Search

Deep-sea marine fishes support important fisheries but estimates of their distributions are often incomplete as the data behind them may reflect fishing practices, access rights, or political boundaries, rather than actual geographic distributions. We use a simple suitable habitat model based on bottom depth, temperature, and salinity to estimate the potential distribution of Greenland halibut (Reinhardtius hippoglossoides). A large presence-only dataset is examined using multivariate kernel densities to define environmental envelopes, which we link to spatial distribution using a pan-Arctic oceanographic model. Occurrences generally fit the model well, although there were gaps in the predicted circum-Arctic distribution likely due to limited survey activity in many of the ice-covered seas around the Arctic Ocean. Bottom temperature and depth were major factors defining model fit to observations, but other factors, such as ecosystem interactions and larval drift could also influence distribution. Model predictions can be tested by increasing sampling effort in poorly explored regions and by studying the connectivity of putative populations. While abundances of Greenland halibut in the High Arctic are currently low, some areas are predicted to be suitable habitat for this species, suggesting that on-going sea-ice melt may lead to fisheries expansion into new areas.

An international symposium addressing pan-Arctic perspectives of the marine ecosystems of the Arctic Ocean took place in October 2017 and this editorial introduces the publications that derived from the conference. The symposium focused in particular upon physical forcing and biogeochemical cycling in surface waters of the Arctic Ocean, connectivity between surface and deep waters in the central basins and adjacent slopes and the ecology of the lesser-known shelf ecosystems. The symposium was the fourth in a sequence that has pan-Arctic integrations of Arctic Ocean ecosystems at its core. The series started in 2002 and its first volume was published under the title Structure and function of contemporary food webs on Arctic shelves (Wassmann, 2006). At the 2002-meeting, a suite of marine Arctic researchers from the main nations that work in the Arctic Ocean started applying the now-ubiquitous term pan-Arctic. The term underlined that the applied research goals and directions were more than a circumarctic perspective, but distinctly considered the entire expanse of the Arctic Ocean. Based upon this exercise, increased interest in the Arctic and some of the scientific endeavors of the 4th International Polar Year central projects and key oceanographers operating in the pan-Arctic region convened at the 2nd pan-Arctic integration symposium, entitled Arctic Marine Ecosystems in an Era of Rapid Climate Change in 2009 (Wassmann, 2011). After a decade of pan-Arctic research and building upon the foundation presented in Wassmann (2006, 2011) a 3rd conference was initiated in 2012, entitled Overarching perspectives of contemporary and future ecosystems in the Arctic Ocean (Wassmann, 2015). This Research Topic brings together 13 publications from the 4th pan-arctic integration symposium held in 2017, entitled Toward a Unifying Pan-Arctic Perspective of the Contemporary and Future Arctic Ocean. We, the editors of the Research Topic, are delighted with the breadth, quality and diversity of the papers. We introduce the essence of the publications under three, summarizing headlines • Physical connectivity, yet regionality • What shapes pan-Arctic primary production • The fate of production. Toward the end we incorporate the knowledge presented in this volume into the overall progress. and status of pan-Arctic marine ecosystem integration that has been achieved, so far, through the four pan-Arctic integration symposia.

Diapause at depth is considered an integral part of the life cycle of Calanus copepods, but few studies have focused on the Arctic species Calanus glacialis and Calanus hyperboreus. By analyzing a large set of pan-arctic observational data compiled from multiple sources, we show that Arctic Calanus has a broad depth distribution in winter, indicating that diapause at depth is a facultative strategy. Both species’ vertical distributions tend to deepen in winter and to be deeper and broader with increasing bottom depth, while individuals are aggregated closer to the sea floor in shallow areas. These results indicate that Arctic Calanus species pursue a relatively deep diapause habitat but are topographically blocked on the shelves. Interspecific differences in depth distribution during diapause suggest the importance of predation. The larger C. hyperboreus has a deeper diapause depth than C. glacialis, potentially to alleviate predation pressure or as a result of predation loss near the surface. Moreover, the mean depth of C. hyperboreus in winter is negatively associated with latitude, indicating a shoaling of the diapause population in the central Arctic Ocean where predation pressure is lower. Our results suggest a complex diapause behavior by Arctic Calanus, with implications for our view of the species’ roles in Arctic ecosystems.

Arctic landfast sea ice has undergone substantial changes in recent decades, affecting ice stability and including potential impacts on ice travel by coastal populations and on industry ice roads. We present a novel approach for evaluating landfast sea ice stability on a pan-Arctic scale using Synthetic Aperture Radar Interferometry (InSAR). Using Sentinel-1 images from spring 2017, we discriminate between bottomfast, stabilized, and nonstabilized landfast ice over the main marginal seas of the Arctic Ocean (Beaufort, Chukchi, East Siberian, Laptev, and Kara seas). This approach draws on the evaluation of relative changes in interferometric fringe patterns. This first comprehensive assessment of Arctic bottomfast sea ice extent has revealed that most of the bottomfast sea ice is situated around river mouths and coastal shallows. The Laptev and East Siberian seas dominate the aerial extent, covering roughly 4100 and 5100 km2, respectively. These seas also contain the largest extent of stabilized and nonstabilized landfast ice, but are subject to the largest uncertainties surrounding the mapping scheme. Even so, we demonstrate the potential for using InSAR for assessing the stability of landfast ice in several key regions around the Arctic, providing a new understanding of how stability may vary between regions. InSAR-derived stability may serve for strategic planning and tactical decision support for different uses of coastal ice. In a case study of the Nares Strait, we demonstrate that interferograms may reveal early-warning signals for the breakup of stationary sea ice.

Glaciers retreat contributed to about 1/3 of the observed sea level rise since 1971 (IPCC). However, long term estimates of glaciers volume changes rely on sparse field observations and region-wide satellite observations are available mostly after 2000. The now declassified images from the American reconnaissance satellite series Hexagon (KH-9), that acquired 6 m resolution stereoscopic images from 1971 to 1986, open new possibilities for glaciers observation.Based on recently published methodology (Dehecq et al., 2020, doi: 10.3389/feart.2020.566802), we process all available KH-9 images over the Arctic (Canadian arctic, Iceland, Svalbard, Russian arctic) to generate Digital Elevation Models (DEMs) and ortho-images for the period 1974-1980. We validate the KH-9 DEMs over Iceland against elevation derived from historical aerial images acquired within a month from the satellite acquisition.Finally, we calculate the glacier elevation change between the historical DEMs and modern elevation obtained from a time series of ASTER stereo images and validated against ICESat-2 elevation. The geodetic glacier mass balance is calculated for all pan-Arctic regions and analyzed with reference to the last 20 years evolution.

The surface layer of the Arctic Ocean carries a higher dissolved organic carbon (DOC) content than other ocean basins. Climate change impacts the Arctic aquatic DOC-pool by e.g., introducing DOC trapped in permafrost soils as they thaw and by increasing the terrestrial runoff and primary production. Sampling for DOC in the Arctic is rather challenging given its remoteness and difficult access to the region and that it is not possible yet to determine DOC concentrations from instruments deployed in the field. Compared to DOC, colored dissolved organic matter (CDOM) absorption spectroscopy is an easy-to-measure, relatively quick and cost-effective approach which is often closely related to DOC concentrations in water samples. In regions in close proximity to rivers, linear relationships between CDOM absorption at 350nm (a350) and DOC often can be found and, thus, have improved prediction of DOC using two end‐members. However, in regions with two or more end‐members of comparable DOC concentrations (shelf seas and oceanic waters) these relationships are difficult to derive, as there might be pools of similar concentration/intensity but different ratio of absorption to DOC (carbon specific absorption coefficient, a*). Here we present an algorithm to estimate DOC concentrations based on quantitative (a350) and qualitative (spectral absorption slope between 275 and 295nm, S275-295) properties of CDOM. The algorithm considers that there is a linear correlation between DOC and a350 but that the slope of the relationship (inverse of a*) varies depending on the exponent of the ultraviolet (UV) spectral slope (S275‐295), that is, the character or source of DOM. We compiled a Pan-Arctic dataset (n=3607) from a wide range of aquatic systems spanning lakes, rivers, estuaries, coastal and shelf seas and open ocean with salinity ranging from 0 to 35.3. DOC ranged between 19 and 2304µM, whereas a350 varied from 0.01–81.33m-1 and S275-295 ranged 12–39µm-1. The algorithm provided significant and robust (r2=0.93; p

It is now well known that the sea ice extent in the Artic has been shrinking in the past three decades in the period known as the Arctic Amplification. A simple assumption would be that if the sea ice extent has been reduced, then the spectral reflectance at the top of the atmosphere - RTOA - would have also decreased across the Arctic. On the other hand, Arctic reflectivity also largely depends on the presence of clouds, shielding the underlying surface, and on changes of their optical and physical properties. Thus, the assessment of trends of spectral reflectivity and cloud properties are essential to understand those forcings and feedbacks considered drivers of Arctic Amplification as well as the interactions between the components of the Arctic cryosphere. In the reported study we observationally tackle the stated problem investigating changes of RTOA at selected wavelengths making use of spaceborne measurements of the Global Ozone Monitoring Experiment (GOME onboard ERS-2 and MetOp A/B/C) and of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY onboard Envisat) for the period 1995-2018. We complement this record with cloud properties and fluxes at top of the atmosphere and at the surface, inferred from measurements of the post-meridiem orbits of the Advanced Very High Resolution Radiometer (AVHRR onboard POES). Although the Pan-Arctic reflectivity has decreased, the analysis of regional trends shows distinct areas where the reflectivity trends diverge. While darkening areas can be attributed to seasonal sea ice decline, an increase of Arctic brightness over sea ice free regions can be largely attributed to changes in the optical properties of clouds. While the multiyear mean of the radiative forcing by clouds points to a TOA cooling and a surface warming, its trends exhibit opposite tendencies. In the last two decades, the cloud radiative effect at TOA is expected to warm the lower latitudes (below 75 N) and to cool the circumpolar belt, while an opposite trend at BOA, amounting to 5 W m-2 per decade, cools the lower Arctic latitudes and warms the permanent sea ice region, this effect being more pronounced in spring months (April to June) than in summer months (July to September).

One of the key changes of the global climate system is the loss of Arctic sea ice, particularly through its impact on ocean-atmosphere interactions. Enhanced evaporation under open-water conditions is widespread from places and periods previously precluded by perennial sea ice cover, leading to an increase in vapor uptake across the Arctic. However, the response of ocean-atmosphere system to sea ice loss varies significantly over time and space. To quantify these variations, the Arctic Water Isotope Network (AWIN) has been established to make continuous water vapor isotope measurements (δD, δ18O, and d-excess) at seven land-based stations from Barrow, Alaska to Ny Alesund, Svalbard. This network has been supplemented by continuous mobile isotope data from the CiASOM project on the Polarstern ice-breaker throughout the MOSAiC “Arctic-drift” expedition. With this network, we comprehensively track water vapor from its source to sink, thereby demonstrating how it varies simultaneously across the entire Arctic Basin.Here, we utilize AWIN measurements to specifically quantify how variations in sea ice extent and distribution affect moisture content, water vapor isotope traits, and transport along several critical storm tracks. By monitoring vapor isotopic changes in air masses advected from one site to another, we are able to track how much moisture is added along a given trajectory. We investigate several primary vapor transport pathways into the Arctic, including the North Atlantic/Greenland Sea, Baffin Bay, and the Bering Strait, and track the geochemical signature of this vapor as it transits along these well-established storm pathways into and within the Arctic. By quantifying isotopic changes between our sites we: 1) identify the distinct isotopic fingerprint of moisture sourced by evaporation from Arctic seas that is critically dependent on variable sea ice conditions, 2) detect moisture addition into critical storm tracks as they transit across the Arctic, and 3) determine the spatial variability of this enhanced Arctic-sourced evaporation and moisture. We find that for every major storm track observed, the Arctic Ocean and surrounding seas are significant sources of enhanced moisture uptake, acting within an amplified water cycle.

As grid resolutions of operational ocean models are becoming finer and approach closer to the coast, the importance of inclusion of tidal forcing in high resolution operational ocean forecasting systems has increasingly been recognized. In the current work, we present a 3D general ocean circulation model of ocean tides in the pan-Arctic region at ~3km horizontal grid resolution and 50 hybrid layers in the vertical, thus representing both barotropic and internal tides. The model system is based on the Hybrid Coordinate Ocean Model (HYCOM) coupled with the Los Alamos Sea Ice Model (CICE). The results showed good agreement when compared with observations from tide gauges and a data-assimilative global barotropic tidal model. Among other results, the evaluation includes results for tidal amplitude and phase of the most energetic constituents (M2, S2, K1 and Q1). The model system is currently operational and its development is supported by the Copernicus Marine Environment Monitoring Service (CMEMS) where its forecasts are disseminated.

Ocean sediment drifts contain important information about past bottom currents but a direct link from the study of sedimentary archives to ocean dynamics is not always possible. To close this gap for the North Atlantic, we set up a new coupled Ice-Ocean-Sediment Model of the entire Pan-Arctic region. In order to evaluate the potential dynamics of the model, we conducted decadal sensitivity experiments. In our model contouritic sedimentation shows a significant sensitivity towards climate variability for most of the contourite drift locations in the model domain. We observe a general decrease of sedimentation rates during warm conditions with decreasing atmospheric and oceanic gradients and an extensive increase of sedimentation rates during cold conditions with respective increased gradients. We can relate these results to changes in the dominant bottom circulation supplying deep water masses to the contourite sites under different climate conditions. A better understanding of northern deep water pathways in the Atlantic Meridional Overturning Circulation (AMOC) is crucial for evaluating possible consequences of climate change in the ocean.

Amplified climate warming has led to permafrost degradation and a shortening of the winter season, both impacting cost-effective overland travel across the Arctic. Here we use, for the first time, four state-of-the-art Land Surface Models that explicitly consider ground freezing states, forced by a subset of bias-adjusted CMIP5 General Circulation Models to estimate the impact of different global warming scenarios (RCP2.6, 6.0, 8.5) on two modes of winter travel: overland travel days (OTDs) and ice road construction days (IRCDs). We show that OTDs decrease by on average −13% in the near future (2021–2050) and between −15% (RCP2.6) and −40% (RCP8.5) in the far future (2070–2099) compared to the reference period (1971–2000) when 173 d yr−1 are simulated across the Pan-Arctic. Regionally, we identified Eastern Siberia (Sakha (Yakutia), Khabarovsk Krai, Magadan Oblast) to be most resilient to climate change, while Alaska (USA), the Northwestern Russian regions (Yamalo, Arkhangelsk Oblast, Nenets, Komi, Khanty-Mansiy), Northern Europe and Chukotka are highly vulnerable. The change in OTDs is most pronounced during the shoulder season, particularly in autumn. The IRCDs reduce on average twice as much as the OTDs under all climate scenarios resulting in shorter operational duration. The results of the low-end global warming scenario (RCP2.6) emphasize that stringent climate mitigation policies have the potential to reduce the impact of climate change on winter mobility in the second half of the 21st century. Nevertheless, even under RCP2.6, our results suggest substantially reduced winter overland travel implying a severe threat to livelihoods of remote communities and increasing costs for resource exploration and transport across the Arctic. Met Office Hadley Centre Climate Programme Bundesministerium für Bildung und Forschunghttp://dx.doi.org/10.13039/501100002347 Horizon 2020 Framework Programmehttp://dx.doi.org/10.13039/100010661 Uniscientia Foundation

Stable isotopes of oxygen and hydrogen in precipitation (δ18OP, δ2HP, d-excess) are valuable hydrological tracers linked to ocean-atmospheric processes such as moisture source, storm trajectory, and seasonal temperature cycles. However, characteristics of δ18OP, δ2HP and d-excess and the processes governing them are yet to be quantified across the Arctic due to a lack of long-term empirical data. The Pan-Arctic Precipitation Isotopes Network (PAPIN) is a new coordinated network of 24 stations aimed at the direct sampling, analysis, and synthesis of precipitation isotope geochemistry in the north. Our ongoing event-based sampling provides a rich spatial dataset during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (“MOSAiC”) expedition and new insight into coupled climate processes operating in the Arctic today. To date, precipitation δ18O and δ2H data (2018-2019) exhibit pronounced spatial and seasonal variability that broadly conforms to theoretical and observed understanding: (1) decreasing δ18OP/ δ2HP with increasing latitude and elevation, (2) decreasing δ18OP/ δ2HP with increasing continentality, and (3) increasing δ18OP/ δ2HP with increasing SAT. However, event-based sampling reveals remarkable variability among these relationships. For example, our observed Arctic mean summer -latitude slope of -0.3‰/degree of latitude is 50% smaller than the annual latitude effect in the mid-latitudes (-0.6‰/degree). This rate decreases to -0.1‰/degree of latitude in Finland and Russia, while in Alaska and northern Canadian a -0.7‰/degree latitudinal rate is observed. Similarly, we observe marked spatial differences in mean δ18O-temperature coefficients. Using back-trajectory analysis, we attribute these nuances to divergent moisture sources and transport pathways into, within, and out of the Arctic, and demonstrate how atmospheric circulation processes drive changes in isotope geochemistry and climate that are linked to sea ice concentration. For example, Alaska moisture derived from the North Pacific Ocean, Sea of Okhotsk, and the Bering Sea remains relatively enriched in 18OP/2H due to higher sea surface temperatures, whereas moisture originating from ice-covered seas to the north is characterized by relatively depleted values. This is the first coordinated network to quantify the spatial patterns of isotopes in precipitation, simultaneously, across the entire Arctic. In combination with a Pan-Arctic network of continuous water vapor isotope analyzers, our process-level studies will resolve the patterns and processes governing the δ18O, δ2H and d-excess values of the Arctic water cycle during the MOSAiC expedition and beyond.

Surface state information, derived from ASCAT microwave sensors (C-band scatterometer), were empirically linked to in-situ arctic ground temperature measurements. The resulting FT2T-regressionmodel was established using the sum of days of year frozen and in-situ mean annual ground temperatures, both at specific depths and years. Regionally, the model showed the best results in Scandinavia and northern Russia with less than 1°C difference to the in-situ data. Overall, the results were valid for most depths and regions, with a slight tendency for underestimation of the ground temperatures on the Eurasian continent (about -1°C) and an overestimation on the American continent up to 2 °C. The most northern parts of Greenland, the Canadian High Arctic Islands and Alaska, however, showed a high positive bias of more than 10°C. Reasons for this overshooting include the limited amount of measurements in those regions, the oceanic influence and possibly snow cover effects. Due to the inaccessibility of many arctic regions, in-situ data availability is still sparse and if available not harmonized. We used the currently revised annual ground temperature dataset from CCI+ Permafrost, which combines in-situ data from the GTNP-database, RosHydroMet and additional regional arctic ground temperature datasets (e.g. Nordicana). The resulting determination coefficients of the FT2T-model showed 55% explained variance at shallow borehole-depths below 80cm and decrease with depth to around 25% at 20 meters. This suggests that the sum of frozen days of year delivers better result at shallow depths in the active layer than at the actual permafrost table. The RMSE showed a dependency on the spread of measurement stations considered in the model calibration step. The more input regions we could use, the larger the RMSE got due to the increase of variability in the input data. Inevitably, it’s the in-situ information which enables the translation between ground temperatures and microwave backscatter and thus it fundamentally affects the accuracy of the result.

MOSAiC is a one of a kind, year-long study of the Arctic Basin’s behavior focused in large part on interactions between sea ice, atmospheric processes, ecosystem dynamics and oceanography, as well as connections between the Arctic and the mid-latitudes. Our MOSAiC project is focused on how the Arctic Basin’s water cycle behaves throughout the year, especially now that sea ice loss allows for a new source of moisture to the atmosphere during times when this basin was formerly frozen over. These massive changes in open water and corresponding fluxes in conjunction with significant shifts in atmospheric circulation, are altering how moisture is transported into, within, and out of the Arctic Basin. In order to help quantify these Arctic hydrologic cycle variations, we have established the AWIN (Arctic Water Isotope Network) that uses continuous water vapor isotope measurements (δD, δ18O, and deuterium excess) at eight land-based stations from Barrow in Alaska to Ny Alesund in Svalbard, as well as on board the Polarstern.With a network of sites rather than a single station, we gain the significant advantage of being able to track water vapor and how it varies from site to site, allowing us to identify the sources of moisture, and how and where that moisture is transported into, within, and out of the Arctic. For this analysis, we focus on the first months of the expedition (October-December 2019) to closely examine cases of critical events including a major low-pressure system in mid-November that impacted much of the Arctic Ocean basin and three key repeating transport regimes – 1) transport into the Arctic from the North Atlantic via the Greenland Sea, 2) transport into the Arctic via Baffin Bay, and 3) transport out of the Arctic via the Greenland Sea, as well as transport within the Arctic during each of these regimes. For example, in the scenario of transport into the Arctic via Baffin Bay, at our site in Thule, Greenland, we see significant reductions in deuterium excess each time the southerly flow initiates, suggesting significant moisture evaporating from nearby in Baffin Bay. We then can track that moisture to another site to observe how much of that locally-sourced vapor is transported to a given downwind location, allowing us to quantify vapor fluxes and isotopic fractionation processes across the Arctic. By examining these scenarios under varying sea ice conditions and large-scale atmospheric circulation patterns, this circum-Arctic network of water isotope measurements is transforming our understanding of the Arctic hydrologic cycle during MOSAiC.

Quantifying mixing rates in the Arctic Ocean is critical to our ability to predict heat flux, freshwater distribution, and circulation. However, turbulence measurements in the Arctic are sparse, an...

Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds., Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347

Monthly mean passive microwave-derived sea-ice motion maps for 36 winters (October–April) are used to examine pan-Arctic sea-ice drift speeds and patterns. The mean Arctic Ocean sea-ice motion consists of three well-known primary circulation regimes: the Beaufort Gyre (BG), transpolar drift (TPD), and a motion system from the Kara Sea (KS). The 36-year mean winter sea-ice drift pattern is used to identify the average boundaries between the circulation regimes mentioned above. Regression analyses of the ice drift speed anomalies show statistically significant positive drift speed trends in BG, TPD and KS. Non-significant trends are associated with negative trends of generally weak drift speeds north of the Canadian Arctic and over the Chukchi/East Siberian Shelf. The first three modes of Empirical Orthogonal Functions were found to explain 30.2%, 13.5% and 8.7% of the spatial variance in the mean winter ice drift patterns and highlight the large variability in the ice drift patterns.

Impacts of 1.5 and 2.0 degrees C Warming on Pan-Arctic River Discharge Into the Hudson Bay Complex Through 2070

Source at https://doi.org/10.1002/ece3.3797. Accepted manuscript version, licensed CC BY-NC-ND 4.0. Arctic sea ice provides microhabitats for biota that inhabit the liquid‐filled network of brine channels and the ice–water interface. We used meta‐analysis of 23 published and unpublished datasets comprising 721 ice cores to synthesize the variability in composition and abundance of sea ice meiofauna at spatial scales ranging from within a single ice core to pan‐Arctic and seasonal scales. Two‐thirds of meiofauna individuals occurred in the bottom 10 cm of the ice. Locally, replicate cores taken within meters of each other were broadly similar in meiofauna composition and abundance, while those a few km apart varied more; 75% of variation was explained by station. At the regional scale (Bering Sea first‐year ice), meiofauna abundance varied over two orders of magnitude. At the pan‐Arctic scale, the same phyla were found across the region, with taxa that have resting stages or tolerance to extreme conditions (e.g., nematodes and rotifers) dominating abundances. Meroplankton, however, was restricted to nearshore locations and landfast sea ice. Light availability, ice thickness, and distance from land were significant predictor variables for community composition on different scales. On a seasonal scale, abundances varied broadly for all taxa and in relation to the annual ice algal bloom cycle in both landfast and pack ice. Documentation of ice biota composition, abundance, and natural variability is critical for evaluating responses to decline in Arctic sea ice. Consistent methodology and protocols must be established for comparability of meiofauna monitoring across the Arctic. We recommend to (1) increase taxonomic resolution of sea ice meiofauna, (2) focus sampling on times of peak abundance when seasonal sampling is impossible, (3) include the bottom 30 cm of ice cores rather than only bottom 10 cm, (4) preserve specimens for molecular analysis to improve taxonomic resolution, and (5) formulate a trait‐based framework that relates to ecosystem functioning.

Due to its year-round accessibility and excellent on-site infrastructure, Kongsfjorden and the Ny-Alesund Research and Monitoring Facility have become established as a primary location to study the impact of environmental change on Arctic coastal ecosystems. Due to its location right at the interface of Arctic and Atlantic oceanic regimes, Kongsfjorden already experiences large amplitudes of variability in physico/chemical conditions and might, thus, be considered as an early warning indicator of future changes, which can then be extrapolated in a pan-Arctic perspective. Already now, Kongsfjorden represents one of the best-studied Arctic fjord systems. However, research conducted to date has concentrated largely on small disciplinary projects, prompting the need for a higher level of integration of future research activities. This contribution, thus, aims at identifying gaps in knowledge and research priorities with respect to ecological and adaptive responses to Arctic ecosystem changes. By doing so we aim to provide a stimulus for the initiation of new international and interdisciplinary research initiatives.

The majority of northern peatlands were initiated during the Holocene. Owing to their mass imbalance, they have sequestered huge amounts of carbon in terrestrial ecosystems. Although recent syntheses have filled some knowledge gaps, the extent and remoteness of many peatlands pose challenges to developing reliable regional carbon accumulation estimates from observations. In this work, we employed an individual- and patch-based dynamic global vegetation model (LPJ-GUESS) with peatland and permafrost functionality to quantify long-term carbon accumulation rates in northern peatlands and to assess the effects of historical and projected future climate change on peatland carbon balance. We combined published datasets of peat basal age to form an up-to-date peat inception surface for the pan-Arctic region which we then used to constrain the model. We divided our analysis into two parts, with a focus both on the carbon accumulation changes detected within the observed peatland boundary and at pan-Arctic scale under two contrasting warming scenarios (representative concentration pathway—RCP8.5 and RCP2.6). We found that peatlands continue to act as carbon sinks under both warming scenarios, but their sink capacity will be substantially reduced under the high-warming (RCP8.5) scenario after 2050. Areas where peat production was initially hampered by permafrost and low productivity were found to accumulate more carbon because of the initial warming and moisture-rich environment due to permafrost thaw, higher precipitation and elevated CO2 levels. On the other hand, we project that areas which will experience reduced precipitation rates and those without permafrost will lose more carbon in the near future, particularly peatlands located in the European region and between 45 and 55°N latitude. Overall, we found that rapid global warming could reduce the carbon sink capacity of the northern peatlands in the coming decades.

Satellite-based hot-spot analysis for the Pan-Arctic, shows that Asia experiences a greater number of fires compared to North America and Europe. While hot spots are prevalent through the year in Asia, Europe (North America) exhibits marked annual (semi-annual) variability. The Potential Fire Danger index (PFIv2) demonstrates increased fire incidence vulnerability across the Arctic and extra-tropics. Though not significant in northwestern North America and eastern Asia, significant-positive trends across the mid-latitudes of Eurasia and Siberia are clear. PFIv2 accurately matches the regional distribution of observed fires, while the worldwide used Fire Weather Index does not. Fire danger has evolved as distributions of short-interval precipitation events and background vegetation characteristics change. In conjunction with increased population and expanded infrastructure, frequent extreme events may increase pressure for new settlements that lead to greater fire exposure across the Pan-Arctic. Thus, PFIv2 may be useful for decision planners and danger managers to anticipate and minimize the adverse effects of indiscriminate fire use.

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range of 496.4–511.5 Tg yr−1, and pan-Arctic methane emissions were in the range of 11.9–28.5 Tg yr−1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2 Tg yr−1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.

The shrinking of land-terminating glaciers and ice caps (GIC) has been documented in high-latitude regions, even though repeat observations upon which to base such studies have been limited in space. Here, we present a new record of satellite-derived area changes for 321 land-terminating GIC throughout Pan-Arctic and for the W. Canada and W. US, with focus on the period from mid-1980s to late-2000s/2011 (the last ca. 25 yr). The mean shrinking rate was −0.06±0.01 km2 yr−1 during a period with climate warming. Most of the observed GIC shrank in area, more so than previously believed: while only 8% advanced. The analysis indicates that the observed GIC have lost an arithmetic average of one-fifth of their area since the mid-1980s (equal to a shrinking rate of ca. −1% yr−1), with the highest rate of loss of −40±4% (−1.7 % yr−1) in Alaska, and the lowest rate of loss of −12±3% (−0.5 % yr−1) in Arctic Russia.

Arctic landfast sea ice has undergone substantial changes in recent decades affecting ice stability with potential impacts on ice travel by coastal populations and industry ice roads. The role of landfast ice as an important habitat has also evolved. We present a novel approach to evaluate sea ice stability on a pan-Arctic scale using Synthetic Aperture Radar Interferometry (InSAR). Using Sentinel-1 images from spring 2017, the approach discriminates between bottomfast, with critical relevance for subsea permafrost, as well as stabilized and non-stabilized floating landfast ice over the main marginal seas of the Arctic Ocean (Beaufort, Chukchi, East Siberian, Laptev and Kara Seas). The analysis draws on evaluation of small-scale lateral motion derived from relative changes in interferometric fringe patterns. This first comprehensive assessment of Arctic bottomfast sea ice extent revealed that by area most of the bottomfast sea ice is situated around river mouths and coastal shallows in the Laptev and East Siberian Seas, covering roughly 4.1 and 5.5 thousand km2 respectively. The fraction between non-stabilized and stabilized ice is lowest in the Beaufort at almost unity, and highest in the adjacent Chukchi Sea. Beyond the simple delineation of landfast ice zones, this work provides a new understanding of how stability regimes may vary between regions and over time. InSAR-derived stability data may serve as a strategic planning and tactical decision-support tool for different uses of coastal ice. Such information may also inform assessments of important sea ice habitats. In a case study, we examined an ice arch situated in Nares Strait demonstrating that interferograms may reveal early-warning signals for the break-up of stationary sea ice.

Earth’s modern climate is defined by the presence of ice at both poles, but that ice is now disappearing. Therefore understanding the origin and causes of polar ice stability is more critical than ever. Here we provide novel geochemical data that constrain past dynamics of glacial ice on Greenland and Arctic sea ice. Based on accurate source determinations of individual ice-rafted Fe-oxide grains, we find evidence for episodic glaciation of distinct source regions on Greenland as far-ranging as ~68°N and ~80°N synchronous with ice-rafting from circum-Arctic sources, beginning in the middle Eocene. Glacial intervals broadly coincide with reduced CO2, with a potential threshold for glacial ice stability near ~500 p.p.m.v. The middle Eocene represents the Cenozoic onset of a dynamic cryosphere, with ice in both hemispheres during transient glacials and substantial regional climate heterogeneity. A more stable cryosphere developed at the Eocene-Oligocene transition, and is now threatened by anthropogenic emissions., With rapidly disappearing ice, understanding the past behavior of the cryosphere is critical. Here, the authors indicate the initiation and disappearance of glaciation on Greenland and Arctic sea ice coincided in the past, synchronous with Antarctic ice and global ice volume, and a CO2 threshold of ~500 p.p.m.v.

The impact of tides on the simulated landfast ice cover is investigated. Pan‐Arctic simulations are conducted with an ice‐ocean (CICE‐NEMO) model with a modified rheology and a grounding scheme. The reference experiment (without tides) indicates there is an overestimation of the extent of landfast ice in regions of strong tides such as the Gulf of Boothia, Prince Regent Inlet and Lancaster Sound. The addition of tides in the simulation clearly leads to a decrease of the extent of landfast ice in some tidally active regions. This numerical experiment with tides is more in line with observations of landfast ice in all the regions studied. Thermodynamics and changes in grounding cannot explain the lower landfast ice area when tidal forcing is included. We rather demonstrate that this decrease in the landfast ice extent is dynamically driven by the increase of the ocean‐ice stress due to the tides. Plain Language Summary Landfast ice is sea ice that is immobile near a coast for a certain period of time. This coastal ice can stay at rest because it is attached to the coast and/or anchored to the sea floor in shallow water. To study landfast ice, we used a numerical model that represents the physical interactions between the atmosphere, the ocean and the sea ice. We compared two simulations done with this model: one without ocean tides and one that includes the tides. The experiment with tides exhibits a lower extent of landfast ice which is more in line with the observations. This decrease in the landfast ice extent when adding the tides is a dynamical process; the strong tidal currents constantly set the sea ice in motion, preventing it to become landfast.

The Arctic freshwater budget is critical for understanding the climate in the northern regions. However, the hydrology of the Arctic circumpolar tundra region (ACTR) and the largest pan-Arctic rivers are still not well understood. In the present paper, we analyze the spatiotemporal variations in terrestrial water storage (TWS) of the ACTR, including three of its largest pan-Arctic river basins (Lena, Mackenzie, Yukon), using monthly Gravity Recovery and Climate Experiment (GRACE) data from 2002 to 2016. Together with global land reanalysis, river runoff, and inundation extent area (IEA) data, we identify declining TWS trends throughout the ACTR that we attribute largely to increasing evapotranspiration driven by increasing summer air temperatures. In terms of regional changes, large and significant negative trends in TWS are observed mainly over the North American continent. At basin scale, we show that, in the Lena River basin, the autumnal TWS signal persists until the winter of the following year, while in the Mackenzie River basin, the TWS levels in the autumn and winter has no significant impact on the following year. As global warming is expected to be particularly significant in the northern regions, our results are important for understanding future TWS trends, with possible further decline.

International audience; Light absorption of the colored fraction of dissolved organic matter (CDOM) is a dominant optical component of the Arctic Ocean (AO). Here we show Pan-Arctic characteristics of CDOM light absorption for various Arctic regions covering both coastal and oceanic waters during the Tara Oceans Polar Circle expedition. The Siberian (or eastern) side of the AO is characterized by higher CDOM absorption values compared to the North American (or western) side. This is due to the difference in watersheds between the eastern and western sides of the AO and is consistent with an Arctic absorption database recently built by Matsuoka et al. (2014). A direct comparison between in situ and satellite data demonstrates that CDOM absorption is derived Arctic-wide from satellite ocean color data with an average uncertainty of 12% (root mean square error of 0.3 m − 1) using our previously published algorithm. For river-influenced coastal waters, we found a single and highly significant relationship between concentrations of dissolved organic carbon (DOC) and CDOM absorption (r 2 > 0.94) covering major Arctic river mouths. By applying this in situ relationship to satellite-derived CDOM absorption, DOC concentrations in the surface waters are estimated for river-influenced coastal waters with an average uncertainty of 28%. Implications for the monitoring of DOC concentrations in Arctic coastal waters are discussed .

The seasonal melt-freeze transitions are fun- damental features of the Arctic climate system. The representation of the pan-Arctic melt and freeze onset (north of 60°N) is assessed in two reanalyse ...

The timing of reproductive events of Calanus glacialis is closely coupled to the two major marine primary production events in the Arctic: the ice algal and phytoplankton blooms. Reproductive strategies vary between different physical and biological environments of the European and Canadian Arctic. In the Canadian Beaufort Sea and the high Arctic Rijpfjorden on Svalbard, C. glacialis utilized the ice algae bloom to fuel spawning in spring, while growth and development of the new generation was primarily supported by the phytoplankton bloom. In the predominantly ice-free Arctic Kongsfjorden (Svalbard), C. glacialis was mainly a capital breeder spawning early in the season in the absence of food. This enabled the offspring to synchronize their growth and development with the phytoplankton bloom and, thus, reproduce successfully despite the lack of an early ice algal bloom. The variability in life history traits observed in the Canadian and European Arctic is compared with data from other Arctic regions to present a pan-Arctic perspective on life cycle strategies of C. glacialis.

Using the Variable Infiltration Capacity (VIC) land surface model forced with gridded climatic observations, the authors reproduce spatial and temporal variations of snow cover extent (SCE) reported by the National Oceanic and Atmospheric Administration (NOAA) Northern Hemisphere weekly satellite SCE data. Both observed and modeled North American and Eurasian snow cover in the pan-Arctic have statistically significant negative trends from April through June over the period 1972–2006. To diagnose the causes of the pan-Arctic SCE recession, the authors identify the role of surface energy fluxes generated in VIC and assess the relationships between 15 hydroclimatic indicators and NOAA SCE observations over each snow-covered sensitivity zone (SCSZ) for both North America and Eurasia. The authors find that surface net radiation (SNR) provides the primary energy source and sensible heat (SH) plays a secondary role in observed changes of SCE. As compared with SNR and SH, latent heat has only a minor influence on snow cover changes. In addition, these changes in surface energy fluxes resulting in the pan-Arctic snow cover recession are mainly driven by statistically significant decreases in snow surface albedo and increased air temperatures (surface air temperature, daily maximum temperature, and daily minimum temperature), as well as statistically significant increased atmospheric water vapor pressure. Contributions of other hydroclimate variables that the authors analyzed (downward shortwave radiation, precipitation, diurnal temperature range, wind speed, and cloud cover) are not significant for observed SCE changes in either the North American or Eurasian SCSZs.

[1] A new satellite passive microwave (PMW) melt onset retrieval algorithm based on temporal variations in the differences of the brightness temperature between 19 and 37 GHz is shown to be as effective as radar (e.g., QuikScat) measurements. The PMW technique shows improved melt estimates that are more closely linked to observed snow-off dates than previous studies. An integrated pan-Arctic (north of 50°N) melt onset date (MOD) dataset is produced by combining estimates on land and sea ice for the entire satellite PMW record. During the 1979–2011 period, significant trends of 2~3 days (decade)−1 to earlier MOD are mainly concentrated over the Eurasian land sector of the Arctic, consistent with changes in spring snow cover extent observed with visible satellite data. The variability and change in melt onset are largely driven by spring surface air temperature, with insignificant influence from low-frequency modes of atmospheric circulation.

There is mounting evidence that permafrost degradation has occurred over the past century. However, the amount of permafrost lost is uncertain because permafrost is not readily observable over long time periods and large scales. This paper uses JULES, the land surface component of the Hadley Centre global climate model, driven by different realisations of twentieth century meteorology to estimate the pan-arctic changes in near-surface permafrost. Model simulations of permafrost are strongly dependent on the amount of snow both in the driving meteorology and the way it is treated once it reaches the ground. The multi-layer snow scheme recently adopted by JULES significantly improves its estimates of soil temperatures and permafrost extent. Therefore JULES, despite still having a small cold bias in soil temperatures, can now simulate a near-surface permafrost extent which is comparable to that observed. Changes in snow cover have been shown to contribute to changes in permafrost and JULES simulates a significant decrease in late twentieth century pan-Arctic spring snow cover extent. In addition, large-scale modelled changes in the active layer are comparable with those observed over northern Russia. Simulations over the period 1967-2000 show a significant loss of near-surface permafrost-between 0.55 and 0.81 million km2 per decade with this spread caused by differences in the driving meteorology. These runs also show that, for the grid cells where the active layer has increased significantly, the mean increase is ~10 cm per decade. The permafrost degradation discussed here is mainly caused by an increase in the active layer thickness driven by changes in the large scale atmospheric forcing. However, other processes such as thermokarst development and river and coastal erosion may also occur enhancing permafrost loss.

Models and observations show that the Arctic is experiencing the most rapid changes in global near-surface air temperature. We developed novel EASE-grid Level 3 (L3) land surface temperature (LST) products from Level 2 (L2) AATSR and MODIS data to provide weekly, monthly and annual LST means over the pan-Arctic region at various grid resolutions (1–25 km) for the past decade (2000–2010). In this paper, we provide: (1) a review of previous validation of MODIS/AATSR L2; (2) a description of the processing chain of L3 products; (3) an assessment of the 25 km products uncertainty, and; (4) a quantification of the bias introduced by over-representing clear-sky days in MODIS L3 products. In addition, we generated uncertainty maps by comparing L3 products with LST from passive microwave sensors (AMSR-E and SSM/I) and the North American Regional Reanalysis (NARR). Results show a close correspondence between MODIS and AATSR monthly products with a mean-difference (MD) of −1.1 K. Comparing L3 products with NARR indicates a close agreement in summer and a systematic bias in winter, which is entirely negative with respect to MODIS L3 (MD: −3.6, Min: −6.8, Max: −1 K). Comparing monthly averaged MODIS L3 to NARR clear-sky to quantify over-representing clear-sky days indicates a decrease of winter and an increase of summer difference compared to NARR all-sky. Finally, we provide suggestions to improve LST retrieval over Arctic regions.

This chapter provides description and interpretation of the two major, well-documented episodes of Arctic-wide migrations. The Paleo-Inuit (also called Paleoeskimo or Arctic Small Tool tradition) migration began around 3,200 B.C., with penetration of the central Arctic by highly mobile, small-scale hunter-gatherer groups. By around 2,500 B.C., the entire eastern Arctic had been peopled by cultures known as Pre-Dorset, Saqqaq, and Independence I. The Thule Inuit migration began around A.D. 1200, when complex maritime-oriented groups from the western Arctic initiated an extremely rapid population movement, spanning the North American Arctic within a generation. The chapter considers the timing and nature of each migration episode, as well as the motivating factors which have been proposed for them, including climate change, social or economic hardship, and acquisition of specific resources such as bowhead whales or metal.

Soil heat content (SHC) provides an estimate of the integrated effect of changes in the land surface energy balance. It considers the specific heat capacity, soil temperature, and phase changes of soil moisture as a function of depth. In contrast, soil temperature provides a much more limited view of land surface energy flux changes. This is particularly important at high latitudes, which have and are undergoing surface energy flux changes as a result of changes in seasonal variations of snow cover extent (SCE) and hence surface albedo changes, among other factors. Using the Variable Infiltration Capacity (VIC) land surface model forced with gridded climate observations, we simulate spatial and temporal variations of SCE and SHC over the pan-Arctic land region for the last half-century. On the basis of the SCE trends derived from NOAA satellite observations in 5° latitude bands from April through June for the period 1972–2006, we define a snow covered sensitivity zone (SCSZ), a snow covered non-sensitivity zone (SCNZ), and a non-snow covered zone (NSCZ) for North America and Eurasia. We then explore long-term trends in SHC, SCE, and surface air temperature (SAT) and their corresponding correlations in NSCZ, SCSZ and SCNZ for both North America and Eurasia. We find that snow cover downtrends have a significant impact on SHC changes in SCSZ for North America and Eurasia from April through June. SHC changes in the SCSZ over North America are dominated by downtrends in SCE rather than increasing SAT. Over Eurasia, increasing SAT more strongly affects SHC than in North America. Overall, increasing SAT during late spring and early summer is the dominant factor that has resulted in SHC changes over the pan-Arctic domain, whereas reduced SCE plays a secondary role that is only important in the SCSZ.

Spatial patterns of minimum monthly river discharge in the North American Pan-Arctic and its potential controls are explored with geographically weighted regression (GWR). Minimum discharge is indicative of soil water conditions; therefore, understanding spatial variability of its controls may provide insights into patterns of hydrologic change. Here, GWR models are applied to determine a suitable combination of independent variables selected from a set of eight variables. A model specification with annual mean river discharge, temperature at time of minimum discharge, and biome describes well the spatial patterns in minimum discharge. However, minimum discharge in larger watersheds is influenced more by temperature and biome distributions than it is in small basins, suggesting that scale is critical for understanding minimum river discharge. This study is the first to apply GWR to explore spatial variation in Pan-Arctic hydrology. Factores de control espaciales y dependientes de escala en las descargas fluviales minimas de rios Pan-Articos en Norteamerica. El articulo explora los patrones espaciales de caudales fluviales minimos mensuales la region pan-artica de Norteamerica y sus posibles factores de control haciendo uso de una regresion ponderada geograficamente (geographically weigted regression-GWR). Los caudales minimos son indicadores de las condiciones del agua en el suelo, y por lo tanto el entendimiento de la variabilidad espacial de los factores que los controlan puede ayudar a comprender los patrones de cambio hidrologico. En el presente estudio, varios modelos de tipo GWR son aplicados para determinar una combinacion adecuada de variables independientes seleccionadas a partir de un conjunto de ocho variables. El modelo que utiliza la media anual media de descarga fluvial, la temperatura en el momento de caudal minimo, y el bioma, proporciona una buena descripcion de los patrones espaciales en la descarga minima. Sin embargo, en las cuencas hidrograficas grandes, la descarga minima esta mas influenciada por la temperatura y la distribucion de los biomas que en el caso de cuencas mas pequenas, lo que sugiere que la escala es fundamental para entender la descarga minima fluvial. Este estudio es el primero en aplicar GWR para comprender la variacion espacial en la hidrologia de la region pan-artica. 基于GWR（地理加权回归模型）对北美泛北极地区月份最小河流流量的空间模式和潜在控制进行研究。最小流量暗示水土条件；因此，理解空间分异及控制可深刻理解水文变化的模式。GWR可从8个变量中提取一组独立变量的适当组合。通过年均河流流量、最小流量时的温度和生物群落，来描述最小下泄流量的空间格局。在大范围流域中，最小流量受到温度和生物群落分布的影响大于在小规模的流域，揭示出在河流最小流量分析中尺度是非常重要的。本文首次将GWR应用于泛北极水文空间异质性分析。

Understanding methane emissions from the Arctic, a fast warming carbon reservoir, is important for projecting changes in the global methane cycle under future climate scenarios. Here we optimize Arctic methane emissions with a nested-grid high-resolution inverse model by assimilating both high-precision surface measurements and column-average SCIAMACHY satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes are integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated by six different biogeochemical models. We find that, the global methane emissions during July 2004–June 2005 ranged from 496.4 to 511.5 Tg yr−1, with wetland methane emissions ranging from 130.0 to 203.3 Tg yr−1. The Arctic methane emissions during July 2004–June 2005 were in the range of 14.6–30.4 Tg yr−1, with wetland and lake emissions ranging from 8.8 to 20.4 Tg yr−1 and from 5.4 to 7.9 Tg yr−1 respectively. Canadian and Siberian lakes contributed most of the estimated lake emissions. Due to insufficient measurements in the region, Arctic methane emissions are less constrained in northern Russia than in Alaska, northern Canada and Scandinavia. Comparison of different inversions indicates that the distribution of global and Arctic methane emissions is sensitive to prior wetland emissions. Evaluation with independent datasets shows that the global and Arctic inversions improve estimates of methane mixing ratios in boundary layer and free troposphere. The high-resolution inversions provide more details about the spatial distribution of methane emissions in the Arctic.

This study evaluates the hydrometric monitoring maintained within the Canadian pan-Arctic and is based on the hydrometric gauges closest to northern seas for 76 river systems throughout 1950–2008. Monitoring is quantified by compiling time series of total gauged area and discharge values from the available hydrometric records. We further evaluate the quality of hydrometric data by examining the availability of hydrometric records, the continuity of individual records, and the influence of water regulation on river systems. The maximum gauged area of the Canadian pan-Arctic was 64% in 1990 before it slowly decreased to 56% in 2008. Larger river systems typically had the most hydrometric data available, though each river system had an average of 46% of their records available. In 1998, a maximum of 22 river systems had more than 30 years of continuous records, which is the maximum attained throughout the study period. For future improvements in hydrometric monitoring, additional gauges on relatively small rivers will need to be deployed. We suggest new gauges should be implemented in the Eastern Hudson Bay, Ungava Bay and Labrador Sea basins in spite of the tremendous need for more in the Arctic Archipelago.