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Coral reefs are facing severe threats and are at risk of accelerated decline due to climate change‐induced changes in their environment. Ongoing efforts to understand the mechanisms of coral response to warming rely on multiple sources of temperature data. Yet, it remains uncertain whether the Sea Surface Temperature (SST) data used for coral reef studies are consistent among different data products, despite potential implications for conservation. A better understanding of the consistency among the different SST data applied to coral reefs may facilitate the fusion of data into a standard product. This will improve monitoring and understanding of the impact of global warming on coral reefs. Four types of SST data across North‐Western and South‐Western Australia are compared to assess their differences and ability to observe high thermal stress during historical coral bleaching events. The four SST data sources included those derived from Global Circulation Models, NOAA CoralTemp SST product, ESA CCI SST product, and coral core derived SST. Coral bleaching risk indicators, Degree Heating Week (DHW), and Degree Heating Month (DHM) were calculated using these sources and compared for consistency. DHW and DHM were inconsistent among data sets and did not accurately reflect high thermal stress metrics during moderate and severe bleaching events. Some reefs did not experience bleaching in spite of high DHWs and DHMs, suggesting a mismatch in data scales, or perhaps other oceanographic factors and coral adaptation. By exploring the differences and similarities among these four data sources, this study highlights the need to compare existing indicators of thermal stress from different data sets. Plain Language Summary: Climate change and warming have resulted in global coral bleaching events, severely compromising our environment's health. Monitoring the changes in ocean temperatures around them is essential to maximizing our efforts to protect them. Different ocean temperature data products exist and are being used without understanding their differences. To highlight these differences, the present study compares historical warming from climate models and remote and in situ sensors and known bleaching events on five reefs across Western Australia. Key Points: Temperature data sources did not provide consistent risk indicators for coral bleachingAcross five reefs, coral bleaching risk indicators differed in their ability to predict the observed coral bleaching eventsTemperature data in daily and monthly temporal resolutions differed in the accuracy of coral bleaching risk indicators [ABSTRACT FROM AUTHOR]

Direct functionalization of alkenes with C(sp3)–H substrates offers unique opportunities for the rapid construction of pharmaceuticals and natural products. Although significant progress has been made over the past decades, the development of green, high step-economy methods to achieve these transformations under mild conditions without the need for pre-functionalization of C(sp3)–H bonds remains a substantial challenge. Therefore, the pursuit of such methodologies is highly desirable. Recently, the direct activation of C(sp3)–H bonds via photocatalytic hydrogen atom transfer (HAT), especially from unactivated alkanes, has shown great promise. Given the potential of this approach to generate a wide range of pharmaceutically relevant compounds, this review highlights the recent advancements in the direct functionalization of alkenes through photocatalytic HAT from C(sp3)–H compounds, as well as their applications in the synthesis and diversification of drugs, natural products, and bioactive molecules, aiming to provide medicinal chemists with a practical set of tools. [ABSTRACT FROM AUTHOR]

Bivalves play a key role in coastal ecosystems by supporting food web, modifying habitats, and their economic value for fisheries. Many bivalve species are under pressure, showing large variations in population sizes and distributions, with climate change and human activities considered as important drivers. The Dutch North Sea hosts high densities of bivalve species, dominated by the cut trough shell Spisula subtruncata , with strong interannual variations and a patchy distribution. To explore the causes of this variation, data of an extensive long-term spatial benthic monitoring program (1995-2021) was analysed using a Bayesian spatio-temporal hurdle model. We considered indicators related to human activities, biological processes, climate change and habitat preference as explanatory variables for the observed long-term temporal and spatial variations. Results revealed that medium sediment grain size was key determinant of S. subtruncata occurrence and density. Increasing sea water temperatures during winter and the post-settlement phase positively affected annual population densities, while strong north-westerly winds led to lower densities. These climate change related factors had an overall positive effect on this species in the region. Human activities like shellfish dredging and sand nourishment had no measurable impact. However, shrimp and flatfish beam trawling overlapped with S. subtruncata occurrence and were negatively related to densities, suggesting higher beam trawling intensity in these areas may negatively impacts densities. Overall, the effects were stronger at medium to finer sediments where the highest densities occurred, indicating a strong habitat-dependent effect. Despite identifying multiple drivers, unexplained annual variation suggests other not included factors like predation pressure, also play a role. More detailed studies on the combined effects of climate change-driven environmental stressors and human activities are needed to fully understand the population dynamics. This knowledge is essential for developing more adequate fisheries and coastal management strategies to sustain biodiversity. [ABSTRACT FROM AUTHOR]

Nanopore sequencing harnesses changes in ionic current as nucleotides traverse a nanopore, enabling real-time decoding of DNA/RNA sequences. The instruments for the dynamic behavior of substances in the nanopore on the molecular scale are still very limited experimentally. This study employs all-atom molecular dynamics (MD) simulations to explore the impact of charge densities on graphene nanopore in the translocation of single-stranded DNA (ssDNA). We find that the magnitude of graphene's charge, rather than the charge disparity between ssDNA and graphene, significantly influences ssDNA adsorption and translocation speed. Specifically, high negative charge densities on graphene nanopores are shown to substantially slow down ssDNA translocation, highlighting the importance of hydrodynamic effects and electrostatic repulsions. This indicates translocation is crucial for achieving distinct ionic current blockades, which plays a central role for DNA sequencing accuracy. Our findings suggest that negatively charged graphene nanopores hold considerable potential for optimizing DNA sequencing, marking a critical advancement in this field. [ABSTRACT FROM AUTHOR]

The aim of the study is to identify the variables relating to the management of labour relations and conflicts that occur within hotel companies and how these enable the generation of employee engagement. A quantitative approach is presented in which a multiple linear regression is used to identify those variables with the greatest influence in making the people who make up the organisation feel committed to it. The tool used to collect information was a questionnaire made up of 56 items measured on a Likert scale and completed by workers with at least 5 years' experience in the sector. Among the variables that generate greater engagement, the following stand out: feeling informed, the possibility of reconciling work and family life, fair pay, pride in belonging, a clear vision of the job or the option of complaining in the event of unfair treatment. There is scope for companies to increase this engagement by including social benefits, the possibility of teleworking or emotional pay. [ABSTRACT FROM AUTHOR]

Today, American tech actors express optimistic ideas about how to fix the Earth and halt climate change. Such "green" initiatives have in common that they capture the world in systems and propose large systemic, and mostly technological, solutions. Because of their reliance on techno-fixes, representatives of Silicon Valley express an ideology of ecomodernism, which believes that human progress can be "decoupled" from environmental decline. In this article, I show how "whole-systems thinking" has become a key discursive element in today's ecomodernist discourses. This discourse has developed from the 1960s onwards – inspired by cybernetic, ecological and computational theories – within the tech culture of California. This paper discusses three key periods in this development, highlighting key publications: the Whole Earth Catalog of the 1960s, the Limits to Growth report in 1972 and the cyberspace manifestoes of the mid 1990s. These periods are key to understand how techno-fixes became a popular answer to the climate crisis, eventually leading to a vision of the world as an ecosystem that can be easily controlled and manipulated, and of technological innovation as harmless and beneficial. I argue that "whole-systems" thinking offers a naive and misleading narrative about the development of the climate crisis, that offers a hopeful yet unrealistic perspective for a future threatened by climate change, built on a misconception of Earth as a datafied planet. [ABSTRACT FROM AUTHOR]

In the social sciences literature, experimentation in civil society as in food co-ops, urban gardens, repair cafés, or sharing platforms is widely considered as promising to address mounting socio-ecological problems. But is this confidence justified at a point in time when fundamental change is more urgent than ever? After all, these forms of experimentation have a history that reaches back to the very beginnings of environmentalism. Why should they trigger a comprehensive socio-ecological transformation today, if they have not done so in the past? For academic confidence in transformative change through experimentation to be plausible, at least one of two conditions would have to be fulfilled: either academic accounts plausibly demonstrate that the meanings and functions of present experiments fundamentally differ from those in the past. Or these accounts convincingly show that societal context conditions today are much more favourable for transformative change through experimentation than in the past. To assess whether or to what extent at least one of these conditions is fulfilled, we pursue a comparative analysis of past and present discourses on eco-political experimentation in civil society and a conjunctural analysis of current context conditions for transformative change through experimentation. Our findings suggest that neither the criterion of substantial difference nor that of favourable context conditions is fulfilled. For this reason, the current academic trust in transformative change through experimentation, arguably, remains implausible. Hence, we caution against spreading hope when doubt seems in order, for unwarranted narratives of hope may come with an unintended side-effect: 'sustaining the unsustainable.' [ABSTRACT FROM AUTHOR]

This study presents an inclusive K-12 AI curriculum for elementary schools, focusing on six design principles to address gender disparities. The curriculum, designed by the researchers and an elementary teacher, uses tangible tools, and emphasizes collaboration in solving daily problems. The MANOVA results revealed initial gender differences in AI knowledge. Following MANCOVA analysis showed significant improvements in AI knowledge, as well as perceptions and behavioral intentions toward AI, effectively bridging the observed knowledge gaps without any significant differences attributed to gender or initial knowledge levels. This evidence underscores the success of tangible and collaborative AI interventions in uniformly enhancing AI knowledge and positively changing perceptions and behavioral intentions among all participants, regardless of gender. Both female and non-binary students felt increased engagement and reduced anxiety toward AI, with improved comprehension and a preference for collaborative learning. This study contributes to the design of inclusive AI interventions, highlighting gender differences and including non-binary students as an essential part of the analysis. [ABSTRACT FROM AUTHOR]

Extremes in lake surface water temperature can have profound impacts on ecosystems. Although extensive research has been conducted on lake heatwaves, little is known about cold‐water extremes, referred to as lake cold spells. Here, we employ a numerical lake model to investigate global lake cold spell dynamics from 1979 to 2100. From 1979 to 2022, lake cold spells have become shorter‐lasting and weaker. Change rates in the occurrence (i.e., total days) and intensity of lake cold spells are −3.96 days decade−1 and 0.26°C decade−1, respectively. In Europe, the decline in lake cold spells is due to increases in the mean of surface water temperatures, whereas in North America, the reduction is due to decreases in the variance of surface water temperature. In the future, lake cold spells will shorten by 19.3 days and weaken by 1.97°C in the end of the 21st century under the high‐greenhouse‐gas‐emission scenario, underscoring a shift in the surface temperature regime that may have an important influence on lake ecosystems. Plain Language Summary: There is a universal warming trend in lake surface water temperature (LSWT), which is causing an increase in lake heatwaves. However, it is unclear how extreme cold‐water events (i.e., lake cold spells) varies in the worldwide. Here, we found that lake cold spells have shortened and weakened in recent decades, and this trajectory are expected to continue under the influence of climate change. We discovered that the statistical features of LSWT, specifically the mean and variance, have a great influence in driving changes in lake cold spells. Our research provides a systematic view of cold extremes in lake surface water, highlighting the vulnerability of lake ecosystems to climate change. Key Points: Lake cold spells have declined from 1979 to 2022Mean and variance of surface water temperature drive the changes in lake cold spellsContinued shortening and weakening of lake cold spells are expected in the late of 21st century [ABSTRACT FROM AUTHOR]

Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Machine learning models can help identify dominant environmental controllers and establish their functional relationships with SOC stocks. The resulting knowledge can be integrated into ESMs to reduce uncertainty and improve predictions of SOC dynamics over space and time. In this study, we used a large number of SOC field observations (n=54 000), geospatial datasets of environmental factors (n=46), and two machine learning approaches (namely random forest, RF, and generalized additive modeling, GAM) to (1) identify dominant environmental controllers of global and biome-specific SOC stocks, (2) derive functional relationships between environmental controllers and SOC stocks, and (3) compare the identified environmental controllers and predictive relationships with those in models used in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Our results showed that the diurnal temperature, drought index, cation exchange capacity, and precipitation were important observed environmental predictors of global SOC stocks. While the RF model identified 14 environmental factors that describe climatic, vegetation, and edaphic conditions as important predictors of global SOC stocks (R2=0.61 , RMSE = 0.46 kg m−2), current ESMs oversimplify the relationships between environmental factors and SOC, with precipitation, temperature, and net primary productivity explaining > 96 % of the variability in ESM-modeled SOC stocks. Further, our study revealed notable disparities among the functional relationships between environmental factors and SOC stocks simulated by ESMs compared with observed relationships. To improve SOC representations in ESMs, it is imperative to incorporate additional environmental controls, such as the cation exchange capacity, and refine the functional relationships to align more closely with observations. [ABSTRACT FROM AUTHOR]

Cloud fraction as a vital component of meteorological satellite products plays an essential role in environmental monitoring, disaster detection, climate analysis and other research areas. Random forest (RF) and multilayer perceptron (MLP) algorithms were used in this paper to retrieve the cloud fraction of AGRI (Advanced Geosynchronous Radiation Imager) on board the Fengyun-4A (FY-4A) satellite based on its full-disk level-1 radiance observation. Corrections have been made subsequently to the retrieved cloud fraction in areas where solar glint occurs using a correction curve fitted with sunglint angle as weight. The algorithm includes two steps: the cloud detection is conducted firstly for each AGRI field of view to identify whether it is clear sky, partly cloudy or overcast within the observation field. Then, the cloud fraction is retrieved for the scene identified as partly cloudy. The 2B-CLDCLASS-lidar cloud fraction product from the CloudSat and CALIPSO active remote sensing satellite is employed as the truth to assess the accuracy of the retrieval algorithm. Comparison with the operational AGRI level-2 cloud fraction product is also conducted at the same time. The results indicate that both the RF and MLP cloud detection models achieved high accuracy, surpassing that of operational products. However, both algorithms demonstrated weaker discrimination capabilities for partly cloudy conditions compared to clear-sky and overcast situations. Specifically, they tended to misclassify fields of view with low cloud fractions (e.g., cloud fraction = 0.16) as clear sky and those with higher cloud fractions (e.g., cloud fraction = 0.83) as overcast. Between the two models, RF exhibited higher overall accuracy. Both RF and MLP models performed well in cloud fraction retrieval, showing lower mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) compared to operational products. The ME for both RF and MLP cloud fraction retrieval models was close to zero, while RF had slightly lower MAE and RMSE than MLP. During daytime, the high reflectance in sunglint areas led to larger retrieval errors for both RF and MLP algorithms. However, after correction, the retrieval accuracy in these regions improved significantly. At night, the absence of visible light observations from the AGRI instrument resulted in lower classification accuracy compared to daytime, leading to higher cloud fraction retrieval errors during nighttime. [ABSTRACT FROM AUTHOR]

The study proposes an approach to elucidate spatiotemporal mesoscale variations of seawater Dimethylsulfide (DMS) concentrations, the largest natural source of atmospheric sulfur aerosol, based on the Gaussian Process Regression (GPR) machine learning model. Presently, the GPR was trained and evaluated by nested cross-validation across the warm-oligotrophic Mediterranean Sea, a climate hot spot region, leveraging the high-resolution satellite measurements and Mediterranean physical reanalysis together with in-situ DMS observations. The end product is daily gridded fields with a spatial resolution of 0.083° × 0.083° (~9 km) that spans 23 years (1998–2020). Extensive observations of atmospheric methanesulfonic acid (MSA), a typical biogenic secondary aerosol component from DMS oxidation, are consistent with the parameterized high-resolution estimates of sea-to-air DMS flux (FDMS). This represents substantial progress over existing coarse-resolution DMS global maps which do not accurately depict the seasonal patterns of MSA in the Mediterranean atmospheric boundary layer. [ABSTRACT FROM AUTHOR]

Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving in response to changing weather, season, climate, and ice dynamics. However, current digital elevation models (DEMs) for the ice sheet are usually based on data from a multi-year period, thus obscuring these changes over time. Here we present four 500 m resolution summer DEMs (PRODEMs) of the Greenland Ice Sheet marginal zone for 2019 through 2022. The PRODEMs cover the marginal zone from the ice edge to 50 km inland, hence capturing all Greenland outlet glaciers. Each PRODEM is based on data fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry using regionally varying kriging of elevation anomalies relative to ArcticDEM. The PRODEMs are validated using leave-one-out cross-validation, and PRODEM19 is further validated against an external data set, showcasing their ability to correctly represent surface elevations within the associated spatially varying prediction uncertainties. We observe a general lowering of surface elevations during the 4-year PRODEM period, but the spatial pattern of change is highly complex and with annual changes superimposed. The PRODEMs enable detailed studies of the marginal ice sheet elevation changes. With their high spatio-temporal resolution, the PRODEMs will be of value to a wide range of researchers and users studying ice sheet dynamics and monitoring how the ice sheet responds to changing environmental conditions. PRODEMs from summer 2019 through 2022 are available at 10.22008/FK2/52WWHG (Winstrup, 2024), and we plan to annually update the product henceforth. [ABSTRACT FROM AUTHOR]

The ATL2MED demonstration experiment involved two autonomous surface vehicles from Saildrone Inc. (SD) which travelled a route from the eastern tropical North Atlantic to the Adriatic Sea between October 2019 and July 2020 (see Table A6). This 9-month experiment in a transition zone between the temperate and tropical belts represents a major challenge for the SD's operations. The sensors on board were exposed to varying degrees of degradation and biofouling depending on the geographical area and season, which led to a deterioration in the measurements. As a result, some maintenance measures were required during the mission. We address the difficulty of correcting the data during a period of COVID-19 restrictions, which significantly reduced the number of discrete samples planned for the SD salinity and dissolved oxygen validation. This article details alternative correction methods for salinity and dissolved oxygen. Due to the lack of in situ data, model products have been used to correct the salinity data acquired by the SD instruments, and then the resulting corrected salinity was validated with data from fixed ocean stations, gliders, and Argo floats. In addition, dissolved oxygen data acquired from the SD instruments after correction using air oxygen measurements were tested and found to be coherent with the variation in oxygen concentrations expected from changes in temperature and phytoplankton abundance (from chlorophyll a). The correction methods are relevant and useful in situations where validation capabilities are lacking, which was the case during the ATL2MED demonstration experiment. For future experiments, a more frequent sample collection would improve the data qualification and validation. [ABSTRACT FROM AUTHOR]

The geography of changes in the fluxes of heat, carbon, freshwater and other tracers at the sea surface is highly uncertain and is critical to our understanding of climate change and its impacts. We present a state estimation framework wherein prior estimates of boundary fluxes can be adjusted to make them consistent with the evolving ocean state. In this framework, we define a discrete set of ocean water masses distinguished by their geographical, thermodynamic and chemical properties for specific time periods. Ocean circulation then moves these water masses in geographic space. In phase space, geographically adjacent water masses are able to mix together, representing a convergence, and air–sea property fluxes move the water masses over time. We define an optimisation problem whose solution is constrained by the physically permissible bounds of changes in ocean circulation, air–sea fluxes and mixing. As a proof-of-concept implementation, we use data from a historical numerical climate model simulation with a closed heat and salinity budget. An inverse model solution is found for the evolution of temperature and salinity that is consistent with "true" air–sea heat and freshwater fluxes which are introduced as model priors. When biases are introduced into the prior fluxes, the inverse model finds a solution closer to the true fluxes. This framework, which we call the optimal transformation method, represents a modular, relatively computationally cost-effective, open-source and transparent state estimation tool that complements existing approaches. [ABSTRACT FROM AUTHOR]

This paper examines a ground-breaking innovation to medieval Easter plays: the creation of the extra-biblical merchant scene, in which the Marys purchase spices prior to their Visitatio Sepulchri. The patron of its earliest known representation was the female religious leader Uta von Kirchberg. An illuminated roundel in the Uta Codex she commissioned towards the end of her term as abbess of Niedermünster (1002–25), depicts the Holy women purchasing spices from a spice merchant. Until the twelfth century, this remained the only representation of an Easter merchant scene, visual or textual. The only textual Easter merchant scene predating the thirteenth century is within the twelfth-century Latin/Catalan Ludus Paschalis of Vic Cathedral, near Barcelona, a highly influential Easter text whose transnational impact has been traced in numerous later Easter texts across Europe, including many with merchant scenes. Around 2000, musicologists David Wulstan and Constant Mews suggested the renowned composer and poet Heloise (c. 1090s–1164) as its author. Widely accepted by musicologists, their attribution's significance for the female impact on the merchant scene is barely acknowledged. Here, I ask: 'how did women influence the creation, promotion and development of the merchant scene's visual, textual and performative manifestations?' By repeatedly reattributing responsibility for decisive input into the development of the merchant scene from anonymous male scribes to identified female religious leaders, my interdisciplinary analysis moves women to the centre of this creative process. [ABSTRACT FROM AUTHOR]

This viewpoint article considers the roles of women's voices, conflicts, and activism in the protection of natural resources in India. This Indian environmentalism could be viewed as part of the ecofeminist movement because of the strong evidence supporting the relationships between women's voices and environmental protection. Through various historical storylines, women have increased their resistance to environmental degradation. In precolonial India, protecting khejri trees originally emerged as a dominant ecological storyline. After independence, the advancement of the same ecological storyline led to the formulation of environmental policies and the creation of a social storyline to defend the rights of women and Adivasis. In the neoliberal age, climate change has become another dominant storyline challenging world leaders to take climate action. This article discusses how these women leaders and child activists spearheaded ethnic-based environmentalism by means of powerful storylines and arguments within the wider environmental discourse in India. [ABSTRACT FROM AUTHOR]

In mid-March 2022, a Siberian High brought intense cold air masses, leading to severe weather conditions across southern Europe, including the Black Sea region. This study investigates the spatial and temporal evolution of cold intermediate water (CIW) masses in the Black Sea, with a particular focus on the successive anomalously cold episodes that occurred in March 2022. The research underscores the significance of the northwestern continental slope and cyclonic gyres, especially as the only cold-water mass observations during the warm winters of 2020 and 2021 were concentrated in these areas. Following two warm winters, the cold episodes of March 2022 revealed notable convection and simultaneous cooling, particularly in the cyclonic interior and the Rim Current periphery, excluding the northeastern periphery. Subsequently, cold waters spreading isopycnally throughout the summer months were transported laterally and reached these regions. Argo float measurements provided clear evidence of widespread replenishment of the CIW, indicating that it is not confined to specific areas. The study also highlights regional variability in the characteristics of CIW formation, which is influenced by local dynamics and preconditioning temperatures. The temperatures of CIW increased from west to east, in line with the sea surface temperature gradient. Notably, thicker and colder CIW was found in the western cyclonic gyre compared to the eastern cyclonic area. Furthermore, the study confirms that the warming trend in CIW, identified in previous research, not only continues but has intensified during the recent period analyzed. These findings, observed under the extreme conditions analyzed in this research, offer valuable insights into the widespread occurrence of CIW formation in the Black Sea. Additionally, the study confirms that the warming trend in CIW, identified in previous studies, continued in the region throughout the warm winter period and after the cold spell in 2022. These insights contribute to a deeper understanding of CIW dynamics and their response to extreme weather events in the Black Sea. [ABSTRACT FROM AUTHOR]

The TEROS 10 and TEROS 12 are widely used capacitance‐based sensors for measuring volumetric water content (θv${{\theta }_v}$), but few systematic studies of the measurement volume and accuracy of these sensors have been published. The objectives of this study were to (1) calibrate and validate these sensors in mineral soils, (2) determine the sensing volume of each sensor, and (3) evaluate the temperature sensitivity of the sensors. Both sensors were calibrated in the laboratory using columns of packed soil at multiple moisture levels from air‐dry to near saturation. Sensors were validated using additional laboratory and field measurements. The sensing volume was determined by quantifying the response of raw sensor outputs while increasing the level of oven‐dry sand, moist sand (0.100 cm3 cm−3), or water around the sensor in the radial and axial directions. Temperature sensitivity was tested in controlled conditions over a range of temperatures from 2°C to 40°C using encapsulated sensors in packed soil columns at constant θv${{\theta }_{v}}$. Linear calibration models resulted in mean absolute error ≤0.030 cm3 cm−3 for both sensors during laboratory and field validations. In moist sand, the sensing volume contributing 95% of the maximum sensor response was 439 cm3 for the TEROS 10 and 423 cm3 for the TEROS 12. Both sensors exhibited changes in θv${{\theta }_v}$ of ≤0.02 cm3 cm−3 when subjected to a temperature change from 2°C to 40°C. For the soils considered here, both sensors demonstrated accuracy that is likely sufficient for a variety of agricultural and hydrological applications. Core Ideas: A linear calibration equation provided mean absolute error (MAE) ≤0.030 cm3 cm−3 for both the TEROS 10 and TEROS 12 sensors.TEROS 10 sensing volume in moist sand ranged from 439 to 1741 cm3 depending on the stopping criterion.TEROS 12 sensing volume in moist sand ranged from 423 to 1825 cm3 depending on the stopping criterion.TEROS 10 and TEROS 12 sensors had small (≤0.02 cm3 cm−3) changes in water content due to soil thermal oscillations. [ABSTRACT FROM AUTHOR]

Satellite remote sensing is the best way to derive sea surface skin temperature (SSTskin) in the Arctic. However, as surface temperature retrieval algorithms in the infrared (IR) part of the electromagnetic spectrum are designed to compensate for atmospheric effects mainly due to water vapor, MODIS SSTskin retrievals have larger uncertainties at high latitudes where the atmosphere is very dry and cold, which is an extreme in the distribution of global conditions. MODIS R2019 SSTskin fields are currently derived using latitudinally and monthly dependent algorithm coefficients, including an additional band above 60°N to better represent the effects of Arctic atmospheres. However, the R2019 processing of MODIS SSTskin still has some unrevealed error characteristics. This study uses 21 years (2002–2022) of collocated, simultaneous satellite brightness temperature (BT) data from Aqua MODIS and in situ buoy-measured subsurface temperature data from iQuam for validation. Unlike elsewhere over the oceans, the 11 μm and 12 μm BT differences are poorly related to the column water vapor at high latitudes, resulting in poor atmospheric water vapor correction. Anomalous BT difference signals are identified, caused by the temperature and humidity inversions in the lower troposphere, which are especially significant during the summer. Although the existence of negative BT differences is physically reasonable, this makes the retrieval algorithm lose its effectiveness. Moreover, the statistics of the MODIS SSTskin data when compared with the iQuam buoy temperature data show large differences (in terms of mean and standard deviation) for the matchups at the Northern Atlantic and Pacific sides of the Arctic due to the disparity of in situ measurements and distinct surface and vertical atmospheric conditions. Therefore, it is necessary to further improve the retrieval algorithms to obtain more accurate MODIS SSTskin data to study surface ocean processes and climate change in the Arctic. [ABSTRACT FROM AUTHOR]

Statement of the problem: The concentration of medical students in the classroom is important in promoting their mastery of knowledge. Multiple teaching characteristics, such as speaking speed, voice volume, and question use, are confirmed to be influential factors. Purpose: This research aims to analyze how teachers' linguistic characteristics affect medical students' classroom concentration based on a speech recognition toolkit and face recognition technology. Materials and methods: A speech recognition toolkit, WeNet, is used to recognize sentences during lectures in this study. Face recognition technology (FRT) is used to detect students' concentration in class. The study involved 80 undergraduate students majoring in stomatology. The classroom videos of 5 class hours in the dental anatomy course were collected in October 2022. A quantitative research methodology is used in this study. Pearson correlation, Spearman correlation and multiple linear regression analyses were used to analyze the impact of time and teachers' linguistic characteristics on students' concentration. Results: As a result of regression analysis, the explanatory power of the effect of the linguistic characteristics was 7.09% (F = 83.82, P < 0.001), with time, volume and question being significant influencing factors (P < 0.01). The local polynomial smooth of the scatter between the concentration degree and the use of questions with time appears to fluctuate cyclically and suggests a potential inverse relationship between the use of questions and the concentration degree. Conclusions: The results of this study support the significant positive influence of volume and questioning technique, the negative influence of time, and the insignificant influence of speaking speed and the interval between sentences on students' concentration. This study also suggested that teachers may adjust their questioning frequency based on their observation of students' concentration. [ABSTRACT FROM AUTHOR]

Leveraging the Copernicus high‐resolution multi‐year Mediterranean Sea Surface Temperature (SST) dataset, 15 selected tropical‐like cyclones (TLCs) are analyzed with the objective of elucidating the anomalies of SST at the time of cyclogenesis and the connection between the change in SST during the cyclone lifetime and its characteristics. The long‐term SST increase associated with climate change is identified by comparing detrended and original anomalies. Detrending removes the effect of the intensification of SST anomaly over time, revealing that no significant anomalies generally emerge in the early stages of the TLC lifetimes. Conversely, winter events exhibit early‐stage positive SST anomalies. Also, high SST values were observed during the intensification of the most intense cyclones. A cold SST anomaly is left after the passage of the cyclones, due to the intense sea surface fluxes extracting heat from the sea. Plain Language Summary: Mediterranean tropical‐like cyclones are severe weather events able to produce large socio‐economic and environmental impact, as well as considerable damage. On average, 1.5 such events affect the Mediterranean each year. In this study we assess the Sea Surface Temperature conditions related to the events reported in the literature of the past four decades. We use a high‐resolution multi‐year SST dataset over the Mediterranean Sea, to reveal the potential relationship between the change in SST before and during the cyclone's lifetime and their features. Our results show that SST plays an important role in the intensification phases of the events, while no significant SST anomaly emerges in the early stages for most of the cyclones. Key Points: No significant SST anomalies are found at the early stage of medicanes, except for the winter cases that exhibit a positive anomalySST value is particularly high for the most intense cyclones (September cases)The passage of the cyclones over the sea induces a cooling mainly during their mature phase [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) represent anomalously warm temperature conditions of seawater that may affect marine life and ocean biogeochemistry. Under such conditions, phytoplankton communities may modify their structure and functions, and their resilience is not assured. This study characterizes the impact of MHWs on the phytoplankton spring bloom in the North‐Western Mediterranean Sea. Here, we synergistically combine autonomous observations from BioGeoChemical‐Argo floats, satellite‐based and marine ecosystem model data, and show that MHW events occurring during winter drastically inhibit phytoplankton carbon biomass in spring by up to 70%. Such reduction is related to the enhanced stratification of the water column under MHWs which hinders the renewal of nutrients from deep‐ocean reservoirs, thus preventing surface phytoplankton from blooming. This process negatively impacts particulate organic carbon stocks within the mixed layer, while severe events cause an earlier shift of phytoplankton phenology that provokes changes in zooplankton biomass distribution. Plain Language Summary: Marine heatwaves (MHWs) are described as an abnormal and prolonged increase of ocean temperatures. These events may occur in all the oceans, and are becoming more frequent than before. Such increase in water temperature might not be tolerated by organisms, which must need to adapt themselves to the new environmental conditions. Consequently, marine ecosystem health is endangered. Here, we analyze the effect that MHWs have on the growth of small algae called phytoplankton. Phytoplankton are vital microscopic organisms for ecosystems that use sunlight to produce organic carbon through photosynthesis. At middle and high latitudes, phytoplankton massively grows (i.e., blooms) once a year at the sea surface, and introduces a major carbon flux into the ecosystem that sustains larger animals. Through combining observations acquired by different platforms (satellites, autonomous in situ BioGeoChemical‐Argo robots, and ecosystem models), we comprehensively study how MHWs affect phytoplankton carbon production during spring blooms and trophic chains at mid‐latitudes. Results show that MHW events occurring in winter lead to a large decrease in phytoplankton carbon biomass (up to 70%) in spring. Winter MHW events, driven by local atmospheric conditions, intensify water column stratification thus hindering the deep‐ocean nutrient transport to the surface, which is essential for phytoplankton to bloom. Key Points: Marine heatwaves (MHWs) intensify water stratification leading to reduction in nutrient supply which inhibits surface phytoplankton spring bloomMHWs lead to a phytoplankton community shift toward smaller cells, while increasing the transparency of surface watersMHWs decrease carbon stocks within the mixed layer, while intense ones shift phytoplankton phenology and affect zooplankton [ABSTRACT FROM AUTHOR]

Introduction: Colon cancer presents significant surgical challenges that necessitate the development of precise strategies. Standardization with complete mesocolic excision (CME) is common, but some cases require extended resections. This study investigates the use of 3D Image Processing and Reconstruction (3D-IPR) to improve diagnostic accuracy in locally advanced colon cancer (LACC) with suspected infiltration and achieve R0 surgery. Methods: Single-center, prospective, observational, comparative, non-randomized study. •Participants: Patients aged > 18 years undergoing LACC surgery, as indicated by CT scans, confirmed via colonoscopy. Exclusion criteria include neoadjuvant therapy, suspected carcinomatosis on CT, and unresectable tumors. •Interventions: 3D-IPR models are used for surgical planning, providing detailed tumor and surrounding structure metrics. Surgical procedures are guided by CT scans and intraoperative findings, categorized by surgical margins as R0, R1, or R2. •Objective: The primary goal is to evaluate 3D-IPR's utility in achieving R0 resection in LACC with suspected infiltration. Secondary objectives include assessing preoperative surgical strategy, comparing CT reports, detecting adenopathy, and identifying vascularization and anatomical variants. • Outcome: The main outcome is the diagnostic accuracy of 3D-IPR in determining tumor infiltration of neighboring structures compared to conventional CT scans, using definitive pathological reports as the gold standard. Results: •Recruitment and Number Analyzed: The study aims to recruit about 20 patients annually over two years, focusing on preoperative 3D-IPR analysis and subsequent surgical procedures. •Outcome Parameters: These include loco-regional and distant recurrence rates, peritoneal carcinomatosis, disease-free and overall survival, and mortality due to oncologic progression. •Harms: No additional risks from CT scans, as they are mandatory for staging colon tumors. 3D-IPR is derived from these CT scans. Discussion: If successful, this study could provide an objective tool for precise tumor extension delimitation, aiding decision-making for radiologists, surgeons, and multidisciplinary teams. Enhanced staging through 3D-IPR may influence therapeutic strategies, reduce postsurgical complications, and improve the quality of life of patients with LACC. Trial registration: Trial is registered at ISRCTN registry as ISRCTN81005215. Protocol version I (Date 29/06/2023). [ABSTRACT FROM AUTHOR]

Previous studies that intercompared global Level‐4 (L4) sea surface temperature (SST) analyses were centered on the assessment of the accuracy and bias of SST by comparing them with independent near‐surface Argo profile temperature data. This type of assessment is centered on the absolute value of SST rather than on SST spatial properties (gradients), which is more relevant to the study of oceanographic features (e.g., fronts, eddies, etc.) and ocean dynamics. Here, we use, for the first time, the spectrum of singularity exponents to assess the structural and dynamical quality of different L4 gap‐filled products based on the multifractal theory of turbulence. Singularity exponents represent the geometrical projection of the turbulence cascade, and its singular spectrum can be related to the probability density function of the singularity exponents normalized by the scale. Our results reveal that the different schemes used to produce the L4 SST products generate different singularity spectra, which are then used to identify a potential loss of dynamical information or structural coherence. This new diagnostic constitutes a valuable tool to assess the structural quality of SST products and can support data satellite SST producers efforts to improve the interpolation schemes used to generate gap‐filled SST products. Plain Language Summary: Gap‐filled sea surface temperature (SST) gridded products are generated by combining satellite and, in some cases, in situ observations. Previous studies intercomparing the different SST products focused on assessing the differences between the SST products and in situ observations. However, what is relevant for ocean dynamics studies is the local spatial differences of the SST fields. In this work, we propose a new diagnostic that allows us to assess the dynamical quality of SST products. This new diagnostic is based on the multifractal theory of turbulence and enables the identification of the regions where the SST fields do not properly describe ocean dynamics. This diagnostic is a valuable tool that can help the data satellite SST producers to improve the way the different observations are blended in order to build SST fields that are more dynamically coherent. Key Points: We proposed a new diagnostic to assess the structural and dynamical properties of sea surface temperature (SST) productsThis diagnostic is based on multifractal theory of turbulence and consists computing the singularity spectrumThe different schemes used to produce gap‐filled SST products may contribute to the loss of dynamical information or structural coherence [ABSTRACT FROM AUTHOR]

This study examined the gendered rights and challenges of ownership, access, and investments in land and shea trees in Ghana. It mainstreams women into policies regarding land and shea tenures. A qualitative approach through focus group discussions and in-depth interviews with key stakeholders was used. From the study, women do not own land or shea trees, but they can exploit them. The loss of farmlands and shea trees through urbanisation worsens women's welfare, incomes, and bargaining power. To ensure the effective management of shea parklands, collaborative governance of land and shea trees between the landowners and local government is proposed. [ABSTRACT FROM AUTHOR]

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Objectives: This study examined the magnitude, changes, and racial/ethnic disparities in the economic costs of the 16-year preclinical phase of dementia—a period of cognitive decline without significant impact on daily activities. Methods: The study utilized two dementia algorithms to classify individuals with incident dementia in the Health and Retirement Study. These cases were compared to matched controls in terms of poverty status, labor force participation, and unsecured debts. Results: Older adults classified with dementia were more likely to drop out of the labor force and become poor than similar older adults without dementia. Racial/ethnic disparities in poverty persisted during the preclinical period, with non-Hispanic Black older adults more likely to leave the labor force and Hispanic older adults more likely to have unsecured debt. Discussion: Findings highlight the economic costs during prodromal phase of dementia, emphasizing need for early interventions to reduce financial strain across diverse older adults. [ABSTRACT FROM AUTHOR]

This study investigates the interannual variations in regional mean sea levels (MSLs) of the northeast Asian marginal seas (NEAMS) during August, focusing on the role of typhoon activity from 1993 to 2019. The NEAMS are connected to the Pacific through the East China Sea (ECS) and narrow, shallow straits in the east, where inflow from the southern boundary (ECS), unless balanced by eastern outflow, leads to significant convergence or divergence, as well as subsequent changes in regional MSLs. Satellite altimetry and tide-gauge data reveal that typhoon-induced Ekman transport plays a key role in MSL variability, with increased inflow raising MSLs during active typhoon seasons. In contrast, weak typhoon activity reduces inflow, resulting in lower MSLs. This study's findings have significant implications for coastal management, as the projected changes in tropical cyclone frequency and intensity due to climate change could exacerbate sea level rise and flooding risks. Coastal communities in the NEAMS region will need to prioritize enhanced flood defenses, early warning systems, and adaptive land use strategies to mitigate these risks. This is the first study to link typhoon frequency directly to NEAMS MSL variability, highlighting the critical role of wind-driven processes in regional sea level changes. [ABSTRACT FROM AUTHOR]

Today's adolescents represent an elective target in addressing environmental challenges. Education is a key factor in achieving a sustainable future for them. However, formal education can represent a challenge when youths are its target, as they are considered the "interactive generation". Game-based learning, and, in particular, Digital Educational Escape Rooms (DERs), have emerged as innovative methods in education, with promising applications in environmental sustainability studies. In this study, we developed 14 Digital Escape Rooms using the Social Cognitive Theory of Bandura as a theoretical framework. These were focused on environmental education and we tested them on a sample of 411 students (aged 12–18 years; 158 female, 38.4%). A one-group quasi-experimental research design was adopted, carrying out a pre-test post-test analysis. Each participant completed assessments at two time points: before engaging in the escape rooms (T0) and after (T1). The assessment tools included the Goal Assessment Scale (GAS) and the Perceived Climate Self-Efficacy Scale. Our findings revealed no significant gender differences in goal achievement. However, at T0, females exhibited higher levels of perceived climate self-efficacy in both individual and collective dimensions. Instead, the Digital Escape Rooms appeared particularly effective in increasing self-efficacy among male participants. These results suggest that Digital Escape Rooms hold potential for enhancing environmental self-efficacy, although gender differences in baseline efficacy levels warrant further exploration. [ABSTRACT FROM AUTHOR]

The study aims to investigate Ecofeminism through the cultural narrative of Homelessness in Halaby's Once in a Promised Land. It investigates the Ecofeminist concept of Nature and Women dualism in Western philosophy, with a focus on the formation of a sphere of otherness through oppressions such as gender, race, and colonization. This qualitative study focuses on the interdependence of gender, nature, and women's experiences in the global village proposed by Maria Mies and Vandana Shiva. Romanticizing and sentimentalizing nature is viewed as a third area in which modern people crave women, namely women's bodies. The current understanding of nature has devolved into a deceptive process, with women perceived as inferior to men and their sexuality as subservient. Homelessness is a major issue in America, with Arab women like Salwa facing colonialism, homelessness, and refugee status. The study emphasizes the importance of accountability and self-awareness in navigating the complex dynamics of gender, nature, and women's experiences for upcoming researchers. [ABSTRACT FROM AUTHOR]

Frailty is a geriatric, multi‐dimensional syndrome that reflects multisystem physiological change and is a transversal measure of reduced resilience to negative events. It is characterized by weakness, frequent falls, cognitive decline, increased hospitalization and dead and represents a risk factor for the development of Alzheimer's disease (AD). The fact that frailty is recognized as a reversible condition encourages the identification of earlier biomarkers to timely predict and prevent its occurrence. SAMP8 (Senescence‐Accelerated Mouse Prone‐8) mice represent the most appropriate preclinical model to this aim and were used in this study to carry transcriptional and metabolic analyses in the brain and plasma, respectively, upon a characterization at cognitive, motor, structural, and neuropathological level at 2.5, 6, and 9 months of age. At 2.5 months, SAMP8 mice started displaying memory deficits, muscle weakness, and motor impairment. Functional alterations were associated with a neurodevelopmental deficiency associated with reduced neuronal density and glial cell loss. Through transcriptomics, we identified specific genetic signatures well distinguishing SAMP8 mice at 6 months, whereas plasma metabolomics allowed to segregate SAMP8 mice from SAMR1 already at 2.5 months of age by detecting constitutively lower levels of acylcarnitines and lipids in SAMP8 at all ages investigated correlating with functional deficits and neuropathological signs. Our findings suggest that specific genetic alterations at central level, as well as metabolomic changes in plasma, might allow to early assess a frail condition leading to dementia development, which paves the foundation for future investigation in a clinical setting. [ABSTRACT FROM AUTHOR]

The document provides a comprehensive bibliography of M. L. Daneel's work, including organizations founded, publications, books in progress, and articles and book chapters. Daneel's research focuses on African Independent Churches, traditional ecologists, and earthkeeping movements in Zimbabwe. His work explores the intersection of Christianity, traditional African culture, and environmental conservation, making significant contributions to African theology and mission studies. [Extracted from the article]

Learning about potential land uses is necessary to make the best use of land resources due to ongoing temporal change caused by human activity. The study uses Landsat 5 and 8 images to investigate changes in land cover, especially agricultural land, in Shanghai, China over the last 20 years in 5-year intervals due to urbanization. Also, through the calculation of environmental indices of the earth's surface, such as normalized difference vegetation index, normalized difference built-up index, normalized difference water index, emissivity, thermal radiance, and land surface temperature, the changes in their values in relation to the land cover changes were investigated. To capture the nature of the changes that have occurred, three other major land covers, such as urban, vegetation, and water classes, were also monitored in parallel with agricultural lands. Land cover and land surface temperature changes were also predicted for 2030 using the Markov chain method and GBM machine learning. Based on the results from 2002 to 2020, the agricultural and other land covers of this city underwent significant changes, and most of the agricultural lands have been lost in favor of the urban expansion. Consequently, the class for urban and impervious areas, has grown by 33.87%, making the class with the largest overall positive growth and, on the other hand, the agricultural land class, which had the largest negative growth at 57%, had a fall. Moreover, despite the increase of 10.5% in 2020 in the class of vegetated areas, the urban area's water class, water body class, has grown by 16.4%. The land cover prediction map predicts areas in water body class and urban and impervious areas to rise, while agricultural land class and vegetated areas will contract. The normalized difference vegetation index index shows a 58.54% decline, while the normalized difference built-up index and normalized difference water index indices and land surface temperature values increase. There is a strong correlation between the normalized difference vegetation index, normalized difference built-up index, normalized difference water index, and thermal radiance indices. The results of prediction and estimation of land cover and surface temperature also indicate reduction of agricultural land for the benefit of increasing urban land and a parallel increase in land surface temperature in 2030. The results of this research can represent the changes that have occurred and their effects as well as a roadmap for planning and policymaking in the future of Shanghai's environment for managers and planners. [ABSTRACT FROM AUTHOR]

This study examined educational and occupational inequality as two aspects of social determinants of health that might mediate the longitudinal relationship between racialization and late life cognitive level and change. Participants were 2371 individuals racialized as Black and White from the ACTIVE study who provided occupational data. Data were analyzed from baseline and five assessments over 10-years using structural equation modeling. Black/White race served as the predictor, occupational complexity (OC) and years of education as mediators, and cognitive (memory, reasoning, and speed of processing) intercept, linear slope, and quadratic slope as the dependent variables. Black/White race showed significant indirect associations through education and OC on level of performance in cognition, linear change in reasoning and memory, and quadratic change in reasoning. Education and OC accounted for 11–16% of the association between race and cognitive level and represent modifiable social determinants of health that are associated with disparities in cognitive aging. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs)‐based intercellular communication (through exosomes, microvesicles, and apoptotic bodies) is conserved across all kingdoms of life. In recent years, exosomes have gained much attention for targeted pharmaceutical administration due to their unique features, nanoscale size, and capacity to significantly contribute to cellular communication. As drug delivery vehicles, exosomes have several advantages over alternative nanoparticulate drug delivery technologies. A key advantage lies in their comparable makeup to the body's cells, which makes them non‐immunogenic. However, exosomes vesicles face several challenges, including a lack of an effective and standard production technique, decreased drug loading capacity, limited characterization techniques, and underdeveloped isolation and purification procedures. Exosomes are well known for their long‐term safety and natural ability to transport intercellular nucleic acids and medicinal compounds across the blood‐brain‐barrier (BBB). Therefore, in addition to revealing new insights into exosomes' distinctiveness, the growing availability of new analytical tools may drive the development of next‐generation synthetic systems. Herein, light is shed on exosomes as drug delivery vehicles in anti‐infective therapy by reviewing the literature on primary articles published between 2002 and 2023. Additionally, the benefits and limitations of employing exosomes as vehicles for therapeutic drug delivery are also discussed. [ABSTRACT FROM AUTHOR]

Lake Sevan in Armenia is a unique, large, alpine lake given its surface, volume, and geographic location. The lake suffered from progressing eutrophication and, since 2018, massive cyanobacterial blooms repeatedly occurred. Although the lake is comparatively intensely monitored, the feasibility to reliably detect the algal bloom events appeared to be limited by the established in situ monitoring, mostly because algal bloom dynamics are far more dynamic than the realized monitoring frequency of monthly samplings. This mismatch of monitoring frequency and ecosystem dynamics is a notorious problem in lakes, where plankton dynamics often work at relatively short time scales. Satellite-based monitoring with higher overpass frequency, e.g., by Sentinel-3 OLCI with its daily overcasts, are expected to fill this gap. The goal of our study was therefore the establishment of a fast detection of algal blooms in Lake Sevan that operates at the time scale of days instead of months. We found that algal bloom detection in Lake Sevan failed, however, when it was only based on chlorophyll due to complications with optical water properties and atmospheric corrections. Instead, we obtained good results when true-color RGB images were analyzed or a specifically designed satellite-based HAB indicator was applied. These methods provide reliable and very fast bloom detection at a scale of days. At the same time, our results indicated that there are still considerable limitations for the use of remote sensing when it comes to a fully quantitative assessment of algal dynamics in Lake Sevan. The observations made so far indicate that algal blooms are a regular feature in Lake Sevan and occur almost always when water temperatures surpass approximately 20 °C. Our satellite-based method effectively allowed for bloom detection at short time scales and identified blooms over several years where classical sampling failed to do so, simply because of the unfortunate timing of sampling dates and blooming phases. The extension of classical in situ sampling by satellite-based methods is therefore a step towards a more reliable, faster, and more cost-effective detection of algal blooms in this valuable lake. [ABSTRACT FROM AUTHOR]

Abstract: Lack of reliable observational metadata represents a key barrier to understanding sea surface temperature (SST) measurement biases, a large contributor to uncertainty in the global surface record. We present a method to identify SST measurement practice by comparing the observed SST diurnal cycle from individual ships with a reference from drifting buoys under similar conditions of wind and solar radiation. Compared to existing estimates, we found a larger number of engine room‐intake (ERI) reports post–World War II and in the period 1960–1980. Differences in the inferred mixture of observations lead to a systematic warmer shift of the bias adjusted SST anomalies from 1980 compared to previous estimates, while reducing the ensemble spread. Changes in mean field differences between bucket and ERI SST anomalies in the Northern Hemisphere over the period 1955–1995 could be as large as 0.5°C and are not well reproduced by current bias adjustment models. [ABSTRACT FROM AUTHOR]

Herein, we report Rh(III) catalyzed aldehydic or aryl C–H alkylation via C–C bond activation of cyclopropanols, facilitating the synthesis of β-functionalized ketones. The protocol employs cyclopropanol as the alkylating agent with 2-aminobenzaldehyde or aniline derivatives to access a variety of unsymmetrical 1,4-diketones or β-aryl ketones, respectively. The practicality of these transformations is showcased through the modification of natural products, gram-scale synthesis, broad substrate scope and postfunctionalizations. [ABSTRACT FROM AUTHOR]

The 2022 and 2023 western Mediterranean summer temperatures exceeded millennial natural variability, reaching unprecedented anomalies of +3.6 °C and +2.9 °C respectively. We show that anthropogenic climate change may turn extreme heatwaves from a rarity of 1 in 10,000 years into events occurring every 4–75 years, depending on future scenarios. This shift underscores the urgency of implementing adaptive strategies as extreme climate events manifest sooner and more intensely than expected. [ABSTRACT FROM AUTHOR]

Lakes are directly exposed to climate variations as their recharge processes are driven by precipitation and evapotranspiration, and they are also affected by groundwater trends, changing ecosystems and changing water use. In this study, we present a downward model development approach that uses models of increasing complexity to identify and quantify the dependence of lake level variations on climatic and other factors. The presented methodology uses high-resolution gridded weather data inputs that were obtained from dynamically downscaled ERA5 reanalysis data. Previously missing fluxes and previously unknown turning points in the system behavior are identified via a water balance model. The detailed lake level response to weather events is analyzed by calibrating data-driven models over different segments of the data time series. Changes in lake level dynamics are then inferred from the parameters and simulations of these models. The methodology is developed and presented for the example of Groß Glienicker Lake, a groundwater-fed lake in eastern Germany that has been experiencing increasing water loss in the last half-century. We show that lake dynamics were mainly controlled by climatic variations in this period, with two systematically different phases in behavior. The increasing water loss during the last decade, however, cannot be accounted for by climate change. Our analysis suggests that this alteration is caused by the combination of regional groundwater decline and vegetation growth in the catchment area, with some additional impact from changes in the local rainwater infrastructure. [ABSTRACT FROM AUTHOR]

Land Surface Temperature (LST) is integral to our understanding of the radiative energy budget of the Earth's surface since it provides the best approximation to the thermodynamic temperature that drives the outgoing longwave flux from surface to atmosphere. Since 5 July 2017, an operational LST product has been available from the Sentinel-3A mission, with the corresponding product being available from Sentinel-3B since 17 November 2018. Here, we present the first paper describing formal products, including algorithms, for the Sea and Land Surface Temperature Radiometer (SLSTR) instruments onboard Sentinel-3A and 3B (SLSTR-A and SLSTR-B, respectively). We evaluate the quality of both the Land Surface Temperature Climate Change Initiative (LST_cci) product and the Copernicus operational LST product (SL_2_LST) for the years 2018 to 2021. The evaluation takes the form of a validation against ground-based observations of LST across eleven well-established in situ stations. For the validation, the mean absolute daytime and night-time difference against the in situ measurements for the LST_cci product is 0.77 K and 0.50 K, respectively, for SLSTR-A, and 0.91 K and 0.54 K, respectively, for SLSTR-B. These are an improvement on the corresponding statistics for the SL_2_LST product, which are 1.45 K (daytime) and 0.76 (night-time) for SLSTR-A, and 1.29 K (daytime) and 0.77 (night-time) for SLSTR-B. The key influencing factors in this improvement include an upgraded database of reference states for the generation of retrieval coefficients, higher stratification of the auxiliary data for the biome and fractional vegetation, and enhanced cloud masking. [ABSTRACT FROM AUTHOR]