Search

The Antarctic Peninsula (West Antarctica) marine ecosystem has undergone substantial changes due to climate-induced shifts in atmospheric and oceanic temperatures since the 1950s. Using 25 years of satellite data (1998-2022), this study presents evidence that phytoplankton biomass and bloom phenology in the West Antarctic Peninsula are significantly changing as a response to anthropogenic climate change. Enhanced phytoplankton biomass was observed along the West Antarctic Peninsula, particularly in the early austral autumn, resulting in longer blooms. Long-term sea ice decline was identified as the main driver enabling phytoplankton growth in early spring and autumn, in parallel with a recent intensification of the Southern Annular Mode (2010-ongoing), which was observed to influence regional variability. Our findings contribute to the understanding of the complex interplay between environmental changes and phytoplankton responses in this climatically key region of the Southern Ocean and raise important questions regarding the far-reaching consequences that these ecological changes may have on global carbon sequestration and Antarctic food webs in the future. Using 25 years of satellite data, this study presents evidence that phytoplankton biomass and bloom phenology in the West Antarctic Peninsula are significantly changing as a response to anthropogenic climate change. These findings raise important questions regarding the effect of these ecological changes on global carbon sequestration and Antarctic food webs in the future. [ABSTRACT FROM AUTHOR]

Palembang has sustained heavy haze pollution events that are related to decrease public health quality. Because ground-based PM2.5 observation in the city has some limitations, such as spatial and temporal coverages. Thus, in this study, we applied the potential of using the surface mass concentration PM2.5 data acquired by the MERRA-2 satellite to predict daytime and night-time PM2.5 levels during heavy haze events in Palembang City. Results of the study revealed that the highest PM2.5 level was about 160 µg/m3 at 02:00 (night-time), while the lowest PM2.5 level was about 50 µg/m3 at 14:00 (daytime). Spatiotemporal variation of PM2.5 over the study area showed that more than half of the area showed PM2.5 above 90 µg/m3 at night. Stable wind conditions (2 m/s) and air temperature (29°C), and relative humidity (74%) in the study area have contributed to particulate matter accumulation. The study concluded that PM2.5 acquired by the MERRA-2 satellite could provide a new reliable source for assessing severe air pollution events. [ABSTRACT FROM AUTHOR]

In numerous regions globally, particularly in Tunisia, the fluoride concentration in industrial wastewater surpasses regulatory thresholds, which posing environmental challenges. Therefore, this research investigates the efficacy of two clays sourced from Jebel Haidoudi Gabes–Tunisia (east longitude 9° 42′ 51.5″ (9.7143°); north latitude 34° 2′ 9.7″ (34.036°)) and Douiret–Tunisia (east longitude 10° 17′ 18.28 (10.28°); north latitude 32° 51′ 24.36″ (32.85°) as adsorbents and compared their performance in removing fluoride. These clays were used as adsorbents after activation with acid for 3.5 and 4.5 h, respectively. The design of Box–Behnken was applied to enhance the influence of initial fluoride concentration (50–300 mg/g), pH (2–6), and contact time (2–5 h). The results highlight the following order of significance for these factors: initial fluoride concentration > contact time > pH. The empirical model predicted that a maximum amounts adsorbed of fluoride with activated clays were obtained at fluoride concentration of 300 mg/L at a contact time of 5 h and pH = 2. A comparative analysis of activated clays from Jebel Haidoudi (142.56 mg/g) and Douiret (136.24 mg/g) elucidates their differential performance in fluoride removal. Results show that the experimental data fit well the pseudo-second-order equation, with R2 close to 1 (0.999) and χ2 low (1 ≥); the isotherm studies illustrate that the most excellent liner fits were obtained use the Langmuir model with highest R2 (0.986 and 0.983) and lowest χ2 (41.07 ad 43.56). These results demonstrate that fluoride removal might be mostly a chemisorption and a monolayer process. Finally, both activated clays could be used as efficient and inexpensive adsorbents. This work offers practical insights for optimizing treatment processes in regions grappling with elevated fluoride concentrations in industrial effluents. [ABSTRACT FROM AUTHOR]

Assessing the daily water requirements of crops and understanding the severity of drought necessitates precise estimation of potential evapotranspiration (PET), particularly in regions with arid climates such as Egypt. In the present study, the RegCM4 regional climate model was used to investigate the sensitivity of the PET of Egypt to two land surface schemes and boundary layer parameterizations. The land surface schemes are the Biosphere Atmosphere Transfer System (BATS) and the Community Land Model version 4.5 (CLM45). The boundary layer schemes considered are the HOLTSLAG (HOLT) and University of Washington (UW). To accomplish this task, four 32-year simulations were conducted spanning from 1979 to 2010, with the first two years considered as spin up. The ERA-Interim reanalysis was used to downscale the RegCM4 model. The simulated PET was evaluated with respect to the high-resolution ERA5-land PET-based product (hPET). The results showed that the BATS showed a bias of −0.8 to −1.8 mm day−1, while the CLM45 showed a bias of −0.8 to −3 mm day−1. Also, fine-tuning the coefficient of the daily mean air temperature succeeded in reducing the PET bias. Additionally, the UW had a lower PET bias than that noted in HOLT. To further reduce the PET bias, the linear-scaling (LS) bias-correction method was used. The LS showed its potential skills in reducing the mean bias of the PET from −2.2 to +0.4 mm day−1 in the evaluation period and to ±0.2 mm day−1 in the validation period. Furthermore, the added value of the LS was confirmed concerning the climatological annual cycle in different locations representing different climate zones of Egypt. In conclusion, accurate estimation of the PET can be ensured using the BATS, the UW schemes, and the LS technique in the present climate or under different warming scenarios. [ABSTRACT FROM AUTHOR]

The 2021 heatwave over Western North America (WNA) led to record‐breaking air temperatures and human‐perceived heat stress (humidex) values. The event was accompanied by drier conditions driven by prolonged atmospheric blocking. During the heatwave, the maximum 6‐day means of humidex and temperature (HX‐6 and TX‐6) exhibited larger anomalies (6.70 and 5.57°C) compared to the 95th percentiles (HX95 and TX95) (4.12 and 3.73°C), relative to 1981–2021 extended summer (June‐September) averages. Extreme indices of humidex show faster and larger increases than those of temperature, reflecting the nonlinear positive relationship between humidex and temperature. Future projections from a multi‐model ensemble of 19 Coupled Model Intercomparison Project Phase six (CMIP6) Global Climate Models (GCMs) clearly show an increase in humidex and temperature extremes, especially under intermediate and high emissions scenarios. Humidex indices (HX‐6 and HX95) show faster and larger increases than temperature indices (TX‐6 and TX95) for the same future years and global warming levels. Controlling for differences in GCM climate sensitivity to greenhouse gas forcing yields robust projections at various global warming levels, reducing the ranges of projected changes from the multi‐model ensemble. At 3.0°C global warming from pre‐industrial, the multi‐model ensemble projects occurrences of HX‐6, TX‐6, HX95, and TX95 over WNA that exceed 2021 levels to occur every 3.9, 1.7, 1.4, and 2.2 years, respectively, increasing to almost annually at 4.0°C. Plain Language Summary: In 2021 summer, Western North America (WNA) experienced an unprecedented heatwave, breaking air temperature and human‐perceived heat stress (humidex) records despite lower humidity due to prolonged atmospheric blocking. During the heatwave, consecutive 6‐day means of heat stress (HX‐6) and temperature (TX‐6) showed larger anomalies (6.70 and 5.57°C) compared to the 95th percentiles (HX95 and TX95) (4.12 and 3.73°C) over the region, relative to their averages over the 1981–2010 summer period (June‐September). Heat stress increased faster and more significantly than air temperature due to their nonlinear relationship. Future projections from 19 climate models reveal clear increases in heat stress and temperature, especially under intermediate and high emission scenarios. Heat stress indices show larger and faster increases than temperature indices at the same future years and global warming levels. Accounting for uncertainty related to climate model sensitivity enhances projection reliability. At 3.0°C global warming from pre‐industrial levels, 2021‐level events over WNA are projected to occur every few years, becoming an almost annual occurrence at 4.0°C. The study underscores the critical need for robust projections using multi‐model ensembles. Key Points: Unprecedented 2021 summer heatwave over Western North America resulted in record‐breaking humidex and air temperature extremesLarger increases in humidex than temperature, exceeding their 2021 levels, under intermediate and high emissions scenariosRobust projections of multi‐model ensemble, mitigating climate sensitivity uncertainty of GCMs response to greenhouse gas emissions [ABSTRACT FROM AUTHOR]

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM‐LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM‐LIN method improved R2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM‐LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation. Plain Language Summary: Natural hazards, such as flooding and extreme heat, can damage our infrastructure and local communities. These hazards often stem from extreme weather conditions such as heavy precipitation and hot temperatures. Global climate change is expected to affect precipitation and air temperature, leading to more extreme weather events and hazards in the future. Predicting frequency and severity of these future events is key to protect our infrastructure and communities. Climate models have been widely used to project statistics of future extremes. However, they come with uncertainties due to numerical approximations, low spatial resolutions etc. Consequently, predictions generated by these models are inherently uncertain. This paper used a new approach to improve future projections of extreme climatic events, focusing on South Florida. Our findings revealed substantial improvements in projecting future events, particularly for extreme precipitation. We also showed that nationally and globally derived simulations may not be suitable for accurately projecting heavy precipitation, but can suffice for air temperature and low/medium precipitation rates. This paper offers promising avenues for refining projections of future weather events. By enhancing our ability to anticipate upcoming weather events more accurately, we can better protect our infrastructure and communities against the challenges posed by climate change. Key Points: A hybrid statistical approach to improve bias correction of GCM precipitation and air temperature simulationsMajor improvements in both climatic variables, especially extreme precipitation, using our hybrid statistical approach in South FloridaCoarse resolution downscaled data may be insufficient for deriving high quantile precipitation at the regional scale [ABSTRACT FROM AUTHOR]

Temperature and water stress are important factors limiting the gross primary productivity (GPP) in terrestrial ecosystems, yet the extent of their influence across ecosystems remains uncertain. This study examines how surface air temperature, soil water availability (SWA) and vapor pressure deficit (VPD) influence ecosystem light use efficiency (LUE), a critical metric for assessing GPP, across different ecosystems and climatic zones at 80 flux tower sites based on in situ measurements and data assimilation products. Results indicate that LUE increases with temperature in spring, with higher correlation coefficients in colder regions (0.79–0.82) than in warmer regions (0.68–0.78). LUE reaches a plateau earlier in the season in warmer regions. LUE variations in summer are mainly driven by SWA, exhibiting a positive correlation indicative of a water‐limited regime. The relationship between the daily LUE and daytime temperature shows a clear seasonal hysteresis at many sites, with a higher LUE in spring than in fall under the same temperature, likely resulting from younger leaves being more efficient in photosynthesis. Drought stress influences LUE through SWA in all ranges of water availability; VPD variation under moderate conditions does not have a clear influence on LUE, but extremely high VPD (exceeding the threshold of 1.6 kPa, often observed during extreme drought‐heat events) causes a dramatic reduction of LUE. Our findings provide insight into how ecosystem productivities respond to climate variability and how they may change under the influence of more frequent and severe heat and drought events projected for the future. Plain Language Summary: The terrestrial ecosystem assimilates carbon through photosynthesis, and its ability to convert sunlight energy to primary production during photosynthesis is commonly measured by light use efficiency (LUE). To understand how temperature, water in the soil, and atmospheric aridity impact carbon assimilation through photosynthesis, we analyzed the drivers of LUE at 80 sites across different ecosystems and different climate regimes in the United States. We found that temperature is the main factor influencing LUE of grassland and forest in spring, and has a greater influence on LUE in colder regions than in warmer regions. Under the same temperature, LUE in the spring is higher than in the autumn season, likely because of new leaves. In summer, deep soil water availability is the primary driver of LUE variations. In addition, extreme aridity of the atmosphere contributes to a dramatic decrease in LUE during compound heat‐drought events. Our findings contribute to advancing our understanding of how climatic factors influence LUE across different ecosystems in a changing climate. Key Points: Light use efficiency (LUE) variation is generally driven by temperature in spring and by water stress in summerSoil water availability dominates the LUE response to moderate droughts, but vapor pressure deficit becomes important under extreme droughtThe primary drivers of LUE variation also depend on background climate and vegetation types [ABSTRACT FROM AUTHOR]

The winter hydrological period is in transition across the Canadian subarctic, as climate warming is shifting precipitation regimes, thawing permafrost, and altering active layer dynamics, and thus increasing the overall amount, and variability, of winter streamflow. Effects of these changes are poorly understood on the Taiga Shield, which comprises ~20% of North America's permafrost‐covered area, and is characterized by a unique 'fill‐and‐spill' hydrology whereby runoff generation requires the exceedance of lake basin storage thresholds. Here, we assessed lake hydrostatic levels and used trail camera images of icings, which are sheet‐like masses of layered ice that are common manifestations of wintertime flow on the Taiga Shield, to understand landscape controls on winter water movement in this region. We further used paired geochemical measurements to explore how source water characteristics affect icing chemistry, and the degree to which icings may modify the chemical composition of active winter flow. We undertake this work over 2 years, and across watersheds of different sizes and lake basin characteristics. We show that icing growth is driven by hydroclimatic controls that include fill‐and‐spill hydrologic constraints and winter air temperatures, and that pre‐freshet pulses of water flow are common within this landscape. Across winters with variable antecedent precipitation levels, a larger catchment was able to support icing growth via continued runoff generation, while small catchments were not. Icings were often chemically dilute compared with source waters, indicating that solute exclusion may actively enrich geochemical concentrations in flowing water. Across icings, chemical variation appeared related to source water type (groundwater versus lake; lake size) and apparent redox conditions. These results highlight that streamwater hydrology and biogeochemistry can be dynamic during the understudied winter period, and illustrate that icings may alter the composition of wintertime flow as it moves through fluvial networks. [ABSTRACT FROM AUTHOR]

Seasonal variations in glycaemic patterns in children and young adults affected by type 1 diabetes are currently poorly studied. However, the spread of Flash Glucose Monitoring (FGM) and continuous glucose monitoring (CGM) systems and of dedicated platforms for the synchronization and conservation of CGM reports allows an efficient approach to the comprehension of these phenomena. Moreover, the impact that environmental parameters may have on glycaemic control takes on clinical relevance, implying a need to properly educate patients and their families. In this context, it can be investigated how blood glucose patterns in diabetic patients may have a link to outdoor temperatures. Therefore, in this study, the relationship between outdoor temperatures and glucose levels in diabetic patients, aged between 4 and 21 years old, has been analysed. For a one-year period (Autumn 2022–Summer 2023), seasonal variations in their CGM metrics (i.e., time in range (TIR), Time Above Range (TAR), Time Below Range (TBR), and coefficient of variation (CV)) were analysed with respect to atmospheric temperature. The results highlight a negative correlation between glucose in diabetic patients and temperature patterns (R value computed considering data for the entire year; Ry = −0.49), behaviour which is strongly confirmed by the analysis focused on the July 2023 heatwave (R = −0.67), which shows that during heatwave events, the anticorrelation is accentuated. The diurnal analysis shows how glucose levels fluctuate throughout the day, potentially correlating with atmospheric diurnal temperature changes in addition to the standard trend. Data captured during the July 2023 heatwave (17–21 July 2023) highlight pronounced deviations from the long-term average, signalling the rapid effects of extreme temperatures on glucose regulation. Our findings underscore the need to integrate meteorological parameters into diabetes management and clinical trial designs. These results suggest that structured diabetes self-management education of patients and their families should include adequate warnings about the effects of atmospheric temperature variations on the risk of hypoglycaemia and about the negative effects of excessive therapeutic inertia in the adjustment of insulin doses. [ABSTRACT FROM AUTHOR]

This study addresses the critical issue of drought zoning in Canada using advanced deep learning techniques. Drought, exacerbated by climate change, significantly affects ecosystems, agriculture, and water resources. Canadian Drought Monitor (CDM) data provided by the Canadian government and ERA5-Land daily data were utilized to generate a comprehensive time series of mean monthly precipitation and air temperature for 199 sample locations in Canada from 1979 to 2023. These data were processed in the Google Earth Engine (GEE) environment and used to develop a Convolutional Neural Network (CNN) model to estimate CDM values, thereby filling gaps in historical drought data. The CanESM5 climate model, as assessed in the IPCC Sixth Assessment Report, was employed under four climate change scenarios to predict future drought conditions. Our CNN model forecasts CDM values up to 2100, enabling accurate drought zoning. The results reveal significant trends in temperature changes, indicating areas most vulnerable to future droughts, while precipitation shows a slow increasing trend. Our analysis indicates that under extreme climate scenarios, certain regions may experience a significant increase in the frequency and severity of droughts, necessitating proactive planning and mitigation strategies. These findings are critical for policymakers and stakeholders in designing effective drought management and adaptation programs. [ABSTRACT FROM AUTHOR]

Significant increase in wintertime air temperature, especially the reduced cold extremes under climate change, might be beneficial to the winter survival of perennial crops. However, climate warming could result in less snowfall, reduced snow cover, as well as changes in climate conditions for fall hardening and winter thaws. How these changes might impact the risks of winter damages to overwintering crops, such as perennial forage crops requires a comprehensive assessment for proactively adapting to climate change in the agricultural sector, especially the beef and dairy industries. Based on the most up-to-date climate projections from a set of global climate models, we used a snow model and a suite of agroclimatic indices for perennial forage crops to assess potential changes in the risks of winter injury to perennial forage crops across Canada in the near-term (2030s), the mid-term (2050s), and the distant future (2070s). Our results show that the risk of exposure to extremely low temperatures (daily Tmin ≤ −15 °C) without snow protection is projected to decrease across Canada with improved conditions for fall hardening. However, winter thaws and rainfall are projected to increase, and this would increase the risk of winter injury due to loss of hardiness together with potential soil heaving and ice encasement. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP), with its unique geographical and climatic conditions, holds a significant role in global climate change. Therefore, it is particularly urgent to fully understand its vegetation phenology. Herbaceous plants are widely distributed in the TP. However, previous studies have predominantly examined the impact of air temperature on the end date of the vegetation growing season (EOS), with less emphasis on the influence of land surface temperature (LST). In this study, the dynamic changes in the EOS from 2001 to 2020 were analyzed by utilizing the Normalized Difference Vegetation Index (NDVI) data published by NASA. Furthermore, the impact of climate change on the EOS was examined, and the dominant factor (air temperature, LST, or precipitation) influencing the EOS was identified. The main findings were as follows: the average annual EOS predominantly occurred between day of year (DOY) 240 and 280, with an advance from the edge of the plateau to the center. The EOS across the entire region displayed a marginal tendency towards delay, with an average rate of 0.017 days/year. Among all vegetation, shrubs showed the most pronounced delay at a rate of 0.04 days/year. In terms of precipitation, the impact of climate change increased precipitation in both summer and autumn, which could delay EOS. In terms of temperature, an increase in summer Tmin, autumn air temperatures and summer LST delayed the EOS, while an increase in autumn LST advanced the EOS. Compared to air temperature and precipitation, LST had a stronger controlling effect on the EOS (the largest pixel area dominated by LST). These results could offer new insights for enhancing the parameters of vegetation phenology models across the TP. [ABSTRACT FROM AUTHOR]

The causal relationship between vegetation and temperature serves as a driving factor for global warming in the climate system. However, causal relationships are typically characterized by complex facets, particularly within natural systems, necessitating the ongoing development of robust approaches capable of addressing the challenges inherent in causality analysis. Various causality approaches offer distinct perspectives on understanding causal structures, even when experiments are meticulously designed with a specific target. Here, we use the complex vegetation–climate interaction to demonstrate some of the many facets of causality analysis by applying three different causality frameworks including (i) the kernel Granger causality (KGC), a nonlinear extension of the Granger causality (GC), to understand the nonlinearity in the vegetation–climate causal relationship; (ii) the Peter and Clark momentary conditional independence (PCMCI), which combines the Peter and Clark (PC) algorithm with the momentary conditional independence (MCI) approach to distinguish the feedback and coupling signs in vegetation–climate interaction; and (iii) the Liang–Kleeman information flow (L-K IF), a rigorously formulated causality formalism based on the Liang–Kleeman information flow theory, to reveal the causal influence of vegetation on the evolution of temperature variability. The results attempt to capture a fuller understanding of the causal interaction of leaf area index (LAI) on air temperature (T) during 1981–2018, revealing the characteristics and differences in distinct climatic tipping point regions, particularly in terms of nonlinearity, feedback signals, and variability sources. This study demonstrates that realizing a more holistic causal structure of complex problems like the vegetation–climate interaction benefits from the combined use of multiple models that shed light on different aspects of its causal structure, thus revealing novel insights that are missing when we rely on one single approach. This prompts the need to move toward a multimodel causality analysis that could reduce biases and limitations in causal interpretations. [ABSTRACT FROM AUTHOR]

The winter mortality of mountain pine beetle (Dendroctonus ponderosae Hopkins) larvae caused by temperatures below survivable thresholds and sudden decreases in temperature is among the most influential factors limiting population growth. Due to the importance of winter mortality in the demise of mountain pine beetle infestations, a widely used winter mortality model was developed at the Canadian Forest Service and the United States Forest Service. It predicts lethal temperatures and survival probabilities given temperature time series over the winter season. We present a rare and possibly the first peer-reviewed validation of this winter mortality model, wherein we independently tested the model at a new region in Canada by comparing model predictions to the observed lower lethal temperature thresholds and cold-associated mortality. Model predictions were biologically reasonable but slightly biased. Bias was exacerbated by the inaccurate translation of air temperature data from weather stations to temperatures under the bark where larvae develop. The spatial prediction of relative mortality observed across the study area in Banff National Park was poor—likely because the mountainous terrain presents a difficult prediction challenge when under-bark temperatures are not directly observed. Our results will help inform users of model constraints and how to optimize the accuracy of model predictions. [ABSTRACT FROM AUTHOR]

The aim of this article is to show the most significant factors influencing the indoor environment in winter considering the operating conditions of an older stable modified for housing 12 horses and an indoor riding arena for teaching and sports purposes. This research focused on assessing the influences affecting the internal environment from the point of view of the construction of the building and ventilation control in the operating conditions of working and non-working days. The analysis of the results showed that the massive masonry structure has sufficient thermal insulation and accumulation, which was manifested by good temperature stability inside the stable of 7.2 ± 1.7 °C when the outside air temperature was −4.80 ± 1.5 °C. At low outdoor air temperatures of −6.44 ± 0.4 °C, the following conditions were found: a higher relative air humidity (76.0 ± 5.3%), a high CO2 concentration 2317.1 ± 931.7 ppm, and a high airborne dust concentration PM10 = 231.94 ± 19.13 μg·m−3 and PM2.5 = 160.13 ± 6.28 μg·m−3. Therefore, it is necessary to improve the solution and function of the stable ventilation. The small size of the windows and their uneven distribution (average daylight factor ei from 0.313 ± 0.154 to 0.835 ± 0.309) caused insufficient daylight in some individual boxes. [ABSTRACT FROM AUTHOR]

Understanding spatial and temporal characteristics and driving factors of ecological sensitivity are an essential prerequisite for effectively managing environmental changes and steering the rational use of land resources. This study employed the Analytic Hierarchy Process and Coefficient of Variation methods to calculate the weights of ten indicators from 2000 to 2018. Then, spatiotemporal change patterns of ecological sensitivity along the Sichuan–Tibet Railway were analyzed. At the same time, four individual parameters, including soil erosion, land use status, topographic factors, and climate conditions, were evaluated to create a multi-perspective understanding of the entire ecological sensitivity. The key factors affecting ecological sensitivity were explored through a geographic detector model. The results indicate that the ecological sensitivity along the Sichuan–Tibet Railway is predominantly high or moderate, with higher sensitivity observed in the western regions and lower sensitivity in the eastern regions. From 2000 to 2018, the ecological environment showed a trend of deterioration, and the spatial and temporal distribution patterns of the four parameters are closely related to the extensive ecological sensitivity. Based on the GeoDetector results, the spatial distribution of ecological sensitivity is mainly related to digital elevation model, precipitation, and air temperature. The interaction between different factors can enhance the effect on ecological sensitivity. The interaction between precipitation and Vegetation Coverage (FVC) has the largest effect. [ABSTRACT FROM AUTHOR]

Detecting trace gases such as hydrogen chloride (HCl) in Mars' atmosphere is among the primary objectives of the ExoMars Trace Gas Orbiter (TGO) mission. Terrestrially, HCl is closely associated with active volcanic activity, so its detection on Mars was expected to point to some form of active magmatism/outgassing. However, after its discovery using the mid‐infrared channel of the TGO Atmospheric Chemistry Suite (ACS MIR), a clear seasonality was observed, beginning with a sudden increase in HCl abundance from below detection limits to 1–3 ppbv in both hemispheres coincident with the start of dust activity, followed by very sudden and rapid loss at the southern autumnal equinox. In this study, we have investigated the relationship between HCl and atmospheric dust by making comparisons in the vertical distribution of gases measured with ACS and aerosols measured co‐located with the Mars Climate Sounder (MCS). This study includes HCl, water vapor, and ozone measured using ACS MIR, water vapor and temperature measured with the near infrared channel of ACS, and temperature, dust opacity, and water ice opacity measured with MCS. In part 1, we show that dust loading has a strong impact in temperature, which controls the abundance of water ice and water vapor, and that HCl is very closely linked to water activity. In part 2, we investigate the quantitative correlations between each quantity and discuss the possible source and sinks of HCl, their likelihood given the correlations, and any issues arising from them. Plain Language Summary: After four full Martian years in orbit since 2018, the ExoMars Trace Gas Orbiter (TGO) has observed three Martian dusty seasons, which occur when it is spring and summer in the southern hemisphere. The first, starting in summer 2018, featured a global dust storm (GDS) after which we made the first detection of hydrogen chloride (HCl) in the Martian atmosphere using the Atmospheric Chemistry Suite (ACS) instrument. Finding this gas was a priority of ExoMars because its presence may indicate that the planet is volcanically active. Since then, we have observed two more dusty periods without a GDS and observed the reappearance of HCl each time. Here, we present the climatology of HCl in both hemispheres over these three dusty periods (in Mars years 34, 35, and 36) and investigate their relationships with temperature and water vapor measured by ACS, and with airborne dust and water ice measured with the Mars Climate Sounder (MCS) on the Mars Reconnaissance Orbiter (MRO). In this paper, we examine how the vertical structure of each quantity changes over time. We show that there is a close relationship between HCl and H2O, and that both are controlled by temperature, driven by dust loading. Key Points: Comparison of trace gas abundance and aerosol extinction between Atmospheric Chemistry Suite on ExoMars TGO and Mars Climate Sounder on Mars Reconnaissance OrbiterReveal the seasonal changes in hydrogen chloride on MarsShow that dust affects atmospheric temperature, which controls water vapor abundance and ice extinction, and thus impacts HCl abundance [ABSTRACT FROM AUTHOR]

Drying is an effective way to solve corn mildew. The heat and humidity flow interface in COMSOL Multiphysics heat transfer module was used to coupling fluid flow, water transport and heat transfer in multiple physical fields, and corn was used as a porous medium for simulation analysis, aiming to find the change rules of temperature field and humidity field. The research shows that the multi‐component model and method should be given priority in practice. The higher the hot air temperature is, the higher the average temperature of corn kernels is, and the faster the relative humidity decreases. The drying rate of corn is the highest at 348 K, and the hot air temperature should be appropriately increased at 333 K denaturation temperature. The higher the wind speed, the better the drying effect of corn kernels, but the improvement of drying effect will decrease with the increase of wind speed. Appropriately increase the wind speed between 2 and 4 m/s to improve the drying efficiency while avoiding excessive energy consumption. The mass transfer resistance of the pericarp cannot be ignored. The drying time of corn kernels closer to the hot air entrance is shorter, and the corn kernels close to the hot air exit are prone to humidity accumulation. Multiple hot air intakes should be set up to reduce the occurrence of uneven drying. Practical applications: Corn is prone to mildew after harvest, resulting in resource waste and economic loss, so it is of great significance to dry corn efficiently. Corn is a typical porous medium, and the research on it can provide the basis for drying other porous medium grains. According to different components, the model of single granule and multi‐granule was established respectively. Use COMSOL Multiphysics simulation software to gain a deeper understanding of the complex physical processes involved in the drying process and provide valuable insights for industrial applications. COMSOL software was used to study the drying condition of corn under the synergic action of multiple physical fields, and effective drying strategies and measures to improve the structure of air drying silo were put forward. [ABSTRACT FROM AUTHOR]

Increased awareness by industry of greenhouse gas (GHG) emissions is forcing companies to examine electrical technologies as alternatives to fossil fuel‐driven thermal ones. Spray drying of milk is recognized as a high‐energy process and is of particular importance to New Zealand. It requires inlet air temperatures higher than most existing electrically‐driven heat‐pumps can reliably achieve. Already some companies internationally are considering freezing and shipping milk concentrates rather than drying which begs the question as to whether the GHG emissions of frozen concentrate outweigh the GHG avoided by not drying. This research note assesses the relative GHG emissions and indicates a GHG advantage for frozen concentrate shipping. Practical applications: Increased awareness of the significance of greenhouse gas (GHG) emissions is forcing companies to examine alternatives to fossil fuel‐driven thermal technologies. Spray drying of milk is recognized as a high‐energy process and is of particular importance to New Zealand. It requires inlet air temperatures higher than most existing electrically‐driven heat‐pumps can achieve and so commonly requires fossil‐fuel use. Already some companies internationally are considering freezing and shipping milk concentrates rather than shipping dried milk. This research note assesses the relative GHG emissions of conventional (fossil‐fuelled) processes, and a novel process involving frozen concentrate. The evaluation shows that significant greenhouse gas reduction is possible by shipping frozen concentrate. [ABSTRACT FROM AUTHOR]

Coffee berry borer (Hypothenemus hampei Ferrari) (Coleoptera: Curculionidae) is the most damaging insect pest of coffee worldwide, causing significant losses in coffee yields and quality. Knowledge of vertical and temporal flight patterns in coffee berry borer could be used to optimize spray timing and precision targeting of areas within the coffee tree, which may be more susceptible. In the present study, we estimated the vertical distribution of coffee berry borer females using traps set at 1-m intervals up to 5 m in height. We also quantified coffee berry borer infestation in the low, mid, and high canopy and documented fruit availability. Temporal flight patterns were estimated using timer traps, and correlation analyses were conducted to determine the relationship between the timing of daily flight and weather variables. Across the 4 study sites, we observed that 77%–84% of the trap catch was at 1 m, 11%–20% was at 2 m, and 1%–4% was at 3–5 m in height. Fruit infestation was significantly higher in the low branches (35%) relative to the high branches (17%). Flight height remained the same year-round, regardless of fruit availability. Coffee berry borer flew in low numbers during the day and night but peaked from 12 to 4 PM. Daily flight was positively correlated with an increase in air temperature and wind speed and negatively correlated with relative humidity. Findings from this study suggest that pesticide sprays should target low- to mid-level branches at 1–2 m in height and aim to be conducted in the early afternoon when coffee berry borer are actively flying and most vulnerable to chemical controls. [ABSTRACT FROM AUTHOR]

The presence of biota in the Black Sea is mostly determined by seawater temperature and salinity. The consensus of many scientists doing research on global warming is that in 2100, the average air temperature will be increase than today's values. With climate changing, precipitation rates will change due to the Black Sea water temperature and the changing atmospheric regime, causing an unbalanced entry of nutrients into the sea, and as a result, excessive plankton proliferation may occur. This may mean that the habitats of the species in the Black Sea are further limited. The increases in sea levels may not be serious, but there is no doubt that there will be some increases. These increases will affect the coastal ecosystem, especially the rich living life in the region where the waves hit the shore, which we call the wave zone, will be adversely affected. These predictions should be followed up with regular scientific monitoring studies and it should be investigated how biota from invertebrates to fish are affected by the changes. This review explored and discussed the long-term changes and causes of biota communities on the southern coast of the Black Sea. [ABSTRACT FROM AUTHOR]

Climate change affects plant growth, food production, ecosystems, sustainable socio-economic development, and human health. The different artificial intelligence models are proposed to simulate climate parameters of Jinan city in China, include artificial neural network (ANN), recurrent NN (RNN), long short-term memory neural network (LSTM), deep convolutional NN (CNN), and CNN-LSTM. These models are used to forecast six climatic factors on a monthly ahead. The climate data for 72 years (1 January 1951–31 December 2022) used in this study include monthly average atmospheric temperature, extreme minimum atmospheric temperature, extreme maximum atmospheric temperature, precipitation, average relative humidity, and sunlight hours. The time series of 12 month delayed data are used as input signals to the models. The efficiency of the proposed models are examined utilizing diverse evaluation criteria namely mean absolute error, root mean square error (RMSE), and correlation coefficient (R). The modeling result inherits that the proposed hybrid CNN-LSTM model achieves a greater accuracy than other compared models. The hybrid CNN-LSTM model significantly reduces the forecasting error compared to the models for the one month time step ahead. For instance, the RMSE values of the ANN, RNN, LSTM, CNN, and CNN-LSTM models for monthly average atmospheric temperature in the forecasting stage are 2.0669, 1.4416, 1.3482, 0.8015 and 0.6292 °C, respectively. The findings of climate simulations shows the potential of CNN-LSTM models to improve climate forecasting. Climate prediction will contribute to meteorological disaster prevention and reduction, as well as flood control and drought resistance. [ABSTRACT FROM AUTHOR]

North Atlantic midlatitude cyclones are among the most severe weather systems, causing enormous economic damages and threatening human lives. The cyclone is typically characterized by cyclonic convergent surface winds, strong updrafts, and precipitation. However, extreme surface winds are often observed within the cyclone where downdrafts develop. The present study investigates the dynamical and thermodynamical characteristics of the horizontal winds impinging on the cold frontal surface and the associated downdrafts. It is shown that the cyclonic winds into the cold frontal surface are mainly responsible for the downdrafts that transport the high‐altitude horizontal momentum to the surface and cause intense surface winds. About half of the North Atlantic midlatitude cyclones are accompanied by the downdrafts especially in the southern and western parts of the cyclone center. Plain Language Summary: In the midlatitudes, air temperature decreases toward the poles, and cyclone systems typically travel eastward along regions characterized by strong meridional temperature gradients. Over the cyclone‐influencing area, the cyclonic, counterclockwise rotating, wind induces southward cold advection on the western side of the cyclone center. Therefore, during the early phase of the North Atlantic midlatitude cyclone, the generation of the cold front, which has a steep gradient of temperature to the west of the cyclone center, and that is a common feature. Even after the formation of the cold front, the horizontal winds keep impinging on the frontal surface. Then the horizontal winds blocked by the frontal surface and downdrafts are induced. The downdrafts transport the upper‐level intense wind speed to the lower level strengthening the surface winds. Key Points: Surface winds within North Atlantic midlatitude cyclones are strengthened by strong downdrafts and downward momentum transportsDowndrafts can be generated by the horizontal winds impinging on the cold frontal surfaceCyclones tend to accompany the downdrafts more to the south and west of the cyclone center [ABSTRACT FROM AUTHOR]

Surface anticyclones connected to the ridge of an upper‐tropospheric Rossby wave are the main dynamical drivers of mid‐latitude summer heatwaves. It is, however, unclear to what extent an anomalously low zonal phase speed of the wave in the upper troposphere is necessary for persistent temperature extremes at the surface. Here, we use spectral decomposition to separate fast and slow synoptic‐scale waves. A composite analysis of ERA5 reanalysis data reveals that, while in some regions heatwaves become more frequent during episodes of weak or no phase propagation, temperature extremes in other regions are commonly associated with more rapidly eastward propagating Rossby waves. Reflected in the mean heatwave duration as well, this relationship is possibly linked to a longitudinal phase preference of slow and fast waves or a meridional storm track shift. These findings open up new questions about the influence of mid‐latitude dynamics on temperature extremes. Plain Language Summary: High pressure systems tend to be associated with mid‐latitude summer heatwaves, defined as multiple consecutive hot days. The persistence of heatwaves raises the question whether the associated high pressure system has to be anomalously persistent as well to cause a heatwave. Using a combination of observational data and atmospheric model output that is commonly regarded as ground truth for prediction purposes we find that this is not the case. By re‐distributing the location of on‐average high air pressure, some regions experience an increased heatwave frequency even if the atmospheric circulation is less persistent than usual. Understanding the link between persistent surface temperature extremes and the atmospheric circulation is important for the prediction and projection of extreme events in a warming climate. Key Points: Phase speed of synoptic‐scale waves is crucial for where, but less important for whether heatwaves occurA longitudinal phase preference of slow and fast waves is reflected in the mean heatwave durationChanges in phase speed are linked to a meridional storm track shift [ABSTRACT FROM AUTHOR]

To understand future summer precipitation changes over the Great Lakes Region (GLR), we performed an ensemble of regional climate simulations through the Pseudo‐Global Warming (PGW) approach. We found that different types of convective precipitation respond differently to the PGW signal. Isolated deep convection (IDC), usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), usually concentrated upwind of the GLR, shift to the downwind region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to increase across almost the entire studied domain, creating a potential environment more favorable for stronger convection systems and less favorable for weaker ones. Meanwhile, changes in the lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, highlighting the significance of these thermodynamic factors in controlling precipitation over the domain. Our results indicate that the decrease in LCL and LCF in areas with increased convective precipitation is mainly due to increased atmospheric moisture. In response to the prescribed warming perturbation, MCSs occur more frequently downwind, while localized IDCs exhibit more intense rain rates, longer durations, and larger rainfall area. Plain Language Summary: To understand how summer rainfall might change in the Great Lakes Region in a warmer future climate, we performed several climate simulations using the Pseudo‐Global Warming approach. We found that different types of heavy rain events react differently to the warming signal. Smaller convective rain events are projected to increase mainly over the northern domain, whereas the larger and sustained rain events are expected to increase over the eastern domain. The increase in rainfall is associated with low‐level atmospheric moisture, which influences the atmospheric stability. With more moisture, the atmosphere becomes more unstable, leading to increased rainfall. The Great Lakes play an important role in providing moisture to their downwind regions, thereby affecting precipitation patterns. Key Points: The location of summer convective precipitation is shifted due to global warmingChanges in lifting condensation level (LCL) and level of free convection (LFC) are the critical factors driving changes in convective precipitationThe lowered LCL and LFC are controlled by the low‐level moisture, not by air temperature [ABSTRACT FROM AUTHOR]

İstanbul is the largest city located in the Mediterranean Basin and has a medium to high risk of climate change and future climate risks. Changes in temperature and other weather variables have had significant impacts on İstanbul. In this context, there is a need for studies on the issues of climate monitoring and climate change vulnerability to reduce the adverse impacts. The aim of this study is to investigate the temperature trends of synoptic weather station in İstanbul Atatürk Airport between 1973 and 2023 to have a general idea about how the temperature has changed over the last half-century and to establish statistically whether a trend is significant or not. The values of minimum (Tmin), maximum (Tmax) and mean (Tmean) temperature related parameters were estimated. Annual, monthly and seasonal temperature trends are also analyzed. The findings of this study indicate a significant (p < 0.001) rise in the mean air temperature (Tmean) of İstanbul over the past 51 years (1973–2023), with an annual warming trend of 0.06 °C. The strongest increasing trend in seasonal mean air temperatures has been observed in the summer season, with an increase of 0.08 °C per year. The trend analysis also shows a statistically non-significant increase in yearly average minimum temperature (Tmin) between 1973 and 2023, with a rate of 0.04 °C per year. However, the annual maximum temperature (Tmax) has shown no changes. [ABSTRACT FROM AUTHOR]

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

The summer of 2019 is particularly well known for the famous heatwaves that swept across the European continent, with its associated drought and record-breaking air temperatures. This was followed by powerful thunderstorms, characterised by hail and heavy rain that damaged the crops on a regional scale. Here, we investigated one of the largest storm cells, lasting more than 6 h, which struck southwestern Romania. High-temporal resolution sampling of storm precipitation was performed for stable isotope measurements, rainfall and air temperature, to follow the storm dynamics. Hydrogen and oxygen isotope measurements show an abrupt decreasing temporal trend followed by superimposed V-shaped patterns interpreted as reflecting moisture replenishment by successive rain bands. To model the stable isotope values of precipitation in relation to the general trend of decreasing air temperatures, we applied a numerical Rayleigh condensation model for a non-constant α isotopic fractionation factor between liquid water and water vapour. The storm is powered by four consecutive moisture fronts, each following a Rayleigh distribution. About 40 % of the water vapour condenses during the sampled storm due to adiabatic expansion and cooling, which lowers saturation. Condensation ceases when cooling and absolute humidity can no longer sustain the dew point, stopping the rain. The timing of the event, occurring late at night and early in the morning, its duration of over 6 h as well as its synoptic scale may indicate a mesoscale convective complex. [ABSTRACT FROM AUTHOR]

This study introduces a novel approach to visibility modelling, focusing on PM1 concentration, its chemical composition, and meteorological conditions in two distinct Polish cities, Zabrze and Warsaw. The analysis incorporates PM1 concentration measurements as well as its chemical composition and meteorological parameters, including visibility data collected during summer and winter measurement campaigns (120 samples in each city). The developed calculation procedure encompasses several key steps: formulating a visibility prediction model through machine learning, identifying data in clusters using unsupervised learning methods, and conducting global sensitivity analysis for each cluster. The multi-layer perceptron methods developed demonstrate high accuracy in predicting visibility, with R values of 0.90 for Warsaw and an RMSE of 1.52 km for Zabrze. Key findings reveal that air temperature and relative humidity significantly impact visibility, alongside PM1 concentration and specific heavy metals such as Rb, Vi, and Cd in Warsaw and Cr, Vi, and Mo in Zabrze. Cluster analysis underscores the localized and complex nature of visibility determinants, highlighting the substantial but previously underappreciated role of heavy metals. Integrating the k-means clustering and GSA methods emerges as a powerful tool for unravelling complex mechanisms of chemical compound changes in particulate matter and air, significantly influencing visibility development. [ABSTRACT FROM AUTHOR]

Wire icing seriously threatens the safety and reliability of power systems. Strengthening the simulation study of icing thickness is crucial for disaster prevention and mitigation, as well as the adjustment of power system operation strategies. The meteorological elements, including air temperature, precipitation and wind speed, are the key factors affecting wire icing. In this study, the meteorological elements related to icing thickness are obtained by numerical models, and the relationship between these elements and icing thickness observations is established to develop a model for simulating icing thickness. The model is applied to study typical icing in Yunnan Province, China. The results indicate that the deviation of the simulated icing thickness is about 2 mm, smaller than that from the traditional model. Batch experiments demonstrate that the new model developed in this research is applicable to the vast majority of 238 observation stations in Yunnan Province for icing thickness simulation, and the method can yield lower simulation deviations. [ABSTRACT FROM AUTHOR]

High temperatures that prevail at sun-exposed sites such as heaths, depressions, or on slopes, increase the risk of desiccation for rove beetles (Staphylinidae). Therefore, atmospheric and sub-atmospheric humidity determine the microclimates and thus habitat preference and activity of xerothermophilous species. In the nature reserve Marienfl ieß, a heathland in the south of Mecklenburg-Western Pomerania, Northeast German Lowlands, air temperature and humidity were recorded year-round along a transect at 10 sites, i.e. where the vegetation was more dense and more humid than where the vegetation was sparse and it was drier, using data loggers placed in the litter layer that recorded the conditions every 30 min in 2021. Monthly visits were made to determine the biomass of vegetation, soil and litter properties, edaphic rove beetle fauna and total abundance and and that of individual species at 1 m2 sites. Statistical analysis of 365 diurnal cycles per site, with pronounced amplitude in air temperature and humidity, clearly delineated the cooler and more humid sites from warmer and drier ones. Between 10 and 22 of the 30 xerothermophilous species (73.3%), such as, e.g. Quedius persimilis Mulsant & Rey, 1876, Xantholinus gallicus Coiff ait, 1956, Cousya longitarsis (Thomson, 1867) and Euaesthetus superlatus Peyerimhoff, 1937, were recorded only at the cooler and moist sites on the heath. Comparison of the abundances and distribution of species revealed that the xerothermophilous heath-dwelling and desiccation-prone species prefer rather constant environmental conditions, i.e. niches in cool and moist habitats on warm and dry heathland. [ABSTRACT FROM AUTHOR]

Possible local influence of an extreme marine heatwave is investigated on unprecedentedly hot summer around northern Japan in 2023. Sea-surface temperatures (SSTs) and subsurface ocean temperatures around northern Japan were also unprecedentedly high in the summer. This was especially the case off the east coast of Japan, where cool Oyashio water was replaced with much warmer water due to a striking poleward meander of the Kuroshio Extension persistent from the spring. Particularly amplified near-surface air temperature anomalies and even stronger warm anomalies in the subsurface ocean suggest that the marine heatwave acted to sustain the atmospheric heatwave. Anomalous upward of latent and sensible heat fluxes from the warmed sea surface are indicative of local oceanic impact. The warm SST anomalies reduced the lower-tropospheric stratification to maintain unfavourable condition for low-level cloud formation, which in turn led to increased surface insolation for further SST warming as positive feedback. The increased moisture in the warmed lower troposphere contributed to the enhanced surface downward longwave radiation. This enhanced greenhouse effect acted not only as positive feedback on the warm SST anomalies that increased evaporation but also as a contributor for the extreme warmth over northern Japan landmass. [ABSTRACT FROM AUTHOR]

This experimental study investigates the influence of indoor plants on three aspects of air quality in office spaces: relative humidity, indoor air temperature, and carbon dioxide concentration. Employing a Latin square design, we rotated three different treatments across three offices over six time periods. These treatments included a control (no plants), a low-volume treatment (five plants), and a high-volume treatment (eighteen plants) of Nephrolepis exaltata (Boston fern). Air quality parameters were continuously monitored at five-minute intervals using Trace Gas Analyzers. Generalised linear mixed modelling (GLMM) was employed to examine the effect of each treatment on relative humidity, indoor air temperature and CO2 concentration. We observed a significant positive correlation between the number of indoor plants and relative humidity levels. In offices without any plants, the median relative humidity was 29.1%. This increased to 38.9% in offices with 5 plants and further to 49.2% in offices with 18 plants. However, we did not find significant associations between the number of indoor plants and indoor air temperature or corrected CO2 concentration. Our research provides support for the use of indoor plants to increase relative humidity, which can have health benefits in dry climates, but does not provide support for using indoor plants to regulate indoor air temperatures or CO2 concentration in office environments. [ABSTRACT FROM AUTHOR]

To analyze vertical characteristics of agricultural precipitation and heat in the mountainous aera of Huaihua, the meteorological data of nine altitudes in Huaihua from 2011 to 2021 were analyzed. The results showed that as the altitude rises, the annual average temperature decrease is 0.47 °C/100 m, the starting stable date and the ending stable date of every node air temperature are delayed or advanced by 2-4 days every 100 meters, the average decrease in active accumulated temperature of ≥0 °C is 179.9 °C d/100 m, the average decrease in effective accumulated temperature of 10 °C is 128.3 °C d/100 m, the average extreme low temperature reduction is about 0.50 °C/100 m, the annual rainfall at various altitudes is above 1 350 mm. Generally, areas with an altitude below 400 m are areas with sufficient heat, which is suitable for the growth of warm crop varieties, the extreme low temperature in winter at an altitude of >700-1000 m significantly decreases, protective measures should be taken for warm crops to overwinter. There is less heat at an altitude of more than 1000 m, so it is recommended to plant crop varieties that love cooling and have strong cold resistance. [ABSTRACT FROM AUTHOR]

Over recent decades, the southeastern United States (Southeast) has become increasingly well represented by the terrestrial climate proxy record. However, while the paleo proxy records capture the region's hydroclimatic history over the last several centuries, the understanding of near surface air temperature variability is confined to the comparatively shorter observational period (1895‐present). Here, we detail the application of blue intensity (BI) methods on a network of tree‐ring collections and examine their utility for producing robust paleotemperature estimates. Results indicate that maximum latewood BI (LWBI) chronologies exhibit positive and temporally stable correlations (r = 0.28–0.54, p < 0.01) with summer maximum temperatures. As such, we use a network of LWBI chronologies to reconstruct August‐September average maximum temperatures for the Southeast spanning the period 1760–2010 CE. Our work demonstrates the utility of applying novel dendrochronological techniques to improve the understanding of the multi‐centennial temperature history of the Southeast. Plain Language Summary: Tree‐ring data are important sources of paleoclimate information, which allow for the longer‐term evaluation of modern climate values and trends. Compared to much of North America, the Southeastern United States (Southeast) contains substantially fewer paleoclimate records from tree rings, and no estimates of past temperature variability which extend before the observational period. Employing a recently developed technique, which uses light reflectance properties of wood to obtain a representative metric of tree‐ring density, we develop a network of temperature‐sensitive tree‐ring records across the Southeast. These records enable us to reconstruct late summer maximum temperatures across the region spanning the period 1760–2023 CE. As few ground‐based, pre‐instrumental temperature records previously existed for this region, our reconstruction allows for an improved understanding of the region's multi‐centennial climatic history. Key Points: Maximum latewood blue intensity from tree rings can effectively be used to develop paleotemperature estimates for the southeastern USThe fidelity of tree‐ring density parameters for paleoclimate reconstruction are influenced by disturbance regimes and microsite conditionsCompared to the last 260 years, regional 20th‐century maximum late summer temperatures are not characterized by unprecedented positive trend [ABSTRACT FROM AUTHOR]

Atmospheric CO2 and temperature are rising concurrently, and may have profound impacts on the transcriptional, physiological and behavioural responses of aquatic organisms. Further, spring snowmelt may cause transient increases of pCO2 in many freshwater systems. We examined the behavioural, physiological and transcriptomic responses of an ancient fish, the lake sturgeon (Acipenser fulvescens) to projected levels of warming and pCO2 during its most vulnerable period of life, the first year. Specifically, larval fish were raised in either low (16°C) or high (22°C) temperature, and/or low (1000 μatm) or high (2500 μatm) pCO2 in a crossed experimental design over approximately 8 months. Following overwintering, lake sturgeon were exposed to a transient increase in pCO2 of 10,000 μatm, simulating a spring melt based on data in freshwater systems. Transcriptional analyses revealed potential connections to otolith formation and reduced growth in fish exposed to high pCO2 and temperature in combination. Network analyses of differential gene expression revealed different biological processes among the different treatments on the edges of transcriptional networks. Na+/K+‐ATPase activity increased in fish not exposed to elevated pCO2 during development, and mRNA abundance of the β subunit was most strongly predictive of enzyme activity. Behavioural assays revealed a decrease in total activity following an acute CO2 exposure. These results demonstrate compensatory and compounding mechanisms of pCO2 and warming dependent on developmental conditions in lake sturgeon. Conserved elements of the cellular stress response across all organisms provide key information for how other freshwater organisms may respond to future climate change. [ABSTRACT FROM AUTHOR]

This study examines the temporal and spatial variability of near‐surface air temperature and the canopy layer urban heat island (UHICL) of Kuwait City. Observations collected at 12 locations across the country of Kuwait and for the period 2010–2022 are analysed on an hourly and 3‐hourly basis to provide monthly and diurnal insights of the city's UHICL characteristics. Research on Kuwait's UHICL was first conducted by Nasrallah et al. (International Journal of Climatology, 10, 401–405). Results presented here have been afforded the benefit of additional stations and more extensive data compared with the earlier study. Mean positive UHICL intensities, ranging from 1.1°C to 3.8°C at night, are observed consistently across all months, owing to the prevalence of clear skies from winter to summer. Negative UHICL intensities, indicating a typical daytime urban cool island (UCICL), are most prominent on summer days, exhibiting a mean hourly magnitude range between 0.6°C and 2.6°C that extends into the early parts of the evening. Heat and cool island effects are maintained up to wind speeds approaching 10 m s−1 at the urban periphery. A coastal site near the city demonstrates strong influences of the Arabian Gulf temperatures and associated sea and land breeze effects on UHICL development. The results can be used for comparison with other desert locales, in the evaluation of urban climate models, for urban planning policies and improving local weather forecasts. This study honours in memoriam Dr. Hassan Nasrallah, who produced the first UHICL study in the Arab World. [ABSTRACT FROM AUTHOR]

The active and passive oxidation of Al in Al–Al 2 O 3 composites was investigated in air at high temperatures. As fresh air impinged on the surface of the Al–Al 2 O 3 composite sample, a thin Al 2 O 3 layer was preferentially formed via passive oxidation of Al, which consumed most of the oxygen and lowered the local P o 2 inside the sample. At low P o 2 , active oxidation of Al occurred and predominated in the interior transition layer, which further lowered the local P o 2 to extremely low values within the non-oxide stability field. The local equilibrium P Al x O y generated by the active oxidation of Al reached a micro-positive pressure state and served as a gas barrier, hindering the inward diffusion of O 2. The P o 2 inside the composite was lowered by Al in the outer layers via a self-gettering process. Subsequently, Al 4 O 4 C and Al 2 OC-AlN solid solution were formed by both the direct reaction of Al(l) and the indirect reaction of Al x O y (g). After sintering in air, the Al–Al 2 O 3 composite exhibited a functional gradient structure with a thin oxide layer and an interior non-oxide-reinforced corundum. A reaction mechanism model was established. [ABSTRACT FROM AUTHOR]

Although the quality of weather forecasts in the polar regions is improving, forecast skill there still lags behind lower latitudes. So far there have been relatively few efforts to evaluate processes in numerical weather prediction systems using in situ and remote sensing datasets from meteorological observatories in the terrestrial Arctic and Antarctic compared to the mid-latitudes. Progress has been limited both by the heterogeneous nature of observatory and forecast data and by limited availability of the parameters needed to perform process-oriented evaluation in multi-model forecast archives. The Year of Polar Prediction (YOPP) site Model Inter-comparison Project (YOPPsiteMIP) is addressing this gap by producing merged observatory data files (MODFs) and merged model data files (MMDFs), bringing together observations and forecast data at polar meteorological observatories in a format designed to facilitate process-oriented evaluation. An evaluation of forecast performance was performed at seven Arctic sites, focussing on the first YOPP Special Observing Period in the Northern Hemisphere (NH-SOP1) in February and March 2018. It demonstrated that although the characteristics of forecast skill vary between the different sites and systems, an underestimation in boundary layer temperature variability across models, which goes hand in hand with an inability to capture cold extremes, is a common issue at several sites. It is found that many models tend to underestimate the sensitivity of the 2 m air temperature (T2m) and the surface skin temperature to variations in radiative forcing, and the reasons for this are discussed. [ABSTRACT FROM AUTHOR]

The impact of latitudinal variations in the Intertropical Convergence Zone (ITCZ) on northern Andean hydroclimate during the Medieval Climate Anomaly (MCA; 950–1,150 CE) and Little Ice Age (LIA; 1,300–1,850 CE) is uncertain. Synthesis of two new lacustrine paleoclimate records from the Eastern Colombian Andes with existing circum‐Andean records shows that effective moisture anomalies were synchronous and in phase across the tropical Andes during the last millennium. During the MCA, when the ITCZ was shifted northward, topographically controlled responses in the northern Andes to vigorous atmospheric convection resulted in low precipitation and high evaporation, while precipitation was also reduced in the southern tropical Andes. During the LIA, precipitation decreased in the northern Andes as the ITCZ migrated southward but was offset by cooling that lowered evaporation, establishing high effective moisture. In the southern tropical Andes, the southward ITCZ position simultaneously strengthened precipitation, increasing effective moisture. MCA‐like responses to continued warming trends could similarly reduce northern Andean precipitation while increasing evaporation, thereby lowering effective moisture and possibly reducing water resource availability. Plain Language Summary: The position of the tropical rain belt has been proposed as a leading control on Andean hydroclimate during the Medieval Climate Anomaly (MCA; 950–1,150 CE) and Little Ice Age (LIA; 1,300–1,850 CE), producing opposite hydroclimate conditions in the northern and southern tropical Andes. Using two new paleoclimate records from the eastern Colombian Andes and existing records from the northern and southern tropical Andes, we show that tropical Andean hydroclimate responses were similar, with generally warmer and drier conditions during the MCA and cooler and wetter conditions during the LIA. Whereas southern tropical Andean responses were in line with variations in the tropical rain belt, northern tropical Andean responses were not. For the northern Andes, we propose that slow‐moving, low‐energy convective precipitation during the MCA was blocked by the eastern Andes, resulting in reduced precipitation at elevation and in the interior Andes while warming increased evaporation. Wet conditions in the northern Andes during the LIA were the result of cool atmospheric temperatures that reduced evaporation and increased effective moisture despite low precipitation. This suggests topography and temperature played important roles in the northern Andean hydroclimate and that further warming could reduce effective moisture through topographic precipitation blocking and increased evaporation. Key Points: Tropical Andean hydroclimate variability was synchronous and in‐phase between the northern and southern hemispheres during the last millenniumOrographic influences on atmospheric convection‐controlled precipitation in the northern tropical Andes during the last millenniumMean annual temperatures controlled effective moisture in the northern tropical Andes vis‐à‐vis evaporation [ABSTRACT FROM AUTHOR]

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

Tomatoes are delicate and prone to damage quickly, which ultimately leads to lower quality and increased post-harvest losses. Hence, an ideal storage environment is very important to maintain the quality of tomato fruits after harvest. Therefore, this study was conducted to determine the effect of storage conditions on the quality parameters of tomato fruits. Experiments were de-signed for six storage periods (4, 8, 12, 16, 20, and 24 days) and two temperatures (12 °C and room air temperature "22 °C"). Three tomato fruit quality parameters (Brix, color, and firmness) have been selected and measured for three tomato varieties (Ghandowra-F1, Forester-F1, and Feisty-Red) grown hydroponically at three salinity levels (2.5, 6.0, and 9.5 dS m−1) of the nutrient solution. Results showed that the highest mean Brix values, for all varieties, were recorded at the highest salinity (9.5 dS m−1), and were significantly (Pr < 0.0001) higher than those at medium (6.0 dS m−1) and low (2.5 dS m−1) salinity levels. In addition, the highest fruit firmness was recorded at high salinity level (9.5 dS m−1), but there was no significant difference to that recorded at medium salinity (6.0 dS m−1). Regarding tomato fruit color, the highest average values were recorded for the Ghandowra-F1 (2.51) and Forester-F1 (2.69) varieties at medium salinity (6.0 dS m−1), while the highest average color value for the Feisty-Red variety (1.54) was obtained at high salinity (9.5 dS m−1). On the other hand, the Brix, color, and firmness of tomato fruits were significantly affected by the storage temperature. Moreover, the mean Brix values (7.66%) were slightly higher at 12 °C storage temperature compared to those at 22 °C (7.38%). In general, the fruit color values gradually increased with the storage period, especially under 22 °C storage temperature, with peak color values of 2.73, 2.70, and 1.66 recorded on the 12th day of the storage period for Ghandowra-F1, Forester-F1, and Feisty-Red, respectively. Tomato fruit firmness decreased faster with the storage period at 22 °C compared to the storage temperature of 12 °C. However, the highest average values of fruit firmness for Ghandowra-F1 (9.37 N cm−1) and Forester-F1 (9.41 N cm−1) recorded at control condition were not significantly different those recorded on the 8th day of storage at 12 °C storage temperature. By contrast, the highest average value of fruit firmness for Feisty-Red (8.85 N cm−1) recorded at control condition was not significant than that recorded on the 4th day of the storage period at 12 °C storage temperature (8.82 N cm−1). Overall, tomato fruits can be stored at 12 °C temperature for up to 20–24 days, without negative effects on fruit quality. [ABSTRACT FROM AUTHOR]

Highlights: The paper concerns the possibility of using an innovative railway rail structure in a contactless track: The correct operation of CWR track, due to the occurrence of additional thermal stresses with a value dependent on changes in rail temperature, requires a systematic diagnosis of its condition; The paper presents the research of longitudinal force load tests for a classic rail and for two cases of an innovative railway rail solution. The research presented in the paper shows that: The proposed proprietary design of the rail used for the railroad track can enable the reduction in the longitudinal force occurring as a result of high ambient temperatures; The use of an innovative rail conception will allow for less steel consumption, which means less emissions into the atmosphere during its production (lower carbon footprint). This paper presents the concept of a modified 60E1 rail dedicated to continuous welded rail (CWR) track. The presented solution is the subject of a patent application by the authors of the publication. The paper describes problems associated with the operation of CWR track and the phenomena of so-called "rail stressing", i.e., stresses created in the rail due to thermal shrinkage that, in extreme cases, can lead to the buckling of the rail track. Simulation calculations of longitudinal track loads to represent the occurrence of thermal force as a result of the occurrence of high air temperatures were carried out for the constructed conventional model of the railroad track as well as the track with the proposed solutions. A discussion of the simulation results is presented, indicating the possibility for the wider application of both varieties of modified rail. [ABSTRACT FROM AUTHOR]

Groundwater flow systems are influenced by the changes in surface waters as well as climatic factors. These teleconnections significantly increase in cases of extreme weather conditions. To prepare and mitigate the effect of such phenomena, the background factors that create and influence natural processes must be recognized. In the present study, 94 shallow groundwater (SGW) wells' water level time series were analyzed in the inner delta of the River Danube (Europe) the Szigetköz region to explore which factors contribute to the development of diurnal periodicity of SGW and what its drivers are. The relationship between surface meteorological processes and SGW dynamics in the Szigetköz region was investigated using hourly data from monitoring wells. Hourly water temperature data exhibited weak correlations with meteorological parameters. However, daily averaged data revealed stronger correlations, particularly between SGW levels and air temperature and potential evapotranspiration. Diurnal periodicity in SGW fluctuations correlated strongly with potential evapotranspiration. The study also demonstrated the role of capillary fringe dynamics in linking surface evapotranspiration with SGW fluctuations. Changes in groundwater levels, even small, can significantly affect soil moisture, vegetation, and ecosystem functioning, highlighting the sensitivity of the unsaturated zone to SGW fluctuations driven by surface processes. [ABSTRACT FROM AUTHOR]

In mid-June to July 2023, North China witnessed extreme heatwaves, marked by intense near-surface warming with an advanced seasonal cycle of local air temperature. An unconventional upper-tropospheric cold vortex in early June, deviating from conventional "heat dome" patterns, preceded the heatwave extremes. The zonal SSTA gradient in Indo-Pacific warm pool initially suppressed Indian summer monsoon convection, which stimulated the cold vortex around North China via a tropical-extratropical teleconnection. This anomaly intensified the air-land thermal contrast, leading to increased sensible heating and reduced soil moisture in situ. The drier soil conditions maintained and further augmented sensible heating, escalating surface air temperature, and culminating in extraordinary heatwaves. The air column was then destabilized to mitigate the upper-level cold vortex. Historical records corroborate the extremity of the air-sea interactions in 2023. The ECMWF real-time subseasonal-to-seasonal (S2S) forecasts successfully capture the air-land feedback in both cold vortex and heatwave stages, albeit with an underestimation of heatwave intensity due to biases in soil moisture anomalies. Consequently, the initial cold vortex condition and air-land-sea interactions yield S2S predictability to the historic 2023 heatwaves in North China. [ABSTRACT FROM AUTHOR]

Chinese Baijiu industry is undergoing industrial modernization. However, the key processes including Daqu processing are directly modified based on empirical knowledge, and the lack of engineering mechanisms lead to the inability of rational design. Here, this study quantitatively analyzed the heat generation and flow during Daqu solid-state fermentation, tracked and recorded the parameters during Daqu processing, simplified the biochemical reactions of the fermentation process, and built a Daqu heat balance model. Through the model, the heat generated during the whole fermentation process was transferred outside of the system through three ways: Water evaporation (54. 22% ), conduction of wall and air flow (42. 00% ), and air temperature rising ( < 1% ). The remaining heat (3. 77% ) was the cumulative heat, which was positively correlated with the temperature rise of the Daqu ( R² =0.85). It was verified that the average error of the model for the temperature change of dacquoise was 5. 05% with R² = 0. 94. Based on the model, the effect of regulating moisture parameters on the temperature of Daqu was explored, which showed the importance of moisture control for regulating the temperature during Daqu preparation. Through the preliminary exploration of the feasibility of regulating and optimizing the future production of Daqu from the perspective of mathematical modeling, the results of the study can provide theoretical support for the construction of modern fermentation process. [ABSTRACT FROM AUTHOR]

The complex meso- and microclimatic heterogeneity inherent to mountainous regions, driven by both topographic and biotic factors, and the lack of observations, poses significant challenges to using climate models to predict and understand impacts at various scales. We present here a six-year dataset (2017–2022) of continuous climatic measurements collected at five elevations from 983 m to 2705 m above sea level in the Val Mazia - Matschertal valley in the Italian Alps. The measurements include the air temperature, relative humidity, wind speed and direction, solar radiation, soil properties, precipitation, and snow height. Collected within the European Long-Term Ecological Research program (LTER), this dataset is freely available in an open access repository. The time series may be valuable for the validation of regional climate models, atmospheric exchange modelling, and providing support for hydrological models and remote sensing products in mountain environments. Additionally, our data may be useful for research on the influence of elevation on ecological processes such as vegetation growth, plant composition, and soil biology. Beyond its utility in advancing such fundamental research, meteorological monitoring data contribute to informed socio-political decisions on climate adaptation strategies, land management, and water resource planning, enhancing the safety and resilience of mountain communities and biodiversity. [ABSTRACT FROM AUTHOR]

Torpor is widespread among bats presumably because most species are small, and torpor greatly reduces their high mass-specific resting energy expenditure, especially in the cold. Torpor has not been recorded in any bat species larger than 50 g, yet in theory could be beneficial even in the world's largest bats (flying-foxes; Pteropus spp.) that are exposed to adverse environmental conditions causing energy bottlenecks. We used temperature telemetry to measure body temperature in wild-living adult male grey-headed flying-foxes (P. poliocephalus; 799 g) during winter in southern Australia. We found that all individuals used torpor while day-roosting, with minimum body temperature reaching 27°C. Torpor was recorded following a period of cool, wet and windy weather, and on a day with the coldest maximum air temperature, suggesting it is an adaptation to reduce energy expenditure during periods of increased thermoregulatory costs and depleted body energy stores. A capacity for torpor among flying-foxes has implications for understanding their distribution, behavioural ecology and life history. Furthermore, our discovery increases the body mass of bats known to use torpor by more than tenfold and extends the documented use of this energy-saving strategy under wild conditions to all bat superfamilies, with implications for the evolutionary maintenance of torpor among bats and other mammals. [ABSTRACT FROM AUTHOR]

Serial correlations within temperature time series serve as indicators of the temporal consistency of climate events. This study delves into the serial correlations embedded in global surface air temperature (SAT) data. Initially, we preprocess the SAT time series to eradicate seasonal patterns and linear trends, resulting in the SAT anomaly time series, which encapsulates the inherent variability of Earth's climate system. Employing diverse statistical techniques, we identify three distinct types of serial correlations: short-term, long-term, and nonlinear. To identify short-term correlations, we utilize the first-order autoregressive model, AR(1), revealing a global pattern that can be partially attributed to atmospheric Rossby waves in extratropical regions and the Eastern Pacific warm pool. For long-term correlations, we adopt the standard detrended fluctuation analysis, finding that the global pattern aligns with long-term climate variability, such as the El Niño-Southern Oscillation (ENSO) over the Eastern Pacific. Furthermore, we apply the horizontal visibility graph (HVG) algorithm to transform the SAT anomaly time series into complex networks. The topological parameters of these networks aptly capture the long-term correlations present in the data. Additionally, we introduce a novel topological parameter, Δσ, to detect nonlinear correlations. The statistical significance of this parameter is rigorously tested using the Monte Carlo method, simulating fractional Brownian motion and fractional Gaussian noise processes with a predefined DFA exponent to estimate confidence intervals. In conclusion, serial correlations are universal in global SAT time series and the presence of these serial correlations should be considered carefully in climate sciences. [ABSTRACT FROM AUTHOR]

High‐resolution climate projections are valuable resources for understanding the regional impacts of climate change and developing appropriate adaptation/mitigation strategies. In this study, we developed a 10‐km gridded hydrometeorological dataset over India by dynamic downscaling of the bias‐corrected Community Earth System Model (CESMv1) climate projections under RCP8.5 scenario using the state‐of‐the‐art Weather Research and Forecasting (WRF) model. The downscaled CESM dataset (DSCESM) is archived in the World Data Center for Climate (WDCC) portal at three temporal resolutions (daily, monthly and monthly climatology) for current (2006–2015), mid‐century (2041–2050) and end‐century (2091–2100) periods. The dataset includes 2‐m air temperature, total accumulated precipitation, wind speed, relative humidity, sensible and latent heat fluxes, along with surface shortwave and outgoing longwave radiation. All the DSCESM variables were evaluated against reanalysis data and station observations for the period 2006–2015. This dataset can help us quantitatively understand regional climate change in India. It can also be used in conjunction with agricultural, hydrological, fire and other application models for climate change impact assessment on various sectors to help develop effective adaptation/mitigation strategies. [ABSTRACT FROM AUTHOR]