Surface Temperature Radiation Research Articles

Field-Layer Vegetation and Water Table Level as a Proxy of CO2 Exchange in the West Siberian Boreal Bog

The Mukhrino field station has participated in the national project on the inventory of carbon fluxes and pools in the terrestrial ecosystems of Russia since 2022. The development of a network of measurements of CO2 fluxes and phytomass covered six types of bog ecosystems typical to Western Siberia. The gross ecosystem exchange (GEE) of the field-layer vegetation (medians for the period from the end of May to the end of July, mgC m−2 h−1; see errors in Results section) decreased in series: Sphagnum bog with sparse low pine trees (“Open bog”), ridges in ridge-hollow patterned bogs (“Ridge”), pine-dwarf shrub-Sphagnum bog (“Tall ryam”), hollows in patterned bogs (“S.hollow”, “E.hollow”) and pine-dwarf shrub-Sphagnum bog (“Ryam”): −220, −200, −125, −120, −109 and −86, respectively. Ecosystem respiration (Reco) here was 106, 106, 182, 55, 97 and 136. The aboveground and belowground phytomass of mosses in this series varied between 368 ± 106–472 ± 184 and 2484 ± 517–6041 ± 2079 g/m2, respectively: the aboveground phytomass of vascular plants and plant litter—15 ± 7–128 ± 95 and 10 ± 6–128 ± 43, respectively. According to the results of mathematical modeling, the best proxy for GEE, in addition to photosynthetically active radiation and soil surface temperature, was the aboveground phytomass of vascular plants (PhV), and for Reco—PhV and the mass of the plant litter of vascular plants.

Evaluation and thermal performance of cool pavement under desert weather conditions: Surface albedo enhancement and carbon emissions offset

Surfaces such as pavement, buildings, and other heat-absorbing surfaces that store more heat than natural vegetation generate the Urban Heat Island (UHI) effect. Temperatures are known to be significantly higher in urbanized areas compared to rural ones.The application of a reflective surface treatment to the pavement improves its solar reflectivity while lowering the warmth of its surface. The main objective of this study is to assess the performance of a cool pavement in an educational complex parking area, under desert climatic conditions to reduce heat islands. White and high reflective material was applied to the tested parking pavement area. Various experimental techniques were used to assess the performance of non treated (baseline) and treated (cool) pavements including spectral radiation, reflectance (albedo), solar irradiance, and pavement surface temperature. The results show that the coated pavement has a 15 % reflectance in ultraviolet A (UVA) and the untreated pavement has a 17 % solar reflectance (baseline basement). There are no potential dangers to human health posed by the coated pavement's reflection of UVA (For visible wavelengths, coated pavement has a reflectance of roughly 70 %, while uncoated pavement has a reflectivity of only 24 %. Under desert climatic conditions, the results show a net decrease in surface temperature of the coated pavement by up to 15 °C compared to the uncoated one. In the summer, for example, raising the albedo of the pavement surface from 24 % to 70 % lowered the surface temperature from 60 °C to 47 °C. This represents a 22 % decrease in pavement surface temperature. The thermal performance analysis of the cool pavement technology reveals that the pavement surface albedo enhancement will help to increase surface reflectance while lowering pavement surface temperature and offsetting CO2 emissions. Increasing the pavement surface albedo by 192 % (from 24 % to 70 %) for the total treated surface area (81,000 m2) in the educational complex will offset 28,350 tons of CO2. The application of a white coating with a high reflective value on concrete and asphalt pavements will help to extend the life of the pavement, reduce the energy consumption of buildings and the emissions of greenhouse gases, minimize the emissions of carbon dioxide caused by the enhancement of albedo (a strategy for mitigating the effects of climate change), improve parking lot visibility, and deal with the effects of heat islands.

An exploratory, intra- and interindividual comparison of the deep neural network automatically measured calf surface radiation temperature during cardiopulmonary running and cycling exercise testing: A preliminary study

Non-invasive and contactless infrared thermography (IRT) measurements have been claimed to indicate acute neural, cardiovascular, and thermoregulatory adaptations during exercise. Due to challenging comparability, reproducibility, and objectivity, investigations considering different exercise types and intensities, and automatic ROI analysis are currently needed. Thus, we aimed to examine surface radiation temperature (Tsr) variations during different exercise types and intensities in the same individuals, ROI, and environmental conditions. Ten healthy, active males performed a cardiopulmonary exercise test on a treadmill in the first week and on a cycling ergometer the following week. Respiration, heart rate, lactate, rated perceived exertion, the mean, minimum, and maximum Tsr of the right calf (CTsr (°C)), and the surface radiation temperature pattern (CPsr) were explored. We executed two-way rmANOVA and Spearman’s rho correlation analyses. Across all IRT parameters, mean CTsr showed the highest association to cardiopulmonary parameters (E.g., oxygen consumption: rs = −0.612 (running); −0.663 (cycling); p < .001). A global significant difference of CTsr was identified between all relevant exercise test increments for both exercise-types (p < .001; η2p = .842) and between both exercise-types (p = .045; η2p = .205). Differences in CTsr between running and cycling significantly appeared after a 3-min recovery period, whereas lactate, heart rate, and oxygen consumption were not different. High correlations between the CTsr values extracted manually and the CTsr values processed automatically by a deep neural network were identified. The applied objective time series analysis enables crucial insights into intra- and interindividual differences between both tests. CTsr variations indicate different physiological demands between incremental running and cycling exercise testing. Further studies applying automatic ROI analyses are needed to enable the extensive analysis of inter- and intraindividual factors influencing the CTsr variation during exercise to allow determine the criterion and predictive validity of IRT parameters in exercise physiology.

Modeling the spatial distribution of the ctenophore Mnemiopsis leidyi A. Agassiz, 1865 in the Black Sea using a fuzzy rule-based system

Species distribution models can predict species occurrences in areas where no data is available by finding relationships between occurrences and environmental parameters. In this study, we applied a fuzzy rule-based system to model the spatial distribution of Mnemiopsis leidyi in the Black Sea and predict the probability of its presence throughout the sea. Six variables were used as predictors, including water turbidity, organic and inorganic particulate carbon, photosynthetically active radiation, light absorption by phytoplankton, sea surface temperature, and chlorophyll-a concentration. The results revealed a 0.807 accuracy of the model based on the confusion matrix. The results also showed that photosynthetically active radiation and sea surface temperature were the most important predictors shaping the distribution of this species. The findings also showed that the northern Black Sea was with the highest probability of presence, especially in Ukraine and Russia’s coastal areas. In the coastal areas of Turkey, the highest presence probability was found near Rize, Trabzon, Ordu, and from Sinop to Zonguldak. Therefore, continuous monitoring of the Turkish coastal area is crucial to better understanding the effects of climate change and anthropogenic influences on the further distribution patterns of this invasive ctenophore in the southeastern Black Sea.

Uncertainty analysis of photovoltaic cells to determine probability of functional failure

In engineering practice, extensive uncertainties exist in photovoltaic (PV) cell material parameters owing to manufacturing process errors and in PV cell working environment parameters owing to environmental uncertainties. Ignoring the uncertainty of these parameters will greatly reduce the reliability of photovoltaic cells. In this study, a PV cell model was used to conduct an uncertainty analysis based on functional failure. Functional failure is defined as output power fluctuation beyond the specified range, and functional safety region is defined as the allowable fluctuation range of output power during operation. A global sensitivity analysis method based on the Monte Carlo method was employed to study the influence of parameter fluctuation on the functional failure probability of a PV cell. An uncertainty analysis method based on Latin hypercube sampling was applied to study the influence of parameters on the probability of PV cell operation in the functional safety domain. The results indicate that the uncertainty of surface temperature had the most significant influence on the failure probability, followed by the ideality factor, radiation intensity, and current temperature coefficient, the series and parallel resistances had the smallest impact. Optimal values of 510.200 W/m2, 284.600 K, and 1.446 were obtained for radiation intensity, surface temperature, and ideality factor, respectively, which ensured that system functional failure probability remained in the safety zone with values of 93.763 %, 99.211 %, and 98.856 %, respectively. Additionally, the lower series resistance and the higher parallel resistance, the more likely the system to operate in the functional safety domain. The results of study expand the evaluation standard for PV cell operation and ensure the desired system output power.

Technological avenues and market mechanisms to accelerate methane and nitrous oxide emissions reductions.

Strategies targeting methane (CH4) and nitrous oxide (N2O) emissions are critical to meeting global climate targets. Existing literature estimates the emissions of these gases from specific sectors, but this knowledge must be synthesized to prioritize and incentivize CH4 and N2O mitigation. Accordingly, we review emissions sources and mitigation strategies in all key sectors (fuel extraction and combustion, landfilling, agriculture, wastewater treatment, and chemical industry) and the role of carbon markets in reducing emissions. The most accessible reduction opportunities are in the hydrocarbon extraction and waste sectors, where half (>3 Gt-CO2e/year) of the emissions in these sectors could be mitigated at no net cost. In total, 60% of CH4 emissions can be mitigated at less than $50/t-CO2. Expanding the scope of carbon markets to include these emissions could provide cost-effective decarbonization through 2050. We provide recommendations for carbon markets to improve emissions reductions and set prices to appropriately incentivize mitigation.

Potential of hybrid radiant cooling with infrared-transparent membranes to improve thermal comfort in hot and humid climate

• Condensation risk limits radiant cooling in a hot and humid climate. • Infrared-transparent membranes prevent condensation on radiant cooling surfaces. • Radiant surface at 4 °C below dew point reduced discomfort hours by 3–6%. • Experiments-modeling should target lower radiant surface temperatures. • Solar gains significantly affected radiant cooling effectiveness. Condensation risk has limited the deployment of radiant cooling systems for improving thermal comfort in hot and humid climates. Infrared-transparent membrane films emerged as a viable alternative to improve hybrid radiant cooling by preventing moisture condensation. This case study assesses the potential of membrane-assisted radiant cooling in a rural school building in Santa Lucia, Atlántico (Colombia), a location with a hot and humid tropical climate throughout the year. The study evaluates different cooling strategies, including natural ventilation, mechanical ventilation, hybrid radiant cooling, and membrane-assisted radiant cooling using EnergyPlus® software. Results for a radiant surface temperature of 4 °C below the dew point show that membrane-assisted radiant cooling could reduce annual discomfort hours by 3–6% compared to conventional radiant cooling. Further experimental and modeling studies should focus on the lowest achievable temperature below the dew point without condensation. Our results suggest that radiant cooling with infrared-transparent membranes is a potentially cost-effective alternative for improving thermal comfort in rural school buildings in hot and humid climates.

OPTIMIZATION MODEL FOR RESERVOIR WATER BODY SURFACE AREA USE IN THE FLOATING PHOTOVOLTAIC POWER PLANT

This research intends to optimize the use of reservoir inundation surface area as the Floating Photovoltaic Power Plant (PLTS). The research location is in the Waduk Jatigede, Cijeungjing Village-Jatigede District-Sumedang Regency, West Java Province, Indonesia. The Jatigede is a multi-function reservoir. This reservoir is used for raw water, irrigation, flood control, recreation, sport, and Floating Photovoltaic Power Plant (PLTS). Based on the data of solar radiation intensity, wind velocity, and surface temperature, this research intends to analyze the effect of EBT on the optimization model for using reservoir water surface.The methodology includes the optimization of reservoir water body surface area use for the Floating Photovoltaic Power Plant (PLTS) using Simplex Linear Programming. The optimization is implemented under the three scenarios as follows: 1) Design of floating PLTS island area with attending the bathymetry measurement; 2) Design of floating PLTS island area without attending the bathymetry measurement by the dimension is 160 m x 320 m; 3) Design of floating PLTS island area without attending the bathymetry measurement by the dimension is 320 m x 320 m. The results show that 1) The utilization of reservoir inundation surface area based on the optimization result is 16,703,000 m2 or 1,670.3 ha (42.25%) from the total of reservoir inundation surface area that is 3,953 ha with the electrical production of PLTS is 3,078 MWp or in average is 5,617 GWp per-year; and 2) the evaluation of Waduk Jatigede performance indicates that the operation pattern based on the simulation by using the Simplex Method can fulfil the demand. The last result of simulation has the reliability of 79.17%, the volatility is 80.00%, and the vulnerability is 28.74%. It means that the reservoir has the ability in amount of 79.17% for fulfilling the demand. Meanwhile the reservoir ability for returning back to the satisfied condition from the failure condition to fulfil the demand is 82.92%, and in the case of the failure, 28.74% of demand cannot be fulfilled with the average deficit is 7.67 million m3 per 15 days every failure event.

Environmental and human factors drive the subtropical marine forests of Gongolaria abies-marina to extinction

Large brown macroalgae are foundational threatened species in coastal ecosystems from the subtropical northeastern Atlantic, where they have exhibited a drastic decline in recent years. This study describes the potential habitat of Gongolaria abies-marina, its current distribution and conservation status, and the major drivers of population decline. The results show a strong reduction of more than 97% of G. abies-marina populations in the last thirty years and highlight the effects of drivers vary in terms of spatial heterogeneity. A decrease in the frequency of high waves and high human footprint are the principal factors accounting for the long-term decline in G. abies-marina populations. UV radiation and sea surface temperature have an important correlation only in certain locations. Both the methodology and the large amount of data analyzed in this study provide a valuable tool for the conservation and restoration of threatened macroalgae.

Towards Exercise Radiomics: Deep Neural Network-Based Automatic Analysis of Thermal Images Captured During Exercise

Infrared thermography is increasingly applied in sports science due to promising observations regarding changes in skin's surface radiation temperature ( Tsr) before, during, and after exercise. The common manual thermogram analysis limits an objective and reproducible measurement of Tsr. Previous analysis approaches depend on expert knowledge and have not been applied during movement. We aimed to develop a deep neural network (DNN) capable of automatically and objectively segmenting body parts, recognizing blood vessel-associated Tsr distributions, and continuously measuring Tsr during exercise. We conducted 38 cardiopulmonary exercise tests on a treadmill. We developed two DNNs: body part network and vessel network, to perform semantic segmentation of 1 107 855 thermal images. Both DNNs were trained with 263 training and 75 validation images. Additionally, we compare the results of a common manual thermogram analysis with these of the DNNs. Performance analysis identified a mean IoU of 0.8 for body part network and 0.6 for vessel network. There is a high agreement between manual and automatic analysis (r = 0.999; p 0.001; T-test: p = 0.116), with a mean difference of 0.01 °C (0.08). Non-parametric Bland Altman's analysis showed that the 95% agreement ranges between - 0.086 °C and 0.228 °C. The developed DNNs enable automatic, objective, and continuous measurement of Tsr and recognition of blood vessel-associated Tsr distributions in resting and moving legs. Hence, the DNNs surpass previous algorithms by eliminating manual region of interest selection and form the currently needed foundation to extensively investigate Tsr distributions related to non-invasive diagnostics of (patho-)physiological traits in means of exercise radiomics.

Diverse cloud radiative effects and global surface temperature simulations induced by different ice cloud optical property parameterizations

The representation of ice cloud optical properties in climate models has long been a difficult problem. Very different ice cloud optical property parameterization schemes developed based on very different assumptions of ice particle shape habits, particle size distributions, and surface roughness conditions, are used in various models. It is not clear as to how simulated climate variables are affected by the ice cloud optical property parameterizations. A total of five ice cloud optical property parameterization schemes, including three based on the ice habit mixtures suitable for general ice clouds, mid-latitude synoptic ice clouds, and tropical deep convective ice clouds, and the other two based on single ice habits (smooth hexagonal column and severely roughened column aggregate), are developed under a same framework and are implemented in the National Center for Atmospheric Research Community Atmospheric Model version 5. A series of atmosphere-only climate simulations are carried out for each of the five cases with different ice parameterizations. The differences in the simulated top of the atmosphere shortwave and longwave cloud radiative effects (CREs) are evaluated, and the global averaged net CRE differences among different cases range from − 1.93 to 1.03 Wm−2. The corresponding changes in simulated surface temperature are found to be most prominent on continental regions which amount to several degrees in Kelvin. Our results indicate the importance of choosing a reasonable ice cloud optical property parameterization in climate simulations.

Thermal Regulation of Coastal Urban Forest Based on ENVI-Met Model—A Case Study in Qinhuangdao, China

Urban forests can improve human comfort by improving the near-surface microclimate. Exploring the microclimate characteristics of urban forests and their impact on human comfort is particularly important to improve the urban thermal environment through scientific urban forest design. Since most previous studies were conducted under typical inland urban climates and little is known about the thermal regulation services of coastal urban forests, this study field measured the thermal surface radiation temperature of 16 open spaces in the urban forest site in Qinhuangdao. Then the ENVI-met software was used to simulate and analyze the microclimate characteristics before and after the park’s building-up, and compare the differences in the human comfort index in different scenarios. Results indicated that: (1) Vegetation have a significant cooling effect on surrounding environment. The farther away from vegetation area, the higher the average surface temperature. (2) Water bodies have the best cooling and humidifying effect on the 9–18 m surrounding environment with the best human comfort index. (3) In summer, air temperature in park decreased by 0.4~1.4 °C, and the relative humidity increased by 0.07~2.81%. (4) After the park’s built-up, the average human comfort index was optimized by 0.02~1.87. Arranging the leisure open space around the water bodies and forest edge space of the deciduous broad-leaved forest could improve human comfort. This research is expected to provide a scientific basis and planning inspiration for the construction of coastal urban forests in the same latitude area.

Experimental Study on Operating Characteristic of a Combined Radiant Floor and Fan Coil Cooling System in a High Humidity Environment

The combined radiant floor and fan coil cooling (RFCAFC) system is widely used due to its high comfort and large energy saving potential. In this study, as an example, the combined RFCAFC system was studied in a high humidity environment in Jinan, Shandong Province, China. The novelty of the combined RFCAFC system lies in its ability to automatically adjust the water supply temperature of the radiant floor and fan coil in real time according to outdoor meteorological conditions, achieving thermal comfort while eliminating the likelihood of condensation on the radiant floor surface. Days with similar outdoor meteorological conditions were grouped, and the comfort level and hourly cooling performance coefficient (EERh) of different operating strategies for different outdoor meteorological conditions were monitored along with other evaluation indicators. The RFCAFC had good energy efficiency and comfort in a high humidity room environment. This study showed that the indoor vertical air temperature difference ranged from 1.6 to 1.8 °C, which met the ASHRAE55-2017 standard. The radiant floor surface temperature uniformity coefficient (S) fluctuated between 0.7 and 1.0, and the time it took the radiant floor surface temperature to reach 63.2% of the total variability range (τ63) for different operation strategies based on different outdoor meteorological conditions ranged between 4.4 and 4.7 h, which was within the normal range. The proportion of the total cooling capacity contributed by fan coil cooling under low temperature and high humidity (LH), high temperature and low humidity (HL), and medium temperature and medium humidity (MM) were 68.0%, 73.8%, and 71.7%, respectively. Based on this study, the following recommendations for the combined cooling system can be made: (1) When the outdoor humidity is high, the radiant floor system should be turned on early to provide cooling capacity. When the outdoor temperature is high, the fan coil system should be turned on early to reduce the indoor temperature. (2) To reduce energy consumption and achieve efficient operation of the system, the radiant floor system should be continuously operated to maximize its contribution to the cooling capacity, while the fan coil can be operated intermittently. Natural cooling can be integrated to provide additional cooling capacity to the room in the hours preceding occupation (i.e., 7:00–9:00). (3) The operation strategy of the combined cooling system must be able to respond in real time to changes in outdoor meteorological conditions to prevent discomfort in times of extreme heat or humidity.

Does Disabling Cloud Radiative Feedbacks Change Spatial Patterns of Surface Greenhouse Warming and Cooling?

AbstractThe processes controlling idealized warming and cooling patterns are examined in 150-yr-long fully coupled Community Earth System Model, version 1 (CESM1), experiments under abrupt CO2forcing. By simulation end, 2 × CO2global warming was 20% larger than 0.5 × CO2global cooling. Not only was the absolute global effective radiative forcing ∼10% larger for 2 × CO2than for 0.5 × CO2, global feedbacks were also less negative for 2 × CO2than for 0.5 × CO2. Specifically, more positive shortwave cloud feedbacks led to more 2 × CO2global warming than 0.5 × CO2global cooling. Over high-latitude oceans, differences between 2 × CO2warming and 0.5 × CO2cooling were amplified by familiar linked positive surface albedo and lapse rate feedbacks associated with sea ice change. At low latitudes, 2 × CO2warming exceeded 0.5 × CO2cooling almost everywhere. Tropical Pacific cloud feedbacks amplified the following: 1) more fast warming than fast cooling in the west, and 2) slow pattern differences between 2 × CO2warming and 0.5 × CO2cooling in the east. Motivated to quantify cloud influence, a companion suite of experiments was run without cloud radiative feedbacks. Disabling cloud radiative feedbacks reduced the effective radiative forcing and surface temperature responses for both 2 × CO2and 0.5 × CO2. Notably, 20% more global warming than global cooling occurred regardless of whether cloud feedbacks were enabled or disabled. This surprising consistency resulted from the cloud influence on non-cloud feedbacks and circulation. With the exception of the tropical Pacific, disabling cloud feedbacks did little to change surface temperature response patterns including the large high-latitude responses driven by non-cloud feedbacks. The findings provide new insights into the regional processes controlling the response to greenhouse gas forcing, especially for clouds.Significance StatementWe analyze the processing controlling idealized warming and cooling under abrupt CO2forcing using a modern and highly vetted fully coupled climate model. We were especially interested to compare simulations with and without cloud radiative feedbacks. Notably, 20% more global warming than global cooling occurred regardless of whether cloud feedbacks were enabled or disabled. This surprising consistency resulted from the cloud influence on forcing, non-cloud feedbacks, and circulation. With the exception of the tropical Pacific, disabling cloud feedbacks did little to change surface temperature response patterns including the large high-latitude responses driven by non-cloud feedbacks. The findings provide new insights into the regional processes controlling the response to greenhouse gas forcing, especially for clouds. When combined with estimates of cooling at the Last Glacial Maximum, the findings also help rule out large (4+ K) values of equilibrium climate sensitivity.

Seasonal and interannual cycles of total phytoplankton phenology metrics in the Persian Gulf using ocean color remote sensing

Spatial and temporal patterns of climatological seasonality, interannual variability, and phytoplankton phenology were estimated using satellite-derived ocean color chlorophyll-a data (Chl-a) 1998 to 2020 in the Persian Gulf from. Biogeography of phytoplankton seasonal and interannual climatology was determined using k-means multivariate clustering analysis applied on the Chl-a time-series data. As a result, two distinct regions were identified: one in the deep north and middle area (DZC) with a minimum value of Chl-a in April–July (0.62–0.76 mg m−3) and maximum in December–February (1.07–1.59 mg m−3), and the other in the north–west coastal areas and along the southwest-southern area (SZC) with a minimum value of Chl-a in March (0.84 mg m−3) and maximum in September–October (1.35–1.42 mg m−3). More than 90% of both DZC and SZC regions remained spatially unchanged during the study period. Spatial shifts from SZC to DZC and DZC to SZC were located along the boundaries between two clusters and covered 5.37% and 1.95% of the whole study area, respectively. Phytoplankton phenological metrics (timings of initiation, peak, termination, and growth duration) were estimated from Chl-a data in the stable regions during the 23-years of the study period. Interannual and seasonal variations of phenological metrics on stable pixels showed unparalleled episodic shifts in phytoplankton growth in the SZC and DZC in December–January and May–September, respectively. The initiation of phytoplankton growth shifts to earlier months by 0.58 days y−1 in the DZC and 0.56 days y−1 in the SZC, while the timings of maximum amplitude of phytoplankton growth become later by 0.59 days y−1 in the DZC and 0.47 days y−1 in the SZC, according to interannual linear trends of phenological metrics. Likewise, a relatively stable trend in phytoplankton growth duration and termination was observed over the whole study area. Geographically, a gradient of the growing period detected from northwest (90–110 days) to the east (175 days). However, the spatial analysis showed that the correlation between depth and phytoplankton phenology was not significant, although depth-dependent patterns were observed in both DZC and SZC regions. Moreover, the spatio-temporal correlation between interannual and seasonal cycles of phytoplankton phenology and wind stress, solar radiation, and Sea Surface Temperature (SST) are discussed in the context of the ecosystem state assessment. The results show that the stratification of water layers in summer and wind mixings are the primary seasonal factors affecting the total phytoplankton phenology in the Persian Gulf.

The Flexible Modelling Framework for the Met Office Unified Model (Flex-UM, using UM 12.0 release)

Abstract. The Met Office Unified Model (UM) is a world-leading atmospheric weather and climate model. In addition to comprehensive simulations of the atmosphere, the UM is capable of running idealised simulations, such as the dry physics Held–Suarez test case, radiative convective equilibrium and simulating planetary atmospheres other than Earth. However, there is a disconnect between the simplicity of the idealised UM model configurations and the full complexity of the UM. This gap inhibits the broad use of climate model hierarchy approaches within the UM. To fill this gap, we have developed the Flexible Modelling Framework for the UM – Flex-UM – which broadens the climate model hierarchy capabilities within the UM. Flex-UM was designed to replicate the atmospheric physics of the Geophysical Fluid Dynamics Laboratory (GFDL) idealised moist physics aqua-planet model. New parameterisations have been implemented in Flex-UM, including simplified schemes for convection, large-scale precipitation, radiation, boundary layer and sea surface temperature (SST) boundary conditions. These idealised parameterisations have been implemented in a modular way, so that each scheme is available for use in any model configuration. This has the advantage that we can incrementally add or remove complexity within the model hierarchy. We compare Flex-UM to ERA5 and aqua-planet simulations using the Isca climate modelling framework (based on the GFDL moist physics aqua-planet model) and comprehensive simulations of the UM (using the GA7.0 configuration). We also use two SST boundary conditions to compare the models (fixed SST and a slab ocean). We find the Flex-UM climatologies are similar to both Isca and GA7.0 (though Flex-UM is generally a little cooler, with higher relative humidity and a less pronounced storm track). Flex-UM has a single Intertropical Convergence Zone (ITCZ) in the slab-ocean simulation but a double-ITCZ in the fixed-SST simulation. Further work is needed to ensure that the atmospheric energy budget closes to within 1–2 W m−2, as the current configuration of Flex-UM gains 9–11 W m−2 (the range covers the two SST boundary conditions). Flex-UM greatly extends the modelling hierarchy capabilities of the UM and offers a simplified framework for developing, testing and evaluating parameterisations within the UM.

Exact solutions for 2D boundary layer flow of two types of viscoelastic fluids and heat transfer on a permeable shrinking sheet with thermal radiation and variable surface temperature: existence of multiple solutions

A study with existence of multiple exact solutions has its own importance, and if the study is performed for a viscoelastic fluid, then the attraction becomes very high. So, here an attempt is performed, where the flow of two types of viscoelastic fluids and heat transfer due to shrinking of a permeable sheet is described. In the energy flow, the impacts of thermal radiation and variable temperature of the wall are simultaneously undertaken. By using similarity approach, in addition to single solution, the dual and triple closed-form solutions of the flow field and temperature are obtained in some specific flow situations of two fluids, namely, second-grade and Walters liquid B. Dual solutions for the flow of second-grade fluid are detected only for stronger mass suction with smaller viscoelastic parameter of second-grade fluid and for both weaker and stronger mass suctions (for two ranges) with larger viscoelastic parameter and unique solution in case of mass injection. However, for the flow of Walters liquid B, boundary layer solution is attained for mass suction only, and most importantly, triple solutions for some mass suction range are found. Now for heat flow, an exceptional result is witnessed: if the wall temperature distribution is assumed suitably, then the heat transfer rate is not dependent on the fluid rheology. Also, influences of involved physical parameters on velocity, temperature and other important quantities are described through some graphs.

Waste Heat Energy Recovering to Increase The Efficiency of Automotive Internal Combustion Engines Using Thermoelectric Generators

The waste heat energy discharged into the atmosphere by a car engine's fuel consumption provides more than 70% of the energy. We can utilise waste heat energy in a car's exhaust system if a thermoelectric generator is used to convert the lost thermal energy into electricity. A thermoelectric generator is a device that uses the Seebeck effect to turn temperature differences into electricity. A thermoelectric generator is a device that uses the Seebeck effect to transform temperature differences into electrical energy. Because the thermoelectric generator requires a temperature difference on both sides to produce electrical energy, the ability to generate electrical power by thermoelectric generation using the missing thermal energy from the vehicle's exhaust system and relatively cool surrounding air temperature has been tested at various air velocity and speeds. On the other hand, we examine the feasibility of installing thermoelectric generation on the engine's front radiator, as well as the differences between utilizing lost thermal energy in the exhaust system and the automobile radiator. The goal of this article is to look at whether a thermoelectric generator could convert waste heat from a vehicle's exhaust system and radiator into usable electrical energy. As a result, laboratory equipment was constructed to mimic a car's exhaust system and radiator in this investigation. Changes in speed, vehicle load, and surrounding environmental variables affect the surface temperature of the exhaust pipe and radiator. The thermoelectric generator's other side will be cooled by air passing over the fins. These factors will result in a temperature difference on both sides of the thermoelectric generator, which will have a direct impact on the quantity of electrical power the device can generate. After the thermoelectric generator has undergone different operating conditions by changing the velocity of the air passing on one side to cool it down, the temperature of the other side will rise when exposed to the heat flux that represents the exhaust surface temperature and radiator surface temperature at those operating conditions. We predict that at 20°C, the output power for each thermoelectric generator device is 1.18 watts in the best environmental conditions that produce the highest temperature difference. Using ANSYS FLUENT SOFTWARE, it was determined that at a high-temperature difference of 45 and above, an increase in the temperature difference by 3°C increases the electrical output energy from As a result, we can anticipate how much electrical energy the thermoelectric generator gadget will produce under various climatic conditions.

The use of sun-shade on safe heat exposure limit on a sunny summer day: a modelling study in Japan.

Sustainable methods are required to reduce the risks of thermal strain and heat-related illness without exacerbating greenhouse gas emissions. We investigated the effects of sun-shade use on safe heat exposure limit on a sunny summer day using historical climate data in Japan. We simulated a heat-acclimatised person standing at rest (metabolic heat production, 70W·m-2) and during light work (100W·m-2) on an asphalt pavement in the sun and sun-shade. Japan has three Köppen climate regions: tropical, temperate and cold. We analysed one city in the tropical region (24°N), three cities in the temperate region (31°N, 35°N and 39°N) and one city in the cold region (40°N). Hourly data were collected from 7 AM to 6 PM, June to September, from 2010 to 2019. The day with the longest daylight hours and the greatest solar radiation intensity was used for analysis. With sun-shade (a white polyester tarpaulin/awning), ambient temperature, global solar radiation and ground surface temperature were assumed to be 0.5°C, 45% and 6°C lower than in the sun, respectively. Sun-shade use eliminated the days with at least 1hour exceeding safe heat exposure limit at rest in all cities. The same was observed for light work in the temperate and cold cities, although the tropical city had 2days exceeding safe heat exposure limit during the decade. Sun-shade use on a sunny summer day can be an effective and sustainable method to reduce heat exposure hazard at rest and during light work in tropical, temperate and cold climate regions.

Experimental study on the radiative heat transfer in a multi-hole porous radiant burner with internal combustion regime

• The effect of internal zone’s height on the radiant efficiency of internal regime. • An increment of 13.1% in radiant efficiency compared to a multi-layer PRB. • A new radiative heat transfer based non-dimensional number is defined. • The radiative non-dimensional number is only a function of geometry, not power. • The maximum radiant efficiency is occurred at the equivalence ratio of 0.9. An experimental study was performed on the radiative heat transfer in a porous radiant burner (PRB) with an internal combustion regime (ICR). A multi-hole plate and a high pore density SiC porous foam were used to form the jet-shaped flames and the ICR, respectively. For local temperature measurement, a movable Cartesian mechanism is used for the thermocouple. The effects of three independent parameters of input power, P , equivalence ratio, ϕ , and the distance between the multi-hole plate and porous medium (PM), d , on radiative surface temperature and radiant efficiency are investigated. The results show that the radiant efficiency increases 13.1% compared to a multi-layer PRB in the literature at the same firing rate. In addition, the maximum radiant efficiency for all operating conditions occurred at ϕ = 0.9 . Moreover, the radiative surface temperature decreases, a decrease of 2.25%, by increasing d from 85 mm to 145 mm at P , ϕ = 8.25 k W , 0.9 . However, the radiative heat transfer of the PM, as well as the radiant efficiency, does not decrease sharply due to the view factor increment by increasing d . Furthermore, it was concluded that a new non-dimensional number, related to the radiative heat transfer, can be defined by dividing the radiative heat transfer to the burner’s outside to the radiative heat transfer to the burner’s side walls. This heat transfer based non-dimensional number is only a function of d , and it behaves like an ascending function that is independent of input power.