Search

Manifestations of climate change are often shown as gradual changes in physical or biogeochemical properties1. Components of the climate system, however, can show stepwise shifts from one regime to another, as a nonlinear response of the system to a changing forcing2. Here we show that the Arctic sea ice regime shifted in 2007 from thicker and deformed to thinner and more uniform ice cover. Continuous sea ice monitoring in the Fram Strait over the last three decades revealed the shift. After the shift, the fraction of thick and deformed ice dropped by half and has not recovered to date. The timing of the shift was preceded by a two-step reduction in residence time of sea ice in the Arctic Basin, initiated first in 2005 and followed by 2007. We demonstrate that a simple model describing the stochastic process of dynamic sea ice thickening explains the observed ice thickness changes as a result of the reduced residence time. Our study highlights the long-lasting impact of climate change on the Arctic sea ice through reduced residence time and its connection to the coupled ocean–sea ice processes in the adjacent marginal seas and shelves of the Arctic Ocean.

The amount of snow on Arctic sea ice impacts the ice mass budget. Wind redistribution of snow into open water in leads is hypothesized to cause significant wintertime snow loss. However, there are no direct measurements of snow loss into Arctic leads. We measured the snow lost in four leads in the Central Arctic in winter 2020. We find, contrary to the general consensus, that under typical winter conditions, minimal snow was lost into leads. However, during a cyclone that delivered warm air temperatures, high winds, and snowfall, 35.0 ± 1.1 cm snow water equivalent (SWE) was lost into a lead (per unit lead area). This corresponded to a removal of 0.7–1.1 cm SWE from the entire surface—∼6–10% of this site’s annual snow precipitation. Warm air temperatures, which increase the length of time that wintertime leads remain unfrozen, may be an underappreciated factor in snow loss into leads.

Sea-ice ridges constitute a large fraction of the ice volume in the Arctic Ocean, yet we know little about the evolution of these ice masses. Here we examine the thermal and morphological evolution of an Arctic first-year sea-ice ridge, from its formation to advanced melt. Initially the mean keel depth was 5.6 m and mean sail height was 0.7 m. The initial rubble macroporosity (fraction of seawater filled voids) was estimated at 29% from ice drilling and 43–46% from buoy temperature. From January until mid-April, the ridge consolidated slowly by heat loss to the atmosphere and the total consolidated layer growth during this phase was 0.7 m. From mid-April to mid-June, there was a sudden increase of ridge consolidation rate despite no increase in conductive heat flux. We surmise this change was related to decreased macroporosity due to transport of snow-slush to the ridge keel rubble via adjacent open leads. In this period, the mean thickness of the consolidated layer increased by 2.1 m. At the peak of melt in June–July we suggest that the consolidation was related to the refreezing of surface snow and ice meltwater and of ridge keel meltwater (the latter only about 15% of total consolidation). We used the morphology parameters of the ridge to calculate its hydrostatic equilibrium and obtained a more accurate estimate of the actual consolidation of the keel, correcting from 2.2 m to 2.8 m for average keel consolidation. This approach also allowed us to estimate that the average keel melt of 0.3 m, in June–July, was accompanied by a decrease in ridge draft of 0.9 m. An ice mass balance buoy in the ridge indicated total consolidation of 2.8 m, of which 2.1 m was related to the rapid mode of consolidation from April to June. By mid-June, consolidation resulted in a drastic decrease of the macroporosity of the interior of keel while the flanks had little or no change in macroporosity. These results are important to understanding the role of ridge keels as meltwater sources and sinks and as sanctuary for ice-associated organisms in Arctic pack ice.

Low-salinity meltwater from Arctic sea ice and its snow cover accumulates and creates under-ice meltwater layers below sea ice. These meltwater layers can result in the formation of new ice layers, or false bottoms, at the interface of this low-salinity meltwater and colder seawater. As part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), we used a combination of sea ice coring, temperature profiles from thermistor strings and underwater multibeam sonar surveys with a remotely operated vehicle (ROV) to study the areal coverage and temporal evolution of under-ice meltwater layers and false bottoms during the summer melt season from mid-June until late July. ROV surveys indicated that the areal coverage of false bottoms for a part of the MOSAiC Central Observatory (350 by 200 m2) was 21%. Presence of false bottoms reduced bottom ice melt by 7–8% due to the local decrease in the ocean heat flux, which can be described by a thermodynamic model. Under-ice meltwater layer thickness was larger below first-year ice and thinner below thicker second-year ice. We also found that thick ice and ridge keels confined the areas in which under-ice meltwater accumulated, preventing its mixing with underlying seawater. While a thermodynamic model could reproduce false bottom growth and melt, it could not describe the observed bottom melt rates of the ice above false bottoms. We also show that the evolution of under-ice meltwater-layer salinity below first-year ice is linked to brine flushing from the above sea ice and accumulating in the meltwater layer above the false bottom. The results of this study aid in estimating the contribution of under-ice meltwater layers and false bottoms to the mass balance and salt budget for Arctic summer sea ice.

A ground-based ultra-wideband radiometer operating at 540, 900, 1380, and 1740 MHz was used to measure microwave thermal emissions from an Arctic sea ice floe as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Expedition. The instrument was deployed on a drifting ice floe near 86°N, 120°E in leg 1 of the expedition (December 2019) and observed second-year ice (potentially with refrozen melt ponds) that experienced new ice growth at its base over a ten-day period. Measured circularly polarized brightness temperatures were compared with the predictions of a radiative transfer (RT) model for a layered medium consisting of ocean, growing new ice, desalinated remnant second-year ice/refrozen melt pond, and snow layers. Characteristics of the sea ice composition used in the model were determined from in-situ measurements. Comparisons of the measured and modeled wideband brightness temperatures showed good agreement consistently over the observation period and for various off-nadir observation angles. The results demonstrate the capabilities of 0.5-2 GHz microwave radiometry for observing sea ice properties and also show the impact of a saline ice layer at the ice bottom on the measured brightness temperature.

This study traces dissolved organic matter (DOM) in different water masses of the Arctic Ocean and its effect on the distributions of trace elements (TEs; Fe, Cu, Mn, Ni, Zn, Cd) using fluorescent properties of DOM and the terrigenous biomarker lignin. The Nansen, Amundsen, and Makarov Basins were characterized by the influence of Atlantic water and the fluvial discharge of the Siberian rivers with high concentrations of terrigenous DOM (tDOM). The Canada Basin and the Chukchi Sea were characterized by Pacific water, modified through contact with productive shelf sediments with elevated levels of marine DOM. Within the surface layer of the Beaufort Gyre, meteoric water (river water and precipitation) was characterized by low concentrations of lignin and terrigenous DOM fluorescence proxies as DOM is removed during freezing. High-resolution in situ fluorescence profiles revealed that DOM distribution closely followed isopycnals, indicating the strong influence of sea-ice formation and melt, which was also reflected in strong correlations between DOM fluorescence and brine contributions. The relationship of DOM and hydrography to TEs showed that terrigenous and marine DOM were likely carriers of dissolved Fe, Ni, Cu from the Eurasian shelves into the central Arctic Ocean. Chukchi shelf sediments were important sources of dCd, dZn, and dNi, as well as marine ligands that bind and carry these TEs offshore within the upper halocline (UHC) in the Canada Basin. Our data suggest that tDOM components represent stronger ligands relative to marine DOM components, potentially facilitating the long-range transport of TE to the North Atlantic. Key Points Dissolved Organic Matter (DOM) distribution in the Arctic Ocean is largely controlled by sea ice formation and melt processes DOM distribution in the Arctic Ocean reveals its potential as a tracer for halocline formation and freshwater source assignments Terrigenous and marine DOM are carriers of trace elements from shelves to the open Arctic Ocean, but terrigenous DOM represent stronger ligands

Multiomics approaches need to be applied in the central Arctic Ocean to benchmark biodiversity change and to identify novel species and their genes. As part of MOSAiC, EcoOmics will therefore be essential for conservation and sustainable bioprospecting in one of the least explored ecosystems on Earth. publishedVersion

We examine the relative effect of warming events (storms) and snow cover on thermodynamic growth of Arctic sea ice in winter. We use a 1-D snow and ice thermodynamic model to perform sensitivity experiments. Observations from the winter period of the Norwegian young sea ICE (N-ICE2015) campaign north of Svalbard are used to initiate and force the model. The N-ICE2015 winter was characterized by frequent storm events that brought pulses of heat and moisture, and a thick snow cover atop the sea ice (0.3–0.5 m). By the end of the winter, sea-ice bottom growth was negligible. We show that the thermodynamic effect of storms to the winter sea-ice growth is controlled by the amount of snow on sea ice. For 1.3 m initial ice thickness, the decrease in ice growth caused by the warming events ranged from −1.4% (for 0.5 m of snow) to −7.5% (for snow-free conditions). The decrease in sea-ice growth caused by the thick snow (0.5 m) was more important, ranging from −17% (with storms) to −23% (without storms). The results showcase the critical role of snow on winter Arctic sea-ice growth.

Uncertainty in snow properties impacts the accuracy of Arctic sea ice thickness estimates from radar altimetry. On first-year sea ice (FYI), spatiotemporal variations in snow properties can cause the Ku-band main radar scattering horizon to appear above the snow/sea ice interface. This can increase the estimated sea ice freeboard by several centimeters, leading to FYI thickness overestimations. This article examines the expected changes in Ku-band main scattering horizon and its impact on FYI thickness estimates, with variations in snow temperature, salinity, and density derived from ten naturally occurring Arctic FYI Cases encompassing saline/nonsaline, warm/cold, simple/complexly layered snow (4-45 cm) overlying FYI (48-170 cm). Using a semi-empirical modeling approach, snow properties from these Cases are used to derive layer-wise brine volume and dielectric constant estimates, to simulate the Ku-band main scattering horizon and delays in radar propagation speed. Differences between modeled and observed FYI thickness are calculated to assess sources of error. Under both cold and warm conditions, saline snow covers are shown to shift the main scattering horizon above from the snow/sea ice interface, causing thickness retrieval errors. Overestimates in FYI thicknesses of up to 65% are found for warm, saline snow overlaying thin sea ice. Our simulations exhibited a distinct shift in the main scattering horizon when the snow layer densities became greater than 440 kg/m3, especially under warmer snow conditions. Our simulations suggest a mean Ku-band propagation delay for snow of 39%, which is higher than 25%, suggested in previous studies.

Kartlegging av ferskvannslag og dannelse av falsk bunnis under sjøisen ved sommarsmelting i sentrale Polhavet Sjøisen i Polhavet er i rask endring. Den er blitt mye tynnere i løpet av de siste tiårene, havet og atmosfæren er i endring, og dette påvirker det marine økosystemet i Polhavet. Klimaprosesser i Arktis er følgelig viktige for hele planeten, og polare prosesser er viktige elementer i klimamodeller. Dette var motivasjonen for ekspedisjonen «Multidisciplinary drifting Observatory for the Study of Arctic Climate» (MOSAiC) i 2019-2020, og målsetningen var å samle inn data om atmosfære, havis, hav og det marine økosystem, og koblete prosesser gjennom et helt år i det sentrale Polhavet. Norsk polarinstitutt deltok i ekspedisjonen med flere forskere støttet av prosjektet HAVOC finansiert av Forskningsrådet. Under issmelting på sommeren samles ofte smeltevann fra is og snø i tynne lag under isen som påvirker koblingen mellom hav og is. Dette bidrar til isdannelse midt på sommeren når mesteparten av isen smelter. Falsk bunnis dannes når det kalde ferskvannet møter enda kaldere saltvann under isen og danner en såkalt «false bottoms» på grensesnittet mellom ferskvann og saltvann. Det er lite forstått om utbredelsen av slike ferskvannslag og hvordan de påvirker sjøisen på sommeren. Under MOSAiC ble det gjennomført kartlegging av disse vannlagene i drivisen, og man fant at de befant seg oftere under tynnere første års is. Dette kan ha påvirkning på blant annet smelting av isen og for is assosierte planter og dyr, særskilt om det skjer enda mer smelting. Disse prosesser må dermed bli bedre representert i klimamodeller slik at endringer i havisen kan bedre forutsies i fremtiden. Quantifying false bottoms and under-ice meltwater layers beneath Arctic summer sea ice with fine-scale observations During the Arctic melt season, relatively fresh meltwater layers can accumulate under sea ice as a result of snow and ice melt, far from terrestrial freshwater inputs. Such under-ice meltwater layers, sometimes referred to as under-ice melt ponds, have been suggested to play a role in the summer sea ice mass balance both by isolating the sea ice from saltier water below, and by driving formation of ‘false bottoms’ below the sea ice. Such layers form at the interface of the fresher under-ice layer and the colder, saltier seawater below. During the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition in the Central Arctic, we observed the presence of under-ice meltwater layers and false bottoms throughout July 2020 at primarily first-year ice locations. Here, we examine the distribution, prevalence, and drivers of under-ice ponds and the resulting false bottoms during this period. The average thickness of observed false bottoms and freshwater equivalent of under-ice meltwater layers was 0.08 m, with false bottom ice comprised of 74–87% FYI melt and 13–26% snow melt. Additionally, we explore these results using a 1D model to understand the role of dynamic influences on decoupling the ice from the seawater below. The model comparison suggests that the ice-ocean friction velocity was likely exceptionally low, with implications for air-ice-ocean momentum transfer. Overall, the prevalence of false bottoms was similar to or higher than noted during other observational campaigns, indicating that these features may in fact be common in the Arctic during the melt season. These results have implications for the broader ice-ocean system, as under-ice meltwater layers and false bottoms provide a source of ice growth during the melt season, potentially reduce fluxes between the ice and the ocean, isolate sea ice primary producers from pelagic nutrient sources, and may alter light transmission to the ocean below.

Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. An international team designed and implemented the program to characterize the Arctic Ocean system in unprecedented detail, from the seafloor to the air-sea ice-ocean interface, from sub-mesoscales to pan-Arctic. The oceanographic measurements were coordinated with the other teams to explore the ocean physics and linkages to the climate and ecosystem. This paper introduces the major components of the physical oceanography program and complements the other team overviews of the MOSAiC observational program. Team OCEAN’s sampling strategy was designed around hydrographic ship-, ice- and autonomous platform-based measurements to improve the understanding of regional circulation and mixing processes. Measurements were carried out both routinely, with a regular schedule, and in response to storms or opening leads. Here we present along-drift time series of hydrographic properties, allowing insights into the seasonal and regional evolution of the water column from winter in the Laptev Sea to early summer in Fram Strait: freshening of the surface, deepening of the mixed layer, increase in temperature and salinity of the Atlantic Water. We also highlight the presence of Canada Basin deep water intrusions and a surface meltwater layer in leads. MOSAiC most likely was the most comprehensive program ever conducted over the ice-covered Arctic Ocean. While data analysis and interpretation are ongoing, the acquired datasets will support a wide range of physical oceanography and multi-disciplinary research. They will provide a significant foundation for assessing and advancing modeling capabilities in the Arctic Ocean.

There have been considerable efforts to understand the hydrography of Storfjorden (Svalbard). A recurring winter polynya with large sea ice production makes it an important region of dense water formation at the scale of the Arctic Ocean. In addition, this fjord is seasonally influenced by freshwater inputs from sea ice melt and the surrounding islands of the Svalbard archipelago, which impacts the hydrography. However, the understanding of factors controlling the optical properties of the waters in Storfjorden are lacking and are crucial for the development of more accurate regional bio-optical models. Here, we present results from the first detailed optical field survey of Storfjorden conducted in early summer of 2020. Our observations are based on spectrometric analysis of water samples and in situ vertical profiles with an absorption and attenuation meter, a fluorometer, and a conductivity, temperature, and depth (CTD) sensor. In addition to the expected seasonal contribution from phytoplankton, we find that in early summer waters in Storfjorden are optically complex with a significant contribution from coloured dissolved organic matter (CDOM, 33 %–64 % of the non-water absorption at 443 nm) despite relatively low CDOM concentrations and in the nearshore or near the seabed from non-algal particles (up to 61 % of the non-water absorption at 550 nm). In surface waters, the spatial variability of light attenuation was mainly controlled by inorganic suspended matter originating from river runoff. A distinct subsurface maximum of light attenuation was largely driven by a subsurface phytoplankton bloom, controlled by stratification resulting from sea ice melt. Lastly, the cold dense bottom waters of Storfjorden from winter sea ice production periodically overflows the sill at the mouth of the fjord and can thus reach the Fram Strait. It contained elevated levels of both non-algal particles and dissolved organic matter, which are likely caused by the dense flows of the nepheloid layer interacting with the sea bed.

There have been considerable efforts to understand the hydrography of the Storfjorden fjord (Svalbard). A recurring winter polynya with large sea ice production makes it an important region of dense water formation at the scale of the Arctic Ocean. In addition, this fjord is seasonally influenced by freshwater inputs from sea-ice melt and the surrounding islands of the Svalbard archipelago which impacts the hydrography. However, the understanding of factors controlling the optical properties of the waters in Storfjorden are lacking and are crucial for development of more accurate regional bio-optical models. Here, we present results from the first detailed optical field survey of Storfjorden conducted in early summer of 2020. In addition to the expected seasonal contribution from phytoplankton, we find that in early summer waters in Storfjorden are optically complex with a significant contribution from coloured dissolved organic matter (33–64 % of the non-water absorption at 443 nm) despite relatively low CDOM concentrations, and in the nearshore or near seabed from non-algal particles (up to 61 % of the non-water absorption at 550 nm). In surface waters, the spatial variability of light attenuation was mainly controlled by inorganic suspended matter originating from river runoff. A distinct subsurface maximum of light attenuation was largely driven by a subsurface phytoplankton bloom, controlled by stratification resulting from sea-ice melt. Lastly, the cold dense bottom waters of Storfjorden, from winter sea ice production, which periodically overflows into the Fram Strait, was found to contain elevated levels of both non-algal particles and dissolved organic matter, which is likely caused by the dense flows of the nepheloid layer interacting with the sea bed.

© Copyright 19 June 2019 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (http://www.copyright.com). Questions about permission to use materials for which AMS holds the copyright can also be directed to permissions@ametsoc.org. Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (http://www.ametsoc.org/CopyrightInformation). This study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.

Recent reports on Arctic underice phytoplankton blooms have directed attention to primary production below the sea ice cover. Such underice blooms cannot be detected from space; thus, methods for autonomous underice measurements are critically needed to extend observations beyond ship-based surveys. One central aspect of the ecology of these blooms is whether they were advected from open-water areas or were able to develop below the ice cover under typically low light conditions. The photoacclimation state of the bloom can provide clues about the growth conditions and therefore its origin. Here we investigate the photoacclimation state of a Phaeocystis pouchetii-dominated underice bloom in the Arctic Ocean using ratios of photoprotective carotenoids (PPC) to photosynthetic carotenoids (PSC) and chlorophyll a. The pigment proxies indicate local growth under the ice pack. Furthermore, a method using in situ light absorption measurements to estimate the PPC:PSC ratio was in agreement with the pigment data. The slope of in situ phytoplankton absorption between 488 and 532nm, affected by both PPC and PSC, had a significant linear relationship to the PPC:PSC ratio, indicating that prediction of photoacclimation state can be obtained from absorption profiles. We also review, with regard to the pigment function, different ways of grouping pigments into PPC or PSC applied in previous studies. Although more validation data sets are needed to assess the impact of pigment packaging on the relationship between PPC:PSC and absorption measurement slopes, our study shows the potential for using in situ absorption measurements to collect information about phytoplankton physiology below sea ice. Plain Language Summary Phytoplankton blooms below sea ice cover, that is, underice blooms, can be advected by ocean currents below the ice pack from ice-free waters where they had sufficient light available for growth. They can also grow below the ice pack if sufficient light is transmitted through the ice, and they are able to adjust to the typically low light conditions. Algal pigments can indicate which of the two scenarios is more likely. Algal pigments capture sunlight for photosynthesis, but some of them are used to protect the algal cells from excess light. The ratio of photoprotective to photosynthetic pigments reveals the photoacclimation state ("short time adjustments") of the algae. In this study we investigate the photoacclimation state of an Arctic underice bloom based on pigment ratios, which indicate local growth below the ice pack. Furthermore, we validate a method to estimate the pigment ratios from light absorption measurements carried out with an instrument in the water column. Studies like these are important for developing methods to study remote areas. Ship-based surveys can only cover a restricted area, and satellite remote sensing does not provide biological information from ice-covered waters. Our study shows promising results for using water column instruments to study phytoplankton physiology.

The Arctic Ocean receives a large loading of dissolved organic matter (DOM) from its catchment and shelf sediments, which can be traced across much of the basin. This signature can be used as a tra...

Sea-ice drift becomes most energetic at last moment in summer when refreezing is about to onset. Perennial ice floes, surviving over all seasons, tend to experience a number of deformation events over yearlong drift, with uneven distribution in thickness. Deformed ice floes protrude tall keels into water of ice-ocean boundary, and then stir it up. Consequently, combination of fast ice drift and deformation-experienced perennial ice could be a primary source of momentum/thermal energy for upper waters through propagation of internal waves. In this study, during MOSAiC expedition, we attempted to perform direct observation of wave generation in ice-ocean boundary layer underneath a drifting ice floe in the central Arctic Ocean. Time series of turbulent signals, represented by Reynolds stress and eddy heat flux , were obtained by an eddy covariance system (ECS), coupling a high-frequency (34 Hz) single-point current meter and a temperature sensor. Vertical/temporal properties of near-inertial waves were obtained by a downward-looking ADCP, collocated with ECS on the same ice floe. At same time, a triangle of high-precision GPS systems tracked ice movement to represent mean drift speed, rotation and deformation about the same floe seamlessly in time. Preliminary analyses of those combined data suggested that pronounced signals of inertial motion occurred in early September of 2020 as sheer ice keels dragged underlying waters, stratified by accumulation of melt water. It then allowed occurrence of near-inertial internal waves that tend to be trapped within the interfacial boundary layer, located within top 20 m. At the conference, we will present latest and quantitative knowledges from the MOSAiC expedition.

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

International audience; Reanalysis datasets from atmospheric models and satellite products are often used for Arctic surface shortwave (SW) and longwave (LW) radiative budget analyses, but they suffer from limitations and require validation against local‒scale observations. These are rare in the high Arctic, especially for longer periods that include seasonal transitions. In this study, radiation and meteorological observations acquired during the Norwegian Young Sea Ice Cruise (N‒ICE2015) campaign over sea ice north of Svalbard (80‒83°N, 5‒25°E) from January to June 2015, cloud lidar observations from the Ice‒Atmosphere‒Ocean Observing System (IAOOS) and the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) are compared to daily and monthly satellite retrievals from the Clouds and the Earth's Radiant Energy System (CERES) and ERA‒Interim and ERA5 reanalyses. Results indicate that surface temperature is a significant driver for winter LW radiation biases in both satellite and reanalysis data, along with cloud optical depth in CERES. In May the SW and LW downwelling irradiances are close to observations and cloud properties are well captured (except for ERA‐Interim), while SW upward irradiances are biased low due to surface albedo biases in all datasets. Net SW and LW radiation biases are comparable (⁓20‒30 Wm‒2) but opposite in sign for ERA‒Interim and CERES in May, which allows for error compensation. Biases reduce to ±10 Wm‒2 in ERA5. In June downward LW remains biased low (8‒10 Wm‒2) in all datasets suggesting unsettled cloud representation issues. Surface albedo always differs by more than 0.1 between datasets, leading to significant SW and total flux differences.

The Arctic Ocean receives a large supply of dissolved organic matter (DOM) from its catchment and shelf sediments, which can be traced across much of the basin’s upper waters. This signature can potentially be used as a tracer. On the shelf, the combination of river discharge and sea-ice formation, modifies water densities and mixing considerably. These waters are a source of the halocline layer that covers much of the Arctic Ocean, but also contain elevated levels of DOM. Here we demonstrate how this can be used as a supplementary tracer and contribute to evaluating ocean circulation in the Arctic. A fraction of the organic compounds that DOM consists of fluoresce and can be measured using in-situ fluorometers. When deployed on autonomous platforms these provide high temporal and spatial resolution measurements over long periods. The results of an analysis of data derived from several Ice Tethered Profilers (ITPs) offer a unique spatial coverage of the distribution of DOM in the surface 800m below Arctic sea-ice. Water mass analysis using temperature, salinity and DOM fluorescence, can clearly distinguish between the contribution of Siberian terrestrial DOM and marine DOM from the Chukchi shelf to the waters of the halocline. The findings offer a new approach to trace the distribution of Pacific waters and its export from the Arctic Ocean. Our results indicate the potential to extend the approach to separate freshwater contributions from, sea-ice melt, riverine discharge and the Pacific Ocean. Key Points: Arctic surface waters with comparable temperature and salinity have contrasting in situ dissolved organic matter fluorescence. Organic matter fluorescence can tracklow salinity waters feeding into the Transpolar Drift and haloclinelayers. Siberian and Chukchishelf waters can be separated based on their fluorescence to salinity relationship

The effect of freshwater sources on wintertime sea-ice CO2processes was studied from the glacier front to the outer Tempelfjorden, Svalbard, in sea ice, glacier ice, brine and snow. March–April 2012 was mild, and the fjord was mainly covered with drift ice, in contrast to the observed thicker fast ice in the colder April 2013. This resulted in different physical and chemical properties of the sea ice and under-ice water. Data from stable oxygen isotopic ratios and salinity showed that the sea ice at the glacier front in April 2012 contained on average 54% of frozen-in glacial meltwater. This was five times higher than in April 2013, where the ice was frozen seawater. In April 2012, the largest excess of sea-ice total alkalinity (AT), carbonate ion ([CO32−]) and bicarbonate ion concentrations ([HCO3−]) relative to salinity was mainly related to dissolved dolomite and calcite incorporated during freezing of mineral-enriched glacial water. In April 2013, the excess of these variables was mainly due to ikaite dissolution as a result of sea-ice processes. Dolomite dissolution increased sea-iceATtwice as much as ikaite and calcite dissolution, implying different buffering capacity and potential for ocean CO2uptake in a changing climate.

Sea ice is a critical component of the Earth system, playing an important role in high-latitudesurface radiation balance and heat, moisture and momentum exchange between atmosphereand ocean. In recent years, rapid changes have been occurring in Arctic sea ice, includingdecline in ice extent/area, decreasing in ice thickness and volume, and shifting towards a first-year ice (FYI) dominated, rather than multi-year ice (MYI) dominated ice pack. These are oneof the most well-known and striking examples of climate change. However, representingthese changes in the model is still in question since most of our knowledge is based on MYI.CICE is a sea ice model developed at Los Alamos National Laboratory since 1994. It iswidely used to simulate the growth, melt and movement of sea ice, and to resolve thebiogeochemical processes. Its column version, Icepack, has been separated from CICE afterCICE V5.1.2, which provides additional opportunity for simulating the evolution of driftingsea ice floes. How about the representation of sea ice in a column model (Icepack) and a 3dmodel (CICE)? In 2012, an ice mass balance buoy (IMB) and a Spectral Radiation Buoy(SRB) were deployed on FYI near the North Pole, and later drifted towards Fram Strait. Thesebuoys collected a complete summer melt season of in-band (350-800 nm) spectral solarradiation and sea ice mass balance data. In this study, we apply the Icepack (version 1.1.1)and CICE (version 5.1.2) to investigate the seasonal evolution of sea ice in 2012 in these two models, andassess how well the physical processes are represented in CICE and Icepack, with the focuson the surface changes.

Water isotopes measured in ice cores are well-known tracers of paleoclimate variations. The ratio of heavy to light isotope in snow is indeed strongly controlled by the temperature during condensation along the entire airmass transport. This allows the utilization of isotope variability in the water cycle in current climatic conditions, and on weather time scales, to try to pinpoint key events and processes building up (or re-stating) the isotope signature of a given air mass. Because isotopic fractionation occurs every time water changes phase, it is highly beneficial to sample concurrently the different water reservoirs (i.e. seawater, sea ice, snow, rain and vapor) in order to truly understand the processes at work.Here we present stable water isotope data from two cruises north of Svalbard within the INTAROS project (summer 2018 and summer 2019). During these cruises, vapor isotope composition was measured quasi-continuously on the coast guard icebreaker KV Svalbard. Seawater and precipitation samples were collected continuously throughout the cruises. The 2018 cruise mainly targeted locations within the Marginal Ice Zone north of Svalbard. On the 2019 cruise, sea ice samples and snow samples were collected at 8 ice stations, all the way to the North Pole. The liquid/solid samples were later analyzed at FARLAB at the University of Bergen.A first analysis of the dataset shows that stable water isotope values vary with air mass origin, with marked differences between '18O-enriched’ air coming from the south-east (Barents Sea) and ‘18O-depleted’ air from the north-west (Inner Arctic) during the second cruise. During the 2019 cruise, vapor in air from the south-east tends to have relatively low d-excess values whereas precipitation is largely at equilibrium with the ambient vapor. This INTAROS dataset will be highly beneficial for studies using (coupled) isotope-enabled models, such as earth system models or high-latitude regional climate models, to validate their representation of the high-latitude water cycle.

Data from GEOTRACES cruises GN01 (HLY1502) and GN04 (PS94) have been archived at the Biological & Chemical Oceanography Data Management Office (BCO-DMO; https://www.bco-dmo.org/deployment/638807) and PANGAEA (https://www.pangaea.de/?q=PS94&f.campaign%5B%5D=PS94) websites, respectively. The inorganic carbon data are available at the NOAA Ocean Carbon Data System (OCADS ; doi :10.3334/CDIAC/OTG.CLIVAR_ARC01_33HQ20150809). In addition to these national data archives, the data used in this paper is available as a supplementary downloadable excel file; International audience; A major surface circulation feature of the Arctic Ocean is the Transpolar Drift (TPD), a current that transports river‐influenced shelf water from the Laptev and East Siberian Seas toward the center of the basin and Fram Strait. In 2015, the international GEOTRACES program included a high‐resolution pan‐Arctic survey of carbon, nutrients, and a suite of trace elements and isotopes (TEIs). The cruises bisected the TPD at two locations in the central basin, which were defined by maxima in meteoric water and dissolved organic carbon concentrations that spanned 600 km horizontally and ~25‐50 m vertically. Dissolved TEIs such as Fe, Co, Ni, Cu, Hg, Nd, and Th, which are generally particle‐reactive but can be complexed by organic matter, were observed at concentrations much higher than expected for the open ocean setting. Other trace element concentrations such as Al, V, Ga, and Pb were lower than expected due to scavenging over the productive East Siberian and Laptev shelf seas. Using a combination of radionuclide tracers and ice drift modeling, the transport rate for the core of the TPD was estimated at 0.9 ± 0.4 Sv (106 m3 s‐1). This rate was used to derive the mass flux for TEIs that were enriched in the TPD, revealing the importance of lateral transport in supplying materials beneath the ice to the central Arctic Ocean and potentially to the North Atlantic Ocean via Fram Strait. Continued intensification of the Arctic hydrologic cycle and permafrost degradation will likely lead to an increase in the flux of TEIs into the Arctic Ocean.