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This paper demonstrates how artificial-intelligence language analysis can inform understanding of human–nature relationships and other social phenomena. We demonstrate three techniques by investigating relationships within the popular word2vec word embedding, which is trained on a sample from over 50,000 worldwide news sources. Our first technique investigates what theory-generated analogies are most similar to nature:people. The resource:user analogy is most similar, followed by the playground:child and gift:receiver analogies. Our second technique explores whether nature-related words are affiliated with words that denote race, class, or gender. Nature words tend slightly toward associations with femininity and wealth. Our third technique demonstrates how the relationship between nature and wellbeing compares to other concepts' relationships to wellbeing—e.g., spirituality–wellbeing, social relations–wellbeing. Nature is more semantically connected to wellbeing than money, social relations, and multiple other wellbeing correlates. Findings are consistent with previous social science and humanities research on human-nature relationships, but do not duplicate them exactly; our results thus offer insight into dominant trends and prevalence of associations. Our analysis also offers a model for using word embeddings to investigate a wide variety of topics. [ABSTRACT FROM AUTHOR]

Introduction: Although the growth of digital tools for cognitive health assessment, there’s a lack of known reference values and clinical implications for these digital methods. This study aims to establish reference values for digital neuropsychological measures obtained through the smartphone-based cognitive assessment application, Defense Automated Neurocognitive Assessment (DANA), and to identify clinical risk factors associated with these measures. Methods: The sample included 932 cognitively intact participants from the Framingham Heart Study, who completed at least one DANA task. Participants were stratified into subgroups based on sex and three age groups. Reference values were established for digital cognitive assessments within each age group, divided by sex, at the 2.5th, 25th, 50th, 75th, and 97.5th percentile thresholds. To validate these values, 57 cognitively intact participants from Boston University Alzheimer’s Disease Research Center were included. Associations between 19 clinical risk factors and these digital neuropsychological measures were examined by a backward elimination strategy. Results: Age- and sex-specific reference values were generated for three DANA tasks. Participants below 60 had median response times for the Go-No-Go task of 796 ms (men) and 823 ms (women), with age-related increases in both sexes. Validation cohort results mostly aligned with these references. Different tasks showed unique clinical correlations. For instance, response time in the Code Substitution task correlated positively with total cholesterol and diabetes, but negatively with high-density lipoprotein and low-density lipoprotein cholesterol levels, and triglycerides. Discussion: This study established and validated reference values for digital neuropsychological measures of DANA in cognitively intact white participants, potentially improving their use in future clinical studies and practice. [ABSTRACT FROM AUTHOR]

There is growing demand for seasonal forecast products for marine applications. The availability of consistent and sufficiently long observational records of ocean variables permits the assessment of the spatial distribution of the skill of ocean variables from seasonal forecasts. Here we use state-of-the-art temporal records of sea surface temperature (SST), sea surface height (SSH) and upper 300m ocean heat content (OHC) to quantify the distribution of skill, up to 2 seasons ahead, of two operational seasonal forecasting systems contributing to the seasonal multi-model of the Copernicus Climate Change Services (C3S). This study presents the spatial distribution of the skill of the seasonal forecast ensemble mean in terms of anomaly correlation and root mean square error and compares it to the persistence and climatological benchmarks. The comparative assessment of the skill among variables sheds light on sources/ limits of predictability at seasonal time scales, as well as the nature of model errors. Beyond these standard verification metrics, we also evaluate the ability of the models to represent the observed long-term trends. Results show that long-term trends contribute to the skill of seasonal forecasts. Although the forecasts capture the long-term trends in general, some regional aspects remain challenging. Part of these errors can be attributed to specific aspects of the ocean initialization, but others, such as the overestimation of the warming in the Eastern Pacific are also influenced by model error. Skill gains can be obtained by improving the trend representation in future forecasting systems. In the meantime, a forecast calibration procedure that corrects the linear trends can produce substantial skill gains. The results show that calibrated seasonal forecasts beat both the climatological and persistence benchmark almost at every location for all initial dates and lead times. Results demonstrate the value of the seasonal forecasts for marine applications and highlight the importance of representing the decadal variability and trends in ocean heat content and sea level. [ABSTRACT FROM AUTHOR]

This study examined the perceptions of three stakeholder groups (faculty, instructional designers, and accessibility services personnel) in relation to the impact of the design of instruction and assessment on student mental health - within a post-secondary campus in Western Canada. The study adopts a broad post-modern paradigm when examining impairment and disability and focuses on the social model of disability as a lens. The methodological approach adopted draws from the phenomenological tradition, but also borrows some tools from narrative enquiry. Inductive coding was carried out to extract thematic categories from the initial 3 interviews. These categories were then used to carry out a thematic analysis of all 13 semi-directive interviews. The themes which emerged from the analysis with most impact include: (i) impact of faulty design on student mental health, (ii) varying stakeholder awareness of this impact, (iii) notion of context specific awareness, (iv) lack of tangible proactive intervention in this sphere, (v) lack of communication between stakeholders, (vi) tension between learner mental health and the notion of challenging pedagogical outcome. The findings overall suggest that a significant degree of awareness does exist across the campus in question with regards to the impact of design of the learning experience on the mental health of students. The degree of awareness about the impact of design on student mental health varies depending on the stakeholder involved and the context, but little proactive intervention to frame guidelines, for inclusive redesign that might be conducive to good mental health, is observable in this post-secondary landscape. Communication across campus stakeholder groups is identified as a significant obstacle to transformation. The article widens the contextualization of these findings through the lens of an ecological analysis of power dynamics and communication patterns in relation to teaching and learning across a campus. [ABSTRACT FROM AUTHOR]

This article examines Christine Montalbetti's novel Plus rien que les vagues et le vent (2014) (Nothing but Waves and Wind, 2017) to propose the ocean as a model to think about contemporary masculinities. This French road novel depicts homosociality in the post-2008 American landscape through the perspective of an outsider homodiegetic narrator. The ocean serves as a narrative model for the novel: its bodily connection with the characters embodies "hybrid masculinities" that emerge from a hybridity of patterns in an ongoing process of negotiation, appropriation and reformulation. In their travels, the characters eventually meet the ocean and testify to a fluid ontology that overturns the Modern detachment from the environment together with its humanist conception of "Man." The ocean's waves suggest a nonlinear timeline and an ongoing posthumanist reformation of subjectivities, like the ever-reshaping shorelines. In Montalbetti's novel, the ocean as a model for hybrid masculinities accounts for novel forms of power relationships, where radical openness pairs with violence. [ABSTRACT FROM AUTHOR]

The infrared (IR) satellite remote sensing of sea surface skin temperature (SSTskin) is challenging in the northern high-latitude region, especially in the Arctic because of its extreme environmental conditions, and thus the accuracy of SSTskin retrievals is questionable. Several Saildrone uncrewed surface vehicles were deployed at the Pacific side of the Arctic in 2019, and two of them, SD-1036 and SD-1037, were equipped with a pair of IR pyrometers on the deck, whose measurements have been shown to be useful in the derivation of SSTskin with sufficient accuracy for scientific applications, providing an opportunity to validate satellite SSTskin retrievals. This study aims to assess the accuracy of MODIS-retrieved SSTskin from both Aqua and Terra satellites by comparisons with collocated Saildrone-derived SSTskin data. The mean difference in SSTskin from the SD-1036 and SD-1037 measurements is ~0.4 K, largely resulting from differences in the atmospheric conditions experienced by the two Saildrones. The performance of MODIS on Aqua and Terra in retrieving SSTskin is comparable. Negative brightness temperature (BT) differences between 11 μm and 12 μm channels are identified as being physically based, but are removed from the analyses as they present anomalous conditions for which the atmospheric correction algorithm is not suited. Overall, the MODIS SSTskin retrievals show negative mean biases, −0.234 K for Aqua and −0.295 K for Terra. The variations in the retrieval inaccuracies show an association with diurnal warming events in the upper ocean from long periods of sunlight in the Arctic. Also contributing to inaccuracies in the retrieval is the surface emissivity effect in BT differences characterized by the Emissivity-introduced BT difference (EΔBT) index. This study demonstrates the characteristics of MODIS-retrieved SSTskin in the Arctic, at least at the Pacific side, and underscores that more in situ SSTskin data at high latitudes are needed for further error identification and algorithm development of IR SSTskin. [ABSTRACT FROM AUTHOR]

Coastal areas are among the most productive areas in the world, ecologically as well as economically. Sea Surface Temperature (SST) has evolved as the major essential climate variable (ECV) and ocean variable (EOV) to monitor land–ocean interactions and oceanic warming trends. SST monitoring can be achieved by means of remote sensing. The current relatively coarse spatial resolution of established SST products limits their potential in small-scale, coastal zones. This study presents the first analysis of the TIMELINE 1 km SST product from AVHRR in four key European regions: The Northern and Baltic Sea, the Adriatic Sea, the Aegean Sea, and the Balearic Sea. The analysis of monthly anomaly trends showed high positive SST trends in all study areas, exceeding the global average SST warming. Seasonal variations reveal peak warming during the spring, early summer, and early autumn, suggesting a potential seasonal shift. The spatial analysis of the monthly anomaly trends revealed significantly higher trends at near-coast areas, which were especially distinct in the Mediterranean study areas. The clearest pattern was visible in the Adriatic Sea in March and May, where the SST trends at the coast were twice as high as that observed at a 40 km distance to the coast. To validate our findings, we compared the TIMELINE monthly anomaly time series with monthly anomalies derived from the Level 4 CCI SST anomaly product. The comparison showed an overall good accordance with correlation coefficients of R > 0.82 for the Mediterranean study areas and R = 0.77 for the North and Baltic Seas. This study highlights the potential of AVHRR Local Area Coverage (LAC) data with 1 km spatial resolution for mapping long-term SST trends in areas with high spatial SST variability, such as coastal regions. [ABSTRACT FROM AUTHOR]

In the growing e-commerce industry, the problem of malicious business operations has become increasingly prominent, exposing many problems such as weak supervision of e-commerce platforms and no way for consumers to complain. In order to solve the problems of counterfeit and shoddy products on e-commerce platforms and promote the sustainable development of the e-commerce industry in China, this paper constructs a three-party evolutionary game model of e-commerce platforms, merchants, and consumers, investigates the influence of each influencing factor on each party's strategy choice, and provides targeted suggestions to e-commerce platforms based on relevant factors. Finally, the impact of several important parameters on the equilibrium solution is discussed through sensitivity analysis. The results show that: 1) the smaller the cost difference between active and negative regulation, the more the e-commerce platform tends to active regulation strategy, but increasing fines for dishonest merchants and consumer complaints have little impact on the e-commerce platform; 2) increasing consumer compensation, creating an honest business environment, and reducing the cost of honest business all help companies tend to operate in good faith; 3) the only factor that affects the tendency of consumer complaint strategies is the cost of complaints. The loss suffered by silence and the compensation given to consumers have little effect on consumers' tendency to complain strategy. The results can provide theoretical guidance for participants to make useful strategic decisions in the e-commerce market. [ABSTRACT FROM AUTHOR]

Water temperature responses to climate change may vary across Earth's estuaries. To understand how climate change influences estuarine surface water temperature, we need global, long‐term records of estuarine temperature. Here, we generated surface water temperature data over 1060 estuaries globally using Landsat 5, 7, and 8 from 1985 to 2022 and compared water warming rates with local air temperature warming rates. Forty‐seven percent of Earth's estuaries are warming, with a global average warming rate of 0.070 ± 0.004°C yr−1 (median = 0.060°C yr−1). Estuaries at higher latitudes showed rapid warming. A 1°C increase in air temperature could lead to a 0.81°C increase in estuarine surface water warming and 1.3°C increase in estuaries above 60.5°N. We inferred the potential influences over estuarine warming based on distinct global spatial patterns in water and air warming and discussed the effects of warming water temperature on estuarine metabolism and water quality. [ABSTRACT FROM AUTHOR]

Observation‐based quantification of ocean carbon dioxide (CO2) uptake relies on synthesis data sets such as the Surface Ocean CO2 ATlas (SOCAT). However, the data collection effort has dramatically declined and the number of annual data sets in SOCATv2023 decreased by ∼35% from 2017 to 2021. This decline has led to a 65% increase (from 0.15 to 0.25 Pg C yr−1) in the standard deviation of seven SOCAT‐based air‐sea CO2 flux estimates. Reducing the availability of the annual data to that in the year 2000 creates substantial bias (50%) in the long‐term flux trend. The annual mean CO2 flux is insensitive to the seasonal skew of the SOCAT data and to the addition of the lower accuracy data set available in SOCAT. Our study highlights the need for sustained data collection and synthesis, to inform the Global Carbon Budget assessment, the UN‐led climate negotiations, and measurement, reporting, and verification of ocean‐based CO2 removal projects. Plain Language Summary: The Surface Ocean CO2 ATlas (SOCAT) data set plays a crucial role in estimating the ocean carbon sink component of the Global Carbon Budget. However, the number of data sets available in SOCAT each year has drastically decreased since 2017. This study shows that the uncertainty in the data‐based ocean CO2 flux estimate has increased by 65% due to this decline in data availability. The estimated fluxes, especially the long‐term flux trend, are remarkably affected by the data availability in SOCAT, reducing the reliability of ocean CO2 uptake estimates in years and regions with sparse observations. Key Points: Lower surface ocean fCO2 data availability leads to higher uncertainty in data‐based estimates of ocean CO2 uptakeThe long‐term trend in the ocean CO2 flux increases by 1.5 times for subsequent years if the data availability is reduced to that in 2000The annual mean CO2 flux is not sensitive to the seasonal skew in the data and to the addition of low accuracy data [ABSTRACT FROM AUTHOR]

Understanding the sea level variability of the Bohai, Yellow Sea, and East China Sea (BYECS) is crucial for the socio-cultural and natural ecosystems of the coastal regions. In this study, based on satellite altimetry data, selected time range from 1993 to 2020, using the cyclostationary empirical orthogonal function (CSEOF) analysis method distinguishes the primary sea level variability modes. The analysis encompasses the seasonal signal, trend, and El Niño-Southern Oscillation (ENSO) associated mode of sea level anomaly. The amplitude of the annual cycle demonstrates a non-stationary signal, fluctuating between-15% and 15% from the average. Monsoons, atmospheric forcing, ocean circulation, winddriven Ekman transport, and the Kuroshio emerge as the primary factors influencing BYECS variability on seasonal scales. The satellite altimetry sea level exhibits an average trend within the range of 3-4 mm/year, while the steric sea level trend is generally smaller, falling within the range of 0-2 mm/year. Throughout the entire period, the contribution of steric sea level to the mean sea level trend consistently remains below 25%. Furthermore, BYECS sea level variations have a sensitive response to strong El Niño years, with a clear regionalization of the response, which is related to the intricate atmospheric circulation and local wind pressures, as well as the influence of ocean circulation. In conclusion, we gained a more comprehensive understanding of sea level variability in the BYECS, especially the annual cycle of sea level amplitude and the response of ENSO. However, more studies still need to be done to differentiate the various factors in sea level variations. [ABSTRACT FROM AUTHOR]

Regulation of excessive inflammation and impaired cell proliferation is crucial for healing diabetic wounds. Although plant‐to‐mammalian regulation offers effective approaches for chronic wound management, the development of a potent plant‐based therapeutic presents challenges. This study aims to validate the efficacy of turmeric‐derived nanoparticles (TDNPs) loaded with natural bioactive compounds. TDNPs can alleviate oxidative stress, promote fibroblast proliferation and migration, and reprogram macrophage polarization. Restoration of the fibroblast–macrophage communication network by TDNPs stimulates cellular regeneration, in turn enhancing diabetic wound healing. To address diabetic wound management, TDNPs are loaded in an ultralight‐weight, high swelling ratio, breathable aerogel (AG) constructed with cellulose nanofibers and sodium alginate backbones to obtain TDNPs@AG (TAG). TAG features wound shape‐customized accessibility, water‐adaptable tissue adhesiveness, and capacity for sustained release of TDNPs, exhibiting outstanding performance in facilitating in vivo diabetic wound healing. This study highlights the potential of TDNPs in regenerative medicine and their applicability as a promising solution for wound healing in clinical settings. [ABSTRACT FROM AUTHOR]

Trade wind clouds are ubiquitous across the subtropical oceans, including the Great Barrier Reef (GBR), playing an important role in modulating the regional energy budget. These shallow clouds, however, are by their nature sensitive to perturbations in both their thermodynamic environment and microphysical background. In this study, we employ the Weather Research and Forecasting (WRF) model with a convection-permitting configuration at 1 km resolution to examine the sensitivity of the trade wind clouds to different local forcings over the GBR. A range of local forcings including coastal topography, sea surface temperature (SST), and local aerosol loading is examined. This study shows a strong response of cloud fraction and accumulated precipitation to orographic forcing both over the mountains and upwind over the GBR. Orographic lifting, low-level convergence, and lower troposphere stability are found to be crucial in explaining the cloud and precipitation features over the coastal mountains downwind of the GBR. However, clouds over the upwind ocean are more strongly constrained by the trade wind inversion, whose properties are, in part, regulated by the coastal topography. On the scales considered in this study, the warm-cloud fraction and the ensuant precipitation over the GBR show only a small response to the local SST forcing, with this response being tied to the surface flux and lower troposphere stability. Cloud microphysical properties, including cloud droplet number concentration, liquid water path, and precipitation, are sensitive to the changes in atmospheric aerosol population over the GBR. While cloud fraction shows little responses, a slight deepening of the simulated clouds is evident over the upwind region in correspondence to the increased aerosol number concentration. A downwind effect of aerosol loading on simulated cloud and precipitation properties is further noted. [ABSTRACT FROM AUTHOR]

The anvil clouds of tropical deep convection have large radiative effects in both the shortwave (SW) and longwave (LW) spectra with the average magnitudes of both over 100 Wm-2. Despite this, due to the opposite sign of these fluxes, the net average of the anvil cloud radiative effect (CRE) over the tropics is observed to be neutral. Research into the response of the anvil CRE to climate change has primarily focused on the feedbacks of anvil cloud height and anvil cloud area, in particular regarding the LW feedback. However, tropical deep convection over land has a strong diurnal cycle which may couple with the shortwave component of the anvil cloud radiative effect. As this diurnal cycle is poorly represented in climate models it is vital to gain a better understanding of how its changes impact the anvil CRE. To study the connection between the deep convective cloud (DCC) lifecycle and CRE, we investigate the behaviour of both isolated and organised DCCs in a 4-month case study over sub-Saharan Africa (May–August 2016). Using a novel cloud tracking algorithm, we detect and track growing convective cores and their associated anvil clouds using geostationary satellite observations from the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI). Retrieved cloud properties and derived broadband radiative fluxes are provided by the Community Cloud retrieval for CLimate (CC4CL) algorithm. By collecting the cloud properties of the tracked DCCs, we produce a dataset of anvil cloud properties along their lifetimes. While the majority of DCCs tracked in this dataset are isolated, with only a single core, the overall coverage of anvil clouds is dominated by those of clustered, multi-core anvils due to their larger areas and lifetimes. We find that the anvil cloud CRE of our tracked DCCs has a bimodal distribution. The interaction between the lifecycles of DCCs and the diurnal cycle of insolation results in a wide range of the SW anvil CRE, while the LW component remains in a comparatively narrow range of values. The CRE of individual anvil clouds varies widely, with isolated DCCs tending to have large negative or positive CREs, while larger, organised systems tend to have a CRE closer to 0. Despite this, we find that the net anvil cloud CRE across all tracked DCCs is close to neutral (- 0.94 ± 0.91 Wm-2). Changes in the lifecycle of DCCs, such as shifts in the time of triggering, or the length of the dissipating phase, could have large impacts on the SW anvil CRE and lead to complex responses that are not considered by theories of LW anvil CRE feedbacks. [ABSTRACT FROM AUTHOR]

Amidst the backdrop of global climate change, it is imperative to comprehend the intricate connections among surface water, vegetation, and climatic shifts within watersheds, especially in fragile, arid ecosystems. However, these relationships across various timescales remain unclear. We employed the Ensemble Empirical Mode Decomposition (EEMD) method to analyze the multifaceted dynamics of surfacewater and vegetation in the Bosten Lake Watershed acrossmultiple temporal scales. This analysis has shed light on how these elements interact with climate change, revealing significant insights. From March to October, approximately 14.9-16.8% of the areas with permanent water were susceptible to receding and drying up. Both the annual and monthly values of Bosten Lake's level and area exhibited a trend of initial decline followed by an increase, reaching their lowest point in 2013 (1,045.0 m and 906.6 km2, respectively). Approximately 7.7% of vegetated areas showed a significant increase in the Normalized Difference Vegetation Index (NDVI). NDVI volatility was observed in 23.4% of vegetated areas, primarily concentrated in the southern part of the study area and near Lake Bosten. Regarding the annual components (6 < T < 24 months), temperature, 3-month cumulative NDVI, and 3-month-leading precipitation exhibited the strongest correlation with changes in water level and surface area. For the interannual components (T= 24 months), NDVI, 3-month cumulative precipitation, and 3-month-leading temperature displayed the most robust correlation with alterations in water level and surface area. In both components, NDVI had a negative impact on Bosten Lake's water level and surface area, while temperature and precipitation exerted positive effects. Through comparative analysis, this study reveals the importance of temporal periodicity in developing adaptive strategies for achieving Sustainable Development Goals in dryland watersheds. This study introduces a robust methodology for dissecting trends within scale components of lake level and surface area and links these trends to climate variations and NDVI changes across different temporal scales. The inherent correlations uncovered in this research can serve as valuable guidance for future investigations into surface water dynamics in arid regions. [ABSTRACT FROM AUTHOR]

The concentration of chlorophyll‐a (CHL) is an important proxy for autotrophic biomass and primary production in the ocean. Quantifying trends and variability in CHL are essential to understanding how marine ecosystems are affected by climate change. Previous analyses have focused on assessing trends in CHL mean, but little is known about observed changes in CHL extremes and variance. Here we apply a quantile regression model to detect trends in CHL distribution over the period of 1997–2022 for several quantiles. We find that the magnitude of trends in upper quantiles of global CHL (>90th) are larger than those in lower quantiles (≤50th) and in the mean, suggesting a growing asymmetry in CHL distribution. On a regional scale, trends in different quantiles are statistically significant at high latitude, equatorial, and oligotrophic regions. Assessing changes in CHL distribution has potential to yield a more comprehensive understanding of climate change impacts on CHL. Plain Language Summary: The marine environment is essential to nature and society, as it provides food and other important services such as Earth's climate regulation and habitat for species. Marine primary productivity is increasingly stressed due to global climate change. Detecting the impact of climate change on primary producers should be a priority given their critical role in the climate system. Most studies focus on the impact of climate change by evaluating the mean state of primary productivity, but little is known about whether and how climate change is impacting variance and extremes. Here we assess changes in chlorophyll‐a (CHL), which is an important proxy for primary production of marine ecosystems. We quantify long‐term changes in different aspects of the CHL distribution (mean, variance, and extremes) using a quantile regression model. We find that CHL high extremes and variability are slightly intensified globally during the 26 years of observational record. Trends in regional scales, especially in high‐latitude and North Atlantic Subtropical Gyre, show that CHL high extremes have been increasing since 1997. Our results suggest that more emphasis should be put into understanding the impact of climate change on the variance and extremes of primary productivity for climate change adaptation and mitigation. Key Points: Long‐term changes are detected in different aspects of the distribution of chlorophyll‐a (not just the mean state)Oceanic chlorophyll‐a high extremes are changing faster than chlorophyll‐a mean globally during 1997–2022On a regional scale, chlorophyll‐a extremes trends are predominant at high latitude (+), equatorial (−), and oligotrophic regions (−) [ABSTRACT FROM AUTHOR]

The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4). [ABSTRACT FROM AUTHOR]

Slow and long-term variations of sea surface temperature anomalies have been interpreted as a red-noise response of the ocean surface mixed layer to fast and random atmospheric perturbations. How fast the atmospheric noise is damped depends on the mixed layer depth. In this work we apply this theory to determine the relevant spatial and temporal scales of surface layer thermal inertia in lakes. We fit a first order auto-regressive model to the satellite-derived Lake Surface Water Temperature (LSWT) anomalies in Lake Garda, Italy. The fit provides a time scale, from which we determine the mixed layer depth. The obtained result shows a clear spatial pattern resembling the morphological features of the lake, with larger values (7.18± 0.3 m) in the deeper northwestern basin, and smaller values (3.18 ± 0.24 m) in the southern shallower basin. Such variations are confirmed by in-situ measurements in three monitoring points in the lake and connect to the first Empirical Orthogonal Function of satellite-derived LSWT and chlorophyll-a concentration. Evidence from our case study open a new perspective for interpreting lake-atmosphere interactions and confirm that remotely sensed variables, typically associated with properties of the surface layers, also carry information on the relevant spatial and temporal scales of mixed-layer processes. [ABSTRACT FROM AUTHOR]

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

The world's 1.4 million lakes (≥10 ha) provide many ecosystem services that are essential for human well‐being; however, only if their health status is good. Here, we reviewed common lake health issues and classified them using a simple human health‐based approach to outline that lakes are living systems that are in need of oxygen, clean water and a balanced energy and nutrient supply. The main reason for adopting some of the human health terminology for the lake health classification is to increase the awareness and understanding of global lake health issues. We show that lakes are exposed to various anthropogenic stressors which can result in many lake health issues, ranging from thermal, circulatory, respiratory, nutritional and metabolic issues to infections and poisoning. Of particular concern for human well‐being is the widespread lake drying, which is a severe circulatory issue with many cascading effects on lake health. We estimated that ∼115,000 lakes evaporate twice as much water as they gain from direct precipitation, making them vulnerable to potential drying if inflowing waters follow the drying trend, putting more than 153 million people at risk who live in close vicinity to those lakes. Where lake health issues remain untreated, essential ecosystem services will decline or even vanish, posing a threat to the well‐being of millions of people. We recommend coordinated multisectoral and multidisciplinary prevention and treatment strategies, which need to include a follow‐up of the progress and an assessment of the resilience of lakes to intensifying threats. Priority should be given to implementing sewage water treatment, mitigating climate change, counteracting introductions of non‐native species to lakes and decreasing uncontrolled anthropogenic releases of chemicals into the hydro‐, bio‐, and atmosphere. Plain Language Summary: Lakes around the world come in an array of sizes, shapes and colors, each telling a unique story of geological history and environmental importance. When lakes are healthy they contribute to the achievement of the global sustainable development goals by providing many important ecosystem services. Lakes are, however, not always healthy. Here, it is shown that lakes can suffer from a large variety of health issues, ranging from thermal, circulatory, respiratory, nutritional and metabolic issues to infections and poisoning. Without improved treatment strategies, many of the health issues may become chronic, affecting millions of people who are dependent on the ecosystem services from the lakes. To prevent and cure lakes from critical health conditions, strategies that are similar to those used in human healthcare should be applied: intervention and preventative actions before health problems occur, regular screening and early identification of lake health issues, and remediation and mitigation efforts at an appropriate scale, spanning from local to global. Key Points: Anthropogenic stressors can cause lake health issues that range from thermal, circulatory, respiratory, nutritional and metabolic issues to infections and poisoningLake health varies geographically, with the highest risk of critical conditions occurring in densely populated low‐income countriesThere is an urgent need to follow‐up the progress of treatments and to make adjustments whenever needed [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) data from the Sentinel-1 (S1) mission with its high temporal and spatial resolution allows for an automated detection of lake ice break-up timings from surface backscatter differences across south (S), southwest (SW), and northwest (NW) Greenland (<71 ° N latitude) during the period 2017 to 2021. Median break-up dates of the 563 studied lakes range between 8 June and 10 July, with the earliest being in 2019 and the latest in 2018. There is a strong correlation between the break-up date and elevation, while a weak relationship with latitude and lake area could be observed. Lake-specific median break-up timings for 2017–2021 increase (i.e., are later) by 3 d per 100 m elevation gain. When assuming an earlier break-up timing of 8 d which corresponds to the observed median variability of ±8 d, the introduced excess energy due to a changing surface albedo from snow-covered ice surface to water translates to melting 0.4 ± 0.1 m thick ice at the melting point or heating up a water depth down to 35 ± 3 m by 1 K across the entire surface area of each respective lake. Upscaling the results to 100 486 lakes across the S, SW, and NW regions, which correspond to 64.5 % of all lakes or 62.1 % of the overall lake area in Greenland, yields an estimate of 1.8 × 10 6 TJ additional energy input. This translates to melting 5.8 Gt ice at the melting point or warming 432.3 Gt water by 1 K. [ABSTRACT FROM AUTHOR]

Purpose: Silicone oil droplets in biopharmaceutical products can originate from sources such as siliconized surfaces of primary packaging materials, potentially triggering the formation of protein–silicone oil particles. To better understand this phenomenon, there is a need for particle detection devices that cannot only distinguish between protein particles and silicone oil droplets but also determine particle sizes ranging from nanometers to micrometers. Method: In this study, we conducted a systematic assessment of imaging flow cytometry (IFC) using the FlowSight® instrument. Our first step was to investigate specific instrument settings using protein particle samples spiked with silicone oil for particle classification. Based on these findings, we established suitable, harmonized working templates. Next, we evaluated the instrument’s accuracy and precision for particle sizes within the range of 0.5 to 100 µm and their respective concentrations. Finally, we investigated any constraints in particle concentration within this size range. Results: This study demonstrates that IFC can effectively distinguish protein particles from silicone oil droplets when the latter is labeled with a specific fluorescent dye. Our findings suggest that fluorescently labeled particles ≥ 0.5 µm can be reliably detected. Through our research, we determined the particle concentration limits for each particle size in the range of 0.5 to 10 µm, with a precision deviation of less than 15%. However, our study also revealed that IFC exhibited insufficient accuracy for the tested particle concentrations within this size range. Additionally, we showed that the measurements were significantly influenced by the instrument settings. Conclusion: Although we addressed numerous new aspects to enhance the experimental procedure of IFC measurements, we conclude that IFC is not an ideal technique for quantifying sub-visible particles. Instead, it should be employed to provide supportive characterization data in conjunction with commonly used sub-visible particle detection methods. If distinguishing between protein particles and silicone oil droplets is essential, IFC is an option, as long as the fluorescent dye is carefully selected. [ABSTRACT FROM AUTHOR]

This article introduces the special issue of REPCS dedicated to the analysis of the restructuring of higher education in Alberta, Canada. It describes the acceleration of the processes of commodification of education and research and the corporatization of institutional governance under the government that took office in April 2019. The Alberta case is situated within the political economy of this petro-state, governed by a right-wing populist party, as well as in relation to the global trends in post-secondary education driven by neoliberal regimes. Further, the article highlights the cracks in the foundations of modern universities that have deeper historical origins than neoliberalism, and that are widening as the governance and raison d'etre of these institutions are challenged by global socio-ecological crises and Indigenous-led decolonization and climate justice movements. Drawing upon firsthand knowledge, as a participant in the struggles at the University of Alberta, as well as extensive research into the government's restructuring agenda and the impacts on the post-secondary sector, the author outlines proposals for reform of the legislative framework governing the relationship between universities and the state, as well as the internal governance of the institution, and assesses the current terrain of agency for such transformation. [ABSTRACT FROM AUTHOR]

Recruiting the public to participate in the scientific process can be invaluable in furthering our understanding of global environmental change. Several long‐term citizen science projects have been active for over a decade, with most involving the public in the data collection phase of the scientific process. Our team has recently inherited a long‐term citizen science project called the Community Lake Ice Collaboration (CLIC). We have benefited from engaging with a community of experienced participants who have collected reliable data for hundreds of lakes across the USA for over 30 yr. Collecting data at this scale would have been logistically and financially challenging without participants volunteering their time and effort. Here, we aim to provide an overview of the lessons we have learned from CLIC and other citizen science projects and develop nine guidelines for establishing and sustaining a long‐term citizen science project. [ABSTRACT FROM AUTHOR]

The article offers information on the impact of the global warming to the lake summer surface water temperatures (LSSWT) for 2015. Topics include the increase in the global surface air temperature (SAT), the prominence of the warm anomalies in LSSWT in central Europe, and the influence of the climatic variability and local characteristics to the LSSWT.

The direct catalytic carboxylation of benzylic tertiary C-H bonds with CO 2 for the synthesis of all-carbon quaternary carboxylic acids represents a significant challenge. Here, we present a redox-neutral approach to address this difficulty by leveraging the synergistic interplay between photocatalysis and cascade hydrogen abstraction cycles. Remarkably, this strategy eliminates the need for sacrificial electron donors, electron acceptors, or stoichiometric additives, offering enhanced atom economy and environmental sustainability. It is particular that the combination of α-amino alkyl radicals with sulfur radicals generated in situ from the decomposition of DMSO was employed to realize the abstraction of benzylic tertiary C-H bonds. Our method enables the direct synthesis of a diverse array of benzylic quaternary carboxylic acids with excellent functional group tolerance as well as the derivatization of bioactive molecules and the gram-scale synthesis of pharmaceuticals under mild reaction conditions., (© 2024 Wiley-VCH GmbH.)

Rapid sensing of molecules is increasingly important in many studies and applications, such as DNA sequencing and protein identification. Here, beyond atomically thin 2D nanopores, we conceptualize, simulate and experimentally demonstrate coupled, guiding and reusable bilayer nanopore platforms, enabling advanced ultrafast detection of unmodified molecules. The bottom layer can collimate and decelerate the molecule before it enters the sensing zone, and the top 2D pore (~2 nm) enables position sensing. We varied the number of pores in the bottom layer from one to nine while fixing one 2D pore in the top layer. When the number of pores in the bottom layer is reduced to one, sensing is performed by both layers, and distinct T- and W-shaped translocation signals indicate the precise position of molecules and are sensitive to fragment lengths. This is uniquely enabled by microsecond resolution capabilities and precision nanofabrication. Coupled nanopores represent configurable multifunctional systems with inter- and intralayer structures for improved electromechanical control and prolonged dwell times in a 2D sensing zone., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 × 1013 locations are processed, yielding 1.4 × 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km−2 yr−1 in 1980 to over 100 km−2 yr−1 after 2007. Data are provided at their native resolution, averaged on a global 0.05° latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05°. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods. [ABSTRACT FROM AUTHOR]

Global warming is destabilizing the cryosphere, with consequences for glaciers, permafrost, sea ice and lake ice. Polar lakes have short ice‐free seasons, and small changes in ice cover duration have the potential to provoke alterations to ecosystem structure. However, these lakes are understudied, and the consequences for mixing regimes, thermal structures and biogeochemical processes remain unclear. We measured three annual cycles of dissolved oxygen, temperature and specific conductivity in a lake at ∼83°N to investigate limnological processes and their interannual variability. There were sharp interannual contrasts in lake dynamics, with state shifts in mixing, stratification and oxygen regimes due to air temperature variability and meteorological events. We also observed unusual thermal profiles that were associated with solute gradients. These striking differences underscore the sensitivity of high Arctic lakes to interannual variations in meteorological forcing, and their susceptibility to regime shifts in response to ongoing global change. Plain Language Summary: Lakes are biodiversity refuges, climate regulators and providers of ecosystem services. High Arctic lakes experience brief summer ice‐free periods and their annual dynamics remain largely unexplored despite their location in one of the most rapidly warming regions on Earth. In particular, patterns of thermal structure and oxygen dynamics have rarely been measured. We studied three complete annual cycles in a coastal lake less than 100 km south of the northernmost land on Earth. The observed limnological dynamics highlight the potential for rapid regime shifts in polar lakes and underline their sensitivity to interannual differences in environmental conditions. Key Points: Pronounced shifts in lake oxygen and temperature dynamics occur due to interannual air temperature variation and meteorological episodesDivergent annual trajectories in lake structure and functioning highlight the vulnerability of high Arctic lakes to climate change [ABSTRACT FROM AUTHOR]

In the spring of 2021, a shipborne comparison of sea surface temperature (SST) measurements was undertaken using Thermal Infrared (TIR) and Passive Microwave (PMW) radiometers. The Danish Meteorological Institute (DMI) and the Technical University of Denmark (DTU) jointly deployed two TIR and two PMW instruments aboard the Norröna ferry, which traversed between Denmark and Iceland for a week. The primary objective was to assess the proximity-based comparison of TIR and PMW measurements, minimizing atmospheric influences and providing valuable insights into skin (TIR) and sub-skin (PMW) SSTs. A linear regression algorithm was developed using TIR SST data as a reference to derive PMW SST from brightness temperature. The data analysis primarily focused on evaluating data variability, identifying discrepancies between TIR and PMW SST, and assessing the overall uncertainty in the retrieval process. The overall root mean squared error (RMSE) of the retrieved PMW SST was 0.88 K during the ship's motion and 0.94 K under stable conditions when the ship was moored. The analysis of the retrieved SST error budget involved the consideration of observed quantities and a forward model, accounting for factors like instrument noise, wind speed, incident angles, and the RMSE of skin and sub-skin temperature. The resulting error budget indicated 0.97 K for the data acquired during motion and 0.34 K for data collected during port stay. [ABSTRACT FROM AUTHOR]

Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across weather forecasting, disaster preparedness, and urban planning, but researchers lack the tools to run these models effectively and efficiently, limiting progress. One of the current challenges is to assimilate observations in highly non-linear dynamical systems, as the practical need is often to detect abrupt changes. We have developed a software platform to improve the use of real-time data in non-linear system representations where non-Gaussianity limits the applicability of data assimilation algorithms such as the ensemble Kalman filter and variational methods. Particle-filter-based data assimilation algorithms have been implemented within a user-friendly open-source software platform in Julia – ParticleDA.jl. To ensure the applicability of the developed platform in realistic scenarios, emphasis has been placed on numerical efficiency and scalability on high-performance computing systems. Furthermore, the platform has been developed to be forward-model agnostic, ensuring that it is applicable to a wide range of modelling settings, for instance unstructured and non-uniform meshes in the spatial domain or even state spaces that are not spatially organized. Applications to tsunami and numerical weather prediction demonstrate the computational benefits and ease of using the high-level Julia interface with the package to perform filtering in a variety of complex models. [ABSTRACT FROM AUTHOR]

Absolute calibration of Earth observation (EO) sensors is key to ensuring long-term stability and interoperability, and it is essential for long-term global climate records and forecasts. The Moon provides a photometrically stable calibration source within the range of the Earth's radiometric levels and is free from atmospheric interference. However, to use this ideal calibration source, one must model the variation in its disc-integrated irradiance resulting from changes in Sun–Earth–Moon geometries. The Lunar Irradiance Model of the European Space Agency (LIME) is a new lunar irradiance model developed from ground-based observations acquired using a lunar radiometer operating from the Izaña Atmospheric Observatory near Mount Teide, located in Tenerife, Spain. Nightly top-of-atmosphere (TOA) irradiance is determined using the Langley plot method, and each observation is traceable to the international system of units (SI) through the radiometer calibration performed at the National Physical Laboratory (NPL). Approximately 590 lunar observations acquired between March 2018 and December 2022 currently contribute to the model parameter derivation, which builds on the widely used ROLO (Robotic Lunar Observatory) model analytical formulation. This paper presents the strategy used to derive LIME parameters: the characterisation of the lunar radiometer, the derivation of nightly top-of-atmosphere lunar irradiance and a description of the model parameter derivation, along with the associated metrologically rigorous uncertainty. The model output has been compared to PROBA-V, Pléiades and Sentinel-3B, as well as to the VITO implementation of the ROLO model. Initial results indicate that LIME predicts 3 %–5 % higher lunar-disc-integrated irradiance than the ROLO model for the visible and near-infrared channels. The model output has an expanded (k=2) radiometric uncertainty of ∼ 2 % at the lunar radiometer wavelengths, and it is expected that planned observations until at least 2024 further constrain the model parameters in subsequent updates. [ABSTRACT FROM AUTHOR]

Human activities, global warming, frequent extreme weather events, and changes in atmospheric composition affect the solar radiation reaching the Earth's surface, affect mass and heat transfer at the air–water interface, and induce oscillations in wind-driven internal waves. This leads to changes in the spatiotemporal characteristics of thermal stratification in lakes, altering lake circulation patterns and vertical mass transfer. However, thermal stratification structures are often overlooked. The intensification of lake thermal stratification due to warming may lead to increased release of bottom pollutants, spreading through the dynamic behavior of the thermocline to the epilimnion. Moreover, the increased heat storage is beneficial for the growth and development of certain phytoplankton, resulting in rapid transitions of the original steady state of lakes. Consequently, water quality deterioration, ecological degradation, and declining biodiversity may occur. Conventional surface water monitoring may not provide comprehensive, accurate, and timely assessments. Model simulations can better predict future thermal stratification behaviors, reducing financial burdens, providing more refined assessments, and thus preventing subsequent environmental issues. [ABSTRACT FROM AUTHOR]

Despite their importance, wetland ecosystems protected by the Ramsar Convention are under pressure from climate change and human activities. These drivers are altering water availability in these wetlands, changing water levels or surface water extent, in some cases, beyond historical variability. Attribution of the effects of human and climate activities is usually focused on changes within the wetlands or their upstream surface and groundwater inputs. However, the reliance of wetland water availability on upwind atmospheric moisture supply is less understood. Here, we assess the vulnerability of 40 Ramsar wetlands to precipitation changes caused by land use and hydroclimatic change occurring in their upwind moisture‐supplying regions. We use moisture flows from a Lagrangian tracking model, atmospheric reanalysis data, and historical land use change (LUC) data to assess and quantify these changes. Our analyses show that historical LUC has decreased precipitation and terrestrial moisture recycling in most wetland hydrological basins, decreasing surface water availability (precipitation minus evaporation). The most substantial effects on wetland water availability occurred in the tropic subtropical regions of Central Europe and Asia. Overall, we found wetlands in Central Asia and South America to be the most vulnerable by a combination of LUC‐driven effects on runoff, high terrestrial precipitation recycling, and recent decreases in surface water availability. This study stresses the need to incorporate upwind effects of land use changes in the restoration, management, and conservation of the world's wetlands. Plain Language Summary: Wetlands protected by the Ramsar Convention face threats from climate change and human activities, impacting their water availability and altering wetland functions. While past studies often focused on threats from their immediate surroundings, our research looks into the influence of changes in their upwind atmospheric moisture supply. We evaluate the vulnerability of 40 Ramsar wetland basins to precipitation shifts caused by land use and hydroclimatic changes in upwind regions, using the output of an atmospheric moisture tracking model and historical data. The results indicate that historical land use changes have reduced precipitation and moisture recycling, leading to a decrease in water availability in some wetlands, notably affecting tropical and subtropical regions of Central Europe and Asia. We assess that wetlands in Asia and South America face are vulnerable to a combination of land use‐induced runoff impacts, high precipitation recycling, and declining surface water availability. This study highlights the need to incorporate upwind effects of land use changes in wetland restoration, management, and conservation efforts globally, recognizing their crucial role for effective strategies for wetland protection amidst evolving environmental conditions. Key Points: Land use changes have led to mean annual runoff (P–E) decreases in wetland hydrological basins globallyThe most substantial land use‐related P–E changes occurred in tropical and subtropical wetlands across Asia and South America and in EuropeWe identify eight wetlands in Asia, South America, and Australia as particularly vulnerable to changes in upwind moisture sources [ABSTRACT FROM AUTHOR]

Alongside declining Arctic sea ice cover during the satellite era, there have also been positive trends in sea ice Arctic average drift speed (AADS) during both winter and summer. This increasing sea ice motion is an important consideration for marine transportation as well as a potential feedback on the rate of sea ice area decline. Earlier studies have shown that nearly all modern global climate models (GCMs) produce positive March (winter) AADS trends for both the historical period and future warming scenarios. However, most GCMs do not produce positive September (summer) AADS trends during the historical period, and nearly all GCMs project decreases in September AADS with future warming. This study seeks to understand the mechanisms driving these projected summertime AADS decreases using output from 17 models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) along with 10 runs of the Community Earth System Model version 2 Large Ensemble (CESM2-LE). The CESM2-LE analysis reveals that the projected summertime AADS decreases are due to changes in sea surface height (SSH) and wind stress which act to reduce sea ice motion in the Beaufort Gyre and Transpolar Drift. During March, changes in internal stress and wind stress counteract tilt force changes and produce positive drift speed trends. The simulated wintertime mechanisms are supported by earlier observational studies, which gives confidence that the mechanisms driving summertime projections are likely also at work in the real world. However, the precise strength of these mechanisms is likely not realistic during summer, and additional research is needed to assess whether the simulated summertime internal stress changes are too weak compared to changes in other forces. The projected summertime wind stress changes are associated with reduced sea level pressure north of Greenland, which is expected with the northward shift of the jet streams. The projected summertime SSH changes are primarily due to freshening of the Arctic Ocean (i.e., halosteric expansion), with thermal expansion acting as a secondary contribution. The associated ocean circulation changes lead to additional piling up of water in the Russian shelf regions, which further reinforces the SSH increase. Analysis of CMIP6 output provides preliminary evidence that some combination of wind stress and SSH changes is also responsible for projected AADS decreases in other models, but more work is needed to assess mechanisms in more detail. Altogether, our results motivate additional studies to understand the roles of SSH and wind stress in driving changes in Arctic sea ice motion. [ABSTRACT FROM AUTHOR]

Antarctic tourism has been growing increasingly and diversifying over the past two decades. In parallel, Antarctic tourism scholarship has particularly focused on tourism development and management. This industry- and policy-focused research has neglected to address how these developments affect place-making processes in Antarctica. This article is grounded in conceptual developments of 'Arctification', a phenomenon that appears to have significant impacts on the making of the Arctic as a place (to visit) using specific narratives in tourism. Thus, this study expands these conceptual developments to Antarctic tourism by investigating tourism's role in place-making in Antarctica through 'Antarctification'. Four types of narratives emerge from tourism promotion materials constituting the core of Antarctification: Antarctica as a place (1) of exploration, (2) that is wild and empty, (3) of superlatives, and (4) needing environmental stewardship and ambassadorship. The use of these narratives locks Antarctica into particular imaginaries designed to attract visitors. Identifying these dominant narratives is critical, as they may markedly impact conservation agendas, Antarctic wildlife encounters, icescapes, and heritage. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) is one of the important parameters of global ocean and climate research, which can be retrieved by satellite infrared and passive microwave remote sensing instruments. While satellite infrared SST offers high spatial resolution, it is limited by cloud cover. On the other hand, passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall, coastal effects, and high wind speeds. To achieve high-precision, comprehensive, and high-resolution SST data, it is essential to fuse infrared and microwave SST measurements. In this study, data from the Fengyun-3D (FY-3D) medium resolution spectral imager II (MERSI-II) SST and microwave imager (MWRI) SST were fused. Firstly, the accuracy of both MERSIII SST and MWRI SST was verified, and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST. After pretreatment and quality control of MERSI SST and MWRI SST, a Piece-Wise Regression method was employed to correct biases in MWRI SST. Subsequently, SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date. Finally, an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST. The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST. Furthermore, the fusion SST retained true spatial distribution details and exhibited an accuracy of -0.12±0.74°C compared to OSTIA SST. This study has improved the accuracy of FY satellite fusion SST products in China. [ABSTRACT FROM AUTHOR]

Our understanding and predictive capability of streamflow processes largely rely on high-quality datasets that depict a river's upstream basin characteristics. Recent proliferation of large sample hydrology (LSH) datasets has promoted model parameter estimation and data-driven analyses of hydrological processes worldwide, yet existing LSH is still insufficient in terms of sample coverage, uncertainty estimates, and dynamic descriptions of anthropogenic activities. To bridge the gap, we contribute the synthesis of Global Streamflow characteristics, Hydrometeorology, and catchment Attributes (GSHA) to complement existing LSH datasets, which covers 21 568 watersheds from 13 agencies for as long as 43 years based on discharge observations scraped from the internet. In addition to annual and monthly streamflow indices, each basin's daily meteorological variables (i.e., precipitation, 2 m air temperature, longwave/shortwave radiation, wind speed, actual and potential evapotranspiration), daily–weekly water storage terms (i.e., snow water equivalence, soil moisture, groundwater percentage), and yearly dynamic descriptors of the land surface characteristics (i.e., urban/cropland/forest fractions, leaf area index, reservoir storage and degree of regulation) are also provided by combining openly available remote sensing and reanalysis datasets. The uncertainties in all meteorological variables are estimated with independent data sources. Our analyses reveal the following insights: (i) the meteorological data uncertainties vary across variables and geographical regions, and the revealed pattern should be accounted for by LSH users; (ii) ∼6 % watersheds shifted between human-managed and natural states during 2001–2015, e.g., basins with environmental recovery projects in northeast China, which may be useful for hydrologic analysis that takes the changing land surface characteristics into account; and (iii) GSHA watersheds showed a more widespread declining trend in runoff coefficient than an increasing trend, pointing towards critical water availability issues. Overall, GSHA is expected to serve hydrological model parameter estimation and data-driven analyses as it continues to improve. GSHA v1.1 can be accessed at 10.5281/zenodo.8090704 and 10.5281/zenodo.10433905 (Yin et al., 2023a, b). [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) have significant social and ecological impacts, necessitating the prediction of these extreme events to prevent and mitigate their negative consequences and provide valuable information to decision-makers about MHW-related risks. In this study, machine learning (ML) techniques are applied to predict sea surface temperature (SST) time series and marine heatwaves in 16 regions of the Mediterranean Sea. ML algorithms, including the random forest (RForest), long short-term memory (LSTM), and convolutional neural network (CNN), are used to create competitive predictive tools for SST. The ML models are designed to forecast SST and MHWs up to 7 d ahead. For each region, we performed 15 different experiments for ML techniques, progressively sliding the training and the testing period window of 4 years from 1981 to 2017. Alongside SST, other relevant atmospheric variables are utilized as potential predictors of MHWs. Datasets from the European Space Agency Climate Change Initiative (ESA CCI SST) v2.1 and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis from 1981 to 2021 are used to train and test the ML techniques. For each area, the results show that all the ML methods performed with minimum root mean square errors (RMSEs) of about 0.1 °C at a 1 d lead time and maximum values of about 0.8 °C at a 7 d lead time. In all regions, both the RForest and LSTM consistently outperformed the CNN model across all lead times. LSTM has the highest predictive skill in 11 regions at all lead times. Importantly, the ML techniques show results similar to the dynamical Copernicus Mediterranean Forecasting System (MedFS) for both SST and MHW forecasts, especially in the early forecast days. For MHW forecasting, ML methods compare favorably with MedFS up to 3 d lead time in 14 regions, while MedFS shows superior skill at 5 d lead time in 9 out of 16 regions. All methods predict the occurrence of MHWs with a confidence level greater than 50 % in each region. Additionally, the study highlights the importance of incoming solar radiation as a significant predictor of SST variability along with SST itself. [ABSTRACT FROM AUTHOR]

The Mediterranean Sea (MS) has undergone significant surface warming, particularly pronounced during summers and associated with devastating impacts on marine life. Alongside the ongoing research on warming trends and marine heatwaves (MHWs), here we address the importance of understanding anomalously warm conditions also on the seasonal timescale. We propose the concept of extreme marine summers (EMSs) and investigate their characteristics in the MS, using sea surface temperature (SST) reanalysis data spanning 1950–2020. We define EMSs at a particular location, as the summers with a mean summer SST exceeding the 95th percentile. A marine summer may become extreme, under various SST substructures. Results show that, in most of the basin, EMSs are formed primarily due to the warmer summer days being warmer than normal. Areas where the warmest (coldest) part of the SST distribution is more variable experience EMSs primarily due to the warmest (coldest) part of the distribution being anomalously warm. MHWs occurring within EMSs are more intense, longer lasting, and more frequent than usual mainly in the northern MS regions. These enhanced MHW conditions occur mainly within the warmest part of the SST distribution. By means of temporal coverage of MHW conditions, a more pronounced occurrence of MHWs in EMSs is found for the central and eastern basin where up to 55 % of MHW days over 1950–2020 fall within EMSs. The role of air–sea heat fluxes in driving EMSs is quantified through a newly proposed metric. Results suggest that surface fluxes primarily drive EMSs in the northern half of the MS, while oceanic processes play a major role in southern regions. Upper-ocean preconditioning also contributes to the formation of EMSs. Finally, a detrended dataset was produced to examine how the SST multi-decadal variability affects the studied EMS features. Despite leading to warmer EMSs basin-wide, the multi-decadal signal does not significantly affect the dominant SST substructures during EMSs. Results also highlight the fundamental role of latent heat flux in modulating the surface heat budget during EMSs, regardless of the long-term trends. [ABSTRACT FROM AUTHOR]

Eurasian rivers provide a quarter of total fresh water to the Arctic, maintaining a persistent fresh layer that covers the surface Arctic Ocean. This freshwater export controls Arctic Ocean stratification, circulation, and basin-wide sea ice concentration. The Lena River supplies the largest volume of runoff and plays a key role in this system, as runoff outflows into the Laptev Sea as a particularly shallow plume. Previous in situ and modelling studies suggest that local wind forcing is a driver of variability in Laptev sea surface salinity (SSS) but there is no consensus on the roles of Lena River discharge and sea ice cover in contributing to this variability or on the dominant driver of variability. Until recently, satellite SSS retrievals were insufficiently accurate for use in the Arctic. However, retreating sea ice cover and continuous progress in satellite product development have significantly improved SSS retrievals, giving satellite SSS data true potential in the Arctic. In this region, satellite-based SSS is found to agree well with in situ data (r>0.8) and provides notable improvements compared to the reanalysis product used in this study (r>0.7) in capturing patterns and variability observed in in situ data. This study demonstrates a novel method of identifying the dominant drivers of interannual variability in Laptev Sea dynamics within reanalysis products and testing if these relationships appear to hold in satellite-based SSS, sea surface temperature (SST) data, and in situ observations. The satellite SSS data firmly establish what is suggested by reanalysis products and what has previously been subject to debate due to the limited years and locations analysed with in situ data; the zonal wind is the dominant driver of offshore or onshore Lena River plume transport. The eastward wind confines the plume to the southern Laptev Sea and drives alongshore transport into the East Siberian Sea, and westward wind drives offshore plume transport into the northern Laptev Sea. This finding is affirmed by the strong agreement in SSS pattern under eastward and westward wind regimes in all reanalyses and satellite products used in this study, as well as with in situ data. The pattern of SST also varies with the zonal wind component and drives spatial variability in sea ice concentration. [ABSTRACT FROM AUTHOR]

In summer, the survival zones of cold‐water species are predicted to narrow by both increasing water temperatures from the surface and by expanding hypoxic zones from the lake bottom. To examine how the abundance of cold‐water fishes changes along environmental gradients, we assessed the vertical environmental DNA (eDNA) distributions of three salmonid species which may have different water temperature tolerances during both stratification and turnover periods using quantitative PCR (qPCR). In addition, we examined on the vertical distribution of diverse fish fauna using an eDNA metabarcoding assay. The results suggested that the kokanee salmon (Oncorhynchus nerka) eDNA were abundant in deep, cold waters. On the other hand, rainbow trout (O. mykiss) eDNA were distributed uniformly throughout the water column, suggesting that they may have high water‐temperature tolerance compared with kokanee salmon. The eDNA concentrations of masu salmon (O. masou) were below the detection limit (i.e., <10 copies μL−1) at all stations and depths and hence could not be quantified during stratification. Together with the finding that the eDNA distributions of other prey fish species were also constrained vertically in species‐specific ways, our results suggest that climate change will result in substantial changes in the vertical distributions of lake fish species and thus affect their populations and interactions. [ABSTRACT FROM AUTHOR]

Background : Research in outdoor adventure education (OAE) and related fields has argued that OAE programming can problematically reproduce dominant ways of being around patriarchy and whiteness. In particular, scholars have forwarded specific critiques of sense of place (SOP) in OAE or related fields. Purpose: This article investigated and critiqued SOP as a fundamental curricular concept and offered an anticolonial analytical tool for educators. The article posited that SOP is a key site of intervention for OAE educators and programs with anticolonial goals because of the historical, sociocultural, and economic foundations of SOP in OAE. Methodology/Approach: This study employed an anticolonial and antiracial capitalist theoretical framework and qualitative methods including thematic study of select literature on environmental conservation and colonialism, analysis of fundamentals of anticolonial pedagogical frameworks, and interview findings from mentor-partners in OAE and related fields. Findings/Conclusions: This study developed an anticolonial analytical tool to understand and interpret SOP in OAE through an anticolonial lens. Implications: The purpose of this tool is to assist practitioners and educators in the analysis of their own SOP pedagogy and practices and to encourage the development of SOP curricula toward anticolonial aims. [ABSTRACT FROM AUTHOR]