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Background: Physical activity (PA) is an important contributor to one's physical and mental health both acutely and across the lifespan. Much research has done on the ambient environment's impact on PA; however, these studies have used absolute values of atmospheric measures such as temperature and humidity, which vary spatiotemporally and make comparisons between studies which differ in location or time of year difficult to square with one another. Methods: Here, we employ the Global Weather Type Classification, Version 2, to determine the combined impact of temperature and humidity on PA in a sample of insufficiently active young adults. We conducted secondary analyses of data from a single-group behavioral intervention trial that varied the number of digital messages sent daily. Young adults (n = 81) wore Fitbit Versa smartwatches for a 6-month period sometime between April 2019 and July 2020, and location was tracked using a custom smartphone application. Results: Mixed linear models indicated that, across 8179 person-days, PA was significantly lower on days with humid conditions and significantly higher on warm dry days, though the latter relationship was no longer significant when controlling for timing in relation to the COVID-19 pandemic declaration. Demographic factors did not affect the relationship between weather and PA. Conclusions: Results are a first step in providing additional guidance for encouraging PA in insufficiently active individuals given forecasted daily weather conditions. Future work should examine seasonal variability in the weather type–PA relationship without the influence of a world-altering event influencing results. [ABSTRACT FROM AUTHOR]

The giant impact between proto-Earth and a Mars-sized planet called Theia resulted in the formation of the Earth–Moon system, and the silicate mantles of the initial bodies may have partly been vaporized. Here, we develop a machine learning potential for MgSiO3 based on the data from first-principles calculations to estimate its critical point. The variations in pressure along different isotherms yield the position of the critical point of MgSiO3 at 0.54 g cm−3 and 6750 ± 250 K, which agrees with the previous theoretical estimation. We also simulate the MgSiO3 melt under a spectrum of critical conditions to understand the changes in coordination environment with density and temperature. The fourfold Si–O coordination hardly changes with increasing density at 3000 K. However, with increasing temperature, the dominance of four-coordinated Si–O diminishes rapidly as density decreases. Regarding Mg–O coordination, the overall trend, which varies with temperature and density, remains largely consistent with Si–O but with a greater diversity in the types of coordination due to more bond breaking events. Our work opens a new avenue by employing machine learning methods to estimate the critical point of silicates. [ABSTRACT FROM AUTHOR]

Dry‐ and wet‐bulb temperature (Td and Tw) are usually to define heatwaves (HWs) which have been enhanced under anthropogenic climate change (ACC) and urbanization. However, responses of various types of HWs (i.e., dry HWs, only high Td; humid HWs, only high Tw; hybrid HWs, both high Td and Tw; total HWs, high Td or Tw), to ACC and urbanization remain unknown. In this study, both observations and simulations show significantly increasing occurrence probability of total HWs over China during 1971–2020, whereas this increase is mainly reflected in hybrid HWs, followed by dry HWs and humid HWs. 68.2%–93.0% of the observed increases in the above four types of HWs can be attributed to ACC; on the other hand, urbanization tends to suppress humid HWs but enhance dry HWs, as a result of contributing to the increase of hybrid HWs by 10.9%. Under future ACC, total HWs are projected to be more frequent as expected, which is mainly sourced from the increasing hybrid HWs because dry/humid HWs are projected to be steady/downward. As a consequence, urban population exposure to ACC‐induced total HWs would remarkably increase to 83.55 billion person‐days by the 2090s, 89.5% of which can be attributed to hybrid HWs. Urbanization would amplify this population exposure of ACC‐induced hybrid HWs from 74.79 billion person‐days to 110.9 billion person‐days. Our results underscore the importance of improving understanding of hybrid HWs in urban areas and developing targeted adaptation planning on a warmer planet. Plain Language Summary: Under global warming and urbanization, increases in heatwaves (HWs) characterized by air temperature and humidity, have profound adverse effects on human health and socio‐economic well‐being. In this study, HWs are divided into four types: humid HWs (dominated by high air humidity), dry HWs (dominated by high air temperature), hybrid HWs (both high temperature and high humid), and total HWs (encompassing all the three above types), to investigate changes in HWs under different temperature and humidity conditions and their responses to anthropogenic climate change (ACC) and urbanization. Both observations and simulations show that occurrence probability of the four types of HWs increased over China in recent decades, of which ACC contributes to 68.2%–93.0% of intensification of HWs. The increasing occurrence probability of total HWs is mainly reflected in hybrid HWs, followed by dry HWs and humid HWs. Urbanization tends to inhibit (promote) rise in humid HWs (dry HWs), resulting in an increase in hybrid HWs. Under urban expansion and global warming, urban population in China will be more exposed to extremes of humid and hot conditions (hybrid and total HWs), especially in densely populated and rapidly urbanizing areas. Key Points: Historical increasing likelihood of total heatwaves (HWs) over China is dominated by that of hybrid HWsUrbanization tends to suppress (enhance) humid (dry) HWs and hence increase likelihood of hybrid HWs under anthropogenic climate changeFuture anthropogenic warming and urban expansion jointly lead to remarkable increase of urban population exposure to hybrid HWs [ABSTRACT FROM AUTHOR]

Wet and cold biases on the Tibetan Plateau (TP) commonly exist in global and regional climate simulations. Previous studies have explored the possible causes of wet and cold biases and contributed to reducing these biases. However, the connection between wet and cold biases remains insufficiently addressed. Our research indicates that the TP wet bias converts into positive snow amount bias not continually but efficiently and concentratedly, under the control of snow phenology in different regions. Furthermore, the complex relationship between snow amount, snow coverage and surface albedo restricts the transformation of snow amount to surface albedo bias, and thus to cold bias. Our research highlights the spatio‐temporally divergent transformation of wet to cold bias on the TP during snow season, providing a novel perspective to understand the intrinsic connection between wet and cold biases and improve climate simulations on the TP. Plain Language Summary: Due to the harsh environment, observational data are limited on the Tibetan Plateau (TP), so climate model is one of necessary tools for climate researches. However, both global and regional climate models generally overestimate precipitation (wet bias) and underestimate near surface air temperature (cold bias) on the TP. Previous studies have pointed out the possible causes of the wet and cold biases, and partly reduced these biases, leaving the connection between these biases unaddressed. Our study finds that the conversion of wet to cold bias during snow season is divergent in different areas of the TP. Under the control of snow duration in different areas, the wet bias efficiently and concentratedly transforms into larger snow amount. Furthermore, the complex relationship between snow amount, snow coverage and surface albedo restricts the transformation of snow amount to surface albedo bias, and thus to cold bias. We reveal the spatio‐temporally divergent transformation of wet to cold bias on the TP during snow season, and these conclusions will contribute to a better improvement of snow and climate modeling on the TP. Key Points: WRF simulations significantly overestimate snow amount and delay snow phenology on the Tibetan Plateau (TP)Snowfall bias is not always transformable into snow amount bias, depending on snow phenologyComplex relationship between snow amount and surface albedo restricts the transformation of wet to cold bias on the TP [ABSTRACT FROM AUTHOR]

The applicability and accuracy of high‐resolution Real‐Time Meso‐scale Analysis (RTMA) system is assessed over India for the first time. The RTMA is a high‐spatial (2.5 km) and temporal resolution analysis system for near‐surface weather conditions. It is used to simulate near‐surface air temperature over India during the Heatwave (HW) period 12th to 20th April 2023. The verification analysis of temperature using the GLDAS gridded temperature shows reasonable improvement in the analysis from RTMA by capturing regional features compared to first‐guess. The spatial and temporal verification using the IMD station observations also confirms the value addition of RTMA in capturing the locations of recorded highest Tmax and their daily variations. The location‐specific heat stress analysis of RTMA shows high skill over many locations during HW days. Heat stress regions have been accurately brought out in the RTMA. Hence, the RTMA can be used for now‐casting and severe weather monitoring. Plain Language Summary: Heat wave (HW) alert systems require accurate high‐resolution surface weather data for better adaption strategies. Real‐Time Meso‐scale Analysis (RTMA) system configured to generate surface weather parameters at a high‐spatial (2.5 km) and temporal (3 hrs) resolution at National Center for Medium Range Weather Forecasting (NCMRWF) for the very first time in India. We verified its performance in representing the HW conditions and extreme temperatures over the Indian region relative to India Meteorological Department (IMD) observations/Global Land Data Assimilation System (GLDAS) during the HW period of 12th to 20th April 2023. Our results indicate significant improvement in the spatial and temporal variations of daily maximum temperature simulated by RTMA system. We have noted lower absolute mean errors of ∼ 0.02 for the RTMA in predicting the Tmax over the HW affected regions of Bihar, Odisha, West Bengal, and East Uttar Pradesh when compared to the GFS model. These improvements have led to the better identification of the locations of higher heat risk through the computation of the Heat Index and highlight the applicability of RTMA. Overall this study clearly brings out the usability of RTMA final analysis fields for now‐casting and severe weather monitoring. Key Points: It is a first‐of‐its‐kind study to understand the applicability and accuracy of high‐resolution RTMA over India by analyzing heatwaveRTMA temperature analysis shows higher skill over the heatwave regions and locations as compared to the background fields and observationsThe study suggested that the RTMA final analysis fields are highly useable for severe weather monitoring and impact‐based weather forecasts [ABSTRACT FROM AUTHOR]

Summary: Current estimates of temperature effects on plants mostly rely on air temperature, although it can significantly deviate from leaf temperature (Tleaf). To address this, some studies have used canopy temperature (Tcan). However, Tcan fails to capture the fine‐scale variation in Tleaf among leaves and species in diverse canopies.We used infrared radiometers to study Tleaf and Tcan and how they deviate from air temperature (ΔTleaf and ΔTcan) in multispecies tropical tree plantations at three sites along an elevation and temperature gradient in Rwanda.Our results showed high Tleaf (up to c. 50°C) and ΔTleaf (on average 8–10°C and up to c. 20°C) of sun‐exposed leaves during 10:00 h–15:00 h, being close to or exceeding photosynthetic heat tolerance thresholds. These values greatly exceeded simultaneously measured values of Tcan and ΔTcan, respectively, leading to strongly overestimated leaf thermal safety margins if basing those on Tcan data. Stomatal conductance and leaf size affected Tleaf and Tcan in line with their expected influences on leaf energy balance.Our findings highlight the importance of leaf traits for leaf thermoregulation and show that monitoring Tcan is not enough to capture the peak temperatures and heat stress experienced by individual leaves of different species in tropical forest canopies. [ABSTRACT FROM AUTHOR]

Most C–H bond activations of natural gas alkanes rely on transition metal complexes. Activations by using main-group systems have been reported but required heating or photo-irradiation under high atmospheric pressure with rather low regioselectivity. Here we report that Lewis acid-carbene adducts facilely undergo oxidative additions to C–H bonds of ethane, propane and n-butane with high selectivity under room temperature and atmospheric pressure. The Lewis acids can be moved by the addition of a base and the carbene-derived products can be easily converted into aldehydes. This work offers a route for main-group element compounds to selectively functionalise C–H bonds of natural gas alkanes and other small molecules. Activation of natural gas alkanes using main-group systems typically requires heating or photo-irradiation under high atmospheric pressure with low regioselectivity. Here the authors report Lewis acid-carbene adduct activation of C–H bonds in ethane, propane and n-butane under one atmospheric pressure and at room temperature with high selectivity. [ABSTRACT FROM AUTHOR]

Introduction: Amidst escalating global temperatures, increasing climate change, and rapid urbanization, addressing urban heat islands and improving outdoor thermal comfort is paramount for sustainable urban development. Green walls offer a promising strategy by effectively lowering ambient air temperatures in urban environments. While previous studies have explored their impact in various climates, their effectiveness in humid climates remains underexplored. Methods: This research investigates the cooling effect of a green wall during summer in a humid climate, employing two approaches: Field Measurement-Based Analysis (SC 1: FMA) and Deep Learning Model (SC 2: DLM). In SC 1: FMA, experiments utilized data loggers at varying distances from the green wall to capture real-time conditions. SC 2: DLM utilized a deep learning model to predict the green wall's performance over time. Results: Results indicate a significant reduction in air temperature, with a 1.5°C (6%) decrease compared to real-time conditions. Long-term analysis identified specific distances (A, B, C, and D) contributing to temperature reductions ranging from 1.5°C to 2.5°C, highlighting optimal distances for green wall efficacy. Discussion: This study contributes novel insights by determining effective distances for green wall systems to mitigate ambient temperatures, addressing a critical gap in current literature. The integration of a deep learning model enhances analytical precision and forecasts future outcomes. Despite limitations related to a single case study and limited timeframe, this research offers practical benefits in urban heat island mitigation, enhancing outdoor comfort, and fostering sustainable and climate-resilient urban environments. [ABSTRACT FROM AUTHOR]

Simple Summary: Low-pressure systems frequently occur during the summer in coastal areas and can be detrimental to commercial poultry houses. The effects of air temperature and humidity vary across different periods. Throughout the generation of low-pressure systems, landfall, and disappearance, air temperature and humidity changes can interfere with the housing environment. However, farmers often overlook the impact of low-pressure systems on large-scale poultry houses, which may impair the production of laying hens. This study investigated the effects of the different low-pressure systems on the housing environment and egg production in large-scale poultry houses in China. The results indicated that a single low-pressure system reduced the laying performance, whereas a sustained low-pressure system mitigated the impact on egg production. This study aimed to determine the effect of low-pressure systems on the environment and the laying performance of large-scale poultry houses during the summer and to provide a basis for farmers to adjust their environmental control strategies under extreme weather conditions. Low-pressure systems (LPSs) are among the most critical weather systems, producing excessive precipitation that causes air temperatures to drop and rise considerably. Acute temperature changes directly affect poultry feed intake (FI) and laying performance. To explore the effects of LPSs on hens, the parameters of air temperature, relative humidity, egg production, and feed utilization efficiency were evaluated during different LPSs in three houses. Results indicated that about 2.8 ± 0.7 d, 2.4 ± 0.5 d, and 2.4 ± 0.5 d before the LPS landfall in houses 1, 2, and 3, respectively, the indoor air temperature started to decrease, with the average decreases being 1.7 °C ± 0.4 °C, 2.4 °C ± 0.6 °C, and 1.8 °C ± 0.4 °C, respectively. Significant differences were observed between different LPSs for reducing indoor air temperature (p < 0.05) in the three houses. In house 1, the egg production rates (EPRs) were decreased by 6.6% and 1.1% when LPSs 1 and 2 landed. The average egg weight (AEW) and FI during the LPS landfall were significantly higher than those before the LPS landfall (p < 0.01). Under successive LPSs landfall in the three houses, the EPRs initially reduced by 3.9%, 4.0%, and 0.5%, respectively, but the second LPS event increased the EPRs by 1.8%, 5.3%, and 1.0%, respectively. Furthermore, the LPS landfall increased the feed conversion ratio (FCRe) in the three houses, all above 2.00. In conclusion, LPSs can reduce heat stress, lower the EPRs, and lead to higher FI, FCRe, and AEW. [ABSTRACT FROM AUTHOR]

In recent years, extreme climate events have shown to be occurring more frequently. As a highly populated area in central China, the Jialing River Basin (JRB) should be more deeply explored for its patterns and associations with climatic factors. In this study, based on the daily precipitation and atmospheric temperature datasets from 29 meteorological stations in JRB and its vicinity from 1960 to 2020, 10 extreme indices (6 extreme precipitation indices and 4 extreme temperature indices) were calculated. The spatial and temporal variations of extreme precipitation and atmospheric temperature were analyzed using Mann–Kendall analysis, to explore the correlation between the atmospheric circulation patterns and extreme indices from linear and nonlinear perspectives via Pearson correlation analysis and wavelet coherence analysis (WTC), respectively. Results revealed that among the six selected extreme precipitation indices, the Continuous Dry Days (CDD) and Continuous Wetness Days (CWD) showed a decreasing trend, and the extreme precipitation tended to be shorter in calendar time, while the other four extreme precipitation indices showed an increasing trend, and the intensity of precipitation and rainfall in the JRB were frequent. As for the four extreme temperature indices, except for TN10p, which showed a significant decreasing trend, the other three indices showed a significant increasing trend, and the number of low-temperature days in JRB decreased significantly, the duration of high temperature increased, and the basin was warming continuously. Spatially, the spatial variation of extreme precipitation indices is more obvious, with decreasing stations mostly located in the western and northern regions, and increasing stations mostly located in the southern and northeastern regions, which makes the precipitation more regionalized. Linearly, most of the stations in the extreme atmospheric temperature index, except TN10p, show an increasing trend and the significance is more obvious. Except for the Southern Oscillation Index (SOI), other atmospheric circulation patterns have linear correlations with the extreme indices, and the Arctic Oscillation (AO) has the strongest significance with the CDD. Nonlinearly, NINO3.4, Pacific Decadal Oscillation (PDO), and SOI are not the main circulation patterns dominating the changes of TN90p, and average daily precipitation intensity (SDII), maximum daily precipitation amount (RX1day), and maximum precipitation in 5 days (Rx5day) were most clearly associated with atmospheric circulation patterns. This also confirms that atmospheric circulation patterns and climate tend not to have a single linear relationship, but are governed by more complex response mechanisms. This study aims to help the relevant decision-making authorities to cope with the more frequent extreme climate events in JRB, and also provides a reference for predicting flood, drought and waterlogging risks. [ABSTRACT FROM AUTHOR]

A large input delay, parametric uncertainties, matched disturbances and mismatched disturbances exist extensively in variable air volume air-conditioning systems, which can deteriorate the control performance of the room temperature and even destabilize the system. To address this problem, an adaptive-gain command filter control framework for the room temperature of variable air volume air-conditioning systems is exploited. Through skillfully designing an auxiliary system, both the filtered error and the input delay can be compensated concurrently, which can attenuate the effect of the filtered error and the input delay on the control performance of the room temperature. Then, a smooth nonlinear term with an adjusted gain is introduced into the control framework to compensate for parametric uncertainties, matched disturbances and mismatched disturbances, which relieves the conservatism of the controller gain selection. With the help of the Lyapunov theory, both the boundedness of all the system signals and the asymptotic tracking performance for the room temperature can be assured with the presented controller. Finally, the contrastive simulation results demonstrate the validity of the developed method. [ABSTRACT FROM AUTHOR]

Even though the streamer process can be identified in nanoseconds and microseconds through experimental measurements, the breakdown time of air discharge is still unknown. The instability of electrons is suspected to be an attachment-instability phenomenon of the channel conductivity. We investigated breakdown time across milliseconds to better understand how the oxygen excitations of the 200–400 nm range influence a high-conductivity channel even with a weaker applied voltage. Experiments were performed with positive impulse voltages ranging from +42 to +75 kV in the step of +6 kV at a 3 cm gap between needle-to-plane electrodes in a horizontal configuration. A spectrometer with an integration time of 70 ms was used to capture the spectra during voltage discharge. The shortest breakdown time was found at +60 kV with 77 ns compared to +66, +72, and +75 kV. We conclude that the shorter breakdown time at +60 kV is primarily due to the oxygen-excited state in O IV at 262.999 nm. This state helps maintain electron flow by preventing electron loss, with a decay time of 2.5 µs, while releasing Joule heat at a temperature of 26,003 K, which optimizes conductivity. This process occurs before the recombination of the O I line at 777.417 nm, which has a significantly shorter decay time of 27 ns. [ABSTRACT FROM AUTHOR]

The hydration heat generated during the concreting of cast-in-place piles causes thermal disturbance to the surrounding permafrost, leading to its thawing. This further affects the stability of the pile foundation and degrades the construction progress. To explore the influence mechanisms of the concrete hydration heat on the permafrost temperature field around the pile, as well as that of different construction seasons on the pile-side boundary conditions and permafrost temperature field, monitoring results of on-site tests and numerical simulation were used to analyze the distribution law of the pile soil temperature field in space and time, and the pile-side boundary conditions and permafrost temperature field during construction seasons. The results show that the temperature trend of the pile foundation can be divided into three stages: a rapid rise phase (0∼2 d), a rapid decline phase (2∼10 d), and a slow decline and stabilization phase (10∼90 d). As the radial distance from the pile center decreases, there occur a corresponding acceleration in temperature increase and an elevated maximum temperature rise (MTR). The influence range of the molding temperature and the hydration heat is about 1∼2 times the pile diameter and less than 1.5 m in the depth direction. Compared to the atmospheric temperature, there is a lag in the change in the permafrost temperature caused by accumulation of ground temperature, and the significant difference between the two leads to an increased rate of heat exchange at the boundary condition. Conducting drilling operation and cast-in-place pile construction in the cold seasons is conducive to reducing the thermal disturbance to the permafrost around the pile in permafrost areas. [ABSTRACT FROM AUTHOR]

Stem water content serves as a pivotal parameter that reflects the plant vitality and maintains their internal water balance. Given the insufficient comprehension regarding the stem water content characteristics and its influencing factors during different stages of the overwintering period, the study focused on Acer truncatum Bunge and developed an Internet of Things (IoT)-based ecological information monitoring system. The system incorporated a proprietary stem water content sensor, allowing non-invasive, in-situ and real time acquisition of stem water content while monitoring diverse environmental parameters. We conducted a detailed elucidation of stem water content variation characteristics and their responses to diverse environmental factors. The results showed: (1) During the overwintering period, stem water content exhibited diurnal variations characterized by " daytime ascent and nighttime descent" across the three stages, exhibiting differences in the moment when the stem water content reaches extremal values and daily fluctuations ranges. Stem water content exhibited minimal fluctuations during deciduous and bud-breaking stages but experienced significant freezing-thawing alternations during the dormant stage, leading to an increased daily fluctuation range. (2) The Pearson correlation coefficients between environmental parameters and stem water content varied dynamically across stages. Path analysis revealed that during the deciduous stage, stem temperature and saturation vapor pressure deficit were dominant factors influencing stem water content; during dormant stage, air temperature and saturation vapor pressure deficit directly impacted stem water content; during the bud-breaking stage, the primary parameters affecting stem water content were saturation vapor pressure deficit and stem temperature. The study provides valuable insights into unveiling the water transport patterns within tree stems tissue and their environmental adaptation mechanisms during the overwintering period, aiding in the scientific development of winter management strategies to protect trees from severe cold and freezing damage, while fostering healthy growth in the subsequent year. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automotive Digest is the property of Automotive Digest Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A new composite material, named TSC/AXAD-2, was developed by incorporating a bis-thiosemicarbazone derivative (TSC) into Amberlite XAD-2 to extract Pb2+ ions from wastewater. The new composite was characterized using XPS, TGA, FTIR, BET, EDX, 1H-NMR, 13C-NMR, and GC-MS analyses. The sorption parameters, such as pH value of media, equilibrium time, initial Pb2+ ion concentration, composite dose, temperature, and eluting agents, were methodically optimized. The utmost adsorption capacity is 45.3 mg.g−1; it was achieved at pH value of of 5.5, 15 min of agitation, room temperature, and initial concentration of 200 mg.L−1 Pb2+ ions. The isotherm studies revealed that the adsorption process closely matches the Langmuir model, with a theoretical retention capacity of 46.12 mg.g−1. Furthermore, kinetic modeling using the pseudo-first-order accurately depicted the adsorption of Pb2+ ions. The thermodynamic study suggested that the adsorption process is exothermic, spontaneous, and more favorable at lower temperatures. The desorption of Pb2+ ions from the loaded composite was conducted with 1.0 M of either HCl or HNO3. The TSC/AXAD-2 composite successfully met WHO and FAO guidelines for removal of Pb2+ ions from wastewater before its discharge into the marine environment. [ABSTRACT FROM AUTHOR]

Recently, numerous studies have highlighted that the climate worldwide is changing rapidly due to increased greenhouse gas (GHG) emissions. The average ambient temperatures across Canada are rising approximately twice as fast as the rest of the world. The projected change in climate may increase the air and surface temperature indices, thus affecting the duration of spring load restrictions (SLRs) on roads, which may potentially impact the trucking industry and economy. Therefore, the best practices must be adjusted when identifying the optimal SLR periods that consider climate change. In Ontario, Canada, the SLR periods are imposed based on subsurface temperature data that is obtained from the road weather information system (RWIS) and spring load adjustment (SLA) stations in conjunction with visual observations. In this study, different methods of determining SLR periods were investigated. Then, new models were developed to correlate the surface cumulative thawing index (CTI) and thawing depth (TD) of a site. These models were developed utilizing atmospheric, surface, and subsurface data that was collected from different SLA and RWIS weather stations at various locations across Ontario, Canada. Finally, the developed models were utilized to predict the SLR periods for future scenarios using data from different global circulation models (GCM) and representative concentration pathways (RCPs). This study concludes that the SLR periods are expected to shrink across Ontario, Canada, by 2100. The results of this study might help different road authorities and trucking agencies maximize the life of the road structure and minimize the economic hardships that are faced during SLR periods. [ABSTRACT FROM AUTHOR]

A 3D model is established to discuss the influence of combustion reaction on jet characteristics. Based on this, combustion behaviors of supersonic jet for single‐flow postcombustion oxygen lance with various secondary nozzle parameters (diameter, inclination angle, and number) are analyzed. The results indicate that after activating combustion reaction, the jet velocity, dynamic pressure, density, and temperature of primary jet at H = 1.45 m are 1.27, 1.15, 0.56, and 1.97 times than those of without considering the combustion, respectively. Enlarging secondary nozzle diameter is helpful to extend the flame core lengths of primary and secondary jets (the axial distance from lance tip to isotherm of 1773 K) as well as the combustion region. With the increase of secondary nozzle angle, the two flame core lengths both decrease, while the combustion zone increases. Increasing the number of secondary nozzles, the flame core length of primary jet increases while that of the secondary jet decreases, and the combustion region first increases and then decreases. As for the influences of the above parameters on flame core lengths of primary and secondary jets as well as the combustion region, the number is the greatest, followed by the inner diameter, and the inclination angle is the smallest. [ABSTRACT FROM AUTHOR]

In recent decades, the annual mean temperature has increased, with unusual alternations of hot and cold years. In addition, the changes in temporal precipitation patterns are caused by complex interactions between temperature change, the global water cycle, and other components of the Earth's systems. To construct a statistical model of these temporal patterns in terms of temperature and precipitation, we propose a logistic mixture of spatial multivariate penalized regression splines for temporal profiles and apply this model to the contiguous United States climate data over 123 years (1900 to 2022) at 252 weather stations. The results reveal that the proposed model identifies climatologically meaningful clusters of weather stations in the contiguous United States with two important meteorological variables, temperature and precipitation, identifying the climate change patterns of each climate zone. The surface air temperature increased in the Northeast and West (Mountain and Pacific) regions, where the climate is affected by the continental Arctic air. A notable increment of precipitation also occurred in the Northeast. In contrast, the South region, where the climate is affected by the tropical Atlantic Ocean, is more stable than other regions in terms of year-to-year variations in temperature and precipitation. [ABSTRACT FROM AUTHOR]

The summer of 2022 has been the so far hottest summer on record in Central Europe. High temperatures negatively affect the physiology of plants and cause considerable thermal stress in particular on the leaf level. The assessment of the temperature-dependent decline of the quantum use efficiency of the photosystem II (Fv/Fm) has gained much popularity to quantify the leaf-level sensitivity to thermal stress. An open question is whether leaves heat to those in vitro estimated threshold temperatures on hot days or if plants can avoid heat stress through transpirational cooling. Therefore, leaf temperatures were monitored on a non-native Austrian oak (Quercus cerris) during a heatwave in July 2022 and compared to observed air temperature and leaf thermal traits assessed with a chlorophyll fluorometer. The highest air temperature recorded during the heatwave was 42.5 °C and surpassed the breaking point temperature (temperature at 5% decline of Fv/Fm; T5) by 0.3 °C, but was 6.1 °C lower than T50 (temperature at 50% decline of Fv/Fm). However, during the hottest day, the maximum leaf temperature was significantly below the air temperature. Even the directly illuminated leaf facing south reached a maximum temperature of only 38.7 °C but reached 39.8 °C on the second hottest day when the air temperature went up to 39.6 °C. All leaves showed a certain degree of homeothermy as the slope between leaf temperature and air temperature was 0.83 (P < 0.05). In conclusion, Austrian oak can buffer thermal stress during heatwaves to a certain degree, however, leaf temperatures are only marginally below critical threshold temperatures. [ABSTRACT FROM AUTHOR]

Increasing summer temperatures and higher probabilities of extreme heat events have led to concerns about tree damage and mortality. However, insufficient attention has been given to conditions leading to heat-related regeneration failures in temperate forests. To address this, managers need to understand how microclimate varies under a range of overstory conditions. We measured air temperatures at 2 cm above-ground underneath a gradient of canopy cover on south-facing slopes in recently thinned Douglas-fir stands in western Oregon, USA. To expand the ecological relevance of these data to impacts on regeneration, we created the stress degree hours (SDH) metric, representing the amount of time—and by how much—temperatures exceeded biologically relevant stress thresholds. Overall, for every 10% increase in canopy cover, maximum temperatures at 2 cm were 1.3 °C lower, the odds of temperatures exceeding stress thresholds for conifer regeneration declined by a multiplicative factor of 0.26, and the total of SDH decreased by 40%. These reductions are large enough to be worthy of attention when managing for tree regeneration. However, data collected during the Pacific Northwest Heat Dome in June 2021 indicate that with various climate change scenarios and heatwave occurrences, temperatures will be unfavorable for regeneration regardless of overstory cover. [ABSTRACT FROM AUTHOR]

Direct air capture (DAC) is a negative emission technology for removing CO2 from the atmosphere to maintain the CO2 level within a reasonable range so as to address greenhouse effects. In this study, the operational optimization of lab‐scale DAC has been investigated using a crossflow air‐liquid contactor loaded with a three dimensionally printed Gyroid packing structure and a potassium sarcosinate solvent. The effects of various parameters, including feed air flow rate, liquid solvent flow rate, contactor geometry, and ambient temperature, are examined. The results demonstrate that the Gyroid packing design achieves comparable CO2 capture performance to conventional packed beds but with a significantly lower pressure drop of up to 77.8%, suggesting its potential as an efficient and cost‐effective solution for gas–liquid contactors in DAC. Additionally, the study explores the climate impact on CO2 capture performance and finds that as the air temperature increases from 35 to 95°F at a fixed relative humidity of 80%, the CO2 capture rate increased from 23.2% to 46.8% with better stability. The research highlights the importance of optimizing contactor design and operational conditions to improve the CO2 capture rate and feasibility of DAC systems as a negative emission technology for addressing greenhouse effects. [ABSTRACT FROM AUTHOR]

Heat exchangers require periodic maintenance. Offline cleaning scheduled shutdowns are usually needed to restore the exchanger effectiveness, drastically reduced when fouling accumulation occurs. An online real-time alternative for monitoring the effectiveness of exchanger (during a period of eleven months of continuous operation) and an adapted version of the ε-NTU method to calculate its effectiveness are discussed. The experimental difficulties of measuring the mass flow rate and the hot air temperature at the exit of the exchanger is examined. Detailed analysis confirmed that the outlet temperature of the hot fluid could introduce errors of up to 30% in the calculation of the exchanger effectiveness. A skillful treatment of the energy balance is proposed to address the issue. The associated uncertainties are estimated by two independent approaches, the so-called classic method, i.e., the Guide to the Expression of Uncertainty in Measurement and the Monte Carlo method. Both confirmed that measurements of the air outlet temperature accounts for more than 50% of the uncertainty associated with the calculation of the exchanger effectiveness. It is suggested that the conventional method (based on measurements of the outlet air temperature) is not suitable for traditional everyday practices to monitor the effectiveness of the heat exchangers of hydrogenerators. [ABSTRACT FROM AUTHOR]

Non-ionic hydrophobic eutectic solvents have emerged as a new class of eutectic solvents. They are prepared by mixing two non-ionic components. They have gained significant interest compared to their counterpart ionic hydrophobic eutectic solvents and hydrophobic ionic liquids due to the availability of a wide array of non-ionic substances that can be used to prepare these solvents. Understanding the distinct physical characteristics of these solvents is crucial to their practical application within process industries and associated fields. The present work reports the development of a density model for these solvents based on the conductor-like screening model (COSMO), a dielectric continuum solvation model. For this purpose, a comprehensive literature search was carried out, and 485 density points of 37 different hydrophobic non-ionic eutectic solvents were collected. COSMO volume, one of the outputs of the COSMO calculations, was correlated with the experimental molar volume for the model development. Two different models were developed, one at 298.15 K and another a general model that can predict the density over a wide temperature range at atmospheric pressure. The developed model only requires the molar ratio and COSMO volumes of the components forming the eutectic solvents to predict the density. The proposed general model performed better than most other models and was comparable with the best one reported in the literature, with an average relative deviation percent (ARD%) of 1.34%. [ABSTRACT FROM AUTHOR]

Asparagus (Asparagus officinalis L.) is an important vegetable crop in southern Ontario, Canada, where winter air and soil temperatures below 0°C are common. Consequently, cultivars growing in this area must possess winterhardiness and freezing tolerance for survival. Asparagus acquires freezing tolerance in the fall through cold acclimation and loses freezing tolerance in the spring through deacclimation. To understand the molecular bases of these processes, transcriptomic analysis (RNA-Seq) was conducted on two cultivars, one adapted, 'Guelph Millennium' (GM), and one unadapted, 'UC157' (UC), to the winter conditions of southern Ontario. RNA extracted from bud and rhizome tissues, sampled on three dates during early spring and late fall, was subjected to sequencing. In the fall, the numbers of differentially expressed (DE) genes at the second and third harvests increased, relative to the first harvest, in dormant buds and rhizomes as freezing tolerance of cultivars increased, and the majority of DE genes were downregulated. In spring, freezing tolerance decreased as plants deacclimated and most genes DE at second and third harvests were upregulated in both cultivars. GM had lower LT50 (lethal temperature at which 50% of plants die) values and hence higher freezing tolerance than UC on specific sampling dates during both spring and fall, and expression patterns of specific genes were correlated with LT50 differences. Functional analysis revealed that these genes were involved in carbohydrate metabolic process, plant hormone signal transduction (auxin and gibberellin), proline metabolism, biosynthesis of secondary metabolites, circadian rhythm, and late embryogenesis abundant proteins and could be associated with cold acclimation and deacclimation processes. These findings will help researchers understand the molecular mechanisms of freezing tolerance in asparagus, leading to breeding and genetic strategies to improve the trait. [ABSTRACT FROM AUTHOR]

The increasing ocean warming due to climate change significantly threatens regional marine ecosystems by raising the frequency and severity of extreme temperature events. This study examines patterns and trends of maximum annual sea surface temperature (Tmax) in the Eastern China Seas from 1985 to 2022. The results show a significant warming trend in Tmax, exceeding the global average, with notable differences between southern and northern regions. The northern Tmax warming rate is faster, with occurrence times significantly advancing, while the southern Tmax warming rate is slower, with occurrence times significantly delayed. The southern Tmax and its timing are closely correlated with the annual maximum air temperature and its timing. In the north, Tmax timing is influenced by latent heat flux (QLH); a significant increase in August QLH inhibits the continued rise of SST, causing Tmax to advance. The study also highlights a significant increase in marine heatwaves at Tmax timing, with higher Tmax indicating a higher occurrence probability. By elucidating these Tmax trends and dynamics, our study enhances understanding of regional climate impacts, supporting targeted conservation efforts and adaptive ecosystem management strategies in the Eastern China Seas. [ABSTRACT FROM AUTHOR]

The influence of northern polar vortex in the stratosphere (SPV) in December‐January on Asia's surface air temperature (SAT) in February has been examined using reanalysis data sets and a barotropic model. An out‐of‐phase interannual linkage between the SPV in December‐January and SAT in February during 1979–2022 has been observed, that is, a strong (weak) SPV corresponds to a cooling (warming) over Asia. Approximately 25% of the SAT over Asia in February can be explained by the SPV in December‐January. This relationship between the SPV and SAT is independent of the Arctic Oscillation. The influence of the SPV on SAT over Asia cannot be solely explained by radiative processes, but is instead related to circulation anomalies in the troposphere. A stronger SPV tends to result in negative geopotential height anomalies with cyclonic circulation over Asia. The SPV‐related geopotential height over Asia is accompanied by a weakened teleconnection pattern between the North Atlantic and Asia, with three centers from the northeastern Atlantic‐eastern Europe‐Asia, and fewer stationary waves propagated from North Atlantic into Asia. These anomalous circulation patterns and anomalous northerly wind over Central Asia in February are beneficial to the colder air transportation from the higher latitudes to Asia, facilitating a surface cooling over Asia. Our results shed light on the interannual linkage between SPV and SAT over Asia, suggesting that the SPV in December‐January could be considered as a new predicator of SAT in February over Asia. Plain Language Summary: Scientists and the public have become increasingly aware of the significant influences of the stratosphere on tropospheric weather and climate. While numerous studies have focused on the crucial roles of stratospheric anomalies in shaping surface air temperature (SAT) anomalies over Europe and North America, relatively little attention has been given to understanding the potential impacts of stratospheric polar vortex over Arctic (SPV) on SAT over Asia. In this study, we found a robust and out‐of‐phase linkage between the SPV in December‐January and SAT in February over Asia during 1979–2022. A stronger SPV tends to induce an anomalous cyclonic circulation characterized by negative geopotential height, facilitating the transport of colder air from higher latitudes to Asia, thereby contributing a cooling effect on the surface. Our findings suggest that the December‐January SPV can serve as a predictor for SAT in February over Asia. Key Points: A strong (weak) SPV in December‐January tends to result in a cooling (warming) over Asia in February on interannual timescalesThe out‐of‐phase linkage between December‐January SPV and February surface air temperature (SAT) is independent of AO in FebruaryThe influence of SPV on Asia SAT is related to the tropospheric circulation anomalies via dynamic process, rather than radiative process [ABSTRACT FROM AUTHOR]

Midlatitude Europe (ME) emerges as a prominent heatwave hotspot with rapid increases in summer surface air temperature and heatwave days since 1979, surpassing the global land averages by approximately 2.6 and 2.3 times, respectively. The circulation analogs‐based dynamic adjustment reveals that approximately 38% and 35% of these trends result from shifts in zonal dipolar circulation patterns over the North Atlantic (NA) and Europe, crucial for the enhanced warming compared to the global land average. The circulation changes are associated with warming sea surface temperatures in the NA. This warming pattern resembles the Atlantic Multidecadal Variability and is predominantly induced by greenhouse gases. Moreover, the stronger air temperature response in ME to decreased aerosols amplifies warming, contributing to the rapid increase in heatwave frequency. These findings highlight a prominent influence of anthropogenic forcings on the swift surge of European heatwaves compared to global land, with a potential implication for adaptation strategies and risk management. Plain Language Summary: Midlatitude Europe is experiencing a significant increase in heatwaves, with summer temperatures and heatwave occurrences rising much faster than the global land averages since 1979. One of the key contributors to this rapid warming is the changes in zonal dipolar circulation patterns over the NA and Europe, which are linked to the warm sea surface temperatures in the NA. This warming pattern, resembling the Atlantic Multidecadal Variability, is largely caused by greenhouse gases and additionally influenced by reduced aerosols and natural forcing. Furthermore, the stronger response of air temperatures in midlatitude Europe to decreased aerosol emissions intensifies summer warming, contributing to a rapid increase in heatwave days. These findings highlight the significant impact of anthropogenic forcings on the observed surge of heatwaves in Europe compared to global land, with an important implication for developing strategies to adapt to these changing climate conditions and managing the associated risks. Key Points: Midlatitude Europe exhibits more rapid increases in summer heatwave frequency than the global land averages in recent decadesAtmospheric circulation changes contributing about one third of the observed warming trend, further intensify the rapid increases in summer heatwave frequencyLocal air temperature response to reduced aerosol emissions contributes about half of the enhanced warming compared to the global land average [ABSTRACT FROM AUTHOR]

Previous research has explored the impact of the Interdecadal Pacific Oscillation (IPO) and Atlantic Multidecadal Oscillation (AMO) on Antarctic surface air temperature (SAT) variability. However, a notable gap remains in our comprehension concerning the response of Antarctic SAT to the four phase combinations of IPO and AMO. In this study, we unveil unique patterns of Antarctic SAT anomalies during four distinct sub-periods based on the phases of IPO and AMO. Notably, Antarctic SAT anomalies exhibit a considerable seasonality, with the most pronounced (weakest) anomalies occurring during the austral winter (summer), a phenomenon consistent across all four sub-periods. These different anomalous SST patterns trigger varying convective rainfall patterns, consequently initiating distinct wavetrains that propagate into the Southern Ocean. These different wavetrains, in turn, induce variations in sea level pressure and surface wind fields, resulting in different Antarctic SAT anomalies primarily through mechanisms related to horizontal thermal advection and downward longwave radiation. Plain language summary: Understanding the variability in Antarctic surface air temperature (SAT) is crucial for unraveling the complex dynamics of the polar climate system and its broader implications for global climate patterns. Fewer studies highlighted the impacts of the four combinations of the phases of IPO and AMO on Antarctic SAT anomalies. In this study, we uncover distinct patterns of Antarctic SAT anomalies during four different periods based on the phases of IPO and AMO. We note that Antarctic SAT anomalies exhibit a considerable seasonality, with the most pronounced (weakest) anomalies occurring during the austral winter (summer), consistently across all four periods. The anomalous SST patterns during different periods trigger distinct wavetrains that propagate into the Southern Ocean, inducing variations in sea level pressure, surface wind fields, and Antarctic SAT anomalies. These findings bear substantial implications for the prediction of Antarctic seasonal SAT variations on interdecadal timescales. Key points: Antarctic SAT anomalies exhibit a considerable seasonality during the four combinations of the phases of the IPO and AMO. These different SST anomalies during the combinations trigger distinct wavetrains that propagate into the Southern Ocean. Different wavetrains induce anomalous sea level pressure and surface wind fields and Antarctic SAT through thermal advection and radiation. [ABSTRACT FROM AUTHOR]

Climate change and extreme weather events are threatening agricultural production worldwide. The anticipated increase in atmospheric temperature may reduce the potential yield of cultivated crops. Agroforestry is regarded as a climate-resilient system that is profitable, sustainable, and adaptable, and has strong potential to sequester atmospheric carbon. Agroforestry practices enhance agroecosystems' resilience against adverse weather conditions via moderating extreme temperature fluctuations, provisioning buffers during heavy rainfall events, mitigating drought periods, and safeguarding land resources from cyclones and tsunamis-type events. Therefore, it was essential to comprehensively analyze and discuss the role of agroforestry in providing resilience during extreme weather situations. We hypothesized that integrating trees in to the agro-ecosystems could increase the resilience of crops against extreme weather events. The available literature showed that the over-story tree shade moderates the severe temperature (2-4°C) effects on understory crops, particularly in the wheat and coffee-based agroforestry as well as in the forage and livestock-based silvipasture systems. Studies have shown that intense rainstorms can harm agricultural production (40-70%) and cause waterlogging. The farmlands with agroforestry have been reported to be more resilient to heavy rainfall because of the decrease in runoff (20-50%) and increase in soil water infiltration. Studies have also suggested that drought-induced low rainfall damages many crops, but integrating trees can improve microclimate and maintain crop yield by providing shade, windshield, and prolonged soil moisture retention. The meta-analysis revealed that tree shelterbelts could mitigate the effects of high water and wind speeds associated with cyclones and tsunamis by creating a vegetation bio-shield along the coastlines. In general, existing literature indicates that implementing and designing agroforestry practices increases resilience of agronomic crops to extreme weather conditions increasing crop yield by 5-15%. Moreover, despite its widely recognized advantages in terms of resilience to extreme weather, the systematic documentation of agroforestry advantages is currently insufficient on a global scale. Consequently, we provide a synthesis of the existing data and its analysis to draw reasonable conclusions that can aid in the development of suitable strategies to achieve the worldwide goal of adapting to and mitigating the adverse impacts of climate change. [ABSTRACT FROM AUTHOR]

A study was conducted on the climatological characteristics of fog and mist at Pula Airport in the northeastern Adriatic, using statistical and machine learning approaches. The study utilized meteorological data from Pula Airport, along with satellite sea surface temperature (SST) data from two coastal areas west and east of the airport, to gain insights into the influence of sea temperature on fog formation. To identify weather patterns associated with the occurrence of fog and mist, wind and mean sea-level pressure (MSLP) data from the ERA5 reanalysis were analyzed using Growing Neural Gas (GNG), a machine learning method. A notable finding was a declining trend in the frequency of fog and mist at the airport, which can be linked to the results of the GNG analysis of the ERA5 data. This analysis showed a decrease in synoptic patterns favorable for fog and mist. Fog occurs mainly between October and March and is primarily associated with weak easterly and northeasterly winds. Additionally, fog is more likely to occur when the sea surface temperature is higher than the air temperature. Mist has similar characteristics to fog, although it is more likely to occur with easterly winds. [ABSTRACT FROM AUTHOR]

This study explores aerosol direct, indirect, and feedback effects on meteorology and fine particulate matter during heat waves of August 2022 over eastern China by using an online coupled regional climate–chemistry–aerosol model. In this period, aerosols exerted mean direct (DRE) and indirect (IRE) radiative effects of −3.9 Wm−2 and −2.4 Wm−2 at TOA, which totally caused a decrease in average surface air temperature by 0.3 °C over east China, accompanied by decreases in PBLH (planetary boundary layer height) and precipitation and an increase in PM2.5 concentration. With the anthropogenic emission reduction from 2013 to 2022, DRE apparently decreased while IRE changed little, leading to a decrease in total aerosol radiative effect (TRE) by 27% at TOA. The weakened TRE resulted in increases in surface air temperature and precipitation by 0.14 °C and 2.7 mm, respectively, on average over east China, with the maximum warming exceeding 0.5 °C in BTH (Beijing–Tianjin–Hebei province). This study highlights a warming trend due to weakened TRE, which may exacerbate heat wave, and an increasing importance of aerosol IRE relative to DRE due to weak sensitivity of cloud properties to aerosol change during the emission reduction. [ABSTRACT FROM AUTHOR]

For the development of efficient management and conservation strategies for wild rodent species, understanding the aspects related to their reproduction, including the interaction of this physiological function with the environment, is essential. This study aimed to evaluate the impacts of weather changes derived from a semiarid region's dry and rainy seasons on the epididymal sperm characteristics of red-rumped agouti (Dasyprocta leporina), a histricognath rodent, still little studied, which inhabits the Brazilian Caatinga. The sperm from the epididymal cauda of 14 agoutis were collected, seven individuals per season (dry and rainy). Samples were evaluated for kinetic parameters, membrane structural and functional integrity, mitochondrial activity, morphology, and morphometry. The environmental variables were measured: maximum air temperature, relative humidity, wind speed, solar radiation, and the total rainfall for dry and rainy seasons were, respectively, 36.2 and 34.1 °C, 66.8 and 80.1%, 4.0 and 1.9 m/s, 527.3 and 441.8 W/m2, and 0.2 and 517.7 mm. There were strong correlations between some sperm parameters and environmental variables, mainly those related to the acquisition of sperm mobility. Sperm concentration and the number of sperm collected were higher in the dry (1028.7 sperm/mL × 10⁶ and 1361.2 × 106 sperm) than in the rainy season (758.9 sperm × 10⁶/mL and 714.6 sperm × 106). During the rainy season, there were fewer sperm defects, higher sperm metrics, and higher membrane structural integrity with mitochondrial activity. Regarding motility patterns, the increases during the rainy season stand out in total and progressive motility, VAP, VSL, VCL, and subpopulations of rapid sperm. In summary, our results suggest that the adverse climatic conditions of the dry season in the semiarid region, mainly high solar radiation and temperature, considerably impair the epididymal sperm quality of red-rumped agoutis. On the contrary, the largest amount of sperm was obtained during this season, probably due to compensatory and adaptive mechanisms of the species to enable its reproduction throughout the year. [ABSTRACT FROM AUTHOR]

Antarctic warm extremes impact the cryosphere, with very warm extremes driving surface melt on ice shelves. Here, we analyze temperatures exceeding the 90th percentile and the associated circulation patterns and radiation anomalies. ERA5 reanalysis data show positive geopotential height anomalies related to the occurrence of warm extremes. The highest temperature during warm extremes appears on the western periphery of high‐pressure systems, consistent with anticyclonic advection. Temperature anomalies during warm extremes are strongest in winter due to the transport of warm and moist air and a strong meridional temperature gradient. In summer, the weak meridional gradients of top‐of‐atmosphere downward solar radiation flux and surface air temperature contribute to weak temperature anomalies. Warm extremes are associated with positive longwave radiation anomalies in all seasons, but with negative shortwave radiation anomalies at the surface except during polar night. These relationships are verified by station observations. Our results confirm that Antarctic warm extremes are mostly driven by meridional advection of warm air, and suggest that these warm air masses are predominantly moist and cloudy. Plain Language Summary: Changes in Antarctic climate will alter the amount of water stored in the kilometer‐thick Antarctic ice cover, and thereby global sea level. So far, only some regions of the continent have experienced substantial warming under climate change, while others remain largely unaffected. In this study, we analyze the relatively warmest Antarctic temperatures in each place and season. We find that these warm extremes depart more strongly from seasonal mean temperatures in winter than in summer. Warm extremes are often a consequence of warmer air being transported from further North and coincide with moist, probably cloudy air that emits more infrared radiation to the surface than dry, cold air. Key Points: Warm extremes accompanied by high‐pressure systems are driven by advectionWinter experiences strongest temperature anomalies during warm extremesLongwave radiation anomalies during warm extremes are positive and contribute to warm extremes, shortwave radiation anomalies are negative [ABSTRACT FROM AUTHOR]

In this study, the Atmospheric Infrared Sounder (AIRS) Observations for Model Intercomparison Projects (Obs4MIPs) V2.1 tropospheric air temperature, specific humidity, and relative humidity data are utilized to evaluate the global tropospheric temperature and humidity simulations in the fully coupled global climate models from the Coupled Model Intercomparison Project phases 3, 5, and 6 (CMIP3, CMIP5, and CMIP6), and possible simulation improvement in CMIP6 models in comparison to CMIP3 and CMIP5 models. Our analyses indicate that all three phases of CMIP models share similar tropospheric air temperature, specific humidity, and relative humidity biases in their multi‐model ensemble means relative to AIRS. Cold biases up to 4 K and positive relative humidity biases up to 20% are found in the free troposphere almost globally with maxima over the mid‐latitude storm tracks. Warm biases up to 2 K are seen over the Southern Ocean in the lower troposphere. Positive specific and relative humidity biases exist over the off‐equatorial oceans while negative specific and relative humidity biases are seen near the equator in the tropical free troposphere, which are related to the double‐intertropical convergence zone bias in the models. Both the air temperature and specific humidity biases are important to the relative humidity biases except in the tropical free troposphere where the specific humidity biases dominate. The tropospheric air temperature, specific humidity, and relative humidity biases are reduced from CMIP3 to CMIP5 and to CMIP6 at almost all pressure levels except at 300 hPa for specific humidity and in the boundary layer for relative humidity. Plain Language Summary: In this study, we use the Atmospheric Infrared Sounder (AIRS) data to assess how well the fully coupled global climate models simulate temperature and humidity in the troposphere. We focus on the climate models from the recent three phases of Coupled Model Intercomparison Project (CMIP3, CMIP5, and CMIP6) and investigate if there is any bias reduction in the recent CMIP6 models compared to the earlier CMIP3 and CMIP5 models. To conduct our evaluation, we compare the CMIP model ensemble averages with the AIRS data and find that all three phases of CMIP models exhibit similar biases in tropospheric temperature and humidity. For example, cold biases up to 4 K and positive relative humidity biases up to 20% are seen in the free troposphere over most regions, with the maximum biases over the midlatitudes. Positive specific and relative humidity biases are found over the off‐equatorial oceans while negative specific and relative humidity biases are seen near the equator in the tropical free troposphere. We also note a possible temperature and humidity bias reduction from the CMIP3 models to the CMIP5 models and then to the CMIP6 models at most pressure levels. Key Points: CMIP Phase 3, 5 and 6 climate models share similar tropospheric air temperature, specific and relative humidity biases relative to Atmospheric Infrared SounderCold biases and positive relative humidity biases are prevalent in free troposphere almost globally with maxima over the mid‐latitude oceansDouble‐intertropical convergence zone bias‐related specific and relative humidity biases are evident in tropical free troposphere: positive (negative) off (near) the equator [ABSTRACT FROM AUTHOR]

The impacts of falling ice radiative effects (FIREs) on land‐atmosphere feedback processes were examined, with a focus on the fidelity of land surface properties and their variability as inferred by global climate models (GCMs). We conducted a pair of sensitivity experiments using the National Center for Atmospheric Research (NCAR) Community Earth System Model Version 1 (CESM1) in fully coupled modes with FIREs turned on and off. This allowed us to investigate the seasonal response of land surface properties to changes in radiation fluxes and land surface temperature (LST) associated with FIREs across global land areas. Our findings indicate that during boreal winter, excluding FIREs results in less surface downward longwave and net flux (∼5–15 Wm−2), leading to a colder land surface (∼2–4 K) and air temperatures (∼1–4 K) at mid‐ and high latitudes. Consequently, the surface frozen soil layer and snow cover persist through spring, delaying snowmelt and thawing until summer. This delay reduces liquid soil moisture, thereby suppressing vegetation productivity in subsequent seasons. Conversely, tropical regions, exhibit contrasting responses, with a warmer land surface (∼0.5 K) and warmer air temperatures (∼0.1–0.5 K) due to increased surface downward shortwave and net flux (∼2–10 Wm−2). This enhancement in radiation fosters increased vegetation productivity throughout the seasonal cycle. These findings illustrate a local response of land surface properties to changes in the surface energy balance and LST, highlighting the significant role that FIREs play in land surface modeling within GCMs. Plain Language Summary: We explored the seasonal response of land surface properties to changes in radiation fluxes and land surface temperature across global land areas using the CESM1‐CAM5 coupled model with falling ice radiative effects (FIREs) both turned on and off. During boreal winter, excluding FIREs reduces surface downward longwave and net flux, resulting in a colder land surface and colder air temperatures at mid‐ and high latitudes. These cold conditions lead to the persistence of the surface frozen soil layer and snow cover through spring, delaying snowmelt and thawing until summer, which in turn reduces liquid soil moisture and suppresses vegetation growth in subsequent seasons. In contrast, tropical regions exhibit a warmer land surface and air temperatures due to increased downward shortwave and net flux, promoting vegetation growth throughout the year. Key Points: Most Coupled Model Intercomparison Project Phase 5 models did not consider falling ice radiative effects (FIREs)Excluding FIREs results in cold air, prolonging frozen soil and snow cover, which suppress vegetation growth at mid‐ to high latitudesExcluding FIREs leads to warmer air temperatures and promotes enhanced vegetation growth in tropical latitudes [ABSTRACT FROM AUTHOR]

In July and August 2022, the Yangtze River basin (YRB) experienced its hottest summer since 1961. The SINTEX‐F2 seasonal prediction system initialized in early May predicted the hotter‐than‐normal summer due to its successful prediction of central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the tropical West Pacific‐East Indian Ocean (TWP_EIO). The common SST forcing explains only about 26% to the heatwave strength, while the internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction account for approximately 65%, based on the analysis of 108 ensemble members. These factors have collectively increased the maximum temperature over the YRB through the enhancement and westward expansion of western North Pacific subtropical high. Our findings quantify the relative contributions of external forcing and internal variations to the unprecedented hot event, offering insights into its forming mechanism and potential predictability. Plain Language Summary: A record‐breaking heatwave event occurred in the YRB in July and August 2022, posing significant risks on human health, power supply, and social economic activities. Recognizing the importance of such an event, our study aims to identify key factors influencing its prediction using the SINTEX‐F2 system. The central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the TWP_EIO provide the dominant predictability, but accounts only about 26% of the heatwave strength. However, internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction collectively explain about 65%. Our results suggest the necessity of large‐ensemble prediction in capturing this kind of unprecedented extreme event. Key Points: The SINTEX‐F2 initialized on 2022 early May captures the warmer‐than‐normal air temperatures in Yangtze River basinThe model successfully predicts co‐occurrences of CP La Niña and negative IOD in 2022However, the direct SST forcing contributes only 26% to the 2022 extreme event in Yangtze River basin [ABSTRACT FROM AUTHOR]

The impact of land variables on temperature forecasts in atmospheric cycling is often underestimated or overlooked. This oversight primarily occurs due to the abundance of meteorological measurements available for assimilation and partly because soil states are assumed to be quickly reset by atmospheric forcing, such as precipitation, justifying no spin‐ups or no updates of soil states during cycling. In this study, by updating soil moisture every 6 hr using different analysis data sets for May 2019, considerable discrepancies were found, highlighting large uncertainties in soil moisture analysis. Different soil moisture analyses produced systematically different temperature forecasts, with errors growing over cycles to be comparable to a typical error magnitude of 2‐m temperature observations (∼2°K). This study demonstrates that temperature forecasts are significantly influenced by whether and how soil moisture is updated, not only near the surface but also up to the low‐mid troposphere and throughout the cycles. Plain Language Summary: This study examines the impact of soil moisture on temperature forecasts in the context of atmospheric cycling. During the 6‐hr cycling for May 2019 over the CONUS domain, updating soil moisture systematically affects temperature forecast bias (>±1°K) in the low‐mid troposphere throughout the cycles. We also observe significant uncertainties across state‐of‐the‐art soil moisture analysis data sets, highlighting the challenges of land data assimilation. Key Points: Temperature forecast errors are significantly affected by whether or how soil moisture is updated in atmospheric cyclingLarge uncertainties are found across different soil moisture analysis data setsUpdating soil moisture alone can mitigate temperature forecast bias in the low‐mid troposphere, systematically improving forecast accuracy [ABSTRACT FROM AUTHOR]

The mechanisms by which clouds impact the variability of the mid‐latitude atmosphere are poorly understood. We use an idealized, dry atmospheric model to investigate the relationship between Atmospheric Cloud Radiative Effects (ACRE) and annular mode persistence. We force the model with time‐varying diabatic heating that mimics the observed ACRE response to the Southern Annular Mode (SAM). Realistic ACRE forcing reduces annular mode persistence by 5 days (−16%), which we attribute to a weakening of low‐frequency eddy forcing via modified low‐level temperature gradients, though this effect is partly compensated by reduced frictional damping due to zonal wind anomalies becoming more top‐heavy. The persistence changes are nonlinear with respect to the amplitude of ACRE forcing, reflecting nonlinearities in the response of the eddy forcing. These results highlight the ACRE's impact on low‐frequency eddy forcing as the dominant cause of changes in annular mode persistence. Plain Language Summary: In this study, we conduct novel modeling experiments aimed at understanding how clouds affect the unforced variability of jet streams—concentrated bands of eastward wind in the mid‐latitude atmosphere. We focus on direct heating and cooling of the atmosphere by clouds, called Atmospheric Cloud Radiative Effects (ACRE), and how these impact the annular mode—the most significant type of jet stream variability, which consists of north‐south shifts of the jet's position. Using a simplified atmospheric model, we investigate how the persistence and structure of the annular mode are impacted by heatings and coolings that mimic the observed ACRE response to the Southern Hemisphere Annular Mode (SAM). We find that the ACRE reduces the persistence of the annular mode (i.e., deviations of the jet stream from its mean position tend to persist for less time), which we attribute to a weakening of the feedback mechanism by which atmospheric waves strengthen the jet where it is already strongest. We identify some compensating effects, but, overall, our results highlight that ACRE impacts jet streams via low‐altitude temperature gradients and atmospheric wave generation. Key Points: The response of Atmospheric Cloud Radiative Effects (ACRE) to the Southern Annular Mode (SAM) reduces SAM's persistenceThe decrease in SAM's persistence is attributed to weakened low‐frequency eddy forcing via disruption of low‐level temperature gradientsThe change in persistence is nonlinear with respect to the amplitude of ACRE forcing [ABSTRACT FROM AUTHOR]

This study investigates the use of a balloon-launched uncrewed aircraft system (UAS) for the measurement of turbulence in the troposphere and lower stratosphere. The UAS was a glider which could conduct an automated descent following a designated flight trajectory and was equipped with in situ sensors for measuring thermodynamic and kinematic atmospheric properties. In addition, this aircraft was equipped with an infrasonic microphone to assess its suitability for the remote detection of clear-air turbulence. The capabilities of the UAS and sensing systems were tested during three flights conducted in New Mexico, USA, in 2021. It was found that the profiles of temperature, humidity, and horizontal winds measured during descent were in broad agreement with those made by radiosonde data published by the US National Weather Service, separated by up to 380 km spatially and by 3 to 5 h temporally. Winds measured during controlled flight descent were consistent with the winds measured by global-positioning-system-derived velocity during balloon ascent. During controlled descent with this particular payload, a nominal vertical resolution on the order of 1 m was achieved for temperature, relative humidity, and pressure with a nominal vertical resolution of the wind velocity vector on the order of 0.1 m ; the aircraft had a glide slope angle from 1 to 4° during this time. Analysis approaches were developed that provided turbulent kinetic energy and dissipation rate, but it was found that the corresponding Richardson number was sensitive to the methodology used to determine the vertical gradients from a single flight. The low-frequency content of the infrasonic microphone signal was observed to qualitatively align with long-wavelength wind velocity fluctuations detected at high altitude. Moreover, the microphone measured more broadband frequency content when the aircraft approached turbulence produced by the boundary layer. [ABSTRACT FROM AUTHOR]

Since 2011, the Global Energy and Water cycle Exchanges (GEWEX) Water Vapor Assessment (G-VAP) has provided performance analyses for state-of-the-art reanalysis and satellite water vapour products to the GEWEX Data and Analysis Panel (GDAP) and the user community in general. A significant component of the work undertaken by G-VAP is to characterise the quality and uncertainty of these water vapour records to (i) ensure full exploitation and (ii) avoid incorrect use or interpretation of results. This study presents results from the second phase of G-VAP, where we have extended and expanded our analysis of total column water vapour (TCWV) from phase 1, in conjunction with updating the G-VAP archive. For version 2 of the archive, we consider 28 freely available and mature satellite and reanalysis data products, remapped to a regular longitude–latitude grid of 2° × 2° and on monthly time steps between January 1979 and December 2019. We first analysed all records for a "common" short period of 5 years (2005–2009), focusing on variability (spatial and seasonal) and deviation from the ensemble mean. We observed that clear-sky daytime-only satellite products were generally drier than the ensemble mean, and seasonal variability/disparity in several regions up to 12 kg m -2 related to original spatial resolution and temporal sampling. For 11 of the 28 data records, further analysis was undertaken between 1988–2014. Within this "long period", key results show (i) trends between - 1.18 ± 0.68 to 3.82 ± 3.94 kg m -2 per decade and - 0.39 ± 0.27 to 1.24 ± 0.85 kg m -2 per decade were found over ice-free global oceans and land surfaces, respectively, and (ii) regression coefficients of TCWV against surface temperatures of 6.17 ± 0.24 to 27.02 ± 0.51 % K -1 over oceans (using sea surface temperature) and 3.00 ± 0.17 to 7.77 ± 0.16 % K -1 over land (using surface air temperature). It is important to note that trends estimated within G-VAP are used to identify issues in the data records rather than analyse climate change. Additionally, breakpoints have been identified and characterised for both land and ocean surfaces within this period. Finally, we present a spatial analysis of correlations to six climate indices within the long period, highlighting regional areas of significant positive and negative correlation and the level of agreement among records. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3) has major effects on the environment and climate. In situ measurements of NH 3 concentrations taken between June 2009 and July 2020 at an urban site in Beijing were analyzed to study its long-term behavior, responses to meteorological conditions, and influences on the formation of secondary inorganic aerosols (SIAs). The 11-year average NH 3 mixing ratio was 26.9±19.3 ppb (median 23.5 ppb). The annual average NH 3 mixing ratio increased from 2009 to 2017 by 50 % and then decreased by 49 % from 2017 to 2020. Notably, the long-term trend for NH 3 at the ground level did not align with the trends derived from satellite observations and emission estimates. The NH 3 concentration exhibited a stronger correlation with the daily variation in water vapor (H 2 O) concentration than with air temperature. Thermodynamic modeling revealed the nonlinear response of SIAs to NH 3 , with increased sensitivity when its concentration was reduced to 40 % of the initial level. Although reducing NH 3 concentrations can improve air quality during winter, controlling acid gas concentrations has a greater effect than controlling NH 3 concentrations on reducing SIA concentrations, until NH 3 and acidic gas concentrations are reduced below 80 % of their current levels. Nevertheless, the increased mass proportion of ammonium salts in SIAs during the observation period indicates that future control measures for NH 3 concentrations may need to be prioritized in Beijing. [ABSTRACT FROM AUTHOR]

Greenhouses are used to create the appropriate environment for plant growth. Controlling the level of lighting using shading nets is one of the most commonly used methods for making suitable environmental modifications in greenhouses. The objective of this study was to examine the impact of three colored shading nets (green, black, and beige at shading rates of 50%) on inside air temperature, relative humidity, and spectral distribution of light in a greenhouse, as well as their effect on the growth and yield of strawberry plants. Data were collected during winter (December and January) and spring (March and April) months from shaded and unshaded blocks. The green net had the highest transmittance to solar radiation (τSR) during the two periods (38% and 35%, respectively) and the highest transmittance to photosynthetically active radiation (τPAR) of 34% during spring months, while the beige net had the highest τPAR of 27% during winter months. The black net had the smallest τPAR values during the two periods (22% and 29%, respectively). The lowest total light levels per season for solar radiation (SR) and photosynthetically active radiation (PAR) (746.8 and 293.7 MJ·m−2, respectively) were obtained under the black net, compared with (906.7 and 320.8 MJ·m−2, respectively) for the beige net, and (969.6 and 337.2 MJ·m−2, respectively) for the green net. The ratio of PAR to SR (PAR:SR) was 41% and 44% outside and inside the greenhouse for the control (without shade), respectively. The black net had the highest ratio of PAR:SR (39%) among the treatment nets. The green net transmitted more light in the blue–green region (400 to 570 nm) and transmitted the highest photon flux at 480 nm, while the beige net increased the infrared radiation flux from 730 nm and above and transmitted the highest photon flux at 604 nm. The study found that the green net increased the ratio of blue to red light (B/R), while the beige and green nets reduced the red to far-red light (R/FR) ratio. The photosynthetic rate, conductance to water, and transpiration were significantly higher for strawberries grown under the beige net. These results indicate that the beige net positively influenced leaf and stem characteristics, leading to improved strawberry yields. The best yields of strawberries were obtained under the beige net and the control group (no shade), surpassing the yields achieved under the black net by 26.3% and 21.4%, respectively. [ABSTRACT FROM AUTHOR]