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Over thousands of years, Indigenous hunters in the Bering and Chukchi seas have adapted to changes in weather, sea ice, and sea state that influence their access to walruses. In recent decades, 10 however, those conditions have been changing at unprecedented rates. Safely adapting to changing conditions will be essential to the well-being of communities. 

Cold exposure remains a significant public health concern, particularly in the Arctic regions prone to extremely cold weather. While the physical health impacts of cold exposure are well documented, understanding the social vulnerability aspects is crucial for effective mitigation and policy development. This study investigates the multifaceted dimensions of social vulnerability in the face of cold temperatures across various communities in Alaska. Alaska, renowned for its extreme cold temperatures and harsh environmental conditions, poses unique challenges to its residents, particularly in the context of social vulnerability. Drawing on a combination of quantitative data analysis and qualitative insights, we examine the factors contributing to social vulnerability, including demographic, economic, geographic, and infrastructural elements, in terms of the Extremely Cold Social Vulnerability Index, for seven Public Health Regions in Alaska. The Universal Thermal Climate Index in two very cold categories (<−27 °C) was used to identify cold exposure. Factors such as income, housing quality, health status, and resilience of the population play crucial roles in determining an individual or community’s sensitivity to, and ability to cope with, cold temperatures. Our analysis reveals that social vulnerability in Alaska is not uniform but varies significantly among regions. The research findings highlight the importance of considering factors of both sensitivity and adaptivity in understanding and addressing social vulnerability, thereby informing the development of targeted strategies and policies to enhance the resilience of Alaskan communities. As cold temperatures are projected to continue to challenge the region, addressing social vulnerability is essential for ensuring the well-being and safety of Alaska’s diverse populations. 

Abstract This paper offers a comprehensive, analytical, and critically informed overview of the current state of ocean multi-use research. It delves into the origins, trajectory, and driving forces behind this emerging research field, all within the broader context of investigations addressing the management of increasingly diverse and intensifying activities at sea. The Bibliometrix R package is employed to analyze the social, geographical, and conceptual dimensions of multi-use scientific production. The results obtained are then compared to a larger corpus of publications focusing on both multiple-use Marine Protected Areas (MPAs) and Marine Spatial Planning (MSP). Finally, the paper addresses research gaps, with a particular emphasis on the transdisciplinary challenges associated with translating this new marine policy concept into practical implementation and extending its application beyond European seas. 

Abstract Some of the largest climatic changes in the Arctic have been observed in Alaska and the surrounding marginal seas. Near-surface air temperature (T2m), precipitation ( P ), snowfall, and sea ice changes have been previously documented, often in disparate studies. Here, we provide an updated, long-term trend analysis (1957–2021; n = 65 years) of such parameters in ERA5, NOAA U.S. Climate Gridded Dataset (NClimGrid), NOAA National Centers for Environmental Information (NCEI) Alaska climate division, and composite sea ice products preceding the upcoming Fifth National Climate Assessment (NCA5) and other near-future climate reports. In the past half century, annual T2m has broadly increased across Alaska, and during winter, spring, and autumn on the North Slope and North Panhandle (T2m > 0.50°C decade −1 ). Precipitation has also increased across climate divisions and appears strongly interrelated with temperature–sea ice feedbacks on the North Slope, specifically with increased (decreased) open water (sea ice extent). Snowfall equivalent (SFE) has decreased in autumn and spring, perhaps aligned with a regime transition of snow to rain, while winter SFE has broadly increased across the state. Sea ice decline and melt-season lengthening also have a pronounced signal around Alaska, with the largest trends in these parameters found in the Beaufort Sea. Alaska’s climatic changes are also placed in context against regional and contiguous U.S. air temperature trends and show ∼50% greater warming in Alaska relative to the lower-48 states. Alaska T2m increases also exceed those of any contiguous U.S. subregion, positioning Alaska at the forefront of U.S. climate warming. Significance Statement This study produces an updated, long-term trend analysis (1957–2021) of key Alaska climate parameters, including air temperature, precipitation (including snowfall equivalent), and sea ice, to inform upcoming climate assessment reports, including the Fifth National Climate Assessment (NCA5) scheduled for publication in 2023. Key findings include widespread annual and seasonal warming with increased precipitation across much of the state. Winter snowfall has broadly increased, but spring and autumn snowfalls have decreased as rainfall increased. Autumn warming and precipitation increases over the North Slope, in particular, appear related to decreased sea ice coverage in the Beaufort Sea and Chukchi Seas. These trends may result from interrelated processes that accelerate Alaska climate changes relative to those of the contiguous United States. 

Manifestations of global warming in the Arctic include amplifications of temperature increases and a general increase in precipitation. Although topography complicates the pattern of these changes in regions such as Alaska, the amplified warming and general increase in precipitation are already apparent in observational data. Changes in snow cover are complicated by the opposing effects of warming and increased precipitation. In this study, high-resolution (0.25°) outputs from simulations by the Community Atmosphere Model, version 5, were analyzed for changes in snow under stabilized global warming scenarios of 1.5 °C, 2.0 °C and 3.0 °C. Future changes in snowfall are characterized by a north–south gradient over Alaska and an east–west gradient over Eurasia. Increased snowfall is projected for northern Alaska, northern Canada and Siberia, while milder regions such as southern Alaska and Europe receive less snow in a warmer climate. Overall, the results indicate that the majority of the land area poleward of 55°N will experience a reduction in snow. The approximate threshold of global warming for a statistically significant increase in temperature over 50% of the pan-Arctic land area is 1.5 °C. The corresponding threshold for precipitation is approximately 2.0 °C. The global warming threshold for the loss of high-elevation snow in Alaska is approximately 2.0 °C. The results imply that limiting global warming to the Paris Agreement target is necessary to prevent significant changes in winter climates in Alaska and the Arctic. 

While recent increases in heavy precipitation events in some midlatitude regions are consistent with climate model simulations, evidence of such increases in high latitudes is more tenuous, partly because of data limitations. The present study evaluates historical and future changes in extreme precipitation events in Alaska. Using the ERA5 reanalysis, station data, and output from two downscaled global climate models, we examine precipitation-driven flood events at five diverse locations in Alaska where major historical floods provide benchmarks: Fairbanks (August 1967), Seward (October 1986), Allakaket/Bettles (August 1994), Kivalina (August 2012), and Haines (December 2020). We place these precipitation events into a framework of historical trends and end-of-century (2065–2100) model projections. In all but one of the flood events, the amount of rainfall was the highest on record for the event duration, and precipitation events of this magnitude are generally projected by the models to remain infrequent. All of the cases had subtropical or tropical moisture sources. None of the locations show statistically significant historical trends in the magnitude of extreme precipitation events. However, the frequencies of heavy precipitation events are projected to increase at most of the locations. The frequency of events with 2 year and 5 year historical return intervals is projected to become more frequent, especially in the Interior, and in some cases increase to several times per year. Decreases are projected only for Seward along Alaska’s southern coast. 

A great many problems in network information theory, both fundamental and applied, involve determining a minimal set of inequalities linking the Shannon entropies of a certain collection of subsets of random variables. In principle this minimal set of inequalities could be determined from the entropy region, whose dimensions are all the subsets of random variables, by projecting out dimensions corresponding to the irrelevant subsets. As a general solution technique, however, this method is plagued both by the incompletely known nature of the entropy region as well as the exponential complexity of its bounds. Even worse, for four or more random variables, it is known that the set of linear information inequalities necessary to completely describe the entropy region must be uncountably infinite. A natural question arises then, if there are certain nontrivial collections of subsets where the inequalities linking only these subsets is both completely known, and have inequality descriptions that are linear in the number of random variables. This paper answers this question in the affirmative. A decomposition expressing the collection of inequalities linking a larger collection of subsets from that of smaller collections of subsets is first proven. This decomposition is then used to provide systems of subsets for which it both exhaustively determines the complete list of inequalities, which is linear in the number of variables. 

Determining the rate region of a network is of great importance in the research area of network coding. Lots of attempts have been made and significant progress has been achieved over the last decade on this topic. Although these researches provide us with multiple ways of calculating the outer or inner bounds of rate region, the sheer complexity of the problem, which involves expressing and projecting a very high dimensional polyhedra, makes it computationally infeasible beyond networks with 10s of edges. Aimed at reducing the complexity of the rate region calculation, in this paper a new theorem that implicitly determines the rate region of a network is proved and a corresponding systematic way of applying the theorem to calculate explicitly the outer bounds to a rate region is proposed. Compared with the traditional method, the proposed method has the potential to calculate the true rate region via the projection of simpler polyhedra that has exponentially less dimensions and is characterized by exponentially less facets. 

Evapotranspiration (ET) is a relevant component of the surface moisture budget and is associated with different drivers. The interrelated drivers cause variations at daily to interannual timescales. This study uses structural equation modeling to diagnose the drivers over an ensemble of 45 high-latitude sites, each of which provides at least several years of in situ measurements, including latent heat fluxes derived from eddy covariance flux towers. The sites are grouped by vegetation type (tundra, forest) and the presence or absence of permafrost to determine how the relative importance of different drivers depends on land surface characteristics. Factor analysis is used to quantify the common variance among the variables, while a path analysis procedure is used to assess the independent contributions of different variables. The variability of ET at forest sites generally shows a stronger dependence on relative humidity, while ET at tundra sites is more temperature-limited than moisture-limited. The path analysis shows that ET has a stronger direct correlation with solar radiation than with any other measured variable. Wind speed has the largest independent contribution to ET variability. The independent contribution of solar radiation is smaller because solar radiation also affects ET through various other drivers. The independent contribution of wind speed is especially apparent at forest wetland sites. For both tundra and forest vegetation, temperature loads higher on the first factor when permafrost is present, implying that ET will become less sensitive to temperature as permafrost thaws.