Atmospheric Temperature Research Articles

The Catalytic Activity of Polyaniline in Hydrogenation Reactions with Molecular Hydrogen.

This study unveils a novel property of polyaniline by establishing its catalytic activity in heterogeneous hydrogenation with molecular hydrogen. Polyaniline was activated by heat-treating at different temperatures in a hydrogen atmosphere. The sample treated at 300 °C exhibited the highest catalytic activity for ethylene hydrogenation in the gas phase at atmospheric pressure and for p-nitrotoluene or α-methylstyrene hydrogenation in the liquid phase. XRD, HRTEM, Raman, XPS, UV-VIS, FTIR, and elemental analysis data as well as electrochemical study indicate that catalytic activity is associated with the conjugated structure of undoped emeraldine base, whereas the polymer cross-linking or an increase in chlorine residues correlates with catalyst deactivation. These results pave the way to use conducting polymers as catalysts for hydrogenation with molecular hydrogen, opening new avenues for their application in catalysis.

Studies on key seed physico-chemical factors and climatic variables regulating hardseededness in green gram (Vigna radiata L.) genotypes

Context Green gram (Vigna radiata) is an important source of plant-based dietary protein. ‘Physical dormancy’ or ‘hardseededness’ is prevalent in many released varieties of green gram in India. Green gram seeds exhibit a variable proportion of hard seeds that do not imbibe water. Presence of hard seeds results in uneven germination, lower field emergence and leads to poor yield. Hardseededness is primarily attributed to thick impermeable seed coat, lignin content, and structural carbohydrates, which is controlled genetically as well as by prevailing environmental interactions. Aim To identify the major biochemical and growing conditions regulating the hardseededness in green gram. Methods Ninehard seeded (HS) and nine non-hard seeded (NHS) genotypes of green gram were evaluated for variation in hardseededness and physico-chemical parameters during two consecutive monsoon and summer season. Key results Hardseededness varied significantly between HS and NHS genotypes as well as between the growing seasons. Physico-chemical parameters like lignin content, cellulose, hemicelluloses, total phenol, and calcium content varied significantly among HS and NHS genotypes and also between monsoon and summer produced seeds. Conclusions Green gram genotypes produced in summer season exhibited lower proportion of hard seeds compared to those grown in the monsoon season. This may be due to higher atmospheric temperature at the time of seed maturity as well as relatively lower lignin, calcium, phenol, and structural carbohydrate content in varieties. Implications Our findings indicated that the summer season may be preferred over monsoon for production of quality seeds of identified hard seeded green gram varieties.

Clouds reduce downwelling longwave radiation over land in a warming climate.

Clouds greatly influence the Earth's energy balance1,2. Observationally constraining cloud radiative feedback, a notably uncertain climate feedback mechanism3-5, is crucial for improving predictions of climate change5-7 but, so far, remains an elusive objective, and the feedback may be different over the ocean versus over land8-10. Here we show a local negative surface longwave cloud feedback over land at the southern Great Plains site, constrained by direct long-term observation of spectrally resolved downwelling longwave radiance11. This negative cloud feedback at thesouthern Great Plains site causes a -1.77 ± 1.15 W m-2 per decade change in downwelling longwave radiation and suggests that cloud changes may partially modulate the warming effect of increased greenhouse gas concentrations and atmospheric temperatures over land. Specifically, our results are derived from an optimal spectral fingerprinting method12-15 designed to separate surface longwave cloud feedback from other surface forcings and feedbacks, by making use of their unique spectral signatures13-18 in the long-term record of spectrally resolved radiances. Furthermore, we show that the results are not sitespecific: negative surface longwave cloud feedbacks, primarily induced by decreasing low cloud cover in warming climates, are commonly observed over land in reanalysis and satellite datasets. Our findings establish a pivotal observational benchmark of radiative forcing and feedback needed for validating climate model performance over land.

High‐Resolution Analysis of Severe Heat Wave Dynamics and Thermal Discomfort Across India

ABSTRACTThe study explores variability and dynamical characteristics of heatwaves during March–June for 1990–2020 over India. Normalised Tmax anomaly is used to identify different heatwave spells in vulnerable regions of North‐central India (NCI) and Southeast coast of India (SECI) using India Meteorological Department (IMD, 1° × 1° resolution) observations, Indian Monsoon Data Assimilation and Analysis (IMDAA, 0.12° × 0.12°), and ECMWF Reanalysis v5 (ERA5, 0.25° × 0.25°). Results highlight that IMDAA exhibited a total 202 days (181 days) heatwaves duration in NCI (SECI) regions while ERA5 exhibited a total 132 days (89 days), respectively, compared with those of IMD (195 and 163 days). The primary heatwave periods for NCI (10 April to 20 June) and SECI region (1 May to 10 June) are well captured by IMDAA, unlike ERA5. The average length of the heatwave is 7.8, 7.5, and 7.76 days (8.15, 7.72, and 6.1 days) over NCI (SECI) in IMD, IMDAA, and ERA5, respectively. The high heat stress is more frequent in SECI than in the NCI region and is common during May–June (May only), as seen in IMDAA (ERA5). The middle to upper‐level anticyclone over NCI is stronger than SECI during heatwaves. Heat advection with stronger 850‐hPa north‐westerlies (~10 ms−1) abates sea breeze in the coastal region, aiding longer heatwaves in the SECI region. Ascending motion induced by surface heating is confined to the lower levels due to the subsidence by the upper‐level anomalous anticyclone, stagnating higher temperatures in the lower atmosphere, depicting a heat dome. The surface temperatures are slightly higher in NCI (31°C–39°C) than in SECI (30°C–37°C). However, the double moist heat dome in SECI has witnessed higher heat stress conditions than NCI. Higher relative humidity in the SECI region is contributed by maritime winds from the Bay of Bengal and Arabian Sea, soil moisture, and so forth. The study highlights the value of atmospheric moisture in differentiating the study regions for heat stress conditions.

A Review: Mechanisms of Ocean Acidification in the Context of Global Warming

Global warming stems mainly from the accumulation of greenhouse gases, which leads to higher atmospheric and ocean temperatures and has far-reaching impacts on marine systems. This paper focuses on the impact of global warming on the El Nio phenomenon and ocean acidification. There are significant changes in the frequency and intensity of El Nio events in the context of global warming, but the exact trends are uncertain. At the same time, the increase in carbon dioxide has led to ocean acidification, which poses a threat to the growth of marine organisms and the stability of ecosystems. An in-depth understanding of the role of El Nio and ocean acidification in climate change is therefore essential for the protection of marine ecosystems. For future marine ecological conservation, a comprehensive analysis of the climatic effects of El Nio and ocean acidification is essential. Only an in-depth study of these factors can lead to a more effective response to the ecological challenges posed by global warming.

Analysis on the Effects of Ocean on Temperature

Nowadays, global climate change is one of the main concerns of modern society and an enormous issue for all humankind. Temperature is closely related to the greenhouse effect, so one of the major topics to be investigated in global climate is the factors affecting temperature rise. To estimate this change, it is typically crucial to forecast the temperature in the future. The Earth's average temperature is determined by a multi-step and complex process that uses statistical techniques and data from various sources. By collecting and summarizing data, this paper mainly focuses on analyzing the trends in sea surface temperature over the past few hundred years. Through recent studies and case analysis, this paper highlights that the ocean has become an indispensable part of mitigating climate warming and stabilizing temperature. The significance of studying the impact of the ocean on temperature lies in its role as a climate regulator, providing scientific basis for global climate change and guidance for regional adaptation efforts. Because of its enormous heat capacity and thermal inertia, the ocean is an important component of the climate system and plays a buffering and regulating role in atmospheric temperature.

On the Ionosphere–Atmosphere–Lithosphere Coupling During the 9 November 2022 Italian Earthquake

In the last decades, the scientific community has been focused on searching earthquake signatures in the Earth’s atmosphere, ionosphere, and magnetosphere. This work investigates an offshore Mw 5.5 earthquake that struck off the Marche region’s coast (Italy) on 9 November 2022, with a focus on the potential coupling between the Earth’s lithosphere, atmosphere, and magnetosphere triggered by the seismic event. Analysis of atmospheric temperature data from ERA5 reveals a significant increase in potential energy (Ep) at the earthquake’s epicenter, consistent with the generation of Atmospheric Gravity Waves (AGWs). This finding is further corroborated by the MILC analytical model, which accurately simulates the observed Ep trends (within 5%), supporting the theory of Lithosphere–Atmosphere–Ionosphere–Magnetosphere coupling. The study also examines the vertical Total Electron Content (vTEC) and finds notable fluctuations at the epicenter, exhibiting periodicities (7–12 min) characteristic of AGWs and traveling ionospheric disturbances. The correlation between ERA5 observations and MILC model predictions, particularly in temperature deviations and Ep distributions, strengthens the hypothesis that earthquake-generated AGWs impact atmospheric conditions at high altitudes, leading to observable ionospheric perturbations. This research contributes to a deeper understanding of Lithosphere–Atmosphere–Ionosphere–Magnetosphere coupling mechanisms and the potential for developing reliable earthquake prediction tools.

The ESO SupJup Survey V: exploring atmospheric variability and orbit of the super-Jupiter AB Pictoris b with CRIRES+

ABSTRACT A growing number of directly-imaged companions have been recently characterized, with robust constraints on carbon-to-oxygen ratios and even isotopic ratios. Many companions and isolated targets have also shown spectral variability. In this work, we observed the super-Jupiter AB Pictoris b across four consecutive nights using VLT/CRIRES+ as part of the ESO SupJup survey, exploring how the constraints on chemical composition and temperature profile change over time using spectral line shape variations between nights. We performed atmospheric retrievals of the high-resolution observations and found broadly consistent results across all four nights, but there were differences for some parameters. We clearly detect H$_2$O, $^{12}$CO, and $^{13}$CO in each night, but abundances varied by ${\sim} 2\sigma$, which was correlated to the deep atmosphere temperature profiles. We also found differences in the $^{12}$C$/^{13}$C ratios in each night by up to ${\sim} 3\sigma$, which seemed to be correlated with the cloud deck pressure. Our combined retrieval simultaneously analysing all nights together constrained broadly the average of each night individually, with the C/O$=0.59\pm 0.01$, consistent with solar composition, and $^{12}$C$/^{13}$C $= 102\pm 8$, slightly higher than the Interstellar Medium (ISM) and Solar System values. We also find a low projected rotational velocity, suggesting that AB Pictoris b is either intrinsically a slow rotator due to its young age or that the spin axis is observed pole-on with a ${\sim} 90^\circ$ misalignment with its orbit inclination. Future observations will be able to further explore the variability and orbit of AB Pictoris b as well as for other companions.

Validation of the Ensemble Generalized Analog Regression Downscaling (En-GARD) Model to Downscale Near-Surface Wind Speed for the Northeast United States

Abstract Wind, often overlooked in climate change impact assessments, is now a crucial atmospheric variable due to our imminent reliance on renewable energy sources like wind energy. Therefore, establishing a wind speed database in higher temporal and spatial resolution is of great importance to assess wind power in historical periods and future projections. This study focuses on enhancing wind data representation and reliability of statistically downscaled model outputs by refining grid spacing from coarser to a desirable finer scale. Employing the Ensemble Generalized Analog Regression Downscaling (En-GARD) technique, we downscaled near-surface wind speed across a northeast (NE) U.S. domain that combines onshore and offshore wind farm areas. We tested multiple atmospheric variable combinations and identified near-surface wind speed (wind speed at 10 m), longitudinal and latitudinal wind at 10 m, and atmospheric temperature at 2 m, as the set that effectively guides the selection of analog days for the analog regression downscaling approach. Validation involved using ERA5 atmospheric reanalysis products (31 km) and high-resolution (4 km) Weather Research and Forecasting (WRF) Model simulations. Downscaling was conducted using a leave-one-year-out approach over 12 years (2001–12). Statistical analysis of the downscaled output over this period demonstrated a significant correlation and low error metrics (less than 20% for normalized RMSE and 16% for normalized MAE), indicating the reliability of the method and paving the way for its future application to downscale climate projection outputs. Significance Statement Wind speed has become a significant atmospheric variable due to our society’s imminent reliance on renewable energy resources like wind power. Often overlooked in climate change assessments, wind speed at a local scale over wind farm locations plays a crucial role in assessing and planning wind power resources in a future climate. We are providing the successful validation of a statistical downscaling methodology for near-surface wind speed at 4-km grid spacing using reanalysis data. The validity of the methodology gives confidence to downscale climate projection models and assess changes in wind speed for future climate scenarios in a follow-up study.

Influence of annealing temperature on the performance of RF magnetron sputtered Sn-doped Ga<sub>2</sub>O<sub>3</sub> films and its solar-blind photodetector

In this study, Sn-doped Ga<sub>2</sub>O<sub>3</sub> thin films are prepared on sapphire substrate by RF magnetron sputtering at ambient temperature, and then annealed at different temperatures (400–800 ℃) in nitrogen atmosphere. The corresponding metal-semiconductor-metal (MSM) solar blind photodetectors (PDs) are prepared based on those films before and after annealing to explore the influence of annealing temperature on the characteristics of the films and device properties. The results show that the as-deposited Sn-doped Ga<sub>2</sub>O<sub>3</sub> film displays amorphous structure. With the increase of annealing temperature, the proportion of O<sub>L</sub>, Ga<sup>3+</sup> and Sn<sup>4+</sup> ions in the film increase, and the band gap of the film decreases slightly, indicating that the conductivity of the film is enhanced and the quality of the film is improved. When the annealing temperature increases to 700 ℃, the <i>β</i>-Ga<sub>2</sub>O<sub>3</sub> (<inline-formula><tex-math id="Z-20241218145251">\begin{document}$\overline {402} $\end{document}</tex-math></inline-formula>) crystal surface diffraction peak appeares, indicating that the film begins to crystallize. As the annealing temperature increases to 800 ℃, the proportion of O<sub>L</sub>, Ga<sup>3+</sup> and Sn<sup>4+</sup> decreases, and the quality and conductive properties of the film deteriorate, which may be attributed to Sn surface segregation and Al diffusion into the film from the substrate. In addition, the average particle size and surface roughness of the film surface increase with annealing temperature increasing, which is consistent with the changing trend of film characteristics. Then, based on Sn-doped Ga<sub>2</sub>O<sub>3</sub> thin films before and after annealing, the MSM solar blind PDs are prepared to explore the influence of annealing temperature on device performance. The quality of the film and its conductive characteristics play a role in regulating the performance of Sn-doped Ga<sub>2</sub>O<sub>3</sub> solar blind PD. The optimal device performance can be obtained when the annealing temperature is 700 ℃, with a low dark current of 89.97 pA, a responsivity of 18.4 mA/W, a light-dark current up to 1264, and the rise/fall time of 0.93 s/0.87 s. In summary, the annealing temperature has an important effect on the characteristics of Sn-doped Ga<sub>2</sub>O<sub>3</sub> films and the performance of solar blind PDs, which has certain guiding significance for the preparation of high-quality Sn-doped Ga<sub>2</sub>O<sub>3</sub> films and high-performance solar blind PDs.

Sonochemical synthesis of CQDs from coffee husk: Insights in aggregation mechanism, optimization and sustainability analysis.

A green methodology for the synthesis of carbon quantum dots (CQDs) from coffee husk without the use of any toxic solvents is proposed in this work. Sonochemical exfoliation of biochar, obtained from the thermal carbonization of coffee husk (from a certified coffee seeds) at low temperature in an air-restricted atmosphere, is described as an alternative procedure for the sustainable production of CQDs. The synthesized CQDs exhibited blue fluorescence with a strong maximum emission band at 410nm when excited at a maximum absorption wavelength of 330nm. The obtained CQDs were evaluated by various physicochemical methods. According to the results, TEM investigation indicates the average size of CQDs is 8.27±1.57nm with a quasi-spherical morphology. The aim of this study is to optimize the synthesis parameters and compare them with common preparation strategies. This paper reports the main requirements for reproducible and scalable production of CQDs solution, such as the mass of the precursors for each process, for the first time. The conversion and yield percentages on a dry basis, mass of CQDs powder agglomerates, and the specific time duration for each individual step are provided to compensate for the variability of the raw material and facilitate statistical comparison of the methodology. A TEM micrographs analysis for CQDs reconstitution process was conducted, which can be considered a potential mechanism for CQDs agglomeration process.

Characterization of Low Visibility and Forecasting Model in Chongqing Central Area

By using the hourly visibility, temperature, pressure, humidity, wind, and atmospheric particulate concentration data in Chongqing from 2015 to 2023, the characteristics of low visibility (visibility <1000 m) in Chongqing and the influence of various factors on low visibility in Chongqing were analyzed. The visibility prediction model was established by using the neural network method, and the effect of introducing the PM2.5 concentration factor on low visibility prediction was analyzed and compared. Findings: Low visibility in Chongqing is dominated by precipitation low visibility (PLV), followed by fog low visibility (FLV), with the least proportion of fog‐haze mixed low visibility (FHLV). However, as visibility decreases further, the proportion of fog with low visibility increases significantly. The average visibility when fog occurs is lower than that when precipitation occurs and also much lower than that of fog‐haze mixed, indicating that low visibility is more affected by atmospheric water vapor. Over the past decade, as air pollutants have decreased each year, the proportion of fog and FHLV has also trended downward. The proportion of fog increases significantly in winter, and the low visibility below 200 m is mainly caused by fog in winter, while the increase of precipitation in June is the main cause of low visibility in this month. The diurnal variation of mean visibility under precipitation is relatively small. In contrast, the mean visibility during fog and fog‐haze mixed conditions is lower at night than during the day. The higher occurrence rate of these two types of low visibility conditions at night is a significant factor contributing to reduced visibility during nighttime. Atmospheric humidity, temperature, and particulate matter concentration are important factors affecting visibility, and visibility decreases significantly with the increase of PM2.5 when relative humidity (RH) is less than 70%, and PM2.5 has a lower effect on visibility when RH is greater than 70%. The forecast effect of introducing the PM2.5 concentration factor into the objective forecast model of visibility is better than that of not introducing the factor. The effect of introducing this factor is better than that of not introducing it, especially in the fall.

Impact of CR Forbush Decreases on Upper Atmospheric Pressure and Temperature in Saudi Arabia

Impact of CR Forbush Decreases on Upper Atmospheric Pressure and Temperature in Saudi Arabia

Influence of temperature on energy production performance at the Azito thermal power plant (southern part of Côte d'Ivoire)

Technological advances in plant design, cooling and materials are essential to optimise performance under variable conditions. These factors are even more critical under climate change, which may exacerbate these thermal challenges. In this study, the impact of temperature variations on the energy production efficiency of the Azito thermal power plant is investigated using the THERMOFLOW model. The simulation results show that the variation of the atmospheric temperature is an important factor that affects the operation of the basic equipment and the auxiliary equipment of the power generation units. The characteristics of the gas turbine, an essential piece of equipment in the combined cycle system, fall short of the manufacturer's specifications. This will reduce the efficiency of the unit.

Comparative soil bacterial metabarcoding after aboveground vs. subsurface decomposition of Mus musculus

Outdoor microcosms, metabarcoding with next-generation sequencing of the 16S rRNA bacterial gene, total body score (TBS) and physicochemical analyses were used to monitor Mus musculus decomposition aboveground (A) and in the subsurface (S), and compared to soil-only controls (C). As determined by MaAsLin2 analysis, significant shifts in bacterial communities at 30 cm depths within the A, S and C treatments distinguished control from experimental soils, and between aboveground and subsurface deposition, demonstrating the potential for gravesoil discrimination during the first 90 days. For example, Dokdonella (p = 0.0002), Edaphobaculum (p = 0.0004) and Lacibacter (p = 0.0034) recorded significant shifts relative to sampling time. Furthermore, Massilia (p = 0.0005), Mycobacterium (p = 0.0006) and Sandaracinus (p = 0.0007) increased in abundance for the aboveground mice treatments. This was confirmed with ANOSIM where p = 0.0082 showed statistically significant difference between the aboveground and subsurface deposition. TBS and physicochemical analyses suggested that nutrient release into the soils occurred during active decay and skin rapture on days 7–13 in the subsurface and days 13–20 aboveground, with a particular increase in soil potassium concentration on day 15. Significant differences in soil temperatures resulted between A and S vs. C microcosms, aligning with atmospheric temperature changes. In summary, complementary application of metabarcoding, total body score, exogenous and physicochemical methods for postmortem interval estimation and clandestine grave location highlighted the feasibility of using temperature records downloaded from meteorological stations and portable X-ray fluorescence as indicators for various phases of decomposition.

Impact of environmental factors on atmospheric radon variations at China Jinping Underground Laboratory

In this study, long-term and continuous monitoring of atmospheric radon concentration, temperature, air pressure, and humidity was conducted at China Jinping Underground Laboratory. The impacts of temperature, humidity, and air pressure on radon concentration in the experimental environment were specifically examined, along with the potential interactions among these factors. Moreover, Radon data were denoised using Singular Spectrum Analysis (SSA) to reveal factors that might influence changes in radon concentration. The possible mechanisms by which these environmental factors influence radon migration have also been explored. This research not only provides new insights into the behavior of radon in underground environments but also offers important references for formulating effective radon management and protective actions.

Research on Performance Prediction of Air Quality Assurance Systems for Gas Turbines Based on Novel Test Method

The quality of air intake significantly impacts the overall performance of gas turbines. A new high-precision testing method for the air intake quality assurance system of gas turbines has been proposed, and the influence of typical intake conditions on the system was studied through this testing method. The research results indicate a positive correlation between filtration efficiency and particle size. Atmospheric temperature, particle concentration, filter differential pressure, and atmospheric humidity all affect filtration efficiency, with their influence decreasing in that order. Additionally, this paper presents a performance prediction model based on the LSTM neural network. The calculation results show that the errors of the filter pressure loss and filtration efficiency model test set are both less than 3%, reflecting the characteristics of pressure loss and efficiency well. The research results have significant engineering application value and provide experimental basis for establishing technical standards and high-precision detection systems for air quality assurance in gas turbines.

Retrieval of Cloud Macro‐Physical Properties Using theFY‐4A Advanced Geostationary Radiation Imager (AGRI) and the Geostationary Interferometric Infrared Sounder (GIIRS)

AbstractThis study presents a novel approach for conducting all‐day retrieval of cloud macro‐physical properties (single‐layer cloud phase, cloud top height, and cloud base height for optical thickness less than 10) using the Advanced Geostationary Radiation Imager (AGRI) and the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the geostationary meteorological satellite Fengyun‐4A based on machine learning methods. Model accuracy was compared after integrating ECMWF Reanalysis v5 (ERA‐5) data, atmospheric temperature and moisture profiles, and GIIRS clear‐column radiance. Results demonstrate that integrating GIIRS clear‐column radiances can enhance the precision of cloud phase classification and the retrieval of cloud macro‐physical properties. This effectively replaces the role of atmospheric temperature and humidity profiles, which are typically required for thermal infrared remote sensing retrieval. Moreover, the issue of delayed acquisition of ERA‐5 atmospheric temperature and humidity profiles is mitigated, enabling near real‐time and all‐day retrieval of cloud macro‐physical properties.

Aerosol Direct Radiative Effects From Extreme Fire Events in Australia, California and Siberia Occurring in 2019–2020

AbstractThis study aims at investigating the biomass burning aerosols (BBA) from 2019 to 2020 extreme wildfires in California, Australia and Siberia, in terms of aerosol characteristics and direct radiative effect. This study is based on the comparison between global climate simulations (ARPEGE‐Climat) and reference aerosol data sets (reanalyzes, ground‐based observations and satellite data). First, our results demonstrate the need to constrain the injection heights in the model in order to realistically represent extinction vertical profiles observed during fire events, both in the troposphere and in the lower stratosphere due to the contribution of pyro‐convection. Without specific vertical emission profiles for fires, the ARPEGE‐Climat simulations fail in representing aerosol extinction vertical profiles. For each region studied, the modeled aerosol optical depth (AOD) is extremely high (above 3 at 550 nm). An important long‐range transport of BBA emitted in Australia and California is shown, with high AOD further from sources. These extremely dense plumes significantly perturb the surface incident solar radiation and exert a large direct (surface) shortwave radiative effect up to −13, −29 and −17 W on monthly average over Australia (January 2020), California (September 2020) and Siberia (August 2019), respectively. A noteworthy positive BBA direct radiative effect (warming) is found at the top of the atmosphere, when dense and strongly absorbing smoke plumes are advected over cloudy oceanic regions, characterized by high surface albedo. This absorption leads to an increase of the solar heating rate up to 0.3 K with possible implications on the atmospheric temperature and dynamics.

Irradiated Atmospheres. I. Heating by Vertical-mixing-induced Energy Transport

Observations have revealed unique temperature profiles in hot Jupiter atmospheres. We propose that the energy transport by vertical mixing could lead to such thermal features. In our new scenario, strong absorbers, TiO, and VO are not necessary. Vertical mixing could be naturally excited by atmospheric circulation or internal gravity wave breaking. We perform radiative transfer calculations by taking into account the vertical-mixing-driven energy transport. The radiative equilibrium is replaced by the radiative-mixing equilibrium. We investigate how the mixing strength, K zz, affects the atmospheric temperature–pressure profile. Strong mixing can heat the lower atmosphere and cool the upper atmosphere. This effect has important effects on the atmosphere's thermal features that would form without mixing. In certain circumstances, it can induce temperature inversions in scenarios where the temperature monotonically increases with increasing pressure under conditions of lower thermal band opacity. Temperature inversions show up as K zz increases with altitude due to shear interaction with the convection layer. The atmospheric thermal structure of HD 209458b can be well fitted with K zz ∝ (P/1 bar)−1/2 cm2 s−1. Our findings suggest vertical mixing promotes temperature inversions and lowers K zz estimates compared to prior studies. Incorporating chemical species into vertical mixing will significantly affect the thermal profile due to their temperature sensitivity.