thermal variability. The framework is employed to examine the North Atlantic Oscillation's (NAO) influence on the North Atlantic Ocean variability, including the Atlantic Multidecadal Variability, with its memory estimated to be years. The NAO and variability in the North Atlantic jet speed explain up to 30% of ocean decadal variability, primarily driven by temporal changes in ocean heat transport. Therefore, decadal fluctuations in ocean temperatures cannot be accurately modeled solely as a passive response to stochastic atmospheric forcing.

Atmospheric variability drives anomalies in the Bering Sea air-sea heat exchange

Abstract High-latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air-sea coupling plays a dominant role in driving Bering Sea upper ocean thermal variability, and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air-sea heat fluxes in the Bering Sea over the period 2010-2022 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September-April, and is primarily a result of near-surface air temperature and specific humidity anomalies. The air-mass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability, and are a result of anomalous cloud coverage, anomalous lower tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper ocean temperature variability through mediation of the surface heat fluxes during the analysis period.

Climate Classification in the Canadian Prairie Provinces Using Day-to-Day Thermal Variability Metrics

Climate Classification in the Canadian Prairie Provinces Using Day-to-Day Thermal Variability Metrics

Empirical evidence for the extent of spatial and temporal thermal variation on sea turtle nesting beaches

Recording sand temperatures has become routine at many sea turtle nesting sites across the world given the impacts of incubation temperatures on hatchling sex ratios. However, the extent of thermal variability found at a nesting site has previously received little attention. Here we examine empirical sand temperature records across five atolls extending 250 km in the Chagos archipelago, Indian Ocean, between October 2012 and July 2023 and quantify the extent of spatial and temporal thermal variability. Our results suggest that sand temperatures at our study site vary seasonally and inter-annually, between beaches in the archipelago, and within beaches in different nesting habitats. The biggest drivers of thermal variability were seasonal and inter-annual differences, which modulated sand temperatures by up to 3.00°C and 1.03°C, respectively. Intra-beach and inter-beach variability further modulated temperatures by up to 0.56°C and 0.85°C, respectively. In addition, mean monthly sand temperatures were relatively low, suggesting that hatchling sex ratios are fairly balanced. The wide range of sand temperatures recorded at this nesting site suggests that it is likely both male-biased and female-biased clutches are produced during the nesting season. Quantifying thermal variability from a long-term sand temperature time series offers valuable insight into a population with temperature-dependent sex determination and, when possible, should be considered when modelling temperature impacts on hatchling sex ratios.

Optimizing the thermal performance of phase change materials in building applications using deep reinforcement learning and Bayesian optimization

This research presents a novel methodology for Deep Reinforcement Learning (DRL) and Bayesian Optimisation of the thermal performance of PCMs in building operations. The developed models utilise a unique and large dataset comprising 1500 building thermal profiles, simulated for various climates and building setups obtained from our industry partners and as open data. PCM-based systems are deployed for thermal insulation of building envelopes to regulate indoor temperature conditions and reduce the need for heating and cooling systems, resulting in enhanced energy efficiency. Through the real-time management of the thermal efficacy of PCMs using the DRL method trained on the large dataset and fine-tuning of the underlying model parameters using Bayesian Optimisation, the optimised system achieves energy saving in heating and cooling load of up to 45 percent, along with the induced reduction in CO2 emission. At the same time, DRL contributes to decreasing the thermal fluctuation in the indoor temperature and keeps it in the narrow range of 1.2 °C in case of high thermal variability scenarios. Currently, the best performance is reported in the literature. This research exemplifies the potential of DRL and Bayesian optimisation in sustainable building. It depicts the applications of advanced intelligent computing algorithms with big building energy data as a novel, robust and superior approach for optimising real-world building energy management systems. The methodology and the improvements in energy savings in thermal and energy management of buildings highlight the novelty and potential benefit of the implemented research as a new intellectual property towards sustainable building design.

Behavioural Thermoregulation of Flowers via Petal Movement.

Widely documented in animals, behavioural thermoregulation mitigates negative impacts of climate change. Plants experience especially strong thermal variability but evidence for plant behavioural thermoregulation is limited. Along a montane elevation gradient, Argentina anserina flowers warm more in alpine populations than at lower elevation. We linked floral temperature with phenotypes to identify warming mechanisms and documented petal movement and pollinator visitation using time-lapse cameras. High elevation flowers were more cupped, focused light deeper within flowers and were more responsive to air temperature than low; cupping when cold and flattening when warm. At high elevation, a 20° increase in petal angle resulted in a 0.46°C increase in warming. Warming increased pollinator visitation, especially under cooler high elevation temperatures. A plasticity study revealed constitutive elevational differences in petal cupping and stronger temperature-induced floral plasticity in high elevation populations. Thus, plant populations have evolved different behavioural responses to temperature driving differences in thermoregulatory capacity.

Intra-Urban Induced Heating Assessment in Kuwait’s Desert Metropolis Using Explainable Machine Learning

Intra-urban induced heating (IUIH) in hot desert cities exhibits distinct patterns and complex diurnal interactions with built environment features, differing significantly from those in temperate areas and remains not fully understood. Understanding how various built environment features contribute to intra-urban thermal variability is an essential first step in developing sub-diurnal targeted heat mitigation strategies. This study presents a data-driven examination of IUIH dynamics in Kuwait’s desert metropolis. Near-surface air temperature observations were collected using high-resolution loop-type traverses at selected hours during a representative summer day to determine IUIH variability. The diurnal impacts of built environment features were modeled using an ensemble learning approach and interpreted with SHapley Additive exPlanations. Among several candidate machine learning regressors evaluated, Random Forest demonstrated strong predictive power (R2 = 0.954) with acceptable error (RMSE = 0.096, MAPE = 0.001) and least bias (MBE = 0.008). The study’s significance lies in its assessment framework that emphasizes explainability of sub-diurnal dynamics, offering detailed insights that challenge traditional assumptions and inform both immediate local climate interventions and strategic urban planning. The findings reveal that simple day-evening comparatives might overlook nuanced sub-diurnal dynamics, such as potential irrigation-induced warming by shrubs observed at mid-day and the complex trade-offs between radiative and transpirative processes by trees in the afternoon and evening. Additionally, the study identifies cooling effects associated with natural land cover, presenting a critical optimization challenge between compact and open urban forms to effectively modulate near-surface air temperatures.

Effect of thermal pretreatment on the reactivity of red mud valorized as aluminosilicate precursor for geopolymer production

Thermal pretreatment has proven to be an effective method to improve the reactivity of red mud to be valorized as an aluminosilicate precursor for geopolymer production. This approach offers the dual advantage of recovering caustic residue in red mud and encapsulating heavy metal, thus, achieving the transformation of red mud into a cleaner and value-added construction material. However, the inconsistent properties of red mud, including variations in chemical composition, particle size, and amorphous content pose challenges and can lead to instability in geopolymer as well as the effectiveness of thermal pretreatment, limiting the scalability of red mud valorization. Here in this study, thermal pretreatment was employed on five types of red mud from three refineries by calcining each red mud at 800 ○C for 2 h and its effect on the reactivity of each red mud was evaluated by comparing the performance of the resultant geopolymer. The results demonstrated a significant enhancing effect from thermal pretreatment, particularly noticeable at NaOH concentrations of 4 M and 8 M. This again highlighted the potential of thermal pretreatment in the conversion of red mud into construction material. However, amplified disparities between each thermal pretreated-red mud were also observed. To further address the challenges associated with thermal pretreatment variability, the dissolubility of reactive content from each thermal pretreated-red mud under alkali environments was quantified through alkali leaching tests and correlated to the mechanical properties of its resultant geopolymer. A strong negative correlation was observed between the concentration of Si, Al, and Fe from thermal pretreated-red mud and the mechanical properties of its resultant geopolymer. This correlation has the potential to facilitate quality control measures for thermal pretreated-red mud and its derived geopolymer, enabling better process optimization and consistency in geopolymer production.

Ocean weather, biological rates, and unexplained global ecological patterns.

As on land, oceans exhibit high temporal and spatial temperature variation. This "ocean weather" contributes to the physiological and ecological processes that ultimately determine the patterns of species distribution and abundance, yet is often unrecognized, especially in tropical oceans. Here, we tested the paradigm of temperature stability in shallow waters (<12.5 m) across different zones of latitude. We collated hundreds of in situ, high temporal-frequency ocean temperature time series globally to produce an intuitive measure of temperature variability, ranging in scale from quarter-diurnal to annual time spans. To estimate organismal sensitivity of ectotherms (i.e. microbes, algae, and animals whose body temperatures depend upon ocean temperature), we computed the corresponding range of biological rates (such as metabolic rate or photosynthesis) for each time span, assuming an exponential relationship. We found that subtropical regions had the broadest temperature ranges at time spans equal to or shorter than a month, while temperate and tropical systems both exhibited narrow (i.e. stable) short-term temperature range estimates. However, temperature-dependent biological rates in tropical regions displayed greater ranges than in temperate systems. Hence, our results suggest that tropical ectotherms may be relatively more sensitive to short-term thermal variability. We also highlight previously unexplained macroecological patterns that may be underpinned by short-term temperature variability.

Warming, stochastic diel thermal fluctuations affect physiological performance and gill plasticity in an amphibious mangrove fish.

Natural temperature variation in many marine ecosystems is stochastic and unpredictable, and climate change models indicate that this thermal irregularity is likely to increase. Temperature acclimation may be more challenging when conditions are highly variable and stochastic, and there is a need for empirical physiological data in these thermal environments. Using the hermaphroditic, amphibious mangrove rivulus (Kryptolebias marmoratus), we hypothesized that compared with regular, warming diel thermal fluctuations, stochastic warm fluctuations would negatively affect physiological performance. To test this, we acclimated fish to: (1) non-stochastic and (2) stochastic thermal fluctuations with a similar thermal load (27-35°C), and (3) a stable/consistent control temperature at the low end of the cycle (27°C). We determined that fecundity was reduced in both cycles, with reproduction ceasing in stochastic thermal environments. Fish acclimated to non-stochastic thermal cycles had growth rates lower than those of control fish. Exposure to warm, fluctuating cycles did not affect emersion temperature, and only regular diel cycles modestly increased critical thermal tolerance. We predicted that warm diel cycling temperatures would increase gill surface area. Notably, fish acclimated to either thermal cycle had a reduced gill surface area and increased intralamellar cell mass when compared with control fish. This decreased gill surface area with warming contrasts with what is observed for exclusively aquatic fish and suggests a preparatory gill response for emersion in these amphibious fish. Collectively, our data reveal the importance of considering stochastic thermal variability when studying the effects of temperature on fishes.

Oxidative stress across multiple tissues in house sparrows (Passer domesticus) acclimated to warm, stable cold, and unpredictable cold thermal treatments.

With climate change increasing not just mean temperatures but the frequency of cold snaps and heat waves, animals occupying thermally variable areas may be faced with thermal conditions for which they are not prepared. Studies of physiological adaptations of temperate resident birds to such thermal variability are largely lacking in the literature. To address this gap, we acclimated winter-phenotype house sparrows (Passer domesticus) to stable warm, stable cold, and fluctuating cold temperatures. We then measured several metrics of the oxidative stress (OS) system, including enzymatic and non-enzymatic antioxidants and lipid oxidative damage, in brain (post-mitotic), kidney (mitotic), liver (mitotic) and pectoralis muscle (post-mitotic). We predicted that high metabolic flexibility could be linked to increases in reactive oxygen damage. Alternatively, if variation in ROS production is not associated with metabolic flexibility, then we predict no antioxidant compensation with thermal variation. Our data suggest that ROS production is not associated with metabolic flexibility, as we found no differences across thermal treatment groups. However, we did find differences across tissues. Brain catalase activity demonstrated the lowest values compared with kidney, liver and muscle. In contrast, brain glutathione peroxidase (GPx) activities were higher than those in kidney and liver. Muscle GPx activities were intermediate to brain and kidney/liver. Lipid peroxidation damage was lowest in the kidney and highest in muscle tissue.

Thermal and precipitation variability across four seasons in Poland (1951–2020)

Abstract This paper shows spatial variability of temperature and precipitation conditions across the four seasons in Poland and examines long-term trends in these parameters. The spatial variability of temperature in Poland is caused primarily by the clash of oceanic air masses from the west and continental air masses from the east. The spatial distribution of precipitation depends strongly on the relief and altitude above sea level. The seasons are generally getting warmer. However, average temperatures increase over time at different rates and levels of significance. Except in winter, no statistically significant trends were found in the seasonal precipitation totals. Seasons are periods when certain climatic conditions prevail. Depending on the criteria adopted, different types of seasons can be distinguished, such as meteorological, thermal, and calendar seasons. These are considered in this research. Consequently, different time frames of seasons result in varying values and patterns of meteorological characteristics. In this research, this concept is presented using Poland as an example.

Physiological responses to a changing winter climate in an early spring-breeding amphibian.

Climate change is swiftly altering environmental winter conditions, leading to significant ecological impacts such as phenological shifts in many species. As a result, animals might face physiological mismatches due to longer or earlier activity periods and are at risk of being exposed to late spring freezes. Our study points for the first time to the complex physiological challenges that amphibians face as a result of changing thermal conditions due to winter climate change. We investigated the physiological responses to a period of warmer winter days and sudden spring freeze in the common toad (Bufo bufo) by acclimating them to 4°C or 8°C for 48 h or exposing them to 4°C or -2°C for 6 h, respectively. We assessed the daily energy demands, determined body condition and cold tolerance, explored the molecular responses to freezing through hepatic tissue transcriptome analysis, and measured blood glucose levels. Toads acclimated to higher temperatures showed a higher daily energy expenditure and a reduced cold tolerance suggesting faster depletion of energy stores and the loss of winter acclimation during warmer winters. Blood sugar levels were higher in frozen toads indicating the mobilization of cryoprotective glucose with freezing which was further supported by changed patterns in proteins related to glucose metabolism. Overall, our results emphasize that increased thermal variability incurs physiological costs that may reduce energy reserves and thus affect amphibian health and survival. This might pose a serious threat to breeding adults and may have subsequent effects at the population level.

Testing metabolic cold adaptation and the climatic variability hypothesis in two latitudinally distant populations of a supratidal water beetle

Temperature significantly impacts ectotherm physiology, with thermal tolerance and metabolic traits typically varying with latitude across species ranges. The drivers of this variation remain unclear, however, despite obvious consequences for population persistence and conservation in the face of ongoing global change. This study explored local adaptation and phenotypic plasticity of metabolic rates and thermal limits in the supratidal rockpool beetle Ochthebius lejolisii. Using populations from localities at different ends of the species range that experience contrasting thermal variability, we simultaneously tested two of the major paradigms of spatial physiological ecology: metabolic cold adaptation (MCA) and the climatic variability hypothesis (CVH). Reciprocal acclimation was conducted under spring temperature regimes of both localities, incorporating local diurnal variation. Metabolic rates were measured by closed respirometry, and thermal tolerance limits estimated through thermography. In line with MCA, the higher-latitude population (colder climate) showed higher metabolic rates and temperature coefficients (Q10s) at lower temperatures than the lower-latitude population. As predicted by the CVH, the lower-latitude population (more variable climate) showed higher upper thermal tolerance but only the higher-latitude population was able to acclimate upper thermal limits. This result suggests trade-offs between physiological thermal limits and thermal plasticity in this species. A limited acclimation capacity could make populations on Mediterranean coasts especially vulnerable in the face of projected increases in extreme temperatures under ongoing climate change.

Variability in oceanographic conditions affecting Mesophotic Ecosystems along the South Eastern Pacific: Latitudinal trends and potential for climate refugia

Oceans have been changing at the fastest pace since the beginning of the Holocene. The South Eastern Pacific (SEP), including the Humboldt Upwelling Ecosystem (HUE) is subject to changes in upwelling winds, temperature, El Niño, and the ever-increasing local anthropogenic stressors, all of which have been documented for surface coastal waters where in-situ and remote observations are readily available. Temporal and spatial changes in the adjacent deeper waters where diverse Mesophotic Ecosystems are found have been scarcely documented. These marine ecosystems have been the focus of ecological studies for less than two decades. Here we provide an overview of the thermal variability at mesophotic depths and assess their potential as climatic refugia along all SEP ecoregions. We analyzed a time series of temperature and salinity from a 19 yr reanalysis based on remote and in-situ observations (CTD, ARGO, XBTs, moorings) to quantify variability in the Tropical (0–5°S), Northern Warm Temperate (5–30°S); Southern Warm Temperate (30–39.5°S) and Magellanic subregions (39.5–45°S), at two mesophotic depth strata (50 and 100 m), and a reference surface (5 m) depth. We assessed variability in the seasonal, interannual (El Niño) and ‘long-term’ (ca. 20 yr) scales, and the relationship with wind velocities. The thermal depth gradient between surface and mesophotic depths did not change smoothly with latitude but peaked within the northern portion of the warm temperate subregion, decreasing towards lower and higher latitudes. Seasonal variation in temperature was also largest in the north and south temperate subregions and minimal in the Magellanic subregion. Depth dampening of seasonal temperature variation was also strengthened at intermediate latitudes and much reduced in the tropics, where seasonal variation at mesophotic depths was similar to that at the surface. The strong interannual El Niño events were identified at all depths in tropical and temperate subregions, with stronger standardized effects at mesophotic layers than at the surface. Long-term (ca. two decades) temperature trends were significant and changed direction from warming to cooling along the SEP but were generally patchier at mesophotic layers. Spatial temperature gradients have remained relatively stable over the past two decades and were stronger at the surface than at mesophotic depths, and stronger within the tropics than in all other subregions. Surprisingly, the velocity of climate change was patchier and generally faster at mesophotic layers than at the surface. We conclude that, judging solely by physical environmental conditions, mesophotic ecosystems may be used by species with very different temperature affinities in temperate subregions, while in the tropics, more overlap in temperature affinities of component species may be found. Importantly, while the seasonal amplitude is reduced at mesophotic depth in most subregions, except the tropics, interannual disturbances affect mesophotic depths at least as strongly as they do surface waters and climate change velocities are faster at mesophotic depths than at surface. Thus, these ecosystems are not sheltered from inter-annual and longer-term forcing and their biotas might be more vulnerable to climate change than shallow coastal ecosystems.