Including Sea Ice Research Articles

Summer Hydrography Conditions at Proglacial Fjord Entrances Along East Greenland

AbstractClimate change is causing widespread melting of land and sea ice in the Arctic, leading to an increase in freshwater input to the ocean. This may have an impact on ocean circulation, marine ecosystems, and biodiversity in the region. Our findings provide new insights into the summer hydrography conditions at proglacial fjord entrances along large parts of the east coast of Greenland. As most freshwater exits the Arctic Ocean through Fram Strait this study focuses on understanding the origin of spatial distribution of temperature and freshwater in the coastal waters in East Greenland. We find that Polar Water and the Atlantic Water variants (Eurasian Basin Atlantic Water/Subpolar Mode Water) dominate coastal waters north and south of Denmark Strait, respectively, and that coastal waters are influenced by advected meltwater from the Arctic Ocean, glacier meltwater and local precipitation. Combining hydrographic observations, water isotope data, and water source fraction analysis, we show that glacier meltwaters can be detected at fjord entrances and down to approximately 200 m. Integrated over the upper 200 m of the water column, glacial meltwater account for approximately 9%, precipitation for around 8% and Polar Water (including sea ice melt) for approximately 83% of the freshwater observed along the East Greenland coast. Below 200 m, Atlantic Water variants dominate the entire coastal section. The freshwater along East Greenland stays close to the coast and we could not detect any glacier meltwater at the slope.

Extraction and analysis of the sea ice parameter dataset of the Bohai Sea from 2011 to 2021 based on GOCI

The Bohai Sea and its surrounding areas are rich in oil and natural gas and play an important role in industry, agriculture and the economy. However, the Bohai Sea suffers severely from sea ice in the winter. While previous research has predominantly focused on methods for retrieving sea ice parameters in the Bohai Sea, analyses of their long-term statistical patterns have been limited. The Geostationary Ocean Color Imager (GOCI) is the first geostationary satellite for ocean color remote sensing, offering high spatial and temporal resolution, which greatly facilitates the extraction of Bohai Sea ice parameters. Utilizing GOCI data, we systematically extracted relevant sea ice parameters for the Bohai Sea region from 2011 to 2021. These parameters include sea ice concentration, sea ice thickness, and sea ice drift. We conducted a comprehensive statistical analysis of the long-term sea ice changes in the Bohai Sea and found that the development process of winter sea ice area is different from the sea ice thickness, and the direction of sea ice drift is basically unchanged. Then we developed statistical models linking sea ice parameters with ocean dynamic factors such as temperature, wind, and drift currents. Among them, the correlation coefficient between the predicted value and the measured value of the sea ice area model is the highest, reaching 0.8382. Furthermore, we examined the previously unexplored relationship between daily sea ice area, sea ice thickness, and accumulated temperature with their respective starting temperatures and accumulation periods. This study provides critical data to support Bohai Sea ice monitoring and marine environmental research. The results of this study contribute to a better understanding of sea ice change trends in the Bohai Sea and inform the development of disaster prevention and mitigation measures.

Impacts of stronger winds and less sea ice on Canadian Beaufort Sea shelf ecosystems since the late 1990s

Continuous and multi-decadal records of faunal abundance and diversity helping to identify the impacts of ongoing global warming on aquatic ecosystems are rare in the coastal Arctic. Here, we used a 50-year-long microfaunal record from a sediment core collected in the Herschel Basin (YC18-HB-GC01; 18 m water depth) to document some aspects of the environmental responses of the southern Canadian coastal Beaufort Sea to climate change. The microfaunal indicators include benthic foraminiferal assemblages, ostracods and tintinnids. The carbonate shells of two foraminiferal species were also analyzed for their stable isotope signatures (δ13C and δ18O). We compiled environmental parameters from 1970 to 2019 for the coastal region, including sea ice data (break-up date, freeze-up date, open season length and mean summer concentration), the wind regime (mean speed, direction of strong winds and the number of storms), hydrological data (freshet date, freshet discharge and mean summer discharge of the Firth and the Mackenzie rivers), and air temperature. Large-scale atmospheric patterns were also taken into consideration. Time-constrained hierarchal clustering analysis of foraminiferal assemblages and environmental parameters revealed a near-synchronous shift around the late 1990s. The microfaunal shift corresponds to an increased abundance of taxa tolerant to variable salinity, turbulent bottom water conditions, and turbid waters towards the present. The same time interval is marked by stronger easterly winds, more frequent storms, reduced sea-ice cover, and a pervasive anticyclonic circulation in the Arctic Ocean (positive Arctic Ocean Oscillation; AOO+). Deeper vertical mixing in the water column in response to intensified winds was fostered by increased open surface waters in summer leading to turbulence, increased particle loading and less saline bottom waters at the study site. Stronger easterly winds probably also resulted in enhanced resuspension events and coastal erosion in addition to a westward spreading of the Mackenzie River plume, altogether contributing to high particulate-matter transport. Increase food availability since ∼2000 was probably linked to enhanced degradation of terrestrial organic carbon, which also implies higher oxygen consumption. The sensitivity of microfaunal communities to environmental variations allowed capturing consequences of climate change on a marine Arctic shelf ecosystem over the last 50 years.

Diverse marine benthic communities and reduced anthropogenic contaminants near Scott Base (Hut Point Peninsula, Ross Island, Antarctica)

AbstractAntarctic marine ecosystems are largely thought to be among the planet’s least impacted, yet habitats adjacent to research stations can be heavily polluted. Despite long-term monitoring and remediation being high priorities for international environmental protection, the ecological responses to contaminants and stressors remains poorly characterised, limiting our ability to manage and reduce human impacts. This study compares epifaunal community composition at two sites close to Scott Base with a reference site further away. We couple these data with environmental characteristics, including current data, sediment properties, and contaminant concentrations within the sediment and in the tissues of two epifaunal species, both from this survey and those previously reported. Previously high concentrations of polychlorinated biphenyls and polyaromatic hydrocarbons are now undetectable and concentrations of heavy metals were mostly similar or reduced compared to previous data from 2002. High within-site variance suggests localised contamination footprints from being situated within a deposition zone and/or from the erosion of anthropogenic debris. Despite the persistence of some metals (arsenic, copper and lead) at one site, our study revealed high biodiversity at all three sites (22–28 taxa per 0.25 m2). Benthic community structure was influenced by a combination of factors, including sea ice characteristics, sediment type and habitat complexity. Overall, our study clearly highlights the influence of human activities on the benthos in adjacent marine habitats. The established monitoring protocols coupling diver and remote sampling will enable regular monitoring, filling a critical need for time-series data in order to detect long-term trends and interactions with climate drivers.

Functional connectivity of an imperilled Arctic ungulate – where melting sea ice and human trails increase isolation

Sea ice loss, disturbance, and habitat modification by humans can alter functional landscape connectivity, with negative impacts on wildlife. Connectivity facilitates movement and gene flow, and contributes to genetic diversity, metapopulation dynamics, and species range-shifts under climate change. For Arctic ungulates, which disperse over large areas including sea ice, environmental change threatens further isolation. Protecting habitat and its linkages is critical and depends on identifying such areas at commensurate, broad scales. Using caribou, the world's most vagile species, we modelled and mapped the drivers of connectivity across ca. 2 million km2 of the Canadian Arctic Archipelago — where the pace of climate change is among the fastest and caribou are threatened with extinction. First, we quantified hierarchical genetic structure and identified two discrete groups. Next, using circuit theory and simultaneous multi-surface optimization, we tested whether land- and sea-scape heterogeneity or geographic distance better accounted for movement and gene flow within each group. We show that anthropogenic interference is far-reaching. High Arctic Peary caribou displayed isolation-by-resistance, where glacier cover, low sea-ice concentrations during fall, and human trails impeded connectivity. In contrast, more southerly barren-ground caribou displayed largely unrestricted gene flow. These divergent outcomes underscore that organism-landscape relationships can vary across space and highlight the importance of intra-specific structure and responses. By leveraging genetic data, our study demonstrates how critical movement pathways can be identified, even for remote and imperilled species. Such knowledge supports broad-scale conservation planning, in particular, by accounting for complex organism-landscape relationships, across vast, heterogeneous ecosystems.

Enhancing Sea Ice Inertial Oscillations in the Arctic Ocean between 1979 and 2019

As the Arctic Ocean continues to warm, both the extent and thickness of sea ice have dramatically decreased over the past few decades. These changes in ice have an impact on sea ice motion, including sea ice inertial oscillations (SIIO). However, the spatial pattern and temporal variations of Arctic SIIO remain poorly understood. In this study, the spatiotemporal characteristics of Arctic SIIO between 1979 and 2019 are revealed based on the sea ice drifting buoy dataset from the International Arctic Buoy Program (IABP). The results indicate the significant enhancement of SIIO during 1979–2019, with the trend of 7.84 × 10−3 (±3.34 × 10−3) a−1 (a−1 means per year) in summer and 1.92 × 10−3 (±0.80 × 10−3) a−1 in winter. Compared with the first 30 years, the magnitude of SIIO in 2009–2019 increases by 66% in summer and 21% in winter. Spatially, the remarkable enhancement of SIIO during 2009–2019 is found in most of the Arctic Ocean. Especially in summer, SIIO are significantly intensified in marginal seas, including the Beaufort Sea, East Siberian Sea and Laptev Sea, which is mainly correlated with the decrease of sea ice concentration in recent years. This study is anticipated to provide insights for spatiotemporal variation of Arctic sea ice inertial motion in recent decades.

A review of recent developments in low-frequency ultra-wideband microwave radiometry for studies of the cryosphere

Over the past decade, a series of airborne experiments in the Arctic and Antarctica explored microwave emission from sea ice and ice sheets at frequencies from 0.5 to 2 GHz. The experiments were motivated by the fact that lower frequencies penetrate deeper into a frozen surface, thus offering the possibility to measure physical temperatures at great depths in ice sheets and, subsequently, other unique geophysical observables including sea ice salinity. These experiments were made feasible by recent engineering advances in electronics, antenna design, and noise removal algorithms when operating outside of protected bands in the electromagnetic spectrum. These technical advances permit a new type of radiometer that not only operates at low frequency, but also obtains continuous spectral information over the band from 0.5 to 2 GHz. Spectral measurements facilitate an understanding of the physical processes controlling emission and also support the interpretation of results from single frequency instruments. This paper reviews the development of low-frequency, wide band radiometry and its application to cryosphere science over the past 10 years. The paper summarizes the engineering design of an airborne instrument and the associated algorithms to mitigate radio frequency interference. Theoretical models of emission built around the morphologic and electrical properties of cryospheric components are also described that identify the dominant physical processes contributing to emission spectra. New inversion techniques for geophysical parameter retrieval are summarized for both Arctic and Antarctic scenarios. Examples that illustrate how the measurements are used to inform on glaciological problems are presented. The paper concludes with a description of new instrument concepts that are foreseen to extend the technology into operation from space.

Evaluating sea ice thickness simulation is critical for projecting a summer ice-free Arctic Ocean

The rapid decline of Arctic sea ice, including sea ice area (SIA) retreat and sea ice thinning, is a striking manifestation of global climate change. Analysis of 40 CMIP6 models reveals a very large spread in both model simulations of the September SIA and thickness and the timing of a summer ice-free Arctic Ocean. The existing SIA-based evaluation metrics are deficient due to observational uncertainty, prominent internal variability, and indirect Arctic response to global forcing. Given the critical roles of sea ice thickness (SIT) in determining Arctic ice variation throughout the seasonal cycle and the April SIT bridging the winter freezing and summer melting processes, we propose two SIT-based metrics, the April mean SIT and summer SIA response to April SIT, to assess climate models’ capability to reproduce the historical change of the Arctic sea ice area. The selected 11 good models reduce the uncertainty in the projected first ice-free Arctic by 70% relative to 11 poor models. The chosen models’ ensemble mean projects the first ice-free year in 2049 (2043) under the shared socio-economic pathways (SSP)2-4.5 (SSP5-8.5) scenario with one standard deviation of the inter-model spread of 12.0 (8.9) years.

Nudging Observed Winds in the Arctic to Quantify Associated Sea Ice Loss from 1979 to 2020

Abstract Over the past decades, Arctic climate has exhibited significant changes characterized by strong pan-Arctic warming and a large-scale wind shift trending toward an anticyclonic anomaly centered over Greenland and the Arctic Ocean. Recent work has suggested that this wind change is able to warm the Arctic atmosphere and melt sea ice through dynamically driven warming, moistening, and ice drift effects. However, previous examination of this linkage lacks a capability to fully consider the complex nature of the sea ice response to the wind change. In this study, we perform a more rigorous test of this idea by using a coupled high-resolution modeling framework with observed winds nudged over the Arctic that allows for a comparison of these wind-induced effects with observations and simulated effects forced by anthropogenic forcing. Our nudging simulation can well capture observed variability of atmospheric temperature, sea ice, and the radiation balance during the Arctic summer and appears to simulate around 30% of Arctic warming and sea ice melting over the whole period (1979–2020) and more than 50% over the period 2000–12, which is the fastest Arctic warming decade in the satellite era. In particular, in the summer of 2020, a similar wind pattern reemerged to induce the second-lowest sea ice extent since 1979, suggesting that large-scale wind changes in the Arctic are essential in shaping Arctic climate on interannual and interdecadal time scales and may be critical to determine Arctic climate variability in the coming decades. Significance Statement This work conducts a set of new CESM1 nudging simulations to quantify the impact of the observed evolution of large-scale high-latitude atmospheric winds on Arctic climate variability over the past four decades. Variations in climate parameters, including sea ice, radiation, and atmospheric temperatures are well replicated in the model when observed winds are imposed in the Arctic. By investigating simulated sea ice melting processes in the simulation, we illustrate and estimate how large-scale winds in the Arctic help melt sea ice in summer. The nudging method has the potential to make Arctic climate attribution more tangible and to unravel the important physical processes underlying recent abrupt climate change in the Arctic.

The Study of Soil Bacterial Diversity and the Influence of Soil Physicochemical Factors in Meltwater Region of Ny-Ålesund, Arctic

Global climate change has caused the changes of the ecological environment in the Arctic region, including sea ice melting, runoff increase, glacial lake expansion, and a typical meltwater area has formed in the Arctic coastal area. In this study, the meltwater areas near six different characteristic areas of Ny-Ålesund in 2018 were taken as the research objects, and high-throughput sequencing of V3–V4 regions of all samples were performed using 16S rDNA. Among the soil samples of six glacial meltwater areas in Ny-Ålesund, Arctic, the meltwater area near the reservoir bay had the highest bacterial abundance, and the meltwater area near the sand had the lowest one. The dominant phyla in soil samples were Proteobacteria, Actinobacteria, Acidobacteria. The NH4+-N content in intertidal soil was higher than that in subtidal soil. Through WGCNA analysis and LEFSE analysis, it was found that the core bacteria significantly related to NH4+-N were basically distributed in the intertidal area. For example, Nitrosomonadaceae, Nitrospira and Sphingomonas were the core bacteria showed significant different abundance in the intertidal area, which have the ability to metabolize NH4+-N. Our findings suggest that NH4+-N plays an important role in soil bacterial community structure in the Arctic meltwater areas.

Evaluation of Sea Ice Simulation of CAS-ESM 2.0 in Historical Experiment

A sea ice model is an important component of an Earth system model, which is an essential tool for the study of sea ice, including its internal processes, interactions with other components, and projected future changes. This paper evaluates a simulation of sea ice by the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM 2.0), focusing on a historical simulation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with the observations, CAS-ESM 2.0 reproduces reasonable seasonal cycle features and the climatological spatial distribution of Arctic and Antarctic sea ice, including sea ice extent (SIE), sea ice concentration, and sea ice thickness and motion. However, the SIE in CAS-ESM 2.0 is too large in winter and too low in summer in both hemispheres, indicating higher seasonal variations of the model relative to observations. Further sea ice mass budget diagnostics show that basal growth contributes most to ice increase in both hemispheres, basal melt and top melt make a comparable contribution to Arctic ice decrease, and basal melt plays a dominant role in Antarctic ice loss. This, combined with surface air temperature (SAT) and sea surface temperature (SST) biases, suggests that the excess of sea ice simulated in wintertime in both hemispheres and the lower SIE simulated in the Antarctic summer are mainly attributable to the bias in SST, whereas the lower SIE simulated in the Arctic summer is probably due to the combined effects of both the SST and SAT biases.

Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements: Uncertainty Analyses

The application of diffusion theory and Monte Carlo lidar radiative transfer simulations presented in Part I of this series of study suggests that snow depth can be derived from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. These methods are now applied to the satellite ICESat-2 lidar measurements over the Arctic sea ice and land surfaces of Northern Hemisphere. Over the Arctic sea ice, the ICESat-2 retrieved snow depths agree well with co-located IceBridge snow radar measured values with a root-mean-square (RMS) difference of 7.8 cm or 29.2% of the mean snow depth. The terrestrial snow depths derived from ICESat-2 show drastic spatial variation of the snowpack along ICESat-2 ground tracks over the Northern Hemisphere, which are consistent with the University of Arizona (UA) and Canadian Meteorological Centre (CMC) gridded daily snow products. The RMS difference in snow depths between ICESat-2 and UA gridded daily snow products is 14 cm, or 28% of the mean UA snow depth. To better understand these results, we also discuss the possible sources of errors in ICESat-2 derived snow depths, including surface roughness within the laser footprint, atmospheric forward scattering, solar background noise, and detector dark current. Simulation results indicate that the snow depth errors would be less than 5 cm if the standard deviation of pulse spreading due to surface roughness is within 50 cm. Our results demonstrate that the ICESat-2 lidar measurements can be used to reliably derive snow depth, which is a critical geophysical parameter for cryosphere studies including sea ice thickness estimation and also provides important constraints in the modeling of terrestrial hydrological processes.

Arctic amplification modulated by Atlantic Multidecadal Oscillation and greenhouse forcing on multidecadal to century scales

Enhanced warming in the Arctic (Arctic amplification, AA) in the last decades has been linked to several factors including sea ice and the Atlantic Multidecadal Oscillation (AMO). However, how these factors contributed to AA variations in a long-term perspective remains unclear. By reconstructing a millennial AA index combining climate model simulations with recently available proxy data, this work determines the important influences of the AMO and anthropogenic greenhouse gas forcing on AA variations in the last millennium, leading to identification of a significant downward trend of AA on top of a sustained strong AMO modulation at the multidecadal scales. The decreased AA during the industrial era was strongly associated with the anthropogenic forcing, proving the emerging role of the forcing in reducing the AA strength.

Sea Surface Salinity Variability in the Bering Sea in 2015–2020

Salinity in the Bering Sea is vital for the physical environment that is tied to the productive ecosystem and the properties of Pacific waters transported to the Arctic Ocean. Its salinity variability reflects many fundamental processes, including sea ice formation/melting and river runoff, but its spatial and temporal characteristics require better documentation. This study utilizes remote sensing products and in situ observations collected by saildrone missions to investigate Sea Surface Salinity (SSS) variability. All Satellite products resolve the large-scale pattern set up by the relatively salty deep basin and the fresh coastal region, but they can be inaccurate near the ice edge and near land. The SSS annual cycle exhibits seasonal maxima in winter to spring, and minima in summer to fall. The amplitude and timing of the seasonal cycle are variable, especially on the eastern Bering Sea shelf. SSS variability recorded by both saildrone, and satellite instruments provide unprecedented insights into short-term oceanic processes including sea ice melting, wind-driven currents during weather events, and river plumes etc. In particular, the Soil Moisture Active Passive (SMAP) satellite demonstrates encouraging skills in capturing the freshening signals induced by spring sea ice melting. The Yukon River plume is another source of intense SSS variability. Surface wind forcing plays an essential role in controlling the horizontal movement of plume water and thereby shaping the SSS seasonal cycle in local regions.

Polar maps of C-band backscatter parameters from the Advanced Scatterometer

Abstract. Maps of backscatter anisotropy parameters from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Advanced Scatterometer (ASCAT), a C-band fan-beam scatterometer, contain unique and valuable data characterising the surface and subsurface of various cryospheric elements, including sea ice and ice sheets. The computational expense and considerable complexity required to produce parameter maps from the raw backscatter data inhibits the wider adoption of ASCAT data. Here, backscatter anisotropy parameter maps gridded at a resolution of 12.5 km per pixel are made available to the community in order to facilitate the exploitation of these parameters for cryospheric applications. These maps have been calculated from the EUMETSAT Level 1B Sigma0 product acquired from ASCAT on board MetOp-A, MetOp-B and MetOp-C. The dataset is unique in that it prioritises anisotropy characterisation over temporal resolution and combines ASCAT data from multiple platforms. The parameterisation chosen assumes a linear falloff of backscatter with incidence angle and a fourth-order Fourier series parameterisation of azimuth angle anisotropy. The product (Fraser and Cartwright, 2022) is available at https://doi.org/10.26179/91c9-4783 presented on three timescales depending on orbital platform availability: 5 d (2007 to 2020 – MetOp-A only – suitable for users requiring a long time series), 2 d (2013 to 2020 – MetOp-A and MetOp-B) and 1 d resolution (2019–2020 – MetOp -A, MetOp-B and MetOp-C – suitable for users needing both high temporal resolution and detailed anisotropy characterisation). Datasets will be updated annually.

Canada’s Internet-Connected Ocean

Over fifteen years ago, Ocean Networks Canada (ONC) began with the world’s first large-scale, interactive, real-time portal into the ocean, bringing continuous, real-time data to the surface for applications in scientific research, societal benefits, and supporting Canada’s ocean industry. This marked the dawn of the Internet-connected ocean, enabling a more fulsome understanding of the ocean through ocean intelligence. These open data have improved our ability to monitor and understand our changing ocean offshore all three coasts of Canada, thanks to diversity of sensor systems to monitor earthquakes and tsunamis, deep sea biodiversity, whales, hydrothermal vents, neutrinos, ocean noise, ocean acidification, forensics experiments, and the impact of climate change, including sea ice thinning in the Arctic. This pioneering approach began in the late 1990s, when scientists began developing a new way of doing ocean science that was no longer limited by weather and ship-time. They imagined a permanent presence in the ocean of sensors to allow a continuous flow of ocean data via the Internet. This big science began to take shape early this century, when a partnership between United States and Canadian institutions was established. ONC evolved out of this international collaboration with seed funding from the Canada Foundation for Innovation, while in the United States, the Ocean Observatories Initiative (OOI) was funded. ONC works closely with OOI on that span the countries’ west coast border. Recently similar observing initiatives in Europe have begun, led by EMSO, which now has a close collaboration with ONC as an Associate Member.

Incorporating environmental covariates into a Bayesian stock production model for the endangered Cumberland Sound beluga population

The Cumberland Sound (CS) beluga (Delphinapterus leucas)population inhabits CS on eastern Baffin Island, Nunavut, Canada, and is listed as threatened under the Canadian Species at Risk Act. The population dynamics of CS beluga whales have been modelled in the past, but the effect of environmental covariates on these models has not previously been considered. An existing Bayesian population model fitted to CS beluga whale aerial survey data from 1990 to 2017 and harvest data from 1960 to 2017 was modified to include sea ice concentration (ICE) and sea surface temperature (SST). ICE and SST were extracted for all years from the CS study area in March and August, respectively, and incorporated into the state process component of the state-space model. The model resulted in a 2018 population estimate of 1245 (95% credible interval [CI] 564-2715) whales and an initial population estimate of 5147 (95% CI 1667-8779). Determining sustainable harvest by calculating the probability of population decline estimated 30% probability of decline after 10 yr with a harvest of ~15 whales annually. Compared to the previous model without environmental covariates, which followed a relatively linear trajectory, our model had more noticeable peaks and troughs in the population trend and wider CIs. The model suggested harvest levels be reduced by ~7 individuals for a management goal with a low risk of decline. The novelty of this approach for beluga whales provides an opportunity for further model development via the addition of various other abiotic and biotic variables related to beluga whale ecology.

Animal Borne Ocean Sensors – AniBOS – An Essential Component of the Global Ocean Observing System

Marine animals equipped with biological and physical electronic sensors have produced long-term data streams on key marine environmental variables, hydrography, animal behavior and ecology. These data are an essential component of the Global Ocean Observing System (GOOS). The Animal Borne Ocean Sensors (AniBOS) network aims to coordinate the long-term collection and delivery of marine data streams, providing a complementary capability to other GOOS networks that monitor Essential Ocean Variables (EOVs), essential climate variables (ECVs) and essential biodiversity variables (EBVs). AniBOS augments observations of temperature and salinity within the upper ocean, in areas that are under-sampled, providing information that is urgently needed for an improved understanding of climate and ocean variability and for forecasting. Additionally, measurements of chlorophyll fluorescence and dissolved oxygen concentrations are emerging. The observations AniBOS provides are used widely across the research, modeling and operational oceanographic communities. High latitude, shallow coastal shelves and tropical seas have historically been sampled poorly with traditional observing platforms for many reasons including sea ice presence, limited satellite coverage and logistical costs. Animal-borne sensors are helping to fill that gap by collecting and transmitting in near real time an average of 500 temperature-salinity-depth profiles per animal annually and, when instruments are recovered (∼30% of instruments deployed annually, n = 103 ± 34), up to 1,000 profiles per month in these regions. Increased observations from under-sampled regions greatly improve the accuracy and confidence in estimates of ocean state and improve studies of climate variability by delivering data that refine climate prediction estimates at regional and global scales. The GOOS Observations Coordination Group (OCG) reviews, advises on and coordinates activities across the global ocean observing networks to strengthen the effective implementation of the system. AniBOS was formally recognized in 2020 as a GOOS network. This improves our ability to observe the ocean’s structure and animals that live in them more comprehensively, concomitantly improving our understanding of global ocean and climate processes for societal benefit consistent with the UN Sustainability Goals 13 and 14: Climate and Life below Water. Working within the GOOS OCG framework ensures that AniBOS is an essential component of an integrated Global Ocean Observing System.

Biogeochemical consequences of a changing Arctic shelf seafloor ecosystem

Unprecedented and dramatic transformations are occurring in the Arctic in response to climate change, but academic, public, and political discourse has disproportionately focussed on the most visible and direct aspects of change, including sea ice melt, permafrost thaw, the fate of charismatic megafauna, and the expansion of fisheries. Such narratives disregard the importance of less visible and indirect processes and, in particular, miss the substantive contribution of the shelf seafloor in regulating nutrients and sequestering carbon. Here, we summarise the biogeochemical functioning of the Arctic shelf seafloor before considering how climate change and regional adjustments to human activities may alter its biogeochemical and ecological dynamics, including ecosystem function, carbon burial, or nutrient recycling. We highlight the importance of the Arctic benthic system in mitigating climatic and anthropogenic change and, with a focus on the Barents Sea, offer some observations and our perspectives on future management and policy.

Unravelling Surface Seawater DMS Concentration and Sea‐To‐Air Flux Changes After Sea Ice Retreat in the Western Arctic Ocean

AbstractThe receding of the seasonal ice cover in the Arctic due to climate change has been predicted by models to increase climate‐active biogenic trace gas emissions, specifically those of dimethylsulfide (DMS). However, insufficient DMS measurements are currently available to either support or refute this hypothesis and to fully understand the various responses of oceanic DMS in a rapidly changing Arctic Ocean environment. Here, we present high‐resolution surface water DMS data collected in the summer of 2014 in combination with a suite of ancillary variables including sea ice cover, salinity, and nutrients. We show that surface seawater DMS concentrations, generally below 0.5 nmol L−1, remained unchanged in the Canada Basin after sea ice retreat probably due to insufficient nutrients supply to the upper mixed layer and resulting low primary production. Moreover, in the Chukchi shelf region, DMS concentrations decreased following a phytoplankton bloom due to the rapid depletion and slow resupply of nutrients. Although the DMS sea‐to‐air fluxes were not high from a global perspective, they increased by a factor of 4‐fold after sea ice retreat in the Arctic Ocean high latitudes. This increase in DMS flux was mainly driven by increased wind speed. This work provides unique observations and insights on how surface seawater DMS and flux to the atmosphere may change in the future Arctic Ocean.