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The relative importance of oceanic modes to global surface air temperature (SAT) and terrestrial precipitation during 1934–2020 was investigated using a variety of statistical and dynamical system methods. Through singular spectrum analysis, we present the distribution of decadal (10–20‐year), multidecadal (20–50‐year), and secular (>50‐year) variabilities of global SAT and terrestrial precipitation anomalies. Three sea surface temperature modes were identified by singular value decomposition that affect the low‐frequency variabilities of global SAT and terrestrial precipitation anomalies—namely, global warming (GW), the Interdecadal Pacific Oscillation (IPO), and the Atlantic Multidecadal Oscillation (AMO). The relative importance GW, the IPO, and the AMO in SAT and terrestrial precipitation was obtained through a normalized multivariate information flow analysis. Besides a high information flow percentage (60%) from GW to global SAT, especially over the northern Indian Ocean and tropical West Pacific, information flow from the AMO to the northwestern Pacific was also found. In terms of terrestrial precipitation, a large area with a wet trend was found over Eurasia at mid‐to‐high latitudes, and this trend was especially remarkable in the boreal winter half‐year (November–April), as compared with that in the boreal summer half‐year (May–October). By employing artificial neutral networks with a self‐organized map to cluster the key patterns of vertically integrated water vapour flux, we found that the synoptic circulation related to the wet trend is characterized by westerly flow that transports water vapour from the northeastern Atlantic to Eurasia, which is favourable for precipitation there both in the boreal winter and summer half‐year. [ABSTRACT FROM AUTHOR]

It is commonly recognized that the observed increase in global mean annual air temperature is strongly related to the increase in global carbon dioxide concentration C, and that both these variables are related to global development. It remains, however, unclear the degree to which local mean annual urban air temperature T is affected by local variables such as annual precipitation depth P and urban area extent A. This study assumes that A is a proxy of local development and C is a proxy of global development and investigates the commingled effects of A, P, and C on T by using long-term annual data observed over the years 1881–2019 from the Modena Observatory in Italy. Linear relationships between T, C and A are found to be spurious since all these series have a monotonic increasing trend with time. Parametric analytic models like logistic functions are found to lack flexibility. Smoothing splines can only give insights into the strength of the relationships but not on their shape defining the functional relationship between variables. Advanced nonlinear models like generalized additive models, instead, are found to combine flexibility in a parametric form, and appear therefore to be suitable models for explaining the complex relationships between A, P, and C on T. The different models are evaluated using traditional goodness of fit statistics like R2, AIC, BIC, and a new index of relation IR which is introduced to jointly evaluate the goodness-of-fit of relationships between variables that may either be dependent or independent. [ABSTRACT FROM AUTHOR]

This study aims to examine the intraseasonal variation of PM2.5 concentration in North China and explore the potential influence of the Eurasian mid-high-latitude intraseasonal oscillation (ISO) on this variation. A statistically significant period of 10–30 days is observed for PM2.5 concentration anomalies in North China. Further study suggests that circulation patterns and associated meteorological factors play a crucial role in pollution events in North China. These factors influence local accumulation of pollutants and hygroscopic growth conditions. Based on the ISO phases, it is found that, at the earliest, the circulation in phase 2 provides favorable conditions for pollution. The circulation involved phase 2 leads to a strong increase in surface air temperature, a decrease in sea level pressure, and an increase in humidity in the low layers. These conditions provide favorable meteorological conditions for the accumulation of PM2.5 in North China. The interannual variability of ISO intensity and its impact on PM2.5 concentration in North China has also been analyzed. The results show that the circulation is stronger and propagates more southeastward during strong ISO years. Under the influence of the anticyclonic circulation in Mongolia during strong ISO years, favorable moisture conditions and atmospheric stability contribute to an increase in pollution. [ABSTRACT FROM AUTHOR]

This study focuses on the analysis of the simulation of the main climatological features of the Orinoco low-level jet (OLLJ) by a set of models included in the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) and their projected changes under three Shared Socioeconomic Pathways (SSPs): SSP2-4.5, SSP3-7.0, and SSP5-8.5. We consider the 1979–2014 period to evaluate the historical simulations using the ERA5 reanalysis as the reference dataset. In general, CMIP6 models are able to capture the activation of the OLLJ during December-January–February (DJF) in the Orinoco basin, as well as the main links between this circulation and low-level moisture transport patterns in northern South America. Regarding the analysis of projections, CMIP6 models suggest a weakening and shrinking of the OLLJ, especially in its exit region, by the end of the twenty-first century, which in turn induces changes in atmospheric moisture transport patterns in the region during DJF. The projected changes of the OLLJ are associated with variations in the regional gradients of mean sea level pressure, near-surface air temperature, and surface sensible heat flux in association with drier conditions in the Orinoco basin. These projections are consistent with previous studies suggesting a drier Orinoco river basin throughout the twenty-first century. Assessing the projected changes of this low-level jet in northern South America improves our understanding of the different phenomena that modulate atmospheric moisture transport in the region, which is particularly important given its high vulnerability to climate change. [ABSTRACT FROM AUTHOR]

Based on the multi-model ensemble mean of CMIP6 simulations, the future changes in frequency, intensity and duration of Compound (both daytime and nighttime) heatwaves (HWs) in summer over China at various global warming levels (GWLs) under the SSP3-7.0 and SSP5-8.5 are assessed. HWs over China become more frequent and hotter, and the duration of HWs becomes longer compared to those in the recent climate. The magnitudes of these changes are primarily dependent on GWLs, but they are not very sensitive to the scenarios. At 4 ℃ GWL, the frequency of HWs increases by more than fivefold under both scenarios, and the intensity (duration) of HWs averaged under the two scenarios is 2.28 ℃ hotter (3.59 days longer) than the one in the recent climate over the entire China. Meanwhile, the maximum duration of HW events can reach more than 25 days in summer in comparison with 8 days in the recent climate. The changes in HW properties are regionally dependent at the four GWLs. For example, the largest increase in HW frequency is over the Northwest China, the largest increase in intensity in HWs is seen over the Northeast and Northwest, and the largest increase in HW duration is over the Southwest China. The extreme rare events (50-year and 100-year events) in the recent climate would become the norm over China and four sub-regions at 4 ℃ GWL. Overall, seasonal mean warming dominates the changes in HW properties over China at the different GWLs. The seasonal mean warming in summer across China is related to the increases of longwave radiation, partly due to increase in greenhouse gas forcing and partly resulted from increased water vapor and the increase of shortwave radiation (under the SSP5-8.5) over eastern China related to decreases in aerosols and total cloud cover. Furthermore, the regional variations in the water vapor over China are consistent with atmospheric circulation changes. The seasonal mean surface warming results in enhanced upward sensible and latent heat fluxes, leading to increased summer mean daily maximum and minimum of near-surface air temperature and the enhancement of HWs properties over the entire China. Changes of shortwave radiation tend to play a weaker role for surface warming under the SSP3-7.0 than those under the SSP5-8.5, which is related to increased aerosol changes under the SSP3-7.0. [ABSTRACT FROM AUTHOR]

Although the influences of El Niño–Southern Oscillation (ENSO) and boreal summer intraseasonal oscillation (ISO) on basin-wide tropical cyclone (TC) activity over the western North Pacific (WNP) have been widely recognized, how the seasonal and subseasonal anomalies of sea surface temperature and atmospheric ISO variations modulate different types of WNP TCs needed further examination, as addressed in this study. Using a fuzzy c-means clustering method, we objectively classified the WNP TCs into seven distinct clusters with different genesis locations and trajectories. The genesis numbers of all seven TC clusters revealed significant spectral variance at the intraseasonal timescale in the bands of 10–30 and 30–90 days. Based on the diagnosis of scale-decomposed genesis potential index, we found that the increase in ISO-related mid-tropospheric moistening plays the most important role in TC genesis for all seven clusters, while anomalous circulations (low-level vorticity and mid-level vertical motion) are secondary. The trajectories associated with straight-moving and recurving TC clusters are modulated by ISO-related steering flows. These modulations of TC activities by ISO vary with the phase of ENSO. The modulations of ISO are significantly greater for TCs generated in the southeast quadrant of the WNP in El Niño years than in La Niña years, while ISO imposes a larger impact on landfalling TCs occurring in La Niña years, which are changed by the low-level winds associated with ENSO conditions. The compound effects of ENSO and ISO on TC clusters provide useful sources of subseasonal TC predictability. Our statistical model using the information of ENSO and ISO shows skillful predictions of WNP TC genesis numbers and track distributions at the lead time up to 30 days. [ABSTRACT FROM AUTHOR]

Air temperature variability and prediction are important considering the potential implications on human health, water resource management, agriculture and land-atmosphere interaction. In this paper, we investigate the delayed influence of El Niño on spring Surface Air Temperature (SAT) variability over India using observations and assess its predictability in coupled climate models. Analysis suggests that El Niño, at its decaying phase, exerts a strong influence on the spring SAT over Southern Peninsular India (SPI). This warming is mainly induced by an anomalous anticyclone, which extends from the Western North Pacific (WNP) region to the SPI. The anomalous anticyclone-induced downdraft reduces the cloud cover and increases incoming shortwave radiation at surface, which in turn causes a dry atmospheric column and dry soil moisture over this region. As a result of this decreased soil moisture, latent heat flux into atmosphere reduces and enhances sensible heat transfer, further contributing to dry soil moisture. Both dry soil moisture and anomalous anticyclone contributes to enhanced SAT over SPI region. It is found that 6 years out of the top 10 warmest years over the SPI region correspond to the decaying phase of El Niño, suggesting the importance of the present study. It is also found that the intense SAT warming over SPI aids in increasing frequencies of Discomfort Index hours (exceeding 28 and 30 °C in a day) and the Universal Thermal Climate Index during El Niño decaying spring years. Further, we have examined the predictability of the spring SAT during decaying El Niño years based on the Asia-Pacific Economic Cooperation Climate Center (APCC) models. It is noted that most of the APCC models reasonably predicted the spatial distribution of warm SAT over India during the El Niño decaying spring season at 1 and 3 month lead. This study highlights the predictability of spring SAT a season in advance over India, which would help in planning better adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

The effects of initial errors in the subseasonal prediction are investigated using the Korea Meteorological Administration (KMA) Global Seasonal Forecasting System version 5 (GloSea5). Two experiments are designed that utilized (1) analysis data from weather prediction and (2) reanalysis data as the atmospheric initial conditions, which are considered processes of the current operational system. A comparison of these two experiments reveals the effect of the atmospheric initial conditions on subseasonal prediction. Additionally, the effects of different initial prescriptions on the hindcasts and forecasts are investigated. GloSea5 generally represents the observed temperature patterns well; however, cold biases are distinct over continents in the Northern Hemisphere, including the East Asia region in the hindcast results. However, the forecast results simulate anomalously high temperatures in most regions, except for parts of the polar and Australian regions. In this study, it is clear that improved atmospheric initial conditions lead to changes in the prediction skills of variables related to seasonal climate variability in mid-latitude regions. In addition, the biases of the surface temperature are reduced in most regions when the atmospheric initial condition are made consistent between the hindcast and forecast. Notably, increased initial errors in real-time forecasts, compared to hindcasts, can cause more biases in surface temperature and atmospheric circulation fields on a subseasonal time scale. [ABSTRACT FROM AUTHOR]

In the traditional tobacco drying process, there is often a problem of uneven drying, which is closely related to drying conditions such as air velocity and temperature. To better understand the drying characteristics of tobacco, its drying kinetic performance were experimentally studied and predicted in this paper. In the drying experiment, the range of air temperature and velocity is 20–60℃ and 0.95–4.93 m/s, respectively. The results show that the effective diffusion coefficient increases with the increase of air temperature and decreases with the increase of air velocity. The effective moisture diffusivity( D eff ) ranges from 2.077 × 10–7 to 9.136 × 10–7 m2/s. Additionally, the activation energy (Ea) is between 14.292 and 21.032 kJ/mol according to Arrhenius law. Among the six commonly used empirical correlations, the logarithmic model has higher prediction accuracy, but it has a prediction deviation of more than 20% in the later stage of drying. Based on the logarithmic model and the two models, a new prediction model of tobacco drying characteristics was proposed with a maximum relative deviation error of less than 1%. [ABSTRACT FROM AUTHOR]

The article provides a comprehensive overview of weather conditions in the United States during November and December 2023. It highlights areas of heavy precipitation, such as the Pacific Northwest and Gulf Coast, as well as regions experiencing dry weather, like the upper Midwest. The article also mentions temperature anomalies, record-setting highs and lows, and significant precipitation events throughout both months. It notes improvements and worsening of drought conditions in different areas. Additionally, the article provides information about specific weather events, such as storms, flooding, and a blizzard, that occurred in various parts of the country. It also mentions the warmest December on record in several states and the fifth-warmest year on record for the United States as a whole. The text also includes details about weather conditions in Alaska during December. [Extracted from the article]

A solar eclipse in April could affect local weather by causing a drop in temperatures, wind speeds, and humidity. During the 2017 eclipse, wind speeds dropped by an average of 6 mph. Additionally, a significant temperature drop can reduce cloud cover. In other news, Maureen Sweeney, an Irish woman whose weather forecast helped determine the date for the D-Day invasion in World War II, passed away at the age of 100. Lastly, a study found that thunderstorm-induced straight-line winds are covering a larger area in the central United States, causing significant damage. Extreme weather events were ranked as the second-highest risk factor for major catastrophic events in a survey conducted by the World Economic Forum. [Extracted from the article]

Canopy temperature (Tc) measurements are increasingly being used to compute crop thermal indices for water stress estimation and improved irrigation management. Conventionally monitoring crop thermal response requires maintenance of a well-watered crop from which non-stressed canopy temperature (Tcns) is measured as a reference for thermal index computation. This study alternatively evaluated the performance of 36 weather data driven model combinations to predict peak time (12:00–17:00 h) Tcns in maize grown in semi-arid climates at the West Central Research, Extension, and Education Center (WCREEC) in North Platte, NE, and at the Limited Irrigation Research Farm (LIRF) in Greeley, CO. Data-driven models considered were multilinear regression (MLR), forward feed neural network (NN), recurrent neural network (RNN), multivariate adoptive regression splines (MARS), random forest (RF), and k-nearest neighbor (KNN). For each of these models, the following weather data combinations were tested: average air temperature (Ta), average relative humidity (RH), wind speed (U2), and solar radiation (Rs) (combination 1); RH, U2, Rs (combination 2), Ta, RH, Rs (combination 3); Ta, RH (combination 4); RH, Rs (combination 5); and Ta, Rs (combination 6). Ranking the performance of weather data × model combinations across both climate sites showed that MARS model with combination 1 was a better predictor of Tcns with R2 of 0.866 and RMSE value of 0.966 °C at WCREEC and R2 of 0.910 and RMSE value of 0.693 °C at LIRF. The performance of site specific (localized) and generalized model combinations was compared and indicated that cross site prediction of Tcns was primarily determined by weather data combinations, rather than model specificity. [ABSTRACT FROM AUTHOR]

The objective of this study was to propose bioclimatic zoning to classify human thermal comfort and discomfort in the state of Minas Gerais, Brazil; both historical and future scenarios are considered. Thus, historical series (1961 to 2017) of the effective temperature index as a function of the wind (ETW) were obtained as a function of the monthly average values of the minimum, mean, and maximum dry-bulb air temperatures (tdb,min, tdb,mean, and tdb,max, respectively), in addition to the mean relative humidity (RH , %) and mean wind speed (V , m s −1). The data were obtained from 34 weather stations and subjected to trend analysis by using the nonparametric Mann–Kendall test, thus enabling the simulation of future scenarios (for 2028 and 2038). Then, to define the thermal ranges of the bioclimatic zoning, maps of ETWmin, ETWmean, and ETWmax were created from geostatistical analysis. Overall, the results show warming trends for the upcoming years in Minas Gerais municipalities. All climatic seasons showed an increase in the frequency of new classifications in the upper adjacent classes, which indicates climate warming. Therefore, when considering future scenarios for the autumn and winter seasons, attention should be given to changes in predicted thermal sensation, especially in the Central Minas Gerais, Belo Horizonte Metropolitan, South/Southwest Minas, Campo das Vertentes, and Zona da Mata. [ABSTRACT FROM AUTHOR]

Here, we evaluated the influence of outdoor environmental conditions (synoptic weather conditions) on human thermal discomfort in the five macro-regions of Pelotas city, located in the southernmost region of Brazil. To do this, meteorological sensors (HOBO MX2301A) were installed outside the residences to measure the air temperature, dew point temperature, and relative humidity between 18 January and 20 August 2019. Two well-established simplified biometeorological indices were examined seasonally: (i) humidex for the summer months and (ii) effective temperature as a function of wind for the autumn and winter months. Our findings showed seasonal differences related to human thermal discomfort and outdoor environmental conditions. The thermal discomfort was highest in the afternoons during the summer months and at night during the winter months. The seasonal variation in human thermal discomfort was highly associated with the meteorological conditions. In summer, the presence of the South Atlantic Subtropical Anticyclone (SASA) contributed to heat stress. The SASA combined with the continent's low humidity contributed to the perceived sensation of thermal discomfort. In the winter, thermal discomfort was associated with the decrease in air humidity caused by high atmospheric pressure systems, which led to a decrease in both air temperature and air moisture content. Our findings suggest that a better understanding of the complex interplay between outdoor environmental factors and human thermal comfort is needed in order to mitigate the negative effects of thermal discomfort. [ABSTRACT FROM AUTHOR]

The indoor climate to which livestock are exposed is a critical factor influencing their performance and productivity. Elevated air temperature and relative humidity could result in heat stress for laying hens. This situation results in severe adverse effects such as weight loss and mortality. Egg fertility and hatchability are also impacted. Consequently, a study was carried out in a naturally ventilated battery-caged laying hen house to measure climatic variables (air temperature, relative humidity and air velocity). The degree of heat stress was assessed using the temperature-humidity index (THI), and the index of temperature and air velocity (ITV) was also evaluated. According to the results obtained, birds reared within the study building would spend most of their productive life under stressful thermal conditions, which could significantly hamper their performance. The air velocity was below 1.0 ms−1 for most of the internal part of the housing, meaning natural air movement at the location was insufficient to provide a suitable environment for the birds. A high THI was recorded for nearly the entire study period. This high THI could indicate high relative humidity about air temperature. The observed ITV values (ITV > 25) suggest that birds throughout the building could be perpetually uncomfortable. The thermal and velocity profile within the structure could further be assessed numerically using computational fluid dynamics. This would enable engineers to make modifications to improve living conditions within the building. [ABSTRACT FROM AUTHOR]

The importance of adsorption in water purification and the need to guard against erroneous conclusions often associated with the use of equilibrium adsorption model studies in adsorption systems informed this work. Water purification by adsorption of Congo red (CR) from synthetic aqueous solution to acid treated corncob charcoal (ATCC) was carried out at three different pH values (8.0, 10.5, and 12.0) and at temperatures 10–40 °C. The maximum adsorption capacity of ATCC for CR was 85.8 mg/g at pH 12. The resulting data from the batch adsorption studies were plotted at different temperatures and were fitted to linear form of three isotherm models; Freundlich, Langmuir, and Temkin. Though all three models fitted the experimental data linearly, only Langmuir model was able to account for the observed thermodynamic behavior of the adsorbent–adsorbate systems under the pH conditions. The standard enthalpy values for the adsorption of CR on ATCC at pH 8.0, 10.5, and 12.0 were −5.010 ± 0.312, −7.024 ± 0.440, and −71.426 ± 3.130 kJ mol−1, respectively. The corresponding entropies at pH 8.0, 10.5, and 12.0 were 98.7 ± 1.0, 87.8 ± 1.5, and 129.0 ± 10.5 J mol−1 K−1, respectively. The effect of pH on the thermodynamic quantities were rationalized on the basis of the type of interaction between the CR and the adsorbent. To determine the most suitable model, it was important to juxtapose the observed dependence of adsorption affinity on temperature with the thermodynamic information of the adsorption studies. [ABSTRACT FROM AUTHOR]

This study conducted field tests to investigate the thermomechanical response of an energy wall under practical intermittent and experimental monotone operation modes. Sensors and thermometers were utilized to measure inlet/outlet water temperature, air temperature, wall temperature, and strain. The heat-exchange performance and three-dimensional thermomechanical behavior of the energy wall were closely monitored and analyzed. The test results revealed that the intermittent heating operation demonstrated superior heat-exchange performance compared to the monotone heating operation, resulting in a reduced magnitude of wall temperature change. Moreover, the study highlighted the influence of physical and thermal boundary conditions on thermally induced stress within the wall. The response of the wall to thermal loading was found to be influenced by various factors, including location, temperature change, and the heating history, particularly in the intermittent operation. [ABSTRACT FROM AUTHOR]

Maintaining frozen ground stability in the Arctic and sub-Arctic is a continuing challenge, particularly with climate warming. One engineering solution to tackle this problem is the use of thermosyphons, an artificial ground cooling apparatus, to stabilize the frozen ground. Passive thermosyphons function when the above-ground condenser section is colder than the subsurface evaporator section. This occurs when the ambient air temperature is colder than the subsurface ground temperature. Passive thermosyphons absorb thermal energy from subsurface ground layers and reject it into the atmosphere. Therefore, this passive technology augments natural ground cooling during the cold winter months. Hybrid thermosyphons operate in passive and active (powered refrigeration) modes. For remote locations, the electrical requirements for active thermosyphons limit their application. However, solar power is a promising method to provide an electrical source to operate active and hybrid thermosyphons. This technical note presents the results from an experimental study that tested the use of a solar array system that powered a refrigeration unit, which provided active cooling to a hybrid thermosyphon. The energy that was generated from the solar array successfully operated the refrigeration unit, provided active cooling to the hybrid thermosyphon, and lowered soil temperatures. This study showed the potential for the future development and application of a more energy-efficient off-grid hybrid thermosyphon system. Maintaining frozen ground stability in the Arctic and sub-Arctic is a constant challenge, especially as the climate is warming. Engineering solutions, such as artificial ground freezing techniques to stabilize the frozen ground, are commonly used in cold climates. Freezing the ground with artificial freezing systems is achieved without power when air temperatures are below freezing. When air temperatures are above freezing, the passive system seizes; however, freezing could continue if linked to a mechanical refrigeration unit. The electrical requirements of this cooling technique, when temperatures are above freezing, severely restrict their use in remote areas. This technical note presents an experimental study where a solar array system was tested for powering a refrigeration unit connected to an artificial freezing system. Freezing was extended at warmer air temperatures (above freezing) with a refrigeration unit that was operated by solar array-generated energy. The refrigeration unit successfully operated, and soil temperatures decreased. Supplying this ground cooling technique with a solar powered system could be possible for future applications. [ABSTRACT FROM AUTHOR]

Meteorological processes are investigated during the development of deep convective clouds over the Yellow Sea inside a quasi‐stationary rainy front in the East Asian region. WRF‐Chem simulations were conducted to assess the effects of aqueous‐phase chemistry on the concentrations of PM2.5 and hydrometers in deep convective clouds and the associated precipitation. A reduction in the south‐north air temperature gradient induced an inactive quasi‐stationary rainy front with nonlinear zonal clouds during the Changma period in the East Asian region in 2017, causing intensified surface heating due to solar radiation. A mesoscale cyclone was formed near the Shantung Peninsula inside the inactive quasi‐stationary rainy front, extending the eastward tongue of the troughs across the Yellow Sea. Deep convective clouds (CC16 on July 16, CC17 on July 17, and CC18 on July 18) formed in a severe mode on the east side of the mesoscale cyclone over the Yellow Sea at midnight as the warm type, as the warm and humid south‐southwesterly winds present at that time produced convection energy. PM2.5 from eastern China flowed into warm‐type CC16, CC17, and CC18 areas, producing more cloud droplets below 500 hPa via activation. In contrast, the release of additional condensation heat amplifies updrafts within convective clouds during efficient nighttime environmental cooling, thereby enhancing the production of cold‐type ice, reaching altitudes of up to 15 km. The WRF‐Chem PM2.5 outcomes indicate a significant increase in heavy rainfall, exceeding 10 mm hr−1, particularly in the context of the development of cold‐type convective clouds. Plain Language Summary: The regional phenomenon of summer rain, known as Changma in Korea, usually occurs with a quasi‐stationary rainy front that forms between the continental polar air mass over the East Asian region and the maritime tropical air mass over the northwest Pacific. An inactive quasi‐stationary rainy front with nonlinear zonal clouds induced by a reduction in the south‐north air temperature gradient during the Changma period led to the efficient absorption of solar radiation on the surface of the East Asian region. In addition, convective clouds have frequently developed over the Yellow Sea inside the inactive quasi‐stationary rainy front, resulting in extreme events with large amounts of short‐term precipitation in inland Korea. We found that aqueous‐phase chemistry in convective clouds led to the production of PM2.5 and nucleated cloud droplets, enhancing precipitation on 16–18 July 2017. While warm‐type convective clouds developed due to warm and humid south‐southwesterly flows over the Yellow Sea, WRF‐Chem‐simulated PM2.5 promoted cold‐type ice production to a top convection height of 15 km. The entrainment of near‐surface PM2.5 aerosols in the south‐southwesterly flows from eastern China and the secondary activations over the boundary layer clouds enhanced heavy rainfall to more than 10 mm hr−1 in cold‐type convective clouds. Key Points: A reduction in the air temperature gradient induced an inactive rainy front, forming a mesoscale cyclone over the Yellow SeaPM2.5 aerosols in eastern China flowed out to the Yellow Sea, wherein the PM2.5 inflows contributed to the development of cold‐type cloudsCold‐type clouds promoted heavy rainfall exceeding 10 mm hr−1 over the Yellow Sea and Korea [ABSTRACT FROM AUTHOR]

Introduction: Root hairs increase the surface area of a plant's root system that is in contact with the soil, thus facilitating plant water and nutrient uptake. However, little is known about the characteristics of the root hairs of herbaceous and woody plants and their specific response patterns to biotic and abiotic variables from the perspective of resource acquisition strategies in the context of global change. Methods: Here, we analyzed 74 published case studies with 1074 observations of root hair traits to identify patterns of root hair length, density and diameter in relation to soil (e.g., soil pH, nutrient levels), growing environments (e.g., greenhouse, field) and climatic factors (e.g., air temperature), as well as genome size and plant age. Results: Root hairs were longer, denser and thicker in woody plants compared with herbaceous plants, and the length and diameter of root hairs in herbaceous plants increased with genome size. With increasing plant age, woody plants had significantly longer and thicker root hairs, while root hair density and diameter declined significantly for herbaceous plants. Soil-cultured plants had longer root hairs than solution-cultured plants. The length and density of root hairs were greater in greenhouse-cultured plants than in field-grown plants, and the latter had thicker root hairs than the former. As soil pH increased, root hair length increased but diameter decreased in woody plants, while root hair density increased in herbaceous plants. Increased soil total nitrogen (N) and potassium (K) significantly increased root hair length, density and diameter in herbaceous plants, while soil total N significantly decreased root hair density in woody plants. Root hair length increased significantly, while root hair density decreased significantly, with higher mean annual temperature and greater precipitation seasonality, while the opposite pattern was true for a wider annual temperature range. Discussion: Our findings emphasize the life-form-specific responses of root hairs to soil and climatic variables. These findings will help deepen our understanding of resource acquisition strategies and their mechanisms in different plant forms under global climate change. [ABSTRACT FROM AUTHOR]

The sensitivity strength of air temperature (T) to surface soil temperature (sST) (namely β hereafter) constitutes a significant factor in how global climate models quantify changes in the climate. This study examines how this sensitivity is represented in the CMIP6 models. Results show regional differences and even contrasts in the β trends at interannual scales between climate models and two reanalysis products during 1980–2014. At high latitudes in the Northern Hemisphere (NH), β is stronger in the CMIP6 models than in the reanalysis data. Additionally, the β trends differ between the CMIP6 and reanalysis data, which may be related to the different precipitation (PR) and soil water availability (PR-ET) trends between the models. In the regions of increasing β intensity at high latitudes in the NH, sST is more sensitive to PR and PR-ET. Consequently, increasing PR and PR-ET leads to slower sST changes, potentially making β intensity stronger in CMIP6 models. However, in the reanalysis data, decreases in PR and PR-ET accelerate sST changes, leading to a weakening of the β intensity. A resulting implication is that β, based on high-emission scenarios, shows a stronger trend during 2015–2100, although this trend could potentially be overestimated. The findings contribute to a better understanding of the sensitivity of T to sST and facilitate the assessment of energy exchange between the land surface and the atmosphere in climate models. [ABSTRACT FROM AUTHOR]

With the rapid global warming in recent decades, the Tibetan Plateau (TP) has suffered severe impacts, such as glacier retreat, glacial lake expansion, and permafrost degradation, which threaten the lives and properties of the local and downstream populations. Regional Reanalysis (RR) is vital for TP due to the limitations of observations. In this work, a 62-year (1961–2022) long atmospheric regional reanalysis with spatial resolution of 9 km (convective gray-zone scale) and temporal resolution of 1 hour over the TP (TPRR) was developed using the Weather Research and Forecasting (WRF) model, combined with re-initialization method, spectral nudging (SN), and several optimizations. TPRR is forced by ERA5 at hourly intervals. TPRR outperforms ERA5, realistically capturing climatological characteristics and seasonal variations of precipitation and T2m (air temperature at 2m above ground level). Moreover, TPRR better reproduces the frequency and intensity of precipitation, as well as the diurnal cycle of precipitation. This study also quantifies the wetting trend of 0.0071 mm/year over the TP amid global warming using TPRR. [ABSTRACT FROM AUTHOR]

Radiative Coolers (RCs) represent an emerging technology that has the potential to significantly reduce urban heat and improve indoor/outdoor thermal comfort in the built environment. Broadband and Selective Radiative Coolers (BRCs and SRCs, respectively) are the two main types of RCs that have been proposed for application in the built environment. Being both typically characterized by high solar reflectance, the former emits thermal radiation within the overall infrared spectrum, whilst the latter emits thermal radiation mainly within the Atmospheric Window (AW) waverange. A variety of both types of RCs have been developed and tested in both in‐lab and in‐field experimental campaigns. Yet, all experiments comprise small scale specimens that do not represent real‐life scale components of the built environment. In addition, no meso scale assessments have been performed with respect to the RCs' performance at a city scale. Here, for the first time, the thermo‐optical performance of both BRCs and SRCs is introduced and investigated in a multilayer Urban Canopy Model (UCM) coupled with extended Weather Research and Forecasting model (WRF) and we simulated 20 different scenarios representing the vast majority of urban layouts. The outcomes show that both types of RCs maintain lower surface temperature and air temperature at 2 m height inside the canyon, compared to conventional roofs. In addition, a city scale application of RCs has been found capable of decreasing ambient temperature up to 1.6°C as potentially experienced by pedestrians. [ABSTRACT FROM AUTHOR]

It is well known that a massive demand for thermal comfort has resulted in a sharp rise in energy use for residential space heating and cooling. This article presents numerical simulations of a room coupled with an earth‐to‐air heat exchanger system operating at the climatic condition of 21.2497° N, 81.6050° E for both summer and winter seasons. The present study involves an estimate of monthly variations in soil temperature at different depths and a suitable geometrical arrangement of pipe is proposed. The thermal performance of the earth‐to‐air heat exchanger system in terms of the outlet air temperature and effectiveness has been calculated. It is shown that with an effectiveness of 0.77 in summer and 0.78 in winter, the present EAHE system reduces the ambient air temperature from 38 to 28.2°C in the summer and it rises from 13 to 22.9°C in winter, respectively. Finally, an improvement in the thermal comfort condition of the room exposed to the solar radiation has been examined at different time intervals and different heights of the room. During the summer the room temperature dropped by 4.2°C while in winter it rose by 5.2°C. Furthermore, the environmental effects of system have been evaluated, showing energy savings of 3.90 kWh/day during summer and 4.83 kWh/day during winter leading to a decrease in CO2 emissions of 6.13 kg/day in summer and 7.59 kg/day in winter. [ABSTRACT FROM AUTHOR]

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Coastal marine heatwaves have destructive and lasting impacts on foundational species and are increasing in frequency, duration, and magnitude. High atmospheric temperatures are often associated with marine heatwaves (MHW) which are defined as 5 days of water temperatures above a seasonally varying 90th percentile threshold. In this study, we consider the prevalence of MHW propagation into surficial sediments to cause sediment heatwaves (SHW). Within a shallow, subtidal seagrass meadow in Virginia, USA, sediment temperature was measured at hourly intervals at a depth of 5 cm between June 2020 and October 2022 at the meadow edge and central meadow interior. The observed sediment temperature along with a 29-year record of water temperature and water level was used to develop a sediment temperature model for each location. Modeled sediment temperatures were used to identify sediment heatwaves that may thermally stress belowground seagrass. At both meadow locations, sediment heatwave frequency increased at a rate twice that of MHWs in the average global open ocean, coinciding with a 172% increase in the annual number of SHW days, from 11 to 30 days year−1 between 1994 and 2022. Sediment heatwaves at both meadow locations co-occurred with a MHW 79–81% of the time, with nearly all SHWs having a zero day lag. The top 10% most extreme MHWs and SHWs occurred between November and April when thermal stress to seagrass was unlikely. In June 2015, a SHW co-occurred with an anomalously long duration MHW that was associated with a 90% decline in seagrass from this system, suggesting that SHWs may have contributed to the observed seagrass loss. These results document heatwave propagation across the pelagic-sediment interface which likely occur broadly in shallow systems with impacts to critical coastal ecosystem processes and species dynamics. [ABSTRACT FROM AUTHOR]

The relationship between air temperature and sovereign bond returns is founded on competing paradigms: macroeconomic, behavioral and energy demand‐based. Which of these theoretical mechanisms receives support from data? To answer this, we examined four decades of bond data from 31 countries. Overall, daily temperature positively affects government bond returns. A 10°F rise leads to an increase in sovereign bond returns between 0.22 and 0.85 basis points. We also document evidence of asymmetric and nonlinear price responses to both temperature levels and shocks. Our results survive a battery of robustness checks and lend support to the macroeconomic and behavioral paradigms, albeit not the energy demand‐based view. [ABSTRACT FROM AUTHOR]

While it is commonly understood that air temperature can greatly affect the process of photosynthesis and the growth of higher plants, the impact of root zone temperature (RZT) on plant growth, metabolism, essential elements, as well as key metabolites like chlorophyll and carotenoids, remains an area that necessitates extensive research. Therefore, this study aimed to investigate the impact of raising the RZT on the growth, metabolites, elements, and proteins of red leaf lettuce. Lettuce was hydroponically grown in a plant factory with artificial light at four different air temperatures (17, 22, 27, and 30°C) and two treatments with different RZTs. The RZT was raised 3°C above the air temperature in one group, while it was not in the other group. Increasing the RZT 3°C above the air temperature improved plant growth and metabolites, including carotenoids, ascorbic acids, and chlorophyll, in all four air temperature treatments. Moreover, raising the RZT increased Mg, K, Fe, Cu, Se, Rb, amino acids, and total soluble proteins in the leaf tissue at all four air temperatures. These results showed that raising the RZT by 3°C improved plant productivity and the metabolites of the hydroponic lettuce by enhancing nutrient uptake and activating themetabolism in the roots at all four air temperatures. Overall, this research demonstrates that plant growth and metabolites can be improved simultaneously with an increased RZT relative to air temperature. This study serves as a foundation for future research on optimizing RZT in relation to air temperature. Further recommended studies include investigating the differential effects of multiple RZT variations relative to air temperature for increased optimization, examining the effects of RZT during nighttime versus daytime, and exploring the impact of stem heating. This research has the potential to make a valuable contribution to the ongoing growth and progress of the plant factory industry and fundamental advancements in root zone physiology. Overall, this research demonstrates that plant growth and metabolites can be improved simultaneously with an increased RZT relative to air temperature. This study serves as a foundation for future research on optimizing RZT in relation to air temperature. Further recommended studies include investigating the differential effects of multiple RZT variations relative to air temperature for increased optimization, examining the effects of RZT during nighttime versus daytime, and exploring the impact of stem heating. This research has the potential to make a valuable contribution to the ongoing growth and progress of the plant factory industry and fundamental advancements in root zone physiology. [ABSTRACT FROM AUTHOR]

Land surface temperature anomalies can be linked to changes in local surface energy balance, although the relationship between surface temperature variability and individual radiative processes remains unclear. In this paper, we quantify the contributions of surface radiative effects and non‐radiative heat fluxes to the variance of monthly land surface temperature using European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data and Coupled Model Intercomparison Project Phase 6 simulations. The surface energy budget equation is used to link changes in surface radiation, surface heat fluxes and land surface temperature. Subsequently, surface radiation is decomposed into the radiative effects of clouds, air temperature, surface albedo and relative humidity using radiative kernels. The contributions of these radiative processes, including their coupling effects, are quantified using covariance matrices. The results reveal the air temperature radiative effect to be the most significant contributor to the variability of land surface temperature. In addition, the covariance terms reveal important coupling effects. For example, the contribution from the cloud radiative effect is found to be substantially dampened by its coupling with surface heat fluxes. The air temperature radiative effect is further decomposed into a forcing component and a feedback component using different regression methods, in an attempt to separate the air temperature radiative effect as the driver of the surface temperature variability. The cloud radiative effect becomes the primary contributor to the variance of surface temperature after separating the air temperature feedback, while the contribution of the air temperature radiative forcing remains important. Plain Language Summary: Land surface temperature is critical environmental variable. Through a statistical analysis of the European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data and Coupled Model Intercomparison Project Phase 6 multi‐model simulations, we have explained the land surface temperature variability in relation to the surface energy fluxes. Specifically, we have attributed the variability of monthly surface radiation to the effects of different meteorological variables such as clouds, air temperature, surface albedo and relative humidity. Our findings suggest that the radiative effect of air temperature is the primary contributor to the variance of land surface temperature in most regions, although this effect includes a strong feedback effect of air temperature to surface temperature changes. After separating this feedback effect, the cloud radiative effect becomes the primary contributor. On the other hand, the contribution from cloud radiative effect is significantly counteracted by its coupling with surface heat fluxes. Key Points: The variance of land surface temperature is decomposed to contributions from surface radiative effects and heat fluxesThe radiative effect of air temperature is found to contribute the most to surface temperature variabilityThe cloud radiative effect is found to be the primary contributor after decoupling the air and surface temperature variations [ABSTRACT FROM AUTHOR]

Slovak bentonite was used as an effective natural adsorbent for the removal of Cd(II) and Co(II). Characterization of the samples was conducted using X-ray diffraction (XRD), high-resolution scanning electron microscopy with an X-ray energy dispersion spectrometer (SEM–EDS), and infrared spectroscopy (FT-IR). Adsorption experiments were carried out for pure water and artificial seawater, each containing cobalt and cadmium cations within the concentration range of 5–60 mg/L. The highest bentonite adsorption capacities of the tested bentonites were 23.5 (Cd) and 32.2 (Co) mg g−1. The kinetics data revealed that, in addition to chemisorption, intraparticle diffusion contributes to metal removal. The physical and structural properties of bentonites play an important role in adsorption. Bentonite P 135 from the Lieskovec deposit showed the highest efficiency for removing both ions, with removal percentages exceeding 90% and 77.5% for pure water and artificial seawater, respectively. The results indicate the suitability of using Slovak bentonites as an alternative sorbent for both metal extractions. The mechanism of metal ion adsorption on bentonite clay can be understood through surface complexation and ion exchange. The examined bentonite deposits show potential as promising natural sorbents for the removal of cobalt and cadmium cations from polluted waters. [ABSTRACT FROM AUTHOR]

The coupling between surface ozone (O3) and vegetation significantly influences regional to global climate. O3 uptake by plant stomata inhibits photosynthetic rate and stomatal conductance, impacting evapotranspiration through land surface ecosystems. Using the climate-vegetation-chemistry coupled ModelE2-YIBs model, we assess the global climatic responses to O3-vegetation interactions during boreal summer of 2010s (2005–2014). High O3 pollution reduces stomatal conductance, resulting in the warmer and drier conditions worldwide. The most significant responses are found in the eastern U.S. and eastern China, where local latent heat flux decreases by -8.17 % and -9.48 %, respectively. Consequently, surface air temperature rises by +0.33 °C and +0.56 °C, and sensible heat flux rises by +16.54 % and +25.46 % in the two hotspot regions. The O3-vegetation interaction also affects atmospheric pollutants. Surface O3 concentrations increase by +1.26 ppbv in eastern China and +0.98 ppbv in eastern U.S. due to the O3-induced inhibition of stomatal uptake. With reduced atmospheric stability following the warmer climate, increased cloudiness but decreased relative humidity jointly reduce aerosol optical depth (AOD) over eastern China. This study suggests that vegetation feedback should be considered for a more accurate assessment of climatic perturbations caused by tropospheric O3. [ABSTRACT FROM AUTHOR]

Climate change (CC) threatens Mediterranean viticulture. Rhizospheric microorganisms may be crucial for the adaptation of plants to CC. Our objective was to assess whether the association of two grapevine varieties with arbuscular mycorrhizal fungi (AMF) increases grapevine's resilience to environmental conditions that combine elevated atmospheric CO2, increased air temperatures, and water deficit. Tempranillo (T) and Cabernet Sauvignon (CS) plants, grafted onto R110 rootstocks, either inoculated (+M) or not (−M) with AMF, were grown in temperature-gradient greenhouses under two environmental conditions: (i) current conditions (ca. 400 ppm air CO2 concentration plus ambient air temperature, CATA) and (ii) climate change conditions predicted by the year 2100 (700 ppm of CO2 plus ambient air temperature +4 °C, CETE). From veraison to maturity, for plants of each variety, inoculation treatment and environmental conditions were also subjected to two levels of water availability: full irrigation (WW) or drought cycles (D). Therefore, the number of treatments applied to each grapevine variety was eight, resulting from the combination of two inoculation treatments (+M and −M), two environmental conditions (CATA and CETE), and two water availabilities (WW and D). In both grapevine varieties, early drought decreased leaf conductance and transpiration under both CATA and CETE conditions and more markedly in +M plants. Photosynthesis did not decrease very much, so the instantaneous water use efficiency (WUE) increased, especially in drought +M plants under CETE conditions. The increase in WUE coincided with a lower intercellular-to-atmospheric CO2 concentration ratio and reduced plant hydraulic conductance. In the long term, mycorrhization induced changes in the stomatal anatomy under water deficit and CETE conditions: density increased in T and decreased in CS, with smaller stomata in the latter. Although some responses were genotype-dependent, the interaction of the rootstock with AMF appeared to be a key factor in the acclimation of the grapevine to water deficit under both current and future CO2 and temperature conditions. [ABSTRACT FROM AUTHOR]

Climate change inevitably affects vegetation growth in the Tibetan Plateau (TP). Understanding the dynamics of vegetation phenology and the responses of vegetation phenology to climate change are crucial for evaluating the impacts of climate change on terrestrial ecosystems. Despite many relevant studies conducted in the past, there still remain research gaps concerning the dominant factors that induce changes in the start date of the vegetation growing season (SOS). In this study, the spatial and temporal variations of the SOS were investigated by using a long-term series of the Normalized Difference Vegetation Index (NDVI) spanning from 2001 to 2020, and the response of the SOS to climate change and the predominant climatic factors (air temperature, LST or precipitation) affecting the SOS were explored. The main findings were as follows: the annual mean SOS concentrated on 100 DOY–170 DOY (day of a year), with a delay from east to west. Although the SOS across the entire region exhibited an advancing trend at a rate of 0.261 days/year, there were notable differences in the advancement trends of SOS among different vegetation types. In contrast to the current advancing SOS, the trend of future SOS changes shows a delayed trend. For the impacts of climate change on the SOS, winter Tmax (maximum temperature) played the dominant role in the temporal shifting of spring phenology across the TP, and its effect on SOS was negative, meaning that an increase in winter Tmax led to an earlier SOS. Considering the different conditions required for the growth of various types of vegetation, the leading factor was different for the four vegetation types. This study contributes to the understanding of the mechanism of SOS variation in the TP. [ABSTRACT FROM AUTHOR]

We report on the first multi-year km-scale global coupled simulations using ECMWF's Integrated Forecasting System (IFS) coupled to both the NEMO and FESOM ocean-sea ice models, as part of the Horizon 2020 Next Generation Earth Modelling Systems (nextGEMS) project. We focus mainly on the two unprecedented IFS-FESOM coupled setups, with an atmospheric resolution of 2.8 km and 4.4 km, respectively, and the same spatially varying ocean resolution that reaches locally below 5 km grid-spacing. This is enabled by a refactored ocean model code that allows for more efficient coupled simulations with IFS in a single-executable setup, employing hybrid parallelisation with MPI and OpenMP. A number of shortcomings in the original NWP-focussed model configurations were identified and mitigated over several cycles collaboratively by the modelling centres, academia, and the wider nextGEMS community. The main improvements are (i) better conservation properties of the coupled model system in terms of water and energy balance, which benefit also ECMWF's operational 9 km IFS-NEMO model, (ii) a realistic top-of-the-atmosphere (TOA) radiation balance throughout the year, (iii) improved intense precipitation characteristics, and (iv) eddy-resolving features in large parts of the mid- and high-latitude oceans (finer than 5 km grid-spacing) to resolve mesoscale eddies and sea ice leads. New developments made at ECMWF for a better representation of snow and land use, including a dedicated scheme for urban areas, were also tested on multi-year timescales. We provide first examples of significant advances in the realism and thus opportunities of these km-scale simulations, such as a clear imprint of resolved Arctic sea ice leads on atmospheric temperature, impacts of km-scale urban areas on the diurnal temperature cycle in cities, and better propagation and symmetry characteristics of the Madden-Julian Oscillation. [ABSTRACT FROM AUTHOR]

Detailed observations of the velocities of Jovian vortices exist at only one height in the atmosphere, so their vertical structures are poorly understood. This motivates this study that computes stable three-dimensional, long-lived planetary vortices that satisfy the equations of motion. We solve the anelastic equations with a high-resolution pseudo-spectral method using the observed Jovian atmospheric temperatures and zonal flow. We examine several families of vortices and find that constant-vorticity vortices, which have nearly uniform vorticity as a function of height, and horizontal areas that go to zero at their tops and bottoms, converge to stable vortices that look like the Great Red Spot (GRS) and other Jovian anticyclones. In contrast, the constant-area vortices proposed in previous studies, which have nearly uniform areas as a function of height, and vertical vorticities that go to zero at their tops and bottoms, are far from equilibrium, break apart, and converge to constant-vorticity vortices. Our late-time vortices show unexpected properties. Vortices that are initially non-hollow become hollow (i.e. have local minima of vertical vorticity at their centres), which is a feature of the GRS that cannot be explained with two-dimensional simulations. The central axes of the final vortices align with the planetary spin axis even if they align initially with the local direction of gravity. We present scaling laws for how vortex properties change with the Rossby number and other non-dimensional parameters. We prove analytically that the horizontal mid-plane of a stable vortex must lie at a height above the top of the convective zone. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) gained increased attention in cryospheric research. While various global satellite LST products are available, none of them is specially designed for the Pan-Arctic region. Based on the recently published EUMETSAT Advanced Very High Resolution Radiometer (AVHRR) fundamental data record (FDR), a new LST product (1981–2021) with daily resolution is developed for the Pan-Arctic region. Validation shows good accuracy with an average mean absolute error (MAE) of 1.71 K and a MAE range of 0.62–3.07 K against in situ LST data from the Surface Radiation Budget Network (SURFRAD) and Karlsruhe Institute of Technology (KIT) sites. Long-term stability, a strong requirement for trend analysis, is assessed by comparing LST with air temperatures from ERA5-Land (T2M) and air temperature data from the EUSTACE (www.eustaceproject.org) global station dataset. Long-term stability might not be fulfilled mainly due to the orbit drift of the NOAA satellites. Therefore, the analysis is split into two periods: the arctic winter months, which are unaffected by solar illumination and, therefore, orbital drift, and the summer months. The analysis for the winter months results in correlation values (r) of 0.44–0.83, whereas for the summer months (r) ranges between 0.37–0.84. Analysis of anomaly differences revealed instabilities for the summer months at a few stations. The same stability analysis for the winter months revealed only one station with instabilities in comparison to station air temperature. Discrepancies between the temperature anomalies recorded at the stations and ERA5-Land T2M were also found. This highlights the limited influence of orbital drift on the LST product, with the winter months presenting good stability across all stations, which makes these data a valuable source for studying LST changes in the Pan-Arctic region over the last 40 years. This study concludes by presenting LST trend maps (1981–2021) for the entire region, revealing distinct warming and cooling patterns. [ABSTRACT FROM AUTHOR]

Introduction: The components of nighttime sap flux (En), which include transpiration (Qn) and stem water recharge (Rn), play important roles in water balance and drought adaptation in plant communities in water-limited regions. However, the quantitative and controlling factors of En components are unclear. Methods: This study used the heat balance method to measure sap flow density in Vitex negundo on the Loess Plateau for a normal precipitation year (2021) and a wetter year (2022). Results: The results showed that the mean values were 1.04 and 2.34 g h-1 cm-2 for Qn, 0.19 and 0.45 g h-1 cm-2 for Rn in 2021 and 2022, respectively, and both variables were greater in the wetter year. The mean contributions of Qn to En were 79.76% and 83.91% in 2021 and 2022, respectively, indicating that the En was mostly used for Qn. Although the vapor pressure deficit (VPD), air temperature (Ta) and soil water content (SWC) were significantly correlated with Qn and Rn on an hourly time scale, they explained a small fraction of the variance in Qn on a daily time scale. The main driving factor was SWC between 40-200 cm on a monthly time scale for the Qn and Rn variations. Rn was little affected by meteorological and SWC factors on a daily scale. During the diurnal course, Qn and Rn initially both declined after sundown because of decreasing VPD and Ta, and Qn was significantly greater than Rn, whereas the two variables increased when VPD was nearly zero and Ta decreased, and Rn was greater than Qn. Discussion: These results provided a new understanding of ecophysiological responses and adaptation of V. negundo plantations to increasing drought severity and duration under climate changes. [ABSTRACT FROM AUTHOR]

The Barents Sea is experiencing large trends in sea ice decline and increasing surface temperatures while at the same time, it is a key region of weather variability in the Arctic and therefore predestined for the occurrence of surface weather extremes. In this study, we identify extreme winter seasons in the Barents Sea, based on a multivariate method, as winters with large seasonal-mean anomalies in one or several surface parameters encompassing surface temperature, precipitation, surface heat fluxes and surface net radiation. Using large-ensemble climate model data for historical (S2000) and end-of-century (S2100) projections following a RCP8.5 emission scenario, we find distinct clusters of extreme winters that are characterized by similar combinations of anomalies in these key surface weather parameters. In particular, we find that, during extreme winters, seasonal-mean anomalies in surface temperature are usually spatially extended with a maximum over sea ice in S2000 simulations, which shifts towards the continental land masses in a warmer climate, as the formation of a warm or cold air reservoir is being hampered by the increasing area of open ocean. Several extreme winters are selected for a detailed investigation of their substructure focusing on the relative importance of anomalies in the occurrence of synoptic-scale weather systems and anomalous surface boundary conditions for the formation of such seasons. Large combined anomalies in the key surface parameters result mainly from the accumulation of recurrent short-term events that are linked to distinct patterns of anomalous frequencies in cyclones, anticyclones and cold air outbreaks. While large seasonal-mean anomalies in surface air temperature can be linked to large-scale patterns facilitating the horizontal advection of relatively warmer (colder) air, which coincides with a lack (surplus) of cold air outbreaks, precipitation anomalies are characterized by local anomalies in cyclone and anticyclone frequency. Additionally, anomalous surface boundary conditions – that is sea ice concentration and sea surface temperatures – facilitate the formation of persistent anomalous surface conditions or further enhance atmospherically driven anomalies due to anomalous surface heat fluxes. In a warmer climate, we find extreme winters with similar substructures as in S2000. However, the increasing distance of the Barents Sea to the sea ice edge causes a decreasing magnitude in seasonal-mean anomalies of surface air temperatures and the atmospheric components of the surface energy balance. A decrease in the variability of both sea ice and sea surface temperatures indicates a decreasing importance in anomalous surface boundary conditions for the formation of future extreme winters in the Barents Sea, while the robust link shown for surface weather systems persists in a warmer climate. [ABSTRACT FROM AUTHOR]

Evapotranspiration is the key and predominant component of the water balance in wetlands. Direct evapotranspiration measurements are challenging in wetlands due to their remoteness and high surface water level. This article describes the actual (ETa and reference evapotranspiration (ET0) from a cultivated wet meadow located in the Biebrza National Park - the largest national park in north-east Poland, Central Europe. The data were sourced from a micrometeorological station equipped with an eddy covariance system to measure heat and vapour fluxes and such meteorological elements as radiation balance components, air temperature and humidity. The values of directly measured ETa were presented daily in the context of available energy and ET0. Daily sums of ETa ranged from below 0.2 mm in winter to 6.5 mm in summer. The share of daily sums of ETa in the ET0 usually ranged from 50 to 60%, with extreme values from 10 to 170%. Aside from giving more insight into Biebrza wetlands' functioning, the actual data produced in this study may be used instead of indirect methods, which were used the most in modelling wetlands areas. [ABSTRACT FROM AUTHOR]

A five-year of monitoring (2018-2022) of the loggerhead sea turtle Caretta caretta nests in "Pozzolana di Ponente" beach on Linosa Island (Pelagie Archipelago, Italy) is here reported. To explore how temperatures affect the hatching success and the possible occurrence of any malformation in hatchlings, incubation temperature values were recorded using data loggers positioned at depths of 5 and 35 cm (for each nest) from the surface, approximately 0.5 m from the nest chamber. The obtained results highlighted important issues related to the success of hatching and the incidence of body anomalies. The temperatures recorded at different depths near the nests (5 and 35 cm) in some periods of incubation of the eggs were above optimal development temperature (i.e., ~33°C), causing high mortality rates, especially during the first two years of the survey (2018-2019). In the next three years (2020-2022), the implementation of shading cover cloths of the nests increased the survival rate and decreased the incidence of malformed individuals. Furthermore, atmospheric temperature data were extrapolated from the "Copernicus Climate Change" web service and included in our analyses to assess any changes over the timeframe analysed. Over five years (2018-2022), the average atmospheric temperature increased slightly by 1.7°C. In light of global warming, the implementation of effective and low-cost mitigation activities, such as the use of shade cloth covers to protect the nests from overheating, should be considered a suitable conservation action. [ABSTRACT FROM AUTHOR]

Slushflows are rapid mass movements of water-saturated snow. They release in gently sloping locations (<30 °) and are hence not restricted to steep slopes. Slushflows are observed worldwide in areas with seasonal snow cover and pose a significant natural hazard in Norway. Hazard prediction and early warning are therefore crucial to prevent casualties and damage to infrastructure. A regional early warning for slushflow hazard was established in Norway in 2013–2014 as the first of its kind in the world. It has been operational since then. Four main variables are central in the methodology used: ground conditions, snow properties, air temperature, and water supply to snow. Gridded forecasting model simulations in the decision-making tool Varsom Xgeo, real-time data from automatic stations, and field observations from the field are assessed. Based on data from historical slushflows, a water supply–snow depth by snow type ratio has been developed as an assessment tool. This approach can be implemented in other areas with slushflow hazard where the necessary input data are available. [ABSTRACT FROM AUTHOR]

Soil temperature plays a critical role in many soil functions, particularly in arid ecosystems, but is scarcely reported as potential indicator of climate change. Although studies have been conducted worldwide to investigate (both measurements and modeling) temperature changes in the soil profile in response to ambient temperature, no information on soil temperature is available in the state of Kuwait. Hydrological and many bio-geochemical processes are more sensitive to soil temperature than air temperature. In this study, we used observed soil temperature data (2007–2016) from three sites with three soil depth increments (5, 50, 100 cm) and compared to regional climate and regression models' output. The most salient finding of this study is the tight association between observed and simulated soil temperature at shallower soil depths from both the regional climate model (RegCM4) and linear regression model. The RegCM4 model poorly predicted (underestimated) soil temperature at deeper soil layers relative to shallower soil layers. Application of the linear scaling (LS) method has significantly improved the RegCM4 model performance with respect to measured soil temperature, which allows an accurate evaluation of the impact of climate change on the soil temperature under different soil management systems. These findings indicate that RegCM4 can be applied as a reliable predictor of soil temperature under arid ecosystems for which there is a gap in site data availability. [ABSTRACT FROM AUTHOR]

Fine-resolution spatio-temporal maps of near-surface urban air temperature (Ta) provide crucial data inputs for sustainable urban decision-making, personal heat exposure, and climate-relevant epidemiological studies. The recent availability of IoT weather station data allows for high-resolution urban Ta mapping using approaches such as interpolation techniques or machine learning (ML). This study is aimed at executing these approaches and traditional numerical modeling within a practical and operational framework and evaluate their practicality and efficiency in cases where data availability, computational constraints, or specialized expertise pose challenges. We employ Netatmo crowd-sourced weather station data and three geospatial mapping approaches: (1) Ordinary Kriging, (2) statistical ML model (using predictors primarily derived from Earth Observation Data), and (3) weather research and forecasting model (WRF) to predict/map daily Ta at nearly 1-km spatial resolution in Warsaw (Poland) for June–September and compare the predictions against observations from 5 meteorological reference stations. The results reveal that ML can serve as a viable alternative approach to traditional kriging and numerical simulation, characterized by reduced complexity and higher computational speeds within the domain of urban meteorological studies (overall RMSE = 1.06 °C and R2 = 0.94, compared to ground-based meteorological stations). The results have implications for identifying the urban regions vulnerable to overheating and evidence-based urban management in response to climate change. Due to the open-sourced nature of the applied predictors and input parsimony, the ML method can be easily replicated for other EU cities. [ABSTRACT FROM AUTHOR]

The water resources of the Third Pole (TP), highly sensitive to climate change and glacier melting, significantly impact the water and food security of millions in Asia. However, projecting future spatial‐temporal runoff changes for TP's mountainous basins remains a formidable challenge. Here, we've leveraged the long short‐term memory model (LSTM) to craft a grid‐scale artificial intelligence (AI) model named LSTM‐grid. This model has enabled the production of hydrological projections for the seven major river basins of TP. The LSTM‐grid model integrates monthly precipitation, air temperature, and total glacier mass changes (total_GMC) data at a 0.25‐degree model grid. Training the LSTM‐grid model employed gridded historical monthly runoff and evapotranspiration data sets generated by an observation‐constrained cryosphere‐hydrology model at the headwaters of seven TP river basins during 2000–2017. Our results demonstrate the LSTM grid's effectiveness and usefulness, exhibiting a Nash‐Sutcliffe Efficiency coefficient exceeding 0.92 during the verification periods (2013–2017). Moreover, river basins in the monsoon region exhibited a higher rate of runoff increase compared to those in the westerlies region. Intra‐annual projections indicated notable increases in spring runoff, especially in basins where glacier meltwater significantly contributes to runoff. Additionally, the LSTM‐grid model aptly captures the runoff changes before and after the turning points of glacier melting, highlighting the growing influence of precipitation on runoff after reaching the maximum total_GMC. Therefore, the LSTM‐grid model offers a fresh perspective for understanding the spatiotemporal distribution of water resources in high‐mountain glacial regions by tapping into AI's potential to drive scientific discovery and provide reliable data. Plain Language Summary: Water resources of the Third Pole (TP) significantly impact the water and food security in Asia. However, projecting future spatial‐temporal runoff changes for the TP's mountain basins remains a challenge. Here, we've leveraged the long short‐term memory (LSTM) model to craft a gridded artificial intelligence model (named LSTM‐grid). Trained by the outputs of an observation‐constrained distributed cryosphere‐hydrology model, the LSTM‐grid has enabled reliable spatiotemporal runoff and evapotranspiration projections for the headwaters of seven TP rivers (Yellow, Yangtze, Mekong, Salween, Brahmaputra, Ganges, Indus) till 2100. Our projections show that the river basins in the monsoon region exhibit a higher rate of runoff increase compared to those in the westerlies region. In particular, the proposed approach in this study can reasonably capture the runoff changes before and after the turning points of glacier melting without prior knowledge, highlighting the growing influence of precipitation on runoff after reaching the maximum total glacier mass changes (of a river basin). Hence, the LSTM‐grid model provides a fresh perspective for understanding the spatiotemporal distribution of water resources in high‐mountain glacial regions. Key Points: We use artificial intelligence and an observation‐constrained cryosphere‐hydrology model to project future runoff for seven high‐mountain Third Pole basinsResults show that river basins in the monsoon region exhibited a higher rate of runoff increase compared to those in the westerlies regionThe proposed approach can aptly simulate runoff changes before and after the turning points of glacier melting without prior knowledge [ABSTRACT FROM AUTHOR]

Water quality and freshwater ecosystems are affected by river discharge and temperature. Models are frequently used to estimate river temperature on large spatial and temporal scales due to limited observations of discharge and temperature. In this study, we use physically based river routing and temperature models to simulate daily discharge and river temperature for rivers in 138 basins in Alaska, including the entire Yukon River basin, from 1990–2021. The river temperature model was optimized for ice free months using a surrogate‐based model optimization method, improving model performance at uncalibrated river gages. A common statistical model relating local air and water temperature was used as a benchmark. The physically based river temperature model exhibited superior performance compared to the benchmark statistical model after optimization, suggesting river temperature model optimization could become more routine. The river temperature model demonstrated high sensitivity to air temperature and model parameterization, and lower sensitivity to discharge. Validation of the models showed a Kling‐Gupta Efficiency of 0.46 for daily river discharge and a root mean square error of 2.04°C for daily river temperature, improving on the non‐optimized physical model and the benchmark statistical model, which had root mean square errors of 3.24 and 2.97°C, respectively. The simulation shows that rivers in northern Alaska have higher maximum summer temperatures and more variability than rivers in the Central and Southern regions. Furthermore, this framework can be readily adapted for use across models and regions. Plain Language Summary: Accurate data on the volume and temperature of river water are essential for understanding how changing river conditions affect water quality and freshwater ecosystems. However, direct measurements of river parameters are often lacking, leading researchers to rely on models for estimation. In this study, we utilized advanced models and techniques to compute daily water volume and temperature in 138 basins across Alaska, including the entirety of the Yukon River basin, spanning from 1990 to 2021. Our findings indicated that rivers in northern Alaska exhibited higher maximum summer water temperatures and more significant temperature fluctuations compared to those in the central and southern regions. Our analysis highlighted that adjusting air temperature and the model's internal variables were crucial in minimizing errors in river temperature prediction. We improved the accuracy of the river temperature model by applying a technique to refine the model output based on the limited available river measurements. Comparing our enhanced model to a simpler statistical approach, we observed superior performance once the necessary adjustments were implemented. Key Points: Our model system produced an accurate, high‐resolution, daily hindcast of Alaskan river temperature and discharge from 1990 to 2021We increased model performance by employing a new optimization of the River Basin Model and forcing it with a climate‐land surface modelA sensitivity analysis highlights important drivers of river temperatures in each region and the need for optimization [ABSTRACT FROM AUTHOR]

This paper illustrates an experimental activity for the closed-loop position control of an actuator made using shape memory alloy (SMA) wire. A solution with the self-sensing effect was implemented to miniaturize the systems, i.e., without external sensors. A proportional control algorithm was initially used, demonstrating the idea's feasibility; the wire can behave simultaneously as an actuator and sensor. An experimental investigation was subsequently conducted for the optimization of the developed actuator. As for the material, a Flexinol wire, Ni-Ti alloy, with a diameter of 0.150 mm and a length of 200 mm, was used. Preliminarily, characterization of the SMA wire at constant and variable loads was carried out; the characteristics detected were elongation vs. electric current and elongation vs. electrical resistance. The control system is PC based with a data acquisition card (DAQ). A drive board was designed and built to read the wire's electrical resistance and power it by pulse width modulation (PWM). A notable result is that the actuator works with good precision and in dynamic conditions, even when it is called to support a load up to 65% different from that for which the electrical resistance–length correlation has previously been experimentally obtained, on which the control is based. This opens up the possibility of using the actuator in a counteracting configuration with a spring, which makes hardware implementation and control management simple. [ABSTRACT FROM AUTHOR]

The construction sector, including in developed countries, plays a notable part in the overall energy consumption worldwide, being responsible for 40% of it. In addition to this, heating, ventilating and air-conditioning (HVAC) systems constitute the largest share in this sector, accounting for 40% of energy usage in construction and 16% globally. To address this, stringent rules and performance measures are essential to reduce energy consumption. This study focuses on mathematical optimisation modelling to enhance the performance of indirect-contact evaporative cooling systems (ICESs), a topic with a significant gap in the literature. This modelling is highly comprehensive, covering various aspects: (1) analysing the impact of the water-spraying unit (WSU) size, working air (WA) velocity and hydraulic diameter (Dh) on the evaporated water vapour (EWV) amount; (2) evaluating temperature and humidity distribution for a range of temperatures without considering humidity at the outlet of the WSU, (3) presenting theoretical calculations of outdoor temperature (Tout) and humidity with a constant WSU size and air mass flow rate (MFR), (4) examining the combined effect of the WA MFR and relative humidity (ϕ) on Tout and (5) investigating how Tout influences the indoor environment's humidity. The study incorporates an extensive optimisation analysis. The findings indicate that the model could contribute to the development of future low-carbon houses, considering factors such as the impact of Tout on indoor ϕ, the importance of low air velocity for achieving a low air temperature, the positive effects of Dh on outdoor air and the necessity of a WSU with a size of at least 8 m for adiabatic saturation. [ABSTRACT FROM AUTHOR]

We report room temperature heterodyne detection of a quantum cascade laser beaten with a local oscillator on a unipolar quantum photodetector in two different atmospheric windows, at 4.8 µm and 9 µm. A noise equivalent power of few pW is measured by employing an active stabilization technique in which the local oscillator and the signal are locked in phase. The measured heterodyne noise equivalent power is six orders of magnitude lower than that obtained with direct detection. [ABSTRACT FROM AUTHOR]

The accuracy of Land Surface Temperature (LST) products retrieved from satellite data in mountainous-coastal areas is not well understood. This study presents an analysis of the spatial and temporal variability of the differences between the LST and in situ observed air and surface temperatures (ISTs) for the southeastern slope of Lake Baikal's surroundings. The IST was measured at 12 ground observation sites located on the southeastern macro-slope of the Primorskiy Ridge (Baikal, Russia) within an elevation range of 460–1656 m above sea level from 2009 to 2021. LST was estimated using 617 Landsat (7 and 8) images from 2009–2021, taking into account brightness temperature, surface emissivity and vegetation cover fraction. The comparison of the LST from satellite data and the IST from ground observation showed relatively high differences, which varied depending on the season and site type. A neural network was suggested and calibrated to improve the LST data. The corrected remote-sensed temperature was found to reproduce the IST very well, with mean differences of about 0.03 °C and linear correlation coefficients of 0.98 and 0.95 for the air and surface IST. [ABSTRACT FROM AUTHOR]

In order to study the improvement of the mechanical properties of basalt fiber geogrids on semi-rigid base asphalt pavement and the prevention and control effect of reflection cracks, this paper laid the basalt fiber geogrid and test sensor in the different positions of the semi-rigid base of Yanchong Expressway experimental Sect. (625 m long) are divided into three working conditions: I, II, and III according to different reinforcement levels. Through the test, the temperature and strain at the corresponding positions of the top and bottom of the semi-rigid base course change with time, and the crack performance of the basalt fiber geogrid-reinforced semi-rigid base course is analyzed under the action of temperature and the linear regression equations between the temperature and the strain of the base course. Atmospheric temperature between substrate strain and substrate temperature is obtained. The field test results show that adding basalt fiber geogrid to the semi-rigid base can prevent reflection cracks and improve the anti-crack performance of the semi-rigid asphalt pavement, the best anti-crack effect in the middle position of the semi-rigid base. [ABSTRACT FROM AUTHOR]