Search

Most pest phenology models are temperature dependent. Generally, the air temperature at reference height is used to predict pest development, but the air temperature varies between inside and outside the crop canopy, where pests reside. Here, we sampled 3 rice planthopper species—Nilaparvata lugens (Stål), Sogatella furcifera (Horváth), and Laodelphax striatellus (Fallén)—and micrometeorological observations in paddy fields to analyze how thermal environments inside the canopy affect pest development. Seasonal variations in the population density of these species were surveyed in 3 experimental fields with 2 water temperature plots (normal and low-water temperature plots).The development periods of the 3 species were predicted individually based on pest phenology models using temperatures recorded at 6 heights (0.0–2.0 m). We calculated the root mean square error (RMSE) values from the predicted and observed development periods for each rice planthopper. The development prediction using the temperature inside the canopy was more accurate than that utilizing the temperature at the reference height (2.0 m). In the low-water temperature plot, the RMSE value for N. lugens, S. furcifera, and L. striatellus was 6.4, 5.6, and 4.1 when using the temperature at the reference height (2.0 m), respectively, and 2.8, 3.8, and 2.9 when employing the temperature inside the canopy at 0.25 m, respectively. The development prediction utilizing the air temperature at the bottom (0.25 m) of canopy, where N. lugens resides, was most effective for N. lugens among the 3 species. These findings suggest the importance of utilizing microhabitat-based temperatures to predict pest development. [ABSTRACT FROM AUTHOR]

Overcooled talus slopes are generally described as islands of sporadic permafrost below the lower alpine limit of permafrost. The negative thermal anomaly of the ground is mainly consecutive to the internal ventilation of the deposit, but it is also conditioned by multiple factors as topography, slope aspect and incline, openwork structure and coarseness of the deposit, air temperature, solar radiation and wind regime. Therefore, the study of the spatiotemporal dynamics of ventilation processes allows a better understanding of the phenomenon. At Cannon Cliff, New Hampshire (USA), several field visits and environmental monitoring allowed us to describe the varying nature and significance of the ventilation mechanisms that can be observed at the ground surface and associated with both the intensity and direction of the airflows in a talus debris accumulation/protalus rampart system. The thermal negative anomalies are strong enough to lower the ground temperature to the point of preserving ice during the late spring and summer seasons. The monitoring of the gradient between external (air) and internal (talus) temperatures coupled with several dendroecological and geomorphological analyses provided a complete environmental picture of the impacts, feedback and extent of the phenomenon. [ABSTRACT FROM AUTHOR]

There are few studies on the climate and glacial scale in the mountains east of the Qinghai–Tibet Plateau. So, we used glacial features to determine the range of the area's paleoglaciers and the equilibrium line altitude (ELA) of theGlA modern and paleoglaciers in the Tianchi area of the Changbai Mountains. Then, the GlaRe toolbox 2015 () was used to reconstruct the surface of the paleoglaciers. The probable air temperature during the glacial advances of the LGM was calculated by applying the P-T and LR models. The results showed the following: (1) the change in ELA is 950 m in the Tianchi area of the Changbai Mountains; (2) glacial coverage in the Tianchi area of the Changbai Mountains during the LGM period was ~27.05 km2 and the glacial volume was ~9.94 km3; and (3) the mean temperature in the Tianchi area of the Changbai Mountains during the LGM was 6.6–9.0 °C lower than today's, and was the principal factor controlling the growth of glaciers. There is a difference in the climate change in monsoon-influenced mountains during the LGM, and this difference may be related to the precipitation in the mountains. [ABSTRACT FROM AUTHOR]

The climatic warming-induced shrinking of permafrost currently encompasses 65% of alpine areas in North China, where a large population relies on its water and land resources. With increasing recognition of the economic and ecological impacts of permafrost basins, forecasts of environmental vulnerability have gained prominence. However, the links between permafrost and winter water resources remain inadequately explored, with most studies focusing on in-situ measurements related to snow cover and frozen layer thickness. Evaluating more complex phenomena, such as the magnitude and persistence of air temperature or low streamflow, depends on numerous climate-driven factors interacting through various subsurface flow mechanisms, basin drainage mechanics, and hydro-climatic correlations at a macroscale. The present study focuses on winter warming, flow increases, and their teleconnections in Xinjiang, China. The research analyzes their links to the atmospheric cycle of the Siberian High (SH) using long-term data spanning 55 years from two large alpine permafrost basins. Changes in variability and correlation persistence were explored for the past decades, and significant variability and connections were constructed using statistical correlation. The years 1980 and 1990 were a turning point when both winter temperatures and winter river flow began to exhibit a notable and consistent upward trend. Subsequently, the period from the mid-1990s to 2013 was characterized by high variability and persistence in these trends. The influence of the SH plays a dominant role in regard to both winter temperatures and river flow, and these variabilities and correlations can be utilized to estimate and predict winter flow in ungauged permafrost rivers in Xinjiang China. [ABSTRACT FROM AUTHOR]

Climate change, which causes significant structural transformations of ecosystems, is becoming one of the most acute environmental problems of our time. Monitoring observations in protected areas, where anthropogenic impacts are minimal, reflect the effect of climate on natural communities. We have studied the change in the structure of summer phytoplankton in Lake Raifskoe (Volga-Kama Nature Reserve) for more than 20 years, as well as the relationship of these changes with environmental factors. This study has shown an increase in the proportion of dinophyte algae in the total biomass of summer phytoplankton in the lake, which is located in the forest zone. This change is more typical for the structure of lake communities in the forest-steppe zone. The leading role in the change in the structure of phytoplankton is played by climate, the air temperature of the warmest month (July) in particular. No effect of climate humidity (precipitation) on the phytoplankton community has been revealed. Our data show that current climate changes lead to rearrangements of phytoplankton communities, as a result of which the biomass structure of summer phytoplankton in the studied lake located in the forest zone of the Middle Volga region can acquire features of the structure of lake communities of the forest-steppe zone. [ABSTRACT FROM AUTHOR]

Lake ice phenology plays a critical role in determining the hydrological and biogeochemical dynamics of the catchment and regional climate. Lakes with complex shorelines and abundant aquatic vegetation are challenging for lake ice phenology retrieval using remote sensing data, primarily due to mixed pixels containing plants, land and ice. To tackle this challenge, a new double-threshold moving t test (DMTT) algorithm, utilizing multisource satellite-derived brightness temperature data at a 3.125-km resolution and long-term weather data, was introduced to capture Lake Ulansu's ice phenology from 1979 to 2023. Compared to the previous moving t test algorithm, the new DMTT algorithm employs air temperature time series to assist in determining abrupt change points and uses two distinct thresholds to calculate the freeze-up start (FUS) and break-up end (BUE) dates. This method improved the detection of ice information effectively for the mixed pixels. Furthermore, we extended Lake Ulansu's ice phenology detection backward to 1941 using a random forest (RF) model. The reconstructed ice phenology from 1941 to 2023 indicated that Lake Ulansu had average FUS and BUE dates of November 15 ± 5 and March 25 ± 6, respectively, with an average ice cover duration of 130 ± 8 days. Air temperature was the primary impact factor, accounting for 56.5 % and 67.3 % of the variations in the FUS and BUE dates, respectively. We reconstructed, for the first time, the longest ice phenology over a large shallow lake with complex surface cover. We argue DMTT can effectively be applied to retrieve lake ice phenology for this type of lake that have not been fully explored worldwide. [ABSTRACT FROM AUTHOR]

Liquid-phase diffusion bonding was performed in air at a bonding temperature of 400 °C, a bonding pressure of 20 MPa, and a heat holding time of 15 min. The specimens for liquid-phase diffusion bonding were AC2C and ADC12, aluminum alloy for casting. After liquid-phase diffusion bonding, solution annealing and aging treatments were also performed on the joints. As a result, the joint strength was improved by about 2 times and the joint efficiency was 90% by using the 3-layer insert material as compared with the Zn single-layer insert material. This was because the Si concentration in the liquid phase decreased by using the 3-layer insert material and Si was discharged to the outer circumference of the joint. By using the 3-layer insert material, the interfacial fracture factor after T6 heat treatment changed from Si particles to Mg oxides. [ABSTRACT FROM AUTHOR]

Coffee production has a large share in Brazilian agribusiness and a cultural and social importance in the country. Worldwide, Brazil is the largest producer of arabica coffee and the second largest of canephora species. In 2020, national production was 14.3 million bags of canephora coffee. Few studies on canephora coffee adaptation to climate changes can be found in the literature. Thus, our goal was to identify areas suitable for Coffea canephora cultivation in Brazil under CMIP-5 climate change framework. The study was carried out for the entire country using data on average air temperature data for the entire year, November, and the coldest month, as well as average annual accumulated water deficit for the period of 1960–2020. These data were gathered from the Meteorological Database for Teaching and Research (BDMEP) of the National Institute of Meteorology of Brazil-INMET (Brazil 1992). Furthermore, BCC-CSM1.1 climate model was used at 125 × 125 km resolution to simulate future climate using WorldClim 2 data for 2041–2080, in the Representative Concentration Pathway (RCP) scenarios 2.6, 4.5, 6.0, and 8.5. Potential climate changes can negatively impact canephora coffee plantations in all CMIP5 RCP scenarios studied. The BCC-CSM1.1 scenarios showed a 65% reduction in total areas suitable for coffee cultivation in Brazil. Rondônia and Bahia were states with the greatest impact of climate change since they had the largest reduction in areas suitable for canephora coffee growth. Currently, both states are major C. canephora producers and can therefore directly compromise regional economy. Thermal excess was the most common class for future scenarios, averaging 56.76% of the entire country. [ABSTRACT FROM AUTHOR]

An attractive candidate to reduce dependence on fossil fuels and replace them by renewable sources is represented by concentrated solar power (CSP) technology, whose wide deployment is still hindered by its high investment costs. In CSP linear collector plants, a key component with high technological content may be identified in receiver tubes, that are traversed by heat transfer fluid and located on focal line on which solar radiation is concentrated by mirrors. The proposed work aims at developing spectrally selective coatings for receiver tubes able to overcome state‐of‐the‐art technological limitation in terms of both vacuum encapsulation and maximum operative temperature, currently limited at 550°C for molten salts CSP plants. To this aim, a multilayer structure was designed and developed for coating a receiver tube to be employed in open‐air environment at temperature of 600°C. The multilayer coating is based on tungsten chromium titanium infrared reflector and includes a solar absorber layer developed with two alternative methods of reactive sputtering and thermal oxidation respectively, finally covered by antireflective and barrier bi‐layer of aluminum oxide and silica. Thermal stability was demonstrated of the new developed coatings, since only small variations were measured of the optical parameters after more than 2000 h of aging in open air conditions at temperature of 600°C (on average less than 5%), with final measured solar absorptance αs of 73% and 87% and thermal emissivity εth at 600°C of 18% and 27% for aged multilayer structures including the absorber layer obtained through thermal oxidation and sputtering process, respectively. These results pave the way for further improvement in terms of both optical performance and operative temperature increase, allowing to enhance efficiency and lower costs, thus contributing to ease to deployment of CSP technology. [ABSTRACT FROM AUTHOR]

There is little empirical data in the published literature on occupant thermal comfort in buildings from the Modern Movement in architecture. We present a field survey of occupant thermal comfort and indoor environmental conditions in Mies van der Rohe's modern S. R. Crown Hall (1956) on the campus of Illinois Institute of Technology in Chicago, IL. Surveys were deployed to 557 student participants on four separate days, including two days in the cooling season and two days in the heating season, to assess their perceptions of thermal comfort throughout the space. Indoor air temperature, relative humidity and mean radiant temperature were measured concurrently in several locations throughout the space. Occupants reported high levels of dissatisfaction with comfort in the space (percent dissatisfied ranging 37%–54%), with somewhat counterintuitive results for this building type. Overcooling was apparent during warm weather and a combination of both over- and under-heating occurred during cold weather, contrary to what was expected in this building with a high thermal transmittance enclosure. There was also high spatial variability in comfort responses and measured indoor environmental conditions. Findings highlight the need to develop contextual approaches to meeting occupant comfort needs in this building while preserving architectural aesthetics/intent. [ABSTRACT FROM AUTHOR]

The configuration of balconies can affect the indoor environmental performance of dwellings, but there is not enough knowledge regarding how a balcony simultaneously impacts all the parameters of indoor environmental quality (IEQ). Therefore, this study aims to evaluate, for the first time, the impacts of different balcony configurations on IEQ. A comprehensive in-situ campaign was carried out on ten balconies and their contiguous rooms in a building in Porto. Air temperature, relative humidity, CO2, PM2.5 and TVOCs concentration, illuminance and sound pressure level were simultaneously monitored. The results show that an open balcony has a positive impact on hygrothermal conditions, controlled daylight illuminance, and reduced traffic noise by up to 10 dBa. The presence of a glazed balcony improved hygrothermal conditions in winter and increased the noise reduction by up to 15 dBA, but caused a reduction in the daylight of up to 64%. The rooms, in which the balcony was eliminated presented the worst hygrothermal conditions, lost the benefits of noise reduction and had an increase in daylight illuminance of up to 136%. It was also found that the impacts are interrelated and that a balcony influences the occupants' behaviour by enhancing window opening. [ABSTRACT FROM AUTHOR]

Development models are used to quantify the dynamics and rate of initial development, the seedling phase duration, and global warming impacts on forest species. Such models relate the physiological age of the plant, through air temperature functions, to its morphological appearance, given by the cumulative leaf number on the main stem. Despite their potential, studies on initial development dynamics are still scarce, especially for native forest species. Thus, this study calibrated and evaluated the performance of two development models—Phyllochron and Wang and Engel—in estimating the cumulative leaf number and seedling phase duration of two Brazilian native forest species— Cybistax antisyphilitica (Mart.) Mart. (Bignoniaceae) and Platycyamus regnellii Benth. (Fabaceae). Cumulative leaf number and seedling phase duration data from outdoor experiments carried out during the 2017 and 2018 growing seasons with 12 sowing dates in Itajubá, Minas Gerais, Brazil, were used. These experiments provided a rich dataset for calibrating and evaluating the Phyllochron and Wang and Engel development models. Both development models were capable of predicting cumulative leaf number with low and acceptable errors for both species and produced less accurate estimates for seedling phase duration. For C. antisyphilitica , both models were remarkably similar in estimating cumulative leaf number and seedling phase duration, with a root-mean-square error of 3.3 leaves and 25 days, respectively. For P. regnellii , the Wang and Engel model was slightly better than the Phyllochron, with an error of fewer than 2.06 leaves and 13.1 days. Using the coefficients calibrated in this study and, preferably, the Wang and Engel model, it is possible to project the development of both forest species under climate change scenarios. [ABSTRACT FROM AUTHOR]

This study's object is an energy efficiency of residential sector. The work is aimed at solving the task to improve the energy efficiency of the housing sector by devising technical solutions for monitoring and managing energy consumption and microclimate parameters of buildings. The proposed proactive management system for residential buildings consists of multi-sensors measuring CO2, temperature and humidity, smart meters of heat and electricity consumption, and smart plugs. The equipment is combined into single system through an integration controller with remote user access through an interactive web interface. A feature of the technical solution is the ability to collect, process, visualize, and archive data on the consumption of energy, as well as on the key parameters of the microclimate of residential premises. The advantages of the system are its flexibility due to the possibility of integrating additional devices during operation, as well as the use of standard communication protocols, which enables the interchangeability of component elements. The implementation and testing were carried out under the conditions of a real pilot site. The use of the system in practice confirmed the efficiency and stability of the operation, making it possible to obtain data on the parameters of energy consumption and microclimate and devising recommendations for reducing energy consumption at the pilot site. It was established that the microclimate meets the requirements of the standards (air temperature is about 22 °С while relative humidity does not exceed 60 %). Decrease in energy consumption can be achieved by reducing the temperature of the heat carrier in the absence of residents, as well as by considering the influence of weather conditions. During periods of residents activity, an excess of the permissible level of CO2 was recorded, therefore, automatic ventilation systems should be provided in the apartments. [ABSTRACT FROM AUTHOR]

High temporal resolution geostationary hyperspectral infrared sounders can simultaneously profile atmospheric temperature and moisture, and track moisture features to provide 3D horizontal winds in clear and partially cloudy scenarios. The thermodynamic information obtained has been integral to enhancing tropical cyclone (TC) forecasts. However, the potential benefits derived from the dynamic information provided by geostationary hyperspectral infrared sounders (GeoHIS) are yet to be fully comprehended for numerical weather prediction (NWP). With the re‐estimated observation error and multivariate hydrometeor background error covariance, the 3D horizontal winds from the Geostationary Interferometric Infrared Sounder (GIIRS) are synergistically assimilated with the hydrometeor information. The impact of the GIIRS‐derived 3D horizontal wind assimilation on Typhoon Maria (2018) and Lekima (2019) analysis and forecast are evaluated. The results show that the assimilating GIIRS‐derived 3D horizontal wind notably reduces the RMSEs of analysis and forecast, particularly in the U and V components. The improvement in accuracy of large‐scale fields substantially enhances the forecasts of typhoons' track and maximum wind speed, as well as the central sea‐level pressure. Moreover, the prediction of the spatial distribution and intensity for landfall precipitation is also improved. The detailed diagnoses of the Maria show that a more southerly subtropical high generated by the additional horizontal wind assimilation improves the rainfall spatial distribution, and the reasonable water vapor transportation caused by the improved dynamic conditions corrects the precipitation intensity. This work highlights the importance of dynamic information in TC forecasting and emphasizes the need for efficient and high‐precision 3D wind measurements to improve NWP. Plain Language Summary: Accurately describing atmospheric winds is vital in weather forecasting, particularly in predicting severe weather such as typhoons. High temporal resolution measurements from geostationary hyperspectral infrared sounder (GeoHIS) offer the weather cube of atmospheric temperature and moisture and provide three‐dimensional (3D) horizontal wind profiles by tracking the moisture features. With upcoming more hyperspectral sounders being deployed in the geostationary ring on operational geostationary weather satellites, it is essential to understand the benefit of dynamic information for numerical weather prediction (NWP). Using 3D wind experimental data from a high temporal resolution Geostationary Interferometric Infrared Sounder (GIIRS) onboard FengYun‐4A, the observation errors are characterized, and cycling assimilation and forecasting experiments are conducted to assess the impact of assimilating 3D wind for Typhoon Maria (2018) and Typhoon Lekima (2019). Improving the model's initial conditions with GIIRS‐derived 3D winds enhances the typhoons' track and intensity forecast accuracy. It helps correct the biased forecast of rainfall spatial distribution and intensity after the typhoons made landfall. The improvements are primarily due to the typhoon's better environmental conditions, particularly the more accurate dynamical conditions, which result in the correction of subtropical high position and water vapor transport. This study emphasizes the need for 3D wind observations and the benefit of weather forecasting, especially in predicting extreme weather events such as tropical cyclones. Accurate wind measurements can help us prepare and respond better to potentially dangerous weather phenomena. Key Points: GIIRS‐derived 3D horizontal wind provides key dynamic information for NWP model and is synergistically assimilated with other observationsAssimilating GIIRS‐derived 3D horizontal wind improves typhoon analysis and forecasting, especially track, intensity, and precipitationSynergistic assimilation of geostationary satellite dynamic and hydrometeor data improves rainfall forecast by optimizing water vapor transportation [ABSTRACT FROM AUTHOR]

One prominent mode of the variability in the summer wet‐bulb temperature (WBT) over eastern China exhibits a distinct north‒south dipole pattern. This pattern demonstrates a positive center in northern China (NC), while a negative center is observed in southern China (SC). Our results indicate that the dipole mode of WBT could be partially ascribed to the impact of spring snow anomalies in eastern Europe–western Siberia (EEWS). The reduction in the snow depth, coupled with dry soil conditions, enhances the surface heat flux and consequently leads to an increase in the near‐surface air temperature. The signal of soil moisture could persist from spring to summer, stimulating the generation of zonal Rossby waves. Consequently, the significant wave flux anomalies propagate from EEWS downstream and influence the atmospheric circulation over eastern China. These patterns play a role in the increase in the surface air temperature and moisture accumulation over NC, ultimately leading to the establishment of the dipole mode of WBT over eastern China in summer. Further analysis indicates that the atypical low sea surface temperature in the tropical Ocean, induced by the El Niño‐Southern Oscillation, establishes a climatic context favorable for the persistence of an anomalous cyclone in the Northwest Pacific (NWP) throughout the summer season. The strengthened convection over the NWP and SC induces a dipole pattern of atmospheric circulation by stimulating a meridional wave train. This pattern creates favorable temperature and moisture conditions, contributing to the development of the dipole mode of the summer WBT across eastern China. Plain Language Summary: In recent decades, the social loss associated with high‐temperature and high‐humidity conditions has sharply increased. The wet‐bulb temperature (WBT) is widely regarded as a highly effective metric for characterizing the combined stress of humidity and heat. In this study, we emphasized one of the important modes (a north‒south dipole pattern) of the variability in the summer WBT over eastern China and revealed the corresponding underlying mechanisms. We found that mid‐high and low latitudinal dynamic processes may exert a synergistic effect on WBT over eastern China. On one side, spring snow depth anomalies could be coupled with spring soil moisture anomalies over eastern Europe–western Siberia and subsequently influence the dipole mode of the summer WBT over eastern China by triggering the stimulation of zonal Rossby waves. On the flip side, the anomalous low sea surface temperature in the tropical Ocean, driven by the ENSO, could yield a climatic state that supports the prolonged existence of an anomalous cyclone over the Northwest Pacific throughout the summer season. This cyclone exerts a significant impact on the dipole mode of the summer WBT over eastern China. Our study compensates for the lack of humid heat effect‐related research across eastern China and contributes to establishing a solid theoretical foundation for comprehending and forecasting the summer WBT in the region. Key Points: One significant pattern of the variability in the summer wet‐bulb temperature (WBT) over eastern China is manifested as a north‒south dipole modeAnomalous spring snowfall over Eurasia can impact the dipole mode of summer WBT over eastern China via the stimulation of zonal Rossby wavesThe anomalous sea surface temperature over tropical ocean, triggered by El Niño‐Southern Oscillation, establishes a climatic context conducive to the dipole mode over eastern China [ABSTRACT FROM AUTHOR]

This study investigates the response of surface air temperature (SAT) to strong tropical volcanic eruptions (STVEs), focusing on the seasonal anchoring of SAT recovery, using the Coupled Model Intercomparison Project 5 (CMIP5) and CMIP6 climate model outputs. The decrease in SAT was more significant in the Northern Hemisphere than in the Southern Hemisphere. After the STVEs, shortwave radiation at the surface (SW) decreased rapidly and reached a minimum in approximately 6 months, whereas the decrease in SAT lasted for approximately 1 year; thus, the SAT minima lagged behind those of SW. The recovery of SAT from the major minimum SAT after the STVEs occurred in the same seasons, the second boreal autumn and winter. The SAT recovery occurred during the climatologically low solar radiation season after the STVEs. During this season, the decreasing effects of the downward SW (DSRS) by volcanic aerosols could become negligible. The weakening of the decrease in SAT and DSRS had a seasonal cycle in the high‐latitude regions of both hemispheres, which could be a significant factor in the seasonal alignment of returning SATs. Furthermore, the SAT response to the El Niño–Southern Oscillation (ENSO) was examined using composite analysis based on the initial state of ENSO. The influence of ENSO on surface cooling after the STVE was at least 1/5 that of the STVEs and might exceed that of the STVEs, particularly in moderate STVEs. These results were commonly found in the CMIP5 and CMIP6 climate models. Plain Language Summary: Strong tropical volcanic eruptions (STVEs) transport volcanic sulfur aerosols into the stratosphere, affecting downward solar radiation and decreasing surface air temperature (SAT) for several years. After the 1991 Pinatubo eruption, the global average surface air temperature dropped by 0.5 K. We investigated the SAT response to the STVEs using the simulation results from multiple climate models. Analyzing many simulations increases the reliability of our results. As is well known from previous studies, a SAT drop has been clearly observed in the Northern Hemisphere. In addition, the SAT response to volcanic aerosols was weakened in the second northern winter after the STVEs, even when the STVE occurred in northern spring and fall. Because solar radiation at the Earth's surface is climatologically weak in northern winter, the effects of volcanic aerosols on SAT decrease can be negligibly small in northern winter. Therefore, the recovery of SAT after STVEs occurred in the northern winter. Key Points: Surface air temperature (SAT) responses to strong tropical volcanic eruptions (STVEs) were investigated using CMIP5/6 climate modelsDecrease in SAT after the STVEs tended to stop in the second winter, even though the timing of the eruption was differentSeasonally anchoring SAT recovery after STVEs is related to weak solar radiation in winter [ABSTRACT FROM AUTHOR]

Mountain snowpack forecasting relies on accurate mass and energy input information to the snowpack. For this reason, coupled snow-atmosphere models, which downscale input fields to the snow model using atmospheric physics, have been developed. These coupled models are often limited in the spatial and temporal extent of their use by computational constraints. In addressing this challenge, we introduce HICARsnow, an intermediate-complexity coupled snow-atmosphere model. HICARsnow couples two physics-based models of intermediate complexity to enable basin-scale snow and atmospheric modeling at seasonal time scales. To showcase the efficacy and capability of HICARsnow, we present results from its application to a high-elevation basin in the Swiss Alps. The simulated snow depth is compared throughout the snow season to aerial LiDAR data. The model shows reasonable agreement with observations from peak accumulation through late-season melt-out, representing areas of high snow accumulation due to redistribution processes, as well as melt patterns caused by interactions between radiation and topography. HICARsnow is also found to resolve preferential deposition, with model output suggesting that parameterizations of the process using surface wind fields only may be inappropriate under certain atmospheric conditions. The two-way coupled model also improves surface air temperatures over late-season snow, demonstrating added value for the atmospheric model as well. Differences between observations and model output during the accumulation season indicate a poor representation of redistribution processes away from exposed ridges and steep terrain, and a low-bias in albedo at high elevations during the ablation season. Overall, HICARsnow shows great promise for applications in operational snow forecasting and studying the representation of snow accumulation and ablation processes. [ABSTRACT FROM AUTHOR]

Primary production in the Sea of Okhotsk is largely supported by dissolved iron (dFe) transported by the Amur river, indicating the importance of dFe discharge from terrestrial environments. However, little is known about the mechanisms of dFe discharge into the Amur river, especially in terms of long-term change in dFe concentration. In the Amur river, extreme increase in dFe concentration was observed between 1995 and 1997, the cause of which remains unclear. As a cause of this iron anomaly, we considered the impact of permafrost degradation. To link the permafrost degradation to long-term variation in dFe concentration, we examined the changes in annual air temperature (Ta), accumulated temperature (AT), and net precipitation for three regions (northeast, south, and northwest) of the basin between 1960 and 2006. Ta and AT were relatively high in one out of every few years, and were especially high during 1988–1990 continuously. Net precipitation in late summer (July to September) has increased since 1977 and has stayed positive until 2006 throughout the basin. Most importantly, we found significant correlations between Ta and late summer dFe concentration with a 7-year lag (r = 0.54–0.69, p < 0.01), which indicate a close relationship between high Ta in year Y and increased late summer dFe concentration in year Y + 7. This correlation was the strongest in northeastern Amur basin where permafrost coverage is the highest. Similar 7-year lag correlation was also found between AT in the northeastern basin and late summer dFe concentration (r = 0.51, p < 0.01). Based on our findings, we propose the following hypothesis as a cause of iron anomaly. (1) Increased net precipitation since 1977 has increased soil moisture, which created suitable conditions for microbial dFe generation; (2) permafrost degradation during the warm years of 1988–1990 promoted iron bioavailability and led to the intensive dFe generation in the deeper part of the active layer; and (3) dFe took approximately 7 years to reach the rivers and extremely increased dFe concentration during 1995–1997. This is the first study to suggest the time-lagged impact of permafrost degradation on iron biogeochemistry in the Amur river basin. [ABSTRACT FROM AUTHOR]

The Arctic Ocean's snow cover is crucial in moderating interactions between sea-ice and the atmosphere, yet fully grasping its isotopic composition and the processes shaping it presents substantial challenges. This study employs a unique dataset from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to explore the complex interactions between deposition processes and post-depositional changes affecting snow on Arctic sea ice. By examining 911 individual snow isotope measurements collected over a full year, we identify a clear layering within the snowpack: the top layer, with lower δ18O values and higher d-excess values, indicates fresh meteoric snowfall, while the bottom layer, affected by the sea ice beneath, shows higher δ18O values and lower d- d-excess values. By integrating these discrete snow samples with continuous vapour isotope data, our research provides insight into interactions between snow and the atmosphere, as well as the processes that alter isotopic signatures within Arctic snow. We observe a significant difference in δ18O values between snow and vapor during autumn, mainly due to delays in sampling after precipitation events, with d-excess ranges suggesting the impact of Atlantic moisture. Winter months exhibit sharp differences in δ18O and d-excess values, indicating kinetic fractionation amid extreme cold as the RV Polarstern traverses from the Siberian to the Atlantic sector of the Arctic Ocean. Conversely, summer months display a convergence in isotopic signatures, reflecting conditions favouring equilibrium fractionation, highlighted by increased air temperatures and humidity levels. While δ18O in vapour readily responds to changes in air temperature and humidity, surface snow δ18O is influenced more by subsequent processes such as sublimation and wind-driven redistribution. Sublimation, intensified by the snow's prolonged surface residence and facilitated by the porosity of snow, plays a key role in isotopic enrichment. Wind-driven snow redistribution, occurring 67 % of the winter, led to a homogenised and depleted surface snow δ18O signal across the sea ice by spreading lower δ18O meteoric snow. This effect was especially pronounced in ridge snow profiles, where the top layers showed a uniform δ18O signal, in stark contrast to flat ice samples. Furthermore, distinct isotopic patterns were detected along the MOSAiC expedition route from a region close to Samoylov Island to Fram Straight near Ny-Ålesund. Snow samples close to Samoylov Island exhibited notable seasonal δ18O variations, which were indicative of a continental climate. In contrast, samples from Ny-Ålesund displayed more consistent fluctuations, influenced by steady Atlantic moisture. [ABSTRACT FROM AUTHOR]

Arctic air masses undergo intense transformations when moving southward from closed sea ice to warmer open waters in marine cold-air outbreaks (CAOs). Due to the lack of measurements of diabatic heating and moisture uptake rates along CAO flows, studies often depend on atmospheric reanalysis output. However, the uncertainties connected to those datasets remain unclear. Here, we present height-resolved airborne observations of diabatic heating, moisture uptake, and cloud evolution measured in a quasi-Lagrangian manner. The investigated CAO was observed on 1 April 2022 during the HALO-(AC) 3 campaign. Shortly after passing the sea-ice edge, maximum diabatic heating rates over 6 Kh-1 and moisture uptake over 0.3 gkg-1h-1 were measured near the surface. Clouds started forming and vertical mixing within the deepening boundary layer intensified. The quasi-Lagrangian observations are compared with the fifth-generation global reanalysis (ERA5) and the Copernicus Arctic Regional Reanalysis (CARRA). Compared to these observations, the mean absolute errors of ERA5 versus CARRA data are 14 % higher for air temperature over sea ice (1.14 K versus 1.00 K) and 62 % higher for specific humidity over ice-free ocean (0.112 gkg-1 versus 0.069 gkg-1). We relate these differences to issues with the representation of the marginal ice zone and corresponding surface fluxes in ERA5, as well as the cloud scheme producing excess liquid-bearing, precipitating clouds, which causes a too-dry marine boundary layer. CARRA's high spatial resolution and demonstrated higher fidelity towards observations make it a promising candidate for further studies on Arctic air mass transformations. [ABSTRACT FROM AUTHOR]

Climate change is modifying river temperature regimes across the world. To apply management interventions in an effective and efficient fashion, it is critical to both understand the underlying processes causing stream warming and identify the streams most and least sensitive to environmental change. Empirical stream thermal sensitivity, defined as the change in water temperature with a single degree change in air temperature, is a useful tool to characterize historical stream temperature conditions and to predict how streams might respond to future climate warming. We measured air and stream temperature across the Snoqualmie and Wenatchee basins, Washington, during the hydrologic years 2015–2021. We used ordinary least squares regression to calculate seasonal summary metrics of thermal sensitivity and time-varying coefficient models to derive continuous estimates of thermal sensitivity for each site. We then applied classification approaches to determine unique thermal sensitivity regimes and, further, to establish a link between environmental covariates and thermal sensitivity regimes. We found a diversity of thermal sensitivity responses across our basins that differed in both timing and magnitude of sensitivity. We also found that covariates describing underlying geology and snowmelt were the most important in differentiating clusters. Our findings and our approach can be used to inform strategies for river basin restoration and conservation in the context of climate change, such as identifying climate-insensitive areas of the basin that should be preserved and protected. [ABSTRACT FROM AUTHOR]

Human activities and climate change have resulted in environmental degradation and increased environmental hazards globally. In Khuzestan province, such hazards have included droughts, heat waves, and dust storms occurring more frequently. To understand the factors contributing to the dust storms, this study evaluated changes in rainfall, air temperature maximum and minimum, and soil temperature (1985–2019), as well as land cover, land surface temperature, and water bodies in 2017 (drought) and 2019 (wet year). The findings of the principal component analysis indicate a reduction in annual water bodies, spring vegetation, and water bodies in the spring, summer, and autumn seasons. The increase in air and land surface temperature accounts for 95% of the variance in dust in the Khuzestan province. Field surveys suggest that various human activities such as hydro dam building, crude oil drilling, extracting crude oil wells in lagoons, changes in farmland use, and water transfer among water basins have intensified the phenomena in the region under study. To manage this critical issue more effectively, it is recommended to review and assess local policies regarding regional ecology and establish cooperative agreements with regional countries such as Iraq, Turkey, Syria, Jordan, and Saudi Arabia which all experience similar natural disasters. [ABSTRACT FROM AUTHOR]

This study focuses on the interannual variability of winter mean surface air temperature (SAT) and subseasonal SAT reversal in North China, which have profound impacts on national life and economic activities. The analysis explores the temporal and spatial distribution characteristics of these variations and their relationship with the Eurasian Zonal Circulation (EZ). The findings reveal distinct interdecadal changes in North China's winter mean SAT, along with a general subseasonal reversal of cold and warm conditions. In comparison to the North Atlantic oscillation/Arctic Oscillation, the EZ has a more significant influence on the interannual variability of winter and subseasonal reversals. Strong EZ years are associated with the weakening of the Siberian High and the Ural Blocking High, causing the East Asian Trough to move eastward, which leads to the retention of cold air from the north and increased SAT in North China. Conversely, weak EZ years exhibit opposite circulation patterns. The winter mean EZ is influenced by preceding autumn Arctic sea ice concentrations (SIC). Reduced autumn SIC results in decreased heat flux and reduced eddy energy, leading to substantial attenuation of the winter storm track across Scandinavia and Western Asia. This attenuation, mediated through the interaction between eddies and mean flow, triggers a slowdown of Eurasian zonal circulation and intensification of the Siberian High. These conditions favor a positive phase of the winter Scandinavia pattern, facilitating the transport of cold Arctic air into North China. Likewise, subseasonal reversals in SIC influence corresponding alterations in the EZ. Plain Language Summary: The winter surface air temperatures (SAT) in North China exhibit notable interdecadal variations and distinct intra‐seasonal changes. These intra‐seasonal variations lead to subseasonal reversals, where early winter may be unusually warm, followed by later winter turning unusually cold, or vice versa. These subseasonal SAT fluctuations are influenced by atmospheric circulation anomalies. In this study, we investigate the spatial and temporal patterns of the mean winter SAT and subseasonal SAT reversals in North China, focusing on their interannual variability. We emphasize the significant impact of anomalous zonal circulation over the middle and high latitudes in Eurasia and explore the relative influence of the Arctic as a boundary forcing factor in circulation anomalies. Key Points: The winter surface air temperature (SAT) and subseasonal SAT reversal in North China have noteworthy interannual variationsThe Eurasian Zonal Circulation (EZ) strongly influences winter SAT and subseasonal reversal variabilityThe physical mechanisms linking autumn Arctic sea ice concentrations to EZ is examined [ABSTRACT FROM AUTHOR]

Surprising significant underperformance of the polynomial complementary relationship (PCR) of evaporation (Szilagyi et al., 2017, https://doi.org/10.1002/2016jd025611) by Wang et al. (2023, https://doi.org/10.1029/2023jd038683) is caused by the (a) station‐by‐station application of a grid‐based estimation procedure of the Priestley‐Taylor parameter (α) value, and (b) choice of the wind function. Application of the Rome wind function in the Penman equation together with either a well‐chosen single (constant) α or α as a function of the wet‐environment air temperature, should result in much improved evaporation estimates by the PCR in line with previous studies. Plain Language Summary: The serious underperformance of the polynomial complementary relationship of evaporation as employed by Wang et al. (2023, https://doi.org/10.1029/2023jd038683) can be significantly improved by the application of a properly chosen constant value of its α parameter or by relating it to the wet‐environment air temperature demonstrated by Szilagyi and Crago (2023, https://doi.org/10.1016/j.jhydrol.2023.129917). Key Points: Such underperformance of the polynomial complementary relationship (PCR) has never been reportedIt is caused mainly by the improper application of its parameter estimation procedureWith the proper Priestley‐Taylor parameter the PCR performs significantly better [ABSTRACT FROM AUTHOR]

Vertical exchange between the atmospheric boundary layer (ABL) and free troposphere (FT) is a key link in coupling the earth's surface and upper atmosphere. This process is usually quantified by numerical simulations, while its reliability is not well assessed until now. Using space‐time intensified ABL observations, we evaluate the ABL‐FT air mass exchange flux derived from the Weather Research and Forecast (WRF) model. A six‐site sounding experiment is conducted in the North China Plain during the wintertime of 2019. The measured data is processed to provide enough information to derive the vertical exchange flux corresponding to the model‐based result, so that a systematic comparison is conducted. Three physical processes involved in ABL‐FT vertical exchange are quantitatively evaluated, that is, temporal variation of ABL height, advection across the inclined ABL top, and vertical motion at the ABL‐FT interface. Results show that the model‐based and observation‐based fluxes are generally agreed in temporal evolution (R = 0.67, p < 0.01), both characterized by 4–6 days periodicity and diurnal cycle. Their relative mean error was about 45% during the whole study period, mainly stemming from the vertical motion term and the advection crossing term. The model inaccuracy in representing these relevant processes at the ABL top is largely responsible for the discrepancy. Besides, the difference may also be attributed to the observational uncertainty (∼22%) that is caused by the measurement's difficulties in determining ABL spatial variation and acquiring vertical velocity. Through this study, the credibility and limitation of the WRF model in deriving ABL‐FT exchange flux are quantified. Plain Language Summary: The vertical exchange between the atmospheric boundary layer (ABL) and free troposphere (FT) plays a crucial role in atmospheric matter transport and energy flow, affecting weather systems, atmospheric chemistry, air pollution and climate change. This process is usually quantified by numerical simulation. This work aims to evaluate the reliability of the air exchange flux derived from a meteorological model, using comprehensive observation data in 1 month. The result shows that the model‐based exchange flux can reproduce the temporal evolution of the observation‐based exchange flux, including 4–6 days periodicity and diurnal variation. The overall relative difference between simulated and observed fluxes is about 45% during the whole study period. A more detailed comparison of each component term is conducted to investigate the causes of the discrepancy. We found that the difference is partly attributed to the model inaccuracy in representing the ABL top spatial variation and the vertical velocity at this layer. Additionally, a 22% uncertainty in observation‐based flux introduced by the relevant data processing is also an important reason. The evaluation result provides a quantitative reference to understand the biases in the meteorological model and their impact on ABL‐FT vertical exchange simulation study. Key Points: The air exchange flux between the boundary layer and free troposphere is reproduced by the WRF model with synoptic and diurnal variationsThe model‐derived exchange flux deviates from observation‐derived flux with a relative difference of 45%The deviation is mainly attributed to simulation‐observation differences in vertical motion and spatial gradient at the boundary layer top [ABSTRACT FROM AUTHOR]

In this study, a numerical and experimental analysis of a solar collector with roughness elements in the form of stainless-steel scourers on the absorber surface is presented. According to the location type and number of the stainless steel scourers, the absorber surfaces are referred to as the complex surface (C1), less complex surface (C2), and flat surface (C3). A Computational Fluid Dynamics (CFD) analysis was carried out using ANSYS-CFX-R18.2 commercial software. The results were verified with the experimental study. After the numerical study was confirmation with the experimental study, then the detailed investigation was performed by numerical simulations. The extracted results of the numerical and experimental analysis concerned the air temperature and velocity, and thermal efficiency, which varied with respect to the type of collector. As a result, the C1 type yielded the highest air velocity and air temperature, while the lowest values of air velocity and temperature were recorded for the C3 type, according to both the numerical analysis and experimental tests. This trend was similar for the efficiencies. The efficiency was nearly 80% for collectors with stainless-steel scourers, whilst it was 55% for the flat plate collector. The results showed that the experimental and numerical results agreed well. [ABSTRACT FROM AUTHOR]

This study investigates the oxidation behavior and microstructure characterization of C‐HRA‐5 (i.e., a new austenitic heat‐resistant steel) in the air at temperatures ranging from 650 to 750 °C over a 1000‐hour duration. The oxidation behavior and mechanism are analyzed using gravimetric evaluation, thermodynamic analysis, microscopic morphology, and microstructure characterization. The results indicate that the oxidation behavior follows a parabolic law at each temperature. With increasing temperature, the oxide film gradually grows and transforms from small lump particles to strips and needles, eventually covering the entire substrate surface over time. Moreover, long‐term oxidation exposure promotes the formation of various phases, including M23C6, σ, MX, Z, nanosized Cu‐rich, and Laves phases, within the metallic substrate. Considering potential applications in new‐generation power plants, this study provides a solid foundation to disclose the possible oxidation of C‐HRA‐5 austenitic heat‐resistant steel at high temperatures. [ABSTRACT FROM AUTHOR]

The climatological mean turbulent air-sea heat exchange maximises along midlatitude sea surface temperature (SST) fronts that anchor midlatitude storm tracks. This implies a crucial role of the air-sea latent heat exchange along the SST fronts on the atmospheric water cycle and storm tracks through the intensification of atmospheric cyclones and their associated precipitation. We investigate the sensitivity of the atmospheric water cycle to the SST front through a set of aqua-planet experiments. Varying the latitude of a zonally symmetric midlatitude SST front, the midlatitude atmospheric water cycle responds through distinct changes in surface latent heat fluxes, precipitation, as well as atmospheric moisture fluxes, whereas the tropical latitudes remain largely unchanged. As storm tracks are self-maintained through the diabatic generation of eddy available potential energy, the position of the storm track is diabatically anchored at the SST front. While the position of the SST front determines the position of the eddy moisture convergence and thus the diabatic heating that energises the storm track, the underlying SST determines the general strength of the water cycle and thus the intensity of the storm track. The strong connection identified between the eddy moisture flux and the SST front implies a diabatic pathway of latent heating to anchor the storm track along SST fronts. [ABSTRACT FROM AUTHOR]

Snow is the most important component of the Arctic climatic and hydrological system and is directly vulnerable to climate change. In recent decades, observations have indicated significant decreases in the Arctic snow cover and snowfall rate, whereas water discharge from circumpolar Arctic river basins into the Arctic Ocean has increased. To evaluate the contribution, not well quantified, of snow to the river discharge increase, we conducted sensitivity simulations with surface air temperature and precipitation as climatic treatment variables, combining a land surface model and a distributed discharge model. Variables were treated assuming higher climate variations in the Arctic cold season in 1979–2018. The surface and subsurface runoffs simulated by the land surface model were set as inflows in the discharge model to estimate river discharge. Snowmelt mostly converted to surface runoff, accounting for 73.6% of the anomalous surface runoff increase and inducing the simulated peak discharge in spring and early summer. This relationship was enhanced by the winter precipitation increase. Snow loss induced by higher air temperature contributed to the decrease in the peak and annual discharges, but caused the peak discharge to occur earlier. Additionally, warmer temperature increased the proportion of rainfall in the partitioning of precipitation, causing more subsurface runoff, particularly in autumn and winter. These results provide a first separate evaluation of factors influencing Arctic water discharge, including seasonal hydrographs, and illustrate the influence of climate warming-induced snowfall and rainfall variations on the circumpolar Arctic river discharge. [ABSTRACT FROM AUTHOR]

We assess the temperature stability requirements of unseeded Nd:YAG lasers in lidar systems for atmospheric temperature profiling through the rotational Raman technique. Taking as a reference a system using a seeded laser assumed to emit pulses of negligible spectral width and wavelength-drift free, we estimate first the effect of the pulse spectral widening of the unseeded laser on the output of the interference filters, then we derive the limits of the allowable wavelength drift for a given bias in the temperature measurement that would add to the noise-induced uncertainty. Finally, using spectroscopic data, we relate the allowable wavelength drift to allowable temperature variations of the YAG rod. We find that, in order to keep the bias affecting atmospheric temperature measurements smaller than 1 K, the Nd:YAG rod temperature should also be kept within 1 K. [ABSTRACT FROM AUTHOR]

The year 2023 marked a turning point for the Antarctic region as the Southern Hemisphere experienced a significant reduction in its sea ice extent, with a record-breaking sea ice minimum in July 2023 of approximately 2.4 million square kilometers below the long-term average. This study highlights the drivers behind this exceptional event by combining observational, satellite, and reanalysis data, with a special focus on the large-scale atmospheric circulation. Throughout the year, the Antarctic Sea ice extent broke record after record, ranking as the lowest sea ice on record from January to October, except for March and April. The exceptionally low sea ice extent from May to August was mainly driven by the prevalence of a zonal wave number 3 pattern, characterized by alternating surface high- and low-pressure systems, which favored the advection of heat and moisture, especially over the Ross Sea (RS), Weddell Sea (WS), and Indian Ocean (IO). The anomalous large-scale circulation was accompanied by record-high sea surface and subsurface temperatures over the regions with reduced sea ice extent. In addition to the air and ocean temperature, record-breaking heat, moisture, and sensible heat fluxes have been observed, especially over the WS, RS, and IO, which further amplified the reduction in the sea ice extent over these areas. Notably, over the Weddell Sea, we observed air temperature anomalies reaching up to 8°C and sea surface temperature anomalies of up to 3°C from May to July. Similar temperature anomalies were recorded over the Ross Sea, particularly in July and August. A change point analysis indicates that a regime shift in the Antarctic Sea ice, as well as in the average mean air temperature and (sub)surface ocean temperature over the Weddell Sea, started around 2015. The low sea ice extent in Antarctica in 2023 was a stark reminder of the ongoing changes in the polar regions. Thus, understanding the underlying mechanisms of these extreme events provides crucial insights into the changing dynamics of Antarctic Sea ice and its broader climatic significance. [ABSTRACT FROM AUTHOR]

Paleoclimatological field reconstructions are valuable for understanding hydroclimatic variability. While being similarly impactful on societies as temperature variability, hydroclimatic variability has still remained less in focus. However, reconstructing globally complete fields of climate variables lacks adequate proxy data from tropical regions like South America, limiting our understanding of past hydroclimatic changes in these areas. This study addresses this gap using low resolution climate archives, including speleothems, previously omitted from reconstructions. Speleothems record climate variations on decadal to centennial time scales and provide a rich dataset for the otherwise proxy data scarce region of tropical South America. By employing a multi-time scale Paleoclimate Data Assimilation approach, we synthesize climate proxy records and climate model simulations, capable of simulating water isotopologues in the atmosphere, to reconstruct 2000 years of South American climate. This includes surface air temperature, precipitation amount, drought index, isotopic composition of precipitation amount, and the intensity of the South American Summer Monsoon. The reconstruction reveals anomalous climate periods: a wetter and colder phase during the Little Ice Age (1500–1850 CE) and a drier, warmer period corresponding to the early Medieval Climate Anomaly (600–900 CE). However, these patterns are not uniform across the continent, with exceptions in northeastern Brazil and the Southern Cone, indicating regional variability. The anomalies are more pronounced than in previous reconstructions, but align with local proxy record studies, thus highlighting the importance of including speleothem proxies. The multi-timescale approach is essential for reconstructing multi-decadal and centennial climate variability. Despite methodological uncertainties regarding climate model biases and proxy record interpretations, this study marks a crucial first step in incorporating speleothems into climate field reconstructions, potentially enhancing insights into past hydroclimatic variability and hydroclimate projections. [ABSTRACT FROM AUTHOR]

This study investigates the spatio-temporal variations in the chlorophyll- a (chl- a) blooms in the Bransfield Strait (BS) at a climatological scale (1998–2018). We propose that suitable monitoring of these blooms can be achieved through remotely sensed observations only if the BS is divided following the Peninsula Front (PF), which ultimately influences the phytoplankton assemblage. Our analysis is based on characterizing climatological fields of sea surface temperature (SST), air temperature, sea ice coverage, chl- a concentrations and wind stress, guided by synoptic novel and historical in situ observations which reveal two niches for phytoplankton assemblage: the Transitional Bellingshausen Water (TBW) and Transitional Weddell Water (TWW) pools. The TBW pool features stratified, less saline, warmer waters with shallow mixed layers, while the TWW pool features well-mixed, saltier, and colder waters. We identify that the 0.6 °C isotherm corresponds to the summertime climatological PF location, effectively dividing the BS into two different scenarios. Furthermore, the 0.5 mg m -3 chl- a isoline aligns well with the 0.6 °C isotherm, serving as a threshold for chl- a blooms of the highest concentrations around the South Shetland Islands. For the first time, these thresholds enable the monthly climatological descriptions of the two blooms developing in the BS on both sides of the PF. We think this approach underscores the potential of combining SST and chl- a data to monitor the year-to-year interplay of the chl- a blooms occurring in the TBW and TWW pools contoured by the PF. [ABSTRACT FROM AUTHOR]

Nigeria's forest reserves no matter where they are located act as the last succour for the entire citizenry by rendering ubiquitous services that significantly contribute to her economy. This study was intended at assessing the Land Surface Temperature (LST) in Owo Forest Reserve Area (FRA) with a view to sustainable forest management. Goal and Objectives: The essential objectives set for the research include: (i.) assessing the vegetation changes in Owo Forest Reserve Area (ii.) evaluating the LST in Owo forest reserve and (iii.) relating changes in vegetation cover to LST in other to ascertain whether the observed difference in vegetation cover has significant effect and contribution either positively or otherwise to LST values obtained in Owo forest reserve. Methodology: Recorded spatial coordinates of some selected points constitute the primary data while the secondary data were the satellite dataset, which includes: the Operational Landsat Imager, Enhanced Thematic Mapper, and Thematic Mapper of different years (1991, 2002, 2014, and 2020) used for mapping the vegetation change in the forest reserves. Specifically, thermal bands of the Landsat image in conjunction with the Normalized Difference Vegetation Index (NDVI) were utilized for mapping the LST which is the hallmark of the research. Various data acquired were processed according to the best practices. Results: The results obtained showed that moderate vegetation (shrubs and scattered trees) has been increasing, which signifies that these categories of vegetation in Owo forest reserve area is not depleting for the whole period of study. It was also discovered from the results garnered from 1991 to 2020 that areas with vegetation (Dense, moderate, and sparse) had the least LST values while the forecast probable future LST values for the year 2030 are in the purview of 24.22°C(minimum) and 53.98°C (maximum) which may have negative implications on the forest reserve. The research recommends a significant increase in the rate of tree planting and preserving green areas (vegetation) in order to mitigate the upsurge of LST while laws guiding illegal logging should be upheld with the utmost tenacity. [ABSTRACT FROM AUTHOR]

This article explores the unique phenomenon of Carlina corymbosa thistle flowers in the Mediterranean having a cooler interior than the surrounding air during the hot summer months. The author conducted temperature measurements and found that the interior of the flowers was consistently cooler than the air outside. The study suggests that this cooling effect is achieved through enhanced transpiration in the flowers, which is more effective in the high ambient temperatures and low humidity of the Mediterranean climate. The article also discusses the potential benefits of this cooling mechanism for the plant's reproduction by attracting pollinators. Further research can be done to test this hypothesis. [Extracted from the article]

A total of 194 specimens of the predatory leech Helobdella stagnalis were collected from Sarchnar Stream, in Sulaimaniyah City along year of 2022 from January to the end of December. The seasonal distribution and occurrence, time of egg laying and hatching in relation with some physico-chemical factors were studied, including air and water temperatures, dissolved oxygen, pH, FCO2, HCO3-, Cl-, Ca+2 and Mg+. The temperature and dissolved oxygen were the most effective factors on leech's population density as well as time of egg lying and juvenile hatching. The highest density was in Autumn, while the lowest was recorded during Summer. Cocoons were seen to laid in late winter and maximum juvenile numbers were recorded during Spring. [ABSTRACT FROM AUTHOR]

Experiments on determination of the sorption isotherms of the heart of a palm at different temperatures have been performed. Some mathematical models, available in the literature, were used to predict the hygroscopic behavior of the palm heart. The thermodynamic properties of the palm heart, such as its isosteric heat of sorption, were determined using the Clausius–Clapeyron equation, and the shelf life of the palm heart was calculated using the Heiss–Eichner prediction model equations with regard for the storage conditions of this product and the requirements for its packaging. The results obtained can be used for optimization of the methods of drying and preservation of palm hearts, which is essential for the enhancement of their quality and the successful promotion of them in the international market. [ABSTRACT FROM AUTHOR]

Question: Ecological indicator values (EIVs) reflect species' optimal conditions on an environmental gradient, such as temperature. Averaged over a community, they are used to quantify thermophilization stemming from climate change, i.e. the reshuffling of communities toward more warm‐adapted species. In forests, understorey plant communities do not keep up with global warming and accumulate a climatic debt. Although the causes are still debated, this thermal lag may be partly explained by forest microclimate buffering. For the first time, we test whether community means of EIVs are able to capture microclimate (here, under forest canopies) temperature across, or also within forests. Location: 157 forest plots across three French deciduous forests covering a large macroclimatic gradient. Methods: To assess whether EIVs can be used to infer the mean and range of microclimate temperature in forests, we measured understorey air temperature for ca. 1 year (10 months) with sensors located 1 m above the ground. We surveyed bryophytes and vascular plants within 400‐m2 plots, and computed floristic temperature from ordinal‐scale EIVs (Ellenberg, Julve) and degree‐scale EIVs (ClimPlant, Bryophytes of Europe Traits) for both temperature and continentality, i.e. temperature annual range. Finally, we fitted linear models to assess whether EIVs could explain the mean and range of microclimate temperature in forests. Results: Vascular plant and bryophyte communities successfully reflected differences in mean annual temperatures across forests but largely failed to do so for microclimate variation within forests. Bryophytes did not perform better than vascular plants to infer microclimate conditions. The annual range of microclimate temperatures was poorly associated with ordinal‐scale EIVs for continentality but was positively correlated with degree‐scale EIVs for annual range within lowland forests, especially for vascular plant communities. Conclusion: Overall, the capabilities of EIVs to infer microclimate was inconsistent. Refined EIVs for temperature are needed to capture forest microclimates experienced by understorey species. [ABSTRACT FROM AUTHOR]

Advection is a prevailing meteorological phenomenon in the arid and semi‐arid environments that directly affects the crop and soil hydrology. It could have a great impact on the rate of standard crop evapotranspiration (ETc) in the irrigated areas. Therefore, it is required to take it into consideration while computing crop water requirement through the physically based meteorological procedures. The objectives of this study are (1) simple modification of the Penman–Monteith (PM) equation in calculation of the grass reference evapotranspiration (ETo) to implement the local advection, (2) comparing the single (Kc) and dual crop coefficient (Kcb) of two quinoa cultivars (Titicaca, and Q5) with and without advection correction and (3) presenting a simple model to calculate the advection factor using the maximum air temperature and mean relative humidity for the future crop growth modelling studies. Both Q5 and Titicaca showed unexpectedly very high ETc and potential transpiration (Tp) as 1568 mm and 1003 mm, and 1156 mm and 829 mm, respectively, due to occurrence of regional advection, whereas very high unrealistic Kc and Kcb values for Q5 revealed the impact of strong local advection and external energy. Therefore, we modified ETo to implement the advection effect through introducing the advection factor, ETc/Rn (Rn is the net radiation), as a function of maximum air temperature and mean relative air humidity during the growing season [ETc/Rn = exp (0.025Tmax – 0.015RHavg)] which resulted in higher ETo values, and consequently lower and more realistic Kc and Kcb. As a result, modified maximum Kc values of 1.14 and 1.55 and the modified maximum Kcb of 0.94 and 1.0 were obtained for Titicaca and Q5 cultivars, respectively. This procedure leads to a more accurate site‐specific Kc estimation and indirectly reliable ETc estimation as a function of advection factor and its multiplication by the non‐modified ETo. Furthermore, for direct estimation of ETc through the PM equation, the coefficients of aerodynamic and canopy resistance components of PM equation were modified for estimation of ETc by the non‐modified Rn, which resulted in accurate estimation of ETc. [ABSTRACT FROM AUTHOR]

Climate change due to enhanced greenhouse effect arising as a result of human activities is considered a major global environmental threat to mankind. This study experimentally investigates and determines the heat flow in and out of the earth surface, and the impact of greenhouse effect on the heat transfer. A high voltage electric bulb was placed between two bottles; an empty bottle containing only air and the other bottle containing a mixture of baking soda and vinegar, evolving CO2. We observed that the vinegar and baking soda in the filled bottle reacted and produced carbon dioxide (CO2). This CO2 absorbs and retains more heat from the high voltage bulb than the empty bottle of normal air. We also observed that visible light passes through the glass and is absorbed by darker surfaces inside. The demonstration of this study proves that greenhouse gases like CO2 is one of major greenhouse gases that are responsible for global warming by trapping heat thereby giving a rapid rise in temperature over time because of the concomitant lower heat loss to its environment. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet is a large contributor to global sea level rise, and current mass losses are projected to accelerate. However, model projections of future ice sheet evolution are limited by the fact that the ice sheet is not in equilibrium with present-day climate but is still adjusting to past changes that occurred over thousands of years. While the influence of such committed adjustments on future ice sheet evolution remains unquantified, it could be addressed by calibrating numerical ice sheet models over larger timescales and, importantly, against empirical data on ice margin positions. To enable such paleo data–model interactions, we need Greenland-wide empirical reconstructions of past ice sheet extent that combine geomorphological and geochronological evidence. Despite an increasing number of field studies producing new chronologies, such a reconstruction is currently lacking in Greenland. Furthermore, a time slice reconstruction can help to (i) answer open questions regarding the rate and pattern of ice margin evolution in Greenland since the glacial maximum, (ii) develop a standardised record of empirical data, and (iii) identify new sites for future field campaigns. Based on these motivations, we here present PaleoGrIS 1.0, a new Greenland-wide isochrone reconstruction of ice sheet extent evolution through the Late Glacial and early- to mid-Holocene informed by both geomorphological and geochronological markers. Our isochrones have a temporal resolution of 500 years and span ∼ 7.5 kyr from approximately 14 to 6.5 kyr BP. We describe the resulting reconstruction of the shrinking ice sheet and conduct a series of ice-sheet-wide and regional analyses to quantify retreat rates, areal extent change, and their variability across space and time. During the Late Glacial and early- to mid-Holocene, we find the Greenland Ice Sheet has lost about one-third of its areal extent (0.89 million km 2). Between ∼ 14 and ∼ 8.5 kyr BP, it experienced a near-constant rate of areal extent loss of 170 ± 27 km 2 yr -1. We find that the ice-sheet-scale pattern of margin retreat is well correlated to atmospheric and oceanic temperature variations, which implies a high sensitivity of the ice sheet to deglacial warming. However, during the Holocene, we observe inertia in the ice sheet system that likely caused a centennial- to millennial-scale time lag in ice extent response. At the regional scale, we observe highly heterogeneous deglacial responses in ice extent evident in both the magnitude and rate of retreat. We hypothesise that non-climatic factors, such as the asymmetrical nature of continental shelves and onshore bed topographies, play important roles in determining the regional- to valley-scale dynamics. PaleoGrIS 1.0 is an open-access database designed to be used by both the empirical and numerical modelling communities. It should prove a useful basis for improved future versions of the reconstruction when new geomorphological and geochronological data become available. [ABSTRACT FROM AUTHOR]

Global surface air temperature increased by ca. 0.5 °C from the 1900s to the mid-1940s, also known as Early 20th Century Warming (ETCW). However, the ETCW started from a particularly cold phase, peaking in 1908–1911. The cold phase was global but more pronounced in the Southern Hemisphere than in the Northern Hemisphere and most pronounced in the Southern Ocean, raising the question of whether uncertainties in the data might play a role. Here we analyse this period based on reanalysis data and reconstructions, complemented with newly digitised ship data from 1903–1916, as well as land observations. The cooling is seen consistently in different data sets, though with some differences. Results suggest that the cooling was related to a La-Niña-like pattern in the Pacific, a cold tropical and subtropical South Atlantic, a cold extratropical South Pacific, and cool southern midlatitude land areas. The Southern Annular Mode was positive, with a strengthened Amundsen–Bellingshausen seas low, although the spread of the data products is considerable. All results point to a real climatic phenomenon as the cause of this anomaly and not a data artefact. Atmospheric model simulations are able to reproduce temperature and pressure patterns, consistent with a real and perhaps ocean-forced signal. Together with two volcanic eruptions just before and after the 1908–1911 period, the early 1900s provided a cold start into the ETCW. [ABSTRACT FROM AUTHOR]

The temperature profile is an important parameter of the atmospheric thermal state in atmospheric monitoring and weather forecasting. The hyperspectral infrared sounder of a geostationary satellite provides abundant spectral information and can retrieve the temperature profile. Based on the mediumwave channel data (independent variable and model input data) of FY-4A/GIIRS (geosynchronous interferometric infrared sounder) and ERA5 reanalysis data (dependent variable and model output data), the atmospheric temperature profile is retrieved by generalized ensemble learning. Firstly, the feature variables of the model are constructed. Because there are many GIIRS channels, a two-step feature selection method is adopted: step 1--establish a blacklist of GIIRS channels; step 2--select feature variables by using the method of importance permutation. Secondly, they are integrated based on optimizing and adjusting the hyperparameters of three basic machine learning models (Random Forest, XGBoost and LightGBM). Generalized ensemble learning nonlinear convex optimization is used to optimize the weight of each basic model. Finally, based on high-frequency GIIRS observations of Typhoon Lekima and Typhoon Higos, testing and method evaluation of the temperature profile retrievals are carried out. The results show that LightGBM achieves the best retrieval result among the three basic models, followed by Random Forest and finally XGBoost. The root-mean-square error of the whole temperature profile in the training dataset of generalized ensemble learning is less than 0.3 K, while that of the testing dataset is less than 1.4 K, and that between 150 hPa and 925 hPa is less than 1 K. The retrieval results correlate well with the radiosonde temperature profile. The performance of generalized ensemble learning is better than the performances of the three basic models, but it depends on the retrieval results of LightGBM. In the Lekima experimental case, compared to other channels selected for temperature retrieval models, the importance of mediumwave channels 9 and 307 of GIIRS ranks first and second, respectively. The method in this paper provides a new solution and technical support for retrieving atmospheric parameters from hyperspectral and other satellite data. [ABSTRACT FROM AUTHOR]

The experimental setup of HVAC testing requires easy but accurate instrumentation, and recent analyses focus on the control based on the mean radiant temperature in order to better perform respect to the users satisfaction. Indeed, the research contribution of this work is the use of Arduino to develop a PID control for an electric heater. As a main feature, this control system can operate by maintaining the set-point on the air temperature or on the mean radiant temperature of the environment where it is placed. The paper describes the design and development of the PID control, as well as the testing of the control system applied to an electric heater, to heat a room in a laboratory in Bologna (Italy). In an Appendix the Matlab script employed to store data on the local pc an to send data to Google Sheets is reported, together with the Google script code employed to write the data from Matlab to the online sheet. As result, the developed PID is accurate in maintaining the required set-point temperature, with minimal deviations from the set-point, in the interval ± 0.2 K. [ABSTRACT FROM AUTHOR]

The ERA5 climate reanalysis dataset plays an important role in applications such as monitoring and modeling climate system changes in polar regions, so the calibration of the reanalysis to ground observations is of great relevance. Here, we compare the 2 m air temperature time series of the ERA5 reanalysis and the near-surface bias-corrected reanalysis to the near-ground air temperature measured at 17 automatic weather stations (AWSs) in the McMurdo Dry Valleys, Antarctica. We find that the reanalysis data have biases that change with the season of the year and do not clearly correlate with elevation. Our results show that future work should rely on secondary observations to calibrate when using the ERA5 reanalysis in polar regions. [ABSTRACT FROM AUTHOR]

Glacial meltwater directly influences glacier dynamics. However, in the case of debris-covered glaciers, the drivers of glacier velocity and the influence of supraglacial lakes have not yet been sufficiently analysed and understood. We present a spatio-temporal analysis of key glacier characteristics for Baltoro Glacier in the Karakoram from October 2016 to September 2022 based on Earth observation data and climate parameters extracted from the High Asia Refined analysis (HAR) data set. For the glacier variables, we used surface velocity, supraglacial lake extent, melt of snow and ice, and proglacial run-off index. For climate variables, we focused on air temperature and precipitation. The surface velocity of Baltoro Glacier was characterized by a spring speed-up, summer peak, and fall speed-up with a relative increase in summer of 0.2–0.3 m d -1 (75 %–100 %) in relation to winter velocities, triggered by the onset of or an increase in basal sliding. Snow and ice melt have the largest impact on the spring speed-up, summer velocity peak, and the transition from inefficient to efficient subglacial drainage. The melt covered up to 64 % (353 km 2) of the entirety (debris-covered and debris-free) of Baltoro Glacier and reached up to 4700 m a.s.l. during the first melt peak and up to 5600 m a.s.l. during summer. The temporal delay between the initial peak of seasonal melt and the first relative velocity maximum decreases downglacier. Drainage from supraglacial lakes (3.6–5.9 km 2) contributed to the fall speed-up, which showed a 0.1–0.2 m d -1 (20 %–30 %) lower magnitude compared to the summer velocity peak. Most of the run-off can be attributed to the melt of snow and ice. However, from mid-June onward, the lakes play an increasing role, even though their contribution is estimated to be only about half of that of the melt. The observed increase in summer air temperatures leads to a greater extent of melt, as well as to a rise in the number and total area of supraglacial lakes. This tendency is expected to intensify in a future warming climate. [ABSTRACT FROM AUTHOR]

The present study to quantify the variations in microclimate under wheat, mustard and chickpea crops was conducted at ICAR-Indian Institute of Farming Systems Research, Modipuram, Meerut (U.P.), India. Air temperature, relative humidity and CO2 concentration below and above the canopies of wheat, mustard and chickpea were recorded at hourly interval from 07:30 to 17:30 hours at different heights (0.5 m, 1.0 m and 2.0 m) from the ground. CO2 probes like GMP-343, (Diffusion aspiration) was used to record data of CO2 concentration and HPM-75 probes was used to capture the observation of air temperature and relative humidity. Results revealed that diurnal air temperature was continuously increasing from morning to afternoon hrs and highest air temperature was recorded at 13:30 hrs (afternoon). Thereafter, air temperature decreased and reached to the lowest at 17:30 hrs irrespective of crops and height from the ground. Analysis of diurnal air temperature variations at different height clearly showed that tall statured crop such as wheat and mustard reached higher air temperature regime early (13.30 hrs) compared to short statured crop like chickpea at 15.30 hrs. Highest relative humidity was observed at 07.30 hrs and lowest relative humidity was recorded either at 13:30 hrs or at 15:30 hrs. As per study maximum CO2 concentration was found at 07:30 hrs morning and minimum at 15:30 hrs. The lowest concentration of CO2 (624 ppm) was recorded from the chickpea field and highest from the mustard field (630 ppm) at the same point of observation during vegetative phase of crops. [ABSTRACT FROM AUTHOR]

The ability to accurately identify fire patterns is the fundamental requirement for fire investigations. The corrosion layers of steel in fire scenes exhibit three distinct characteristics. First, due to steel's nonflammable nature, steel patterns can be preserved better at the fire site than patterns formed on other combustible materials; second, both the high temperature and the smoke during the fire affect the high‐temperature oxidation process; and third, the corrosion layer of steels inevitably undergoes further evolution after the fire because of the subsequent room‐temperature corrosion. This study focuses on investigating Q235 steel because of its extensive use in construction and vehicles. The pattern evolution processes of high‐temperature oxidation at elevated temperatures in air, polyethylene (PE), and polyvinyl‐chloride (PVC) combustion smoke and the corresponding subsequent corrosion at room temperature were systematically investigated from the perspective of macroscopic and microscopic morphology. The results showed that the smoke atmosphere played an important role in the formation of the corrosion layer of Q235 steel. Compared with samples oxidized in air, samples oxidized in PE combustion smoke exhibited a uniform and dense oxide layer on the surface, which inhibited the corrosion at room temperature further. The PVC combustion smoke accelerated the high‐temperature oxidation of the sample, and its influence on the subsequent room‐temperature oxidation process was closely correlated with the temperature of the high‐temperature oxidation. The results of this study provide important references for understanding the formation of the corrosion layer of Q235 steel for fire investigations. [ABSTRACT FROM AUTHOR]

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics. Plain Language Summary: Estimating air temperature at street‐level is a difficult task because of the complex environment in cities and the limitations of the current urban numerical models. In recent years, with the rapid development of data collection and analysis techniques, it is possible to fully utilize the hyper‐local data harvested from urban areas by advanced machine learning algorithms. In this study, we present a modeling pipeline to estimate point‐scale street‐level air temperature from conventional urban weather model and a suite of hyper‐resolution urban data sets. These data sets were collected using state‐of‐art techniques, such as sub‐meter level Light Detection and Ranging technology and wireless weather observation network. We demonstrated the use of this modeling method over the City of Chicago and estimated the street‐level temperature. The modeling results have multiple real‐world applications, such as to provide navigation suggestions to reduce thermal discomfort of the pedestrians as an example. Moreover, it is possible to expand the use of our model to other areas given the current data availability. The results of this study can also help the development of the next‐generation urban climate and weather models and guide observation efforts in cities. These together can build the strength for the holistic understanding of urban microclimate dynamics. Key Points: The study presents a modeling framework to estimate street‐level air temperature using a suite of detailed urban climate informaticsModel results showed hyper‐local urban features have significant impacts on street‐level temperature but with a limited influence radiusThe investigations on model sensitivity implies the existence of the optimum scale in urban modeling and critical locations in observation [ABSTRACT FROM AUTHOR]

Physical and climatic variables such as Tree Canopy coverage, Normalized Difference Vegetation Index (NDVI), Distance to Roads, Distance to the Coast, Impervious Surface, and Precipitation can affect land surface temperature (LST). This paper examines the relationships using linear regression models and explores LST trends in the Miami Statistical Area (MSA) between 2002 and 2021. This study evaluates the effect of dry and wet seasons as well as day and night data on LST. A multiscale investigation is used to examine LST trends at the MSA scale, the individual county level, and at the pixel level to provide a detailed local perspective. The multiscale results are needed to understand spatiotemporal LST distributions to plan mitigation measures such as planting trees or greenery to regulate temperature and reduce the impacts of surface urban heat islands. The results indicate that LST values are rising in the MSA with a positive trend throughout the 20-year study period. The rate of change (RoC) for the wet season is smaller than for the dry season. The pixel-level analysis suggests that the RoC is primarily in rural areas and less apparent in urban areas. New development in rural areas may trigger increased RoC. This RoC relates to LST in the MSA and is different from global or regional RoC using air temperature. Results also suggest that climatic explanatory variables have different impacts during the night than they do in the daytime. For instance, the Tree Canopy variable has a positive coefficient, while during the day, the Tree Canopy variable has a negative relationship with LST. The Distance to the Coast variable changes from day to night as well. The increased granularity achieved with the multiscale analysis provides critical information needed to improve the effectiveness of potential mitigation efforts. [ABSTRACT FROM AUTHOR]