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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]

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]

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]

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]

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]

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]

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]

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]

Summary Climate change not only leads to higher air temperatures but also increases the vapour pressure deficit (VPD) of the air. Understanding the direct effect of VPD on leaf gas exchange is crucial for precise modelling of stomatal functioning. We conducted combined leaf gas exchange and online isotope discrimination measurements on four common European tree species across a VPD range of 0.8–3.6 kPa, while maintaining constant temperatures without soil water limitation. In addition to applying the standard assumption of saturated vapour pressure inside leaves (ei), we inferred ei from oxygen isotope discrimination of CO2 and water vapour. ei desaturated progressively with increasing VPD, consistently across species, resulting in an intercellular relative humidity as low as 0.73 ± 0.11 at the highest tested VPD. Assuming saturation of ei overestimated the extent of reductions in stomatal conductance and CO2 mole fraction inside leaves in response to increasing VPD compared with calculations that accounted for unsaturation. In addition, a significant decrease in mesophyll conductance with increasing VPD only occurred when the unsaturation of ei was considered. We suggest that the possibility of unsaturated ei should not be overlooked in measurements related to leaf gas exchange and in stomatal models, especially at high VPD. [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]

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]

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]

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]

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]

This article presents modeling results and a comprehensive analysis of evaporative cooling systems designed for electric motors using the refrigerants R744 (trans-critical), R134a, R600a, and R290. This study aims to determine the most suitable refrigerant for use in a cooling system, optimize the system design, and calculate the maximum achievable motor power while adhering to specified temperature constraints. The modeling was validated by an experimental setup, which had the cooling system's configuration featuring three circuits for motor housing, stator, and rotor cooling, respectively. The modeling of an evaporative system was used to present the cooling efficiency under varying loads and external temperature conditions. Mathematical modeling encompasses complex algorithms to simulate heat transfer phenomena, accounting for fluid dynamics and refrigeration cycle dynamics. The analyses revealed trends in winding temperature, rotor temperature, air temperature inside the motor, heat transfer coefficient, coefficient of performance (COP), and motor power across different operating conditions while using different cooling refrigerants. The maximal heat transfer coefficients were calculated for all the refrigerants for winding temperatures in the range from 32 to 82 °C, while air temperature and rotor temperatures were between 42 and 105 °C and 76 and 185 °C, respectively. Lowering the evaporation temperature of the coolant to −35 °C resulted in a significant decrease in the winding temperature to 15 °C, air temperature to 38 °C, and maximum rotor temperature to 118 °C at a motor power of 90 kW. Refrigerant R744 emerged as a promising option, offering high heat transfer coefficients and achieving high motor power within temperature limits. At the same time, the COP was lower when compared with other working fluids because of the high ambient temperature on the gas cooler side. [ABSTRACT FROM AUTHOR]

This article proposes new values and geospatial models of winter and summer external design temperatures for designing buildings' heating, ventilation, and air-conditioning (HVAC) systems. The climatic design parameters applicable in Poland for the sizing of these installations are approximately 50 years old and do not correspond to Poland's current climate. New values of climatic design parameters were determined following the methods described in European standards and the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Handbook of Fundamentals. The determined climatic design parameters, particularly the winter and summer external design temperatures, were compared with those currently in force by law in Poland. The external air design dry-bulb temperatures presented in the article were developed based on meteorological and climatic data from the years 1991–2020 from two data sources: synoptic data from the Institute of Meteorology and Water Management (IMWM) in Poland and reanalysis models of the ERA5 database of the European Centre for Medium-Range Weather Forecasts (ECMWF). According to ASHRAE, with 99.6% and 0.4% frequency of occurrence, external air design dry-bulb temperatures for winter and summer were used to develop mathematical geospatial models of external design temperatures for the Central Europe area with Poland's territory in the centre part. Scattered data from 667 meteorological stations were interpolated to 40,000 uniform mesh points using a biharmonic spline interpolation method to develop these models. Linear regression and ANOVA analysis for the ERA5-generated data from 900 checkpoint data items were used to estimate the correctness of these models. Verified models were used to calculate winter and summer external design temperature isolines presented together with colour space representation on Mercator projected maps of Central Europe. [ABSTRACT FROM AUTHOR]

The widespread availability of Land Surface Temperature (LST) data from various sources presents a contemporary challenge for urban climate studies: how to efficiently compare these data with the results of traditional methods of temperature monitoring, which typically assume measurements at 2 m under sheltered conditions. In this line, the current study is based primarily on data extracted from a network of 31 points of hourly temperature monitoring at the 2 m level (Tair2m), in use between 2019 and 2021, in the city of Suceava in north-eastern Romania. These data allowed a detailed mapping for each hourly time step through multiple regression, adjusted by IDW, which was identified as the best interpolation method of Tair2m. These data were analyzed in parallel with LST data derived from Landsat imagery available in the analyzed period for 35 summer days with no or low cloud cover. The mapping results of both the Tair2m and LST data describe the main characteristics of the Suceava urban agglomeration (SvMA) heat island, which presents polynuclear features with intensities—as expressed by the temperature difference between the cores of the heat island and the surrounding rural areas—spanning during the summer noontime between 3.0 °C based on Tair2m and 7.1 °C on LST, respectively. The values of the Tair2m–LST differences were 0.68 °C on average, ranging from 5.33 to −19.17 °C, directly proportional to the imperviousness ratio (IMD) values, reaching the highest values in the local climate zones (LCZs) with a high built-up ratio (up to −19.17 °C) and the lowest (0.5 ÷ −0.5 °C) for those with bare soils, with isolated bushes and trees, with few or no buildings. The study results could serve as a tool to downscale the LST data to the level of Tair2m, which is useful for interpretation of the data derived from these commonly used tools in urban climate monitoring. [ABSTRACT FROM AUTHOR]

Urumqi is located in the arid region of northwestern China, known for being one of the most delicate ecological environments and an area susceptible to climate change. The urbanization of Urumqi has progressed rapidly, yet there is a lack of research on the urbanization effect (UE) in Urumqi in terms of the regional climate. This study investigates the UE of Urumqi (urban built-up area) on the regional thermal environment and its mechanisms for the first time, based on the WRF (Weather Research and Forecasting) model (combined with the Urban Canopy Model, UCM) simulation data of 10 consecutive years (2012–2021). The results show that the UE on surface temperature (Ts) and air temperature at 2 m (T2m) is strong (weak) during the night (daytime) in all seasons, and the UE on these is largest (smallest) in spring (winter). In addition, the maximum UE on both Ts and T2m is present over southern Urumqi in winter, whereas the maximum UE is identified over the northern Urumqi in other seasons. The maximum UE on Ts occurred in northwestern Urumqi at 18 LST (Local Standard Time, i.e., UTC+6) in autumn (reaching 5.2 °C), and the maximum UE on T2m occurred in northern Urumqi at 4 LST in summer (reaching 2.6 °C). Urbanization showed a weak cooling effect during daytime in summer and winter, reflecting the unique characteristics of the UE in arid regions, which are different from those in humid regions. The maximum cooling of Ts occurred in northern Urumqi at 11 LST in summer (reaching −0.4 °C), while that of T2m occurred at 10 LST in northern and northwestern Urumqi in winter (reaching −0.25 °C), and the cooling effect lasted for a longer period of time in summer than in winter. The UE of Urumqi causes the increase of Ts mainly through the influence of net short-wave radiation and geothermal flux and causes the increase of T2m through the influence of sensible heat flux and net long-wave radiation. The UE on the land surface energy balance in Urumqi can be used to explain the seasonal variation and spatial differences of the UEs on the regional thermal environment and the underlying mechanism. [ABSTRACT FROM AUTHOR]

Accurate air temperatures underpin environmental research. Most professional meteorological air temperature measurements still expose thermometers within traditional, naturally ventilated screens. Their representation of true air temperature depends on screen airflow, and therefore local winds. Accuracies of daily maximum (Tmax) and minimum (Tmin) air temperatures are assessed by comparison between a naturally ventilated large conventional screen and a co‐located aspirated reference screen. In over 1200 days' data, the naturally ventilated Tmin and Tmax both showed small (median < 0.06°C) cold bias, but, in 1% of cases, warm Tmax bias and cold Tmin bias >|1°C|. The Tmin cold bias is associated with calm clear nights, and the Tmax warm bias events with calm winter days at low sun angles, allowing solar heating of the screen. The prevalence of poor natural ventilation, potentially affecting Tmin and Tmax, is estimated across European sites. Poor ventilation occurred at Tmin for 12% of values, and at Tmax for 4%. Climatological averaging will reduce these effects, but, without corroborating wind data, statistical changes in Tmin or Tmax, including identifying “Tropical Nights” (Tmin > 20°C) or occurrences of winter extremes, may have limited value. Wider adoption of aspirated thermometer screens, with an initial overlap period, will largely eliminate these effects. [ABSTRACT FROM AUTHOR]

In order to accurately and easily predict the variation of the average temperature of the concrete rectangular hollow pier. Firstly, the temperature distribution of the concrete rectangular hollow pier of Changjiahe Special Bridge was observed for 212 days. Then, based on the observation data, the functional relationship between the average concrete hollow pier temperature and the outside air temperature, and the air temperature inside the hollow pier was studied. Finally, based on this functional relationship, a prediction model for the range of variation of the mean temperature of the hollow pier was given and verified. The results of the study show that: the change of external shade temperature can be regarded as the superposition of different cyclic changes and random changes; the change rule of the average temperature of the concrete hollow pier is the same as that of the air temperature, both presenting day-by-day cyclic and step changes; the linear correlation coefficients between the daily maximum and daily minimum average hollow pier temperature and the daily average air temperature are R = 0.980 and R = 0.973, respectively; the daily average air temperature, the daily average air temperature inside the pier and daily average hollow pier temperature are R = 0.980, R = 0.998; the daily variation of the average hollow pier temperature and the daily variation of the air temperature are approximately linear, with a correlation coefficient of R = 0.899; assuming that the average temperature of the concrete hollow pier is a folding change, based on the above relationship, a method of predicting the time-by-time average temperature of the concrete hollow piers is proposed, as well as two methods of predicting the average temperature of the test piers. Average temperature change range method. Comparing the predicted values with the measured values, it is found that the predicted values are in good agreement with the measured values. [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]

Summers with extremely high vapor pressure deficit contribute to crop losses, ecosystem damages, and wildfires. Here, we identify very rare summer vapor pressure deficit extremes globally in reanalysis data and climate model simulations, and quantify the contributions of temperature and atmospheric moisture anomalies to their intensity. The simulations agree with reanalysis data regarding these physical characteristics of historic vapor pressure deficit extremes, and show a +33/+28% increase in their intensity in the northern/southern mid-latitudes over this century. About half of this drastic increase in the magnitude of extreme vapor pressure deficit anomalies is due to climate warming, since this quantity depends exponentially on temperature. Further contributing factors are increasing temperature variability (e.g., in Europe) and the expansion of soil moisture-limited regions. This study shows that to avoid amplified impacts of future vapor pressure deficit extremes, ecosystems and crops must become more resilient not only to an increasing mean vapor pressure deficit, but additionally also to larger seasonal anomalies of this quantity. Global climate simulations are analyzed to identify extreme summer temperature and humidity conditions that are harmful to crops and ecosystems, and it is shown that climate change leads to a drastic intensification of such events in extratropical regions. [ABSTRACT FROM AUTHOR]

The unprecedented growth in population and swift industrial advancements exert considerable strains on the ecosystem, particularly within medium-sized and large urban landscapes. The critical investigation into the intricate links between current and prospective land utilization, as well as the ecosystem service value (ESV), holds considerable empirical relevance for the calibration of land usage frameworks, thereby contributing to the sustainable evolution of extensive urban zones. Utilizing GlobeLand 30 data, the present research probes into the pattern of land transformation and the spatial-temporal dispersal of ESV in Henan's Yellow River vicinity over a span from 2000 to 2020. For the enhancement of land usage alignment, a Markov-PLUS fusion model was devised to gauge three disparate ESV transition scenarios slated for 2030, namely, natural development scenario (NDS), cropland protection scenario (CPS), and ecological protection scenario (EPS). The principal determinants of land transformation within the 2000-2020 period were recognized as elevation, populace concentration, and atmospheric temperature. Amid the rapid accretion of construction land engulfing substantial cropland and grassland areas, there was an ESV diminution to the tune of 1.432 billion RMB between 2000 and 2020. The ESV's high-value regions were discerned within relatively undisturbed ecosystem zones, with the lower-value sections identified in cropland and constructed areas, where human interventions exerted pronounced effects on the ecosystem. In accordance with the 2030 land usage simulations and analyses, in contrast to alternative scenarios, the EPS exhibited the least fluctuation in land type alterations in 2030, demonstrated the most pronounced escalation in cold spot concentration, and reached a peak agglomeration level. This underscores that the EPS not only offers a refinement in land utilization configuration but also mediates the equilibrium between economic and ecological considerations. The insights derived from this investigation afford innovative evaluative methods for spatial planning, ecological recompense, and sustainable land exploitation within largeand medium-scale urban domains. [ABSTRACT FROM AUTHOR]

The main objective of this work was to investigate the influence of environmental factors, including air temperature (AT), relative humidity (RH) and temperature–humidity index (THI), on the difference between rectal temperature (RT) and eye temperature (ET) of dairy cows. The monitoring of these parameters is important for the further possible introduction of digitalization in animal welfare, especially in dairy cattle. The mean calculated difference between rectal temperature and eye temperature (RT–ET) was 1.5 °C. The average value of AT was 16.4 °C, and the average value of RH was 59.2%. The average value of THI was 60.4. The results of the study showed that, for the temperature difference ET-RT, a low degree of correlation was found both with temperature and with the temperature-humidity index THI (R = 0.22; R = 0.23). However, the observed temperature difference of the animal (ET-RT) showed a moderate degree of dependence on the relative humidity of air (R = −0.32). Although the positive correlation coefficient for AT and THI points to the higher criticality of summer measurements, the negative correlation coefficient for RH supports the use of infrared thermography for determining the temperature of animals even in a moister barn environment. [ABSTRACT FROM AUTHOR]

The study analyzed available data series of the Sava River's water temperature measured at the Zagreb gauging station. Official data from the Croatian Meteorological and Hydrological Service (DHMZ) in Zagreb were utilized. Over the 73 years from 1948 to 2020, there are only 53 years with complete measurement records. Despite this limiting fact, it was considered important to analyze the behavior of the Sava River's water temperatures in Zagreb over the past 70 years, during which a significant increase in air temperatures has been observed in the region, particularly in the city of Zagreb. Analyses were conducted on the characteristic (minimum, mean, and maximum) water temperatures over timescales of years, months, and days. The relationship between water temperatures (TW) and air temperatures (TA) measured at the Grič Observatory and the flows (Q) of the Sava River in Zagreb were investigated. A trend of rising water temperatures was observed throughout the entire period from 1948 to 2020, with the intensity significantly increasing in the recent period starting from 1988. The trend of rising air temperatures is the primary driver of the increase in the water temperatures of the Sava River in Zagreb. However, the impact of reduced water flow, especially during the warm season, should not be overlooked. This effect is amplified by the observed trend of decreasing minimum flows of the Sava during the warm season, from June to September. As a result, the most significant rise in water temperatures of the Sava River in Zagreb occurs during prolonged low-water summer periods, particularly in July. A strong trend has been observed in the increasing number of days per year with mean daily water temperatures of the Sava River exceeding 20 °C. This higher water temperature occurs increasingly earlier in the year, lasts longer, and ends later, often extending into September. [ABSTRACT FROM AUTHOR]

Over a period of 30 years (1993–2022), headwater catchments in the Slavkov Forest (Czech Republic) exhibited a robust increase in stream water DOC (dissolved organic carbon) concentrations following a significant reduction in acidic atmospheric deposition. Sulfur deposition decreased from 34 kg ha−1 yr−1 in 1993 to 2.6 kg ha−1 yr−1 in 2022. Three Norway-spruce-dominated research sites—Černý Potok (CEP), a 15.2 ha peatbog catchment, Lysina (LYS), a 27.3 ha granitic catchment, and Pluhův Bor (PLB), a 21.6 ha serpentinite catchment, were investigated. The three–year average DOC concentration increased from 48.2 mg L−1 (1993–1995) to 68.3 mg L−1 (2020–2022) at CEP (0.69 mg L−1 yr−1). LYS showed an increase from 16.9 mg L−1 to 25.4 mg L−1 (0.30 mg L−1 yr−1 annually). The largest increase was recorded at PLB, with an increase from 15.7 mg L−1 to 36.7 mg L−1 (0.89 mg L−1 yr−1). A decline in ionic strength was identified as the main driver of the DOC increase. The annual runoff declined significantly at CEP and LYS from 465 mm to 331 mm as a result of rising air temperatures and reduced precipitation between 2014 and 2022. PLB (average of 266 mm) did not show a statistically significant decline. Recently, PLB experienced significant deforestation that likely lowered transpiration and thus increased catchment runoff. As a result, DOC fluxes did not change significantly at CEP (average 210 kg ha−1 yr−1) and LYS (90 kg ha −1 yr−1). However, PLB's DOC flux more than doubled, increasing from 44 to 106 kg ha−1 yr−1. Drivers connected with global change, such as increasing temperatures, or potential chemical drivers, such as reductions in Al concentrations and pH changes, were not able to explain the observed changes in DOC concentra tions and fluxes. [ABSTRACT FROM AUTHOR]

In this study, we report observations of propagating radial carpet beams (RCBs) through a turbulent atmosphere at ground level with a 120 m path length. RCBs are a class of nondiffracting, accelerating, self-healing, and self-amplifying beams, and generated in the diffraction of a plane wave from amplitude/phase radial gratings having different spoke numbers. Observations were made at different times of the day. The intensity profile of an RCB becomes complicated when the number of grating spokes used to generate the beam is large, and includes high intensity spots, called main intensity spots (MISs), which are symmetrically placed at the central area around the beam axis and whose number is equal to (twice) the number of spokes of the amplitude (phase) grating used to generate the beam. With the aid of a telescope and a CCD camera, successive frames of the intensity pattern of the RCBs having different levels of structural complexity are recorded at the end of the path. For the data recorded at different times of the day, we calculate the variance of displacements of MISs along the radial direction. We observe that displacements of the MISs increase with increasing mean temperature of the air; on the other hand, as the complexity of the beam intensity pattern increases, the displacements of the MISs decrease. In order to compare the resilience of different RCBs and a well-known structured beam against atmospheric turbulence, we investigate deformation of the intensity profiles of a Laguerre–Gaussian (LG) beam having a topological charge 20 and different RCBs at the end of the path. It is shown that under the same turbulence condition, highly complex RCBs are more resilient to the destructive effects of the atmospheric turbulence. In particular, for the RCBs generated with gratings having 30 spokes and more, the number of MISs of the received intensity patterns is changed by less than 1% even when the turbulence strength is high. But for the LG beam, its intensity ring is clearly broken in different places, which makes it impossible to follow its maximum intensity in the radial direction [ABSTRACT FROM AUTHOR]

Understanding the genotype-by-environment interaction (GEI) and considering it in the selection process is a sine qua non condition for the expansion of Brazilian eucalyptus silviculture. This study's objective is to select high-performance and stable eucalyptus clones based on a novel selection index that considers the Factor Analytic Selection Tools (FAST) and the clone's reliability. The investigation explores the nuances interplay of GEI and extends its insights by scrutinizing the relationship between latent factors and real environmental features. The analysis, conducted across seven trials in five Brazilian states involving 78 clones, employs FAST. The clonal selection was performed using an extended FAST index weighted by the clone's reliability. Further insights about GEI emerge from the integration of factor loadings with 25 environmental features through a principal component analysis. Ten clones, distinguished by high performance, stability, and reliability, have been selected across the target population of environments. The environmental features most closely associated with factor loadings, encompassing air temperature, radiation, and soil characteristics, emerge as pivotal drivers of GEI within this dataset. This study contributes insights to eucalyptus breeders, equipping them to enhance decision-making by harnessing a holistic understanding-from the genotypes under evaluation to the diverse environments anticipated in commercial plantations. [ABSTRACT FROM AUTHOR]

Color centers in wide band-gap semiconductors, which have superior quantum properties even at room temperature and atmospheric pressure, have been actively applied to quantum sensing devices. Characterizing the quantum properties of the color centers in the semiconductor materials and ensuring that these properties are uniform over a wide area are key issues for developing quantum sensing devices based on color centers. In this article, we have developed an optics design protocol optimized for evaluating the quantum properties of color centers and have used this design approach to develop a new microscopy system called columnar excitation fluorescence microscope (CEFM). The essence of this system is to maximize the amount of fluorescence detection of polarized color centers, which is achieved by large-volume and uniform laser excitation along the sample thickness with sufficient laser power density. This laser excitation technique prevents undesirable transitions to undesirable charge states and undesirable light, such as unpolarized color center fluorescence, while significantly increasing the color center fluorescence. This feature enables fast measurements with a high signal-to-noise ratio, making it possible to evaluate the spatial distribution of quantum properties across an entire mm-size sample without using a darkroom, which is difficult with typical confocal microscope systems. [ABSTRACT FROM AUTHOR]

In cold regions, the freezing and thawing of embankments often cause significant damage to road surfaces. Research indicates that this freeze-thaw process is closely related to the distribution of temperature and moisture within the embankment. Therefore, an in-depth study of the moisture and temperature conditions and the resulting deformation under freeze-thaw effects is fundamental for analyzing crack-related diseases in road surfaces. The authors have developed a monitoring system for moisture and temperature in cold region highway embankments to conduct long-term observations. Based on the collected data, the distribution patterns of moisture and temperature fields in the embankment were analyzed. The results indicate that temperature changes at different locations within the embankment generally correspond to atmospheric temperature changes, exhibiting a periodic sinusoidal pattern. The annual variation in embankment temperature shows a nonlinear negative correlation with depth. [ABSTRACT FROM AUTHOR]

As global temperatures rise, droughts are becoming more frequent and severe. To predict how drought might affect plant communities, ecologists have traditionally designed drought experiments with controlled watering regimes and rainout shelters. Both treatments have proven effective for simulating soil drought. However, neither are designed to directly modify atmospheric drought. Here, we detail the efficacy of a silica gel atmospheric drought treatment in outdoor mesocosms with and without a co‐occurring soil drought treatment. At California State University, Los Angeles, we monitored relative humidity, temperature, and vapor pressure deficit every 10 min for 5 months in bare‐ground, open‐top mesocosms treated with soil drought (reduced watering) and/or atmospheric drought (silica dehumidification packets suspended 12 cm above soil). We found that silica packets dehumidified these mesocosm microclimates most effectively (−5% RH) when combined with reduced soil water, regardless of the ambient humidity levels of the surrounding air. Further, packets increased microclimate vapor pressure deficit most effectively (+0.4 kPa) when combined with reduced soil water and ambient air temperatures above 20°C. Finally, packets simulated atmospheric drought most consistently when replaced within 3 days of deployment. Our results demonstrate the use of silica packets as effective dehumidification agents in outdoor drought experiments. We emphasize that incorporating atmospheric drought in existing soil drought experiments can improve our understandings of the ecological impacts of drought. [ABSTRACT FROM AUTHOR]

The shrinking Arctic sea-ice area (SIA) in recent decades is a striking manifestation of the ongoing climate change. Variations of the Arctic sea ice have been continuously observed by satellites since 1979, relatively well monitored since the 1950s, but are highly uncertain in the earlier period due to a lack of observations. Several reconstructions of the historical gridded sea-ice concentration (SIC) data were recently presented based on synthesized regional sea-ice observations or by applying a hybrid model–empirical approach. Here, we present an SIC reconstruction for the period 1901–2019 based on established co-variability between SIC and surface air temperature, sea surface temperature, and sea level pressure patterns. The reconstructed sea-ice data for March and September are compared to the frequently used HadISST1.1 and SIBT1850 datasets. Our reconstruction shows a large decrease in SIA from the 1920 to 1940 concurrent with the Early 20th Century Warming event in the Arctic. Such a negative SIA anomaly is absent in HadISST1.1 data. The amplitude of the SIA anomaly reaches about 0.8 mln km2 in March and 1.5 mln km2 in September. The anomaly is about three times stronger than that in the SIBT1850 dataset. The larger decrease in SIA in September is largely due to the stronger SIC reduction in the western sector of the Arctic Ocean in the 70°–80°N latitudinal zone. Our reconstruction provides gridded monthly data that can be used as boundary conditions for atmospheric reanalyses and model experiments to study the Arctic climate for the first half of the 20th century. [ABSTRACT FROM AUTHOR]

The increasing concentration of atmospheric CO2 since the Industrial Revolution has affected surface air temperature. However, the impact of the spatial distribution of atmospheric CO2 concentration on surface air temperature biases remains highly unclear. By incorporating the spatial distribution of satellite-derived atmospheric CO2 concentration in the Beijing Normal University Earth System Model, this study investigated the increase in surface air temperature since the Industrial Revolution in the Northern Hemisphere (NH) under historical conditions from 1976–2005. In comparison with the increase in surface temperature simulated using a uniform distribution of CO2, simulation with a nonuniform distribution of CO2 produced better agreement with the Climatic Research Unit (CRU) data in the NH under the historical condition relative to the baseline over the period 1901–30. Hemispheric June–July–August (JJA) surface air temperature increased by 1.28°C ± 0.29°C in simulations with a uniform distribution of CO2, by 1.00°C ± 0.24°C in simulations with a non-uniform distribution of CO2, and by 0.24°C in the CRU data. The decrease in downward shortwave radiation in the non-uniform CO2 simulation was primarily attributable to reduced warming in Eurasia, combined with feedbacks resulting from increased leaf area index (LAI) and latent heat fluxes. These effects were more pronounced in the non-uniform CO2 simulation compared to the uniform CO2 simulation. Results indicate that consideration of the spatial distribution of CO2 concentration can reduce the overestimated increase in surface air temperature simulated by Earth system models. [ABSTRACT FROM AUTHOR]

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the "warm Arctic, cold East Asia" (WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) to the Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling. [ABSTRACT FROM AUTHOR]

The cyclic oxidation behavior of an additive manufactured CoCrMo alloy with 0.14 wt.% C was investigated at 914 °C for 32 cycles, each lasting 10 h, resulting in a total exposure time of 320 h. The oxidation rate was assessed for mass gain after finishing each 40 h oxidation cycle. It was experimentally determined that the oxidative process at 914 °C of this CoCrMo alloy follows a parabolic law, with the process being fast at the beginning and slowing down after the first 40 h. The microstructural analysis revealed that in the as-printed state, the phases developed were primarily the γ matrix and minor traces of ε phase. The oxidative process ensured an increase in the ε phase and precipitation of carbides which produced a 12% increase in the material's hardness after the first 40 h of exposure at 914 °C. The oxidation process led to the development of an oxide scale comprising a dense Cr2O3 layer and a porous layer of CoCr2O4 spinel, the latter spalling after the 240 h of exposure. Despite this spallation, the oxide scale continued to develop in the presence of O, Cr, and Co. The experimental analysis provided valuable insights regarding the material's behavior under prolonged exposure at high temperature in air, demonstrating its suitability as a candidate for additive manufactured mandrels used for bending metallic pipe fitting elbows. [ABSTRACT FROM AUTHOR]

The adequate representation of interactions between the land surface and the atmosphere is of crucial importance in modern numerical weather prediction (NWP) systems. In this context, this study examines how errors in the planetary boundary layer (PBL) depend on the quality of near-surface prediction over land for medium-range NWP. Two series of 10-day forecasts from Environment and Climate Change Canada (ECCC)'s global deterministic prediction system were evaluated: one similar to what is currently used in ECCC's operational systems and the other with improved land surface modeling and land data assimilation. An objective evaluation was performed for the 2019 summer season in North America, with a special emphasis on three specific areas: northern Canada, the central US, and the southeastern US. The results indicate that the impact of the new land surface package is more difficult to interpret in the PBL than it is at the screen level. The error differences between the two experiments are quite distinct for the three regions examined. As expected, random errors (standard deviations) for air temperature and specific humidity in the PBL are directly linked with their own random errors at the screen level, with correlation coefficients decreasing from a value of one at the surface to values of about 0.2–0.3 a few kilometers above the surface. Less expected, however, is the fact that random errors in the lower atmosphere also strongly depend on changes in air temperature biases at the surface. Warmer near-surface conditions lead to increased random errors for air temperature in the lower atmosphere, in association with the development of the deeper PBL, with greater spatial variability. This finding is of particular interest when evaluating new configurations of NWP systems for implementation in national meteorological and environmental prediction centers. [ABSTRACT FROM AUTHOR]

Dust storms are one of the important natural hazards that affect the lives of inhabitants all around the world, especially in North Africa and the Middle East. In this study, wind speed, wind direction, and air temperature patterns are investigated in one of the dustiest cities in Sistan Basin, Zahedan City, located in southeast Iran, over a 17-year period (2004–2020) using a WRF model and ground observation data. The city is located near a dust source and is mostly affected by local dust storms. The World Meteorology Organization (WMO) dust-related codes show that the city was affected by local dust, with 52 percent of the total dust events occurring during the period (2004–2021). The city's weather station reported that 17.5% and 43% were the minimum and maximum dusty days, respectively, during 2004–2021. The summer and July were considered the dustiest season and month in the city. Since air temperature, wind speed, and wind direction are important factors in dust rising and propagation, these meteorological factors were simulated using the Weather Research and Forecasting (WRF) model for the Zahedan weather station. The WRF model's output was found to be highly correlated with the station data; however, the WRF simulation mostly overestimated when compared with station data during the study period (2004–2020). The model had a reasonable performance in wind class frequency distribution at the station, demonstrating that 42.6% of the wind was between 0.5 and 2, which is in good agreement with the station data (42% in the range of 0.5–2). So, the WRF model effectively simulated the wind class frequency distribution and the wind direction at Zahedan station, despite overestimating the wind speed as well as minimum, maximum, and average air temperatures during the 17-year period. [ABSTRACT FROM AUTHOR]

This study evaluates the effectiveness of the Weather Research and Forecasting (WRF) model in simulating high-resolution atmospheric conditions for Almaty, Kazakhstan, a city prone to stagnant winter air. While the previously used Bougeault and Lacarrere scheme for parameterizing the planetary boundary layer was applied in high-resolution modeling, the number of vertical levels was increased, and a detailed local climate zones (LCZs) map was included. Ground-based observations from meteorological stations and monitoring stations, remote sensing data, and radiosonde measurements are used to verify the model. Comparison results with ground-based observations show that the WRF model with the LCZ map provides a better representation of the wind and thermal regimes of Almaty compared to the three-class land use map, including in high resolution. A good correspondence of wind direction is demonstrated by comparing the modeling results with pollutant transport plumes recorded by remote sensing data. In addition, a good correlation was found between land surface temperature from satellite data and air temperature simulated by WRF with a resolution of 333 m. A comparison of simulated data and aerological measurements confirmed that downscaling did not have a significant impact on boundary layer calculations. Analysis of turbulent processes showed that the adopted model effectively describes the attenuation and dissipation of turbulent kinetic energy and reflects the typical diurnal variations of meteorological processes in the atmosphere of Almaty in the anticyclonic winter period. The results of high-resolution WRF modeling can form the basis for the development of a hybrid system capable of modeling atmospheric processes at the building level. [ABSTRACT FROM AUTHOR]

Surface ozone (O3) and nitrogen oxides (NOx = NO + NO2) measured at the rural station in Belsk (51.83° N, 20.79° E), Poland, over the period of 1995–2023, were examined for long-term variability of O3 and its relationship to changes in the air temperature and NOx. Negative and positive trends were found for the 95th and 5th percentile, respectively, in the O3 data. A weak positive correlation (statistically significant) of 0.33 was calculated between O3 and the temperature averaged from sunrise to sunset during the photoactive part of the year (April–September). Recently, O3 maxima have become less sensitive to temperature changes, reducing the incidence of photochemical smog. The ozone–climate penalty factor decreased from 4.4 µg/m3/°C in the 1995–2004 period to 3.9 µg/m3/°C in the 2015–2023 period. The relationship between Ox (O3 + NO2) and NOx concentrations averaged from sunrise to sunset determined the local and regional contribution to Ox variability. The seasonal local and regional contributions remained unchanged in the period of 1995–2023, stabilizing the average O3 level at Belsk. "NOx-limited" and "VOC-limited" photochemical regimes prevailed in the summer and autumn, respectively. For many winter and spring seasons between 1995 and 2023, the type of photochemical regime could not be accurately determined, making it difficult to build an effective O3 mitigation policy. [ABSTRACT FROM AUTHOR]