Surface Temperature Variability Research Articles

Multi-decadal climate variability and satellite biases have amplified model-observation discrepancies in tropical troposphere warming estimates

Most coupled model simulations substantially overestimate tropical tropospheric warming trends over the satellite era, undermining the reliability of model-projected future climate change. Here we show that the model-observation discrepancy over the satellite era has arisen in large part from multi-decadal climate variability and residual biases in the satellite record. Analyses indicate that although the discrepancy is closely linked to multi-decadal variability in the tropical Pacific sea surface temperatures, the overestimation remains over the satellite era in model simulations forced by observed time-varying sea surface temperatures with a La Niña-like pattern. Regarding moist thermodynamic processes governing tropical tropospheric warming, however, we find a broad model-observation consistency over a post-war period, suggesting that residual biases in the satellite record may contribute to model-observation discrepancy. These results underscore the importance of sustaining an accurate long-term observing system as well as constraining the model representation of tropical Pacific sea surface temperature change and variability.

Temporal variability of sea surface temperature affects marine macrophytes range retractions as well as gradual warming

Record mean sea surface temperatures (SST) during the past decades and marine heatwaves have been identified as responsible for severe impacts on marine ecosystems, but the role of changes in the patterns of temporal variability under global warming has been much less studied. We compare descriptors of two time series of SST, encompassing extirpations (i.e. local extinctions) of six cold-temperate macroalgae species at their trailing range edge. We decompose the effects of gradual warming, extreme events and intrinsic variability (e.g. seasonality). We also relate the main factors determining macroalgae range shifts with their life cycles characteristics and thermal tolerance. We found extirpations of macroalgae were related to stretches of coast where autumn SST underwent warming, increased temperature seasonality, and decreased skewness over time. Regardless of the species, the persisting populations shared a common environmental domain, which was clearly differentiated from those experiencing local extinction. However, macroalgae species responded to temperature components in different ways, showing dissimilar resilience. Consideration of multiple thermal manifestations of climate change is needed to better understand local extinctions of habitat-forming species. Our study provides a framework for the incorporation of unused measures of environmental variability while analyzing the distributions of coastal species.

External factors driving surface temperature changes above geothermal systems: answers from deep learning

Introduction: The surface expression of enhanced geothermal heat fluxes above an active hydrothermal system causes a surface thermal anomaly (ΔT). The thermal anomaly is expressed by the difference between the temperature within the heated zone (Th) and the temperature of non-heated surfaces (T0). Given that the resulting thermal anomaly at the surface is of extremely low magnitude (1°C–5°C at Vulcano, Italy), it is extremely sensitive to overprinting by external factors, namely, meteorological influences on surface temperature variation, such as solar heating, wind and rain.Methods: To test the sensitivity of the surface to external drivers, we installed two surface temperature measurement stations within the Vulcano’s Fossa crater, one inside the thermal anomaly and one outside (separation = 50 m), with a weather station co-located with the T0 station. Time series of Th and T0 were collected for 2020, when the Vulcano Fossa hydrothermal system was at a low and stable level of activity so that external drivers would have been the main influences on Th and T0, and hence also ΔT. To test for divergence from normality in terms of diurnal and seasonal variations in Th and T0, and the role of external factors in causing abnormality, we used the deep learning engine DITAN: a domain-agnostic framework to detect and interpret anomalies in time-series data.Results: During the year, DITAN found 16 cases of two types of meteorological events: intense low-pressure systems and high-intensity rainstorms (cloudbursts). Passage of 13 abnormal low-pressure systems were detected (10 between February and May, and three in December), with three abnormal rainstorm events (all in December); all three being coincident with the abnormal low pressure events. We find just two abnormalities in the time series for of Th and T0, both of which coincide with passage of abnormal low-pressure systems, and neither of which coincide with abnormal rain events. We conclude that diurnal and annual heating and cooling cycles, subject to normal meteorological inputs and at a surface above a geothermal-heated source, are immune to anomalous behaviour to the external (meteorological) variations.

Past orbital evolution and its effects on the surface of (162173) Ryugu

ABSTRACT The Japanese probe Hayabusa 2 recently visited the NEA (162173) Ryugu. This mission provided valuable information about the asteroid, including in situ images and a surface sample brought back to the Earth. The data suggests that Ryugu has likely been affected by space weathering, but the underlying cause of the surface modification remains unclear. This paper aims to shed light on the problem by providing new information about the possible past orbital path of Ryugu. We used a procedure to estimate how Ryugu has dynamically evolved since it entered the NEAs’ region and whether this can explain the observed data. We have conducted numerical integrations of the N-body gravitational problem. The system comprises the Sun, the Solar system’s eight planets, and a group of 29 000 test particles initially placed in the main asteroidal belt (MAB) near the ν6 secular resonance. We then tracked the particles that left the MAB and eventually arrived close to Ryugu’s current orbit. Our analysis showed that out of 307 clones of Ryugu, only three came very close to the Sun at a distance of less than 0.1 au. Consequently, it is unlikely that Ryugu has undergone significant surface temperature variations. We also computed that ∼70 per cent of the clones have spent more than 5 Myr at an equivalent distance of 1 au from the Sun. This result suggests that Ryugu has been exposed to significant amounts of solar radiation over a long period, which may have resulted in space weathering effects on its surface.

Development of a micro-infrared thermometry method for surface temperature distribution and variation of millimeter particle during high-temperature reaction

Temperature strongly affects the conversion efficiency, local reactivity, and particle stabilization of the reactions, particularly at high temperature. This study integrated infrared thermography with a high-temperature hot stage reactor to develop a methodology of continuous temperature measurement for a single particle reaction at high temperatures. The external optical transmission transmittance and temperature field core were corrected, and the relationship between the measured temperature (Tr) and true temperature (T0) was obtained by adjusting the sample emissivity. Sample temperature with known emissivity at elevated temperature was measured with 1% deviation. The instantaneous temperature measurement for the gasification process was carried out and the overall emissivities of coal particles were corrected. Temperature distribution and variation on the coal particle surface during the gasification process were further obtained and consistent with the previous research results. The proposed online temperature measurement method provides a new approach for gaining insights into particle reaction states.

Variability of the Indian Ocean Dipole post-2100 reverses to a reduction despite persistent global warming

Previous examination of the Indian Ocean Dipole (IOD) response to greenhouse warming shows increased variability in the eastern pole but decreased variability in the western pole before 2100. The opposing response is due to a shallowing equatorial thermocline promoting sea surface temperature (SST) variability in the east, but a more stable atmosphere decreasing variability in equatorial zonal winds that weakens SST variability in the west. Post-2100, how the IOD may change remains unknown. Here we show that IOD variability weakens post-2100 in majority of models under a long-term high emission scenario to 2300. Post-2100, the atmosphere stability increases further and persistent ocean warming arrests or even reverses the eastern Indian Ocean shallowing thermocline. These changes conspire to drive decreased variability in both poles, reducing amplitude of moderate, strong and early-maturing positive IOD events. Our result highlights a nonlinear response of the IOD to long-term greenhouse warming under the high emission scenario.

Assessing satellite-derived wind speeds: insights from buoy measurements and analysis of deviation factors

ABSTRACT To evaluate the latest generation of satellite wind speed from AMSR2, ASCAT, GMI, SSMIS, SMAP, and WindSat, buoy measurements were obtained from buoys in coastal and tropical open ocean areas. Root mean square errors were calculated, resulting in values of 1.19 m/s for AMSR2, 1.25 m/s for ASCAT, 1.37 m/s for GMI, 1.38 m/s for SSMIS, 2.48 m/s for SMAP, and 1.18 m/s for WindSat. Numerous data pairs fall above the 45-degree line, mainly due to decreased buoy ac-curacy during high winds. Factors contributing to this include underestimation of buoy readings due to rough sea states and wind profile distortion. Satellite biases exhibit unimodal fluctuations over a one-year cycle, aligning with annual sea surface temperature variations. Statistical effects in extreme wind speed range cause abnormal fluctuations in statistics. Higher latitudes experi-ence larger deviations due to rough sea state. Ocean currents affect satellite wind speed observa-tions, particularly when aligned with wind direction. Coastal wind speed gradients primarily influenced from land contamination like rugged mountainous terrain along the West Coast of North America. Coastal upwelling also contributes to bias, with the west coast showing higher bias. A global comparison between SMAP and WindSat retrieval wind speeds demonstrates SMAP’s poor ability to monitor general wind speeds and validates the satellite-buoy experiment.

Local summer temperature changes over the past 440 ka revealed by the total air content in the Antarctic EPICA Dome C ice core

Abstract. Seasonal temperature reconstructions from ice cores are missing over glacial–interglacial timescales, preventing a good understanding of the driving factors of Antarctic past climate changes. Here the total air content (TAC) record from the Antarctic EPICA Dome C (EDC) ice core is analyzed over the last 440 ka (thousand years). While the water isotopic record, a tracer for annual mean surface temperature, exhibits a dominant ∼100 kyr cyclicity, the TAC record is associated with a dominant ∼40 kyr cyclicity. Our results show that the TAC record is anti-correlated with the mean insolation over the local astronomical summer half-year. They also show for the first time that it is highly anti-correlated with local summer temperature simulated with an Earth system model of intermediate complexity. We propose that (1) the local summer insolation controls the local summer temperature; (2) the latter, through the development of temperature gradients at the near-surface of the ice sheet (<2 m), is affecting the surface snow structure; and (3) those snow structure changes propagating down to the bottom of the firn through densification are eventually controlling the pore volume at the bubble close-off and consequently the TAC. Hence, our results suggest that the EDC TAC record could be used as a proxy for local summer temperature changes. Also, our new simulations show that the mean insolation over the local astronomical summer half-year is the primary driver of Antarctic summer surface temperature variations, while changes in atmospheric greenhouse gas (GHG) concentrations and Northern Hemisphere (NH) ice sheet configurations play a more important role in Antarctic annual surface temperature changes.

Spatial and Temporal Variations in Land Surface Temperature as an Indicator of Learning Comfort Level in Banten Province

Increasing population and rapid development of built-up land can cause an increase in land surface temperature. These changes are often associated with many factors, including changes in land use, and surface parameters, economic development, and vegetation. This research aims to analyze the temperature factor as an indicator of indoor thermal comfort to support the learning process in schools in the Banten Province area. This research uses a spatial temporal approach with descriptive statistical analysis. Based on the results, show that the land surface temperature at each school location in Banten province shows conditions that are not constant. The number of schools with uncomfortable conditions varies from 2019 (89.07%), 2020 (42.65%), 2021 (45.66%), 2022 (82.66%), and 2023 (52.44%). This shows that there has been a decrease in uncomfortable conditions for studying by 36.63% in the last 5 years.

Analysing Spatiotemporal Variability of Chlorophyll-a Concentration and Water Surface Temperature in Coastal Lagoons of the Ebro Delta (NW Mediterranean Sea, Spain)

Coastal lagoons are highly productive transitional water bodies threatened by human factors and vulnerable to global climate change effects. Monitoring biophysical parameters in these ecosystems is crucial for their preservation. In this work, we used Sentinel-2 and Landsat imagery combined with in situ data to (1) develop preliminary algorithms for retrieving the Chl-a concentration and water surface temperature of six lagoons located in the Ebro Delta (NE Mediterranean Sea, Spain), and to (2) compute maps and trend lines for analysing their spatiotemporal evolution from 2015 to 2022. Our findings showed that the algorithms’ accuracy ranged from 72% to 78% and had limited potential under high Chl-a concentration regimes. Even so, they revealed the lagoons’ trophic status, usual fluctuations, and deviations of both parameters attributed to seasonal (i.e., light and temperature) and short-term physical (i.e., winds) forcing, as well as valuable spatial patterns potentially useful for conservation efforts and land use planning. Future work will focus on the acquisition of a larger in situ data sample under a range of environmental conditions to improve the algorithms’ robustness, which in turn will allow the investigation of natural and human factors controlling the dynamics of the two investigated parameters.

Combining Neural Networks and CMIP6 Simulations to Learn Windows of Opportunity for Skillful Prediction of Multiyear Sea Surface Temperature Variability

AbstractWe use neural networks and large climate model ensembles to explore predictability of internal variability in sea surface temperature (SST) anomalies on interannual (1–3 years) and decadal (1–5 and 3–7 years) timescales. We find that neural networks can skillfully predict SST anomalies at these lead times, especially in the North Atlantic, North Pacific, Tropical Pacific, Tropical Atlantic and Southern Ocean. The spatial patterns of SST predictability vary across the nine climate models studied. The neural networks identify “windows of opportunity” where future SST anomalies can be predicted with more certainty. Neural networks trained on climate models also make skillful SST predictions in reconstructed observations, although the skill varies depending on which climate model the network was trained. Our results highlight that neural networks can identify predictable internal variability within existing climate data sets and show important differences in how well patterns of SST predictability in climate models translate to the real world.

Analyzing the thermal performance of transient heat transfer mechanism due to the combined effects of solar energy and variable surface temperature: Growing applications of solar energy in co-axial pipes

The current analysis is carried out to study the laminar convective heat transfer characteristics that change with time in the co-axial pipes along the impact of heat radiation and variable surface temperature. The flow is assumed along the axial direction of the pipe, and variable boundary condition is assumed at the surface of the pipe due to the variable surface temperature. A two-dimensional mathematical model made up of non-linear partial differential equations is solved using the implicit finite difference method. The project involves predicting the thermal efficiency of a pipe's time dependent flow across a number of flow model-relevant parameter ranges. Graphical representations highlighted the derived predictions. After separating the numerical solutions into the time independent and the time dependent components, the time dependent energy and surface shearness were found using the data from the time independent component. Comprehensive detail of the obtained results for the non-dimensional parameters included in the flow formulation is predicted for steady state velocity, temperature distribution, time dependent surface sheerness, and time dependent energy sheerness, which is given in results and discussion section of the manuscript. Major focus is given on the influence of the radiation parameter on the above-mentioned primary measures. Furthermore, it is concluded that in all cases, the steady state flow is as R→∞ and velocity profile as U→1 and θ→0, which ensured the accuracy of the obtained results by satisfying the boundary conditions. For various values of the fluid's absorption parameter D = 1.0, 3.0, 5.0, and 10.0, the flow profile is increased and U→1 as R→∞. Simultaneously, thermal distribution also increases and θ→0 as R→∞.

Spatio-temporal analysis of LST, NDVI and SUHI in a coastal temperate city using local climate zone

Extreme heat due to changing climate poses a new challenge for temperate climates. The challenge is further aggravated by inadequate research, policy, or preparedness to effectively respond and recover from its impacts. While urban morphology is crucial in mitigating urban heat, it has received limited attention in urban planning, highlighting the need for further exploration, particularly in temperate regions. To illustrate the challenge and its potential mitigations, we use the example of the coastal temperate city of Cardiff. To establish the interrelations between urban morphology and urban heat island patterns, we explored the spatiotemporal variations in land surface temperature (LST), normalised difference vegetation index (NDVI), and surface urban heat island (SUHI) to local climate zone (LCZ) classification for Cardiff. Results showed a significant variation in SUHI in the LCZ zones. Both LST and NDVI land were found to vary significantly across the LCZ zones demonstrating their association with the urban form and morphology of the locality. For built-up areas, a more compact built-environment with smaller vegetation cover and larger building density was 2.0 °C warmer than the open built-environment when comparing the mean summer LSTs. On average, the natural classes exhibit a LST that is 8.0 °C lower than the compact built-environment and 6.0 °C lower than the open built-environment. Consequently, the high-density, built-up LCZs have a greater SUHI effect compared to the natural classes. Therefore, temperate climate cities will benefit from incorporating an open built-environment that has sufficient greenery and open spaces. These findings help determine the optimal urban form for temperate climates and develop heat mitigation strategies while planning, designing, or improving the new and existing urban areas. In addition, the LCZ map applied in this study for Cardiff will enable international comparison and testing of proven climate change adaptation and mitigation techniques for similar urban areas.

The examination of the relationship between land cover and land surface temperature in Karang Baru Sub-District, Aceh Province, Indonesia

Abstract Land cover change can lead to variations in land surface temperature, primarily because different materials have varying capacities to receive, absorb, and re-emit solar radiation. Karang Baru, situated as the capital of Aceh Tamiang Regency near North Sumatra, one of the most densely populated Regency, has been experiencing continuous development since 2002, following its separation from East Aceh Regency. The development in Karang Baru has resulted in a noticeable influence on land surface temperature. The primary objective of this study is to investigate the relationship between land cover and land surface temperature in Karang Baru from 2002 to 2022. This research classified land cover using the supervised classification method employing the Maximum Likelihood Algorithm, and land surface temperature was estimated using the Split Window Algorithm method. Subsequently, simple regression analysis in this context indicates a quantitative approach to understanding the relationship between land cover and land surface temperature in Karang Baru, providing valuable insights for environmental and urban planning considerations. The findings of this research indicate that the type of land cover indeed influences the land surface temperature in Karang Baru. In summary, this study establishes that land cover can substantially impact the regional surface temperature, with temperature increases associated with surfaces featuring buildings, roads, fields, or similar materials. In contrast, vegetated surfaces tend to exhibit lower land surface temperatures in the area.

Multi‐Year Potential Predictability of the Wintertime Heavy Precipitation Potentials in East Asia

AbstractWe validate the multiyear potential predictability of wintertime heavy precipitation potential in East Asia by combining initialized decadal hindcasts of the global climate model and large ensemble simulations from a high‐resolution global atmospheric model. By analyzing a set of initialized hindcasts, the major predictive components of sea surface temperature (SST) variability beyond interannual timescales are identified as high‐latitudes multidecadal variability and the so‐called trans‐basin variability (TBV). A set of 100 ensemble simulations using a high‐resolution atmospheric model showed a significantly large signal‐to‐noise ratio for the wintertime heavy precipitation potential in East Asia, which is closely related to the TBV. When the SST around the maritime continent is higher, the anomalously low pressure in the northwestern Pacific enhances low‐level cold air transport due to the winter monsoon. Consequently, the resultant weaker baroclinicity in the lower atmosphere reduces storm activity and wintertime heavy precipitation potential in East Asia.

ECR Spotlight – Agnès Lewden

ECR Spotlight is a series of interviews with early-career authors from a selection of papers published in Journal of Experimental Biology and aims to promote not only the diversity of early-career researchers (ECRs) working in experimental biology but also the huge variety of animals and physiological systems that are essential for the ‘comparative’ approach. Agnès Lewden is an author on ‘ Changes in body surface temperature reveal the thermal challenge associated with catastrophic moult in captive gentoo penguins’, published in JEB. Agnès is a post-doctoral fellow in the lab of Dr Aude Leynaert and Dr Antoine Stier at IUEM – LEMAR – Technopole Brest Iroise, France, investigating captive and wild populations of penguins to understand core and body surface temperature variations in the function of physiological state and environmental parameters.

Contribution of Atmospheric Factors in Predicting Sea Surface Temperature in the East China Sea Using the Random Forest and SA-ConvLSTM Model

Atmospheric forcings are significant physical factors that influence the variation of sea surface temperature (SST) and are often used as essential input variables for ocean numerical models. However, their contribution to the prediction of SST based on machine-learning methods still needs to be tested. This study presents a prediction model for SST in the East China Sea (ECS) using two machine-learning methods: Random Forest and SA-ConvLSTM algorithms. According to the Random Forest feature importance scores and correlation coefficients R, 2 m air temperature and longwave radiation were selected as the two most important key atmospheric factors that can affect the SST prediction performance of machine-learning methods. Four datasets were constructed as input to SA-ConvLSTM: SST-only, SST-T2m, SST-LWR, and SST-T2m-LWR. Using the SST-T2m and SST-LWR, the prediction skill of the model can be improved by about 9.9% and 9.43% for the RMSE and by about 8.97% and 8.21% for the MAE, respectively. Using the SST-T2m-LWR dataset, the model’s prediction skill can be improved by 10.75% for RMSE and 9.06% for MAE. The SA-ConvLSTM can represent the SST in ECS well, but with the highest RMSE and AE in summer. The findings of the presented study requires much more exploration in future studies.

Moderate Indian Ocean Dipole dominates spring fire weather conditions in southern Australia

Patterns of the Indian Ocean Dipole (IOD) exhibit strong diversity, ranging from being dominated by the western tropical Indian ocean (WTIO) to by the eastern tropical Indian ocean. How the different types of the IOD variability patterns affect Australian fires differently is unknown, nor is it certain how the impacts may change under greenhouse warming. Here, we find that the moderate IOD, dominated by WTIO sea surface temperature (SST) variability, plays a primary role in affecting southern Australian fire weather conditions during austral spring. During a positive moderate IOD, broad-scaled warm SST anomalies in WTIO force an atmospheric stationary Rossby wave with a high-pressure anomaly over southern Australia. This elevated pressure and associated anomalous atmospheric conditions provide suitable fire weather with hot, dry, and windy conditions, raising fire risks in southern Australia. Such impact is distinctively different from that strong IOD-induced. As predicted by climate models, decreased moderate IOD variability in the future will result in weakened Australian fire weather responses.

Analysis of scuffing through temperature measurement experiment and numerical simulation for spiral bevel gears

Tooth surface scuffing failure, as one of the primary failure modes of gears, frequently occurs during the operation of gear mechanisms. Scuffing properties of spiral bevel gears were investigated through a numerical analysis and experimental study. A novel temperature model for a single tooth was proposed to predict scuffing temperatures on the tooth surface. The model allows the analysis of variations in tooth surface temperature, considering both operating conditions and tooth contact scenarios. Experiments were carried out to explore tooth surface adhesion of spiral bevel gears under precisely defined operating conditions. Measurement of tooth surface temperatures was conducted by combining non-contact infrared temperature sensors and temperature-measuring cameras. This experiment verifies temperature changes on the tooth surface adhesion of spiral bevel gears. The combination of two temperature measurement methods ensures accurate temperature measurements, with errors below 8%, and facilitates the swift opening of the end cover. Experimental validation of the scuffing prediction model yields a maximum temperature difference of 5.93%. The method establishes a theoretical foundation for evaluating tooth surface adhesion of spiral bevel gears.

Numerical Modeling of Atmospheric Temperature and Stratospheric Ozone Sensitivity to Sea Surface Temperature Variability

The results of numerical experiments with a chemistry–climate model of the lower and middle atmosphere are presented to study the sensitivity of the polar stratosphere of the Northern and Southern Hemispheres to sea surface temperature (SST) variability, both as a result of interannual variability associated with the Southern Oscillation, and because of long-term increases in SST under global warming. An analysis of the results of model experiments showed that for both scenarios of SST changes, the response of the polar stratosphere for the Northern and Southern Hemispheres is very different. In the Arctic, during the El Niño phase, conditions are created for the polar vortex to become less stable, and in the Antarctic, on the contrary, for it to become more stable, which is expressed in a weakening of the zonal wind in the winter in the Arctic and its increase in the Antarctic, followed by a spring decrease in temperature and concentration of ozone in the Antarctic and their increase in the Arctic. Global warming creates a tendency for the polar vortex to weaken in winter in the Arctic and strengthen it in the Antarctic. As a result, in the Antarctic, the concentration of ozone in the polar stratosphere decreases both in winter (June–August) and, especially, in spring (September–November). Global warming may hinder ozone recovery which is expected as a result of the reduced emissions of ozone-depleting substances. The model results demonstrate the dominant influence of Brewer–Dobson circulation variability on temperature and ozone in the polar stratosphere compared with changes in wave activity, both with changes in SST in the Southern Oscillation and with increases in SST due to global warming.