In this study, we cover observations of the rapid consolidation and enhanced melt of Arctic sea-ice ridges. During the freezing period, the consolidated part of sea ice ridges is usually up to 1.6–1.8 times thicker than surrounding level ice. Meanwhile, during the melt season, ridges are often observed to be fully consolidated, but this process is not fully understood. We present the evolution of the morphology and temperature of a first-year ice ridge studied during MOSAiC from its formation to advanced melt. From October to May, the draft of first-year ice at the MOSAiC coring site increased from 0.3 m to 1.5 m, while from January to July, the consolidated layer thickness in the ridge reached 3.9 m. We observed several types of ridge consolidation. From the beginning of January until mid-April, the ridge consolidated slowly through heat loss to the atmosphere, with a total consolidated layer growth of 0.7 m. From mid-April to mid-June, there was a rapid increase in ridge consolidation rates, despite conductive heat fluxes not increasing. In this period, the mean thickness of the consolidated layer increased by 2.2 m. We also estimated a substantial snow mass fraction (6%–11%) of ridges using analysis of oxygen isotope composition. Our observations suggest that this sudden change was related to the transport of snow-slush inside the ridge keel via adjacent open leads that decreased ridge macroporosity, which could result in more rapid consolidation.

During the summer season, sea ice melts from the surface and bottom. The melt rates substantially vary for sea ice ridges and undeformed first- and second-year ice. Ridges generally melt faster than undeformed ice, while the melt of ridge keels is often accompanied by further summer growth of their consolidated layer, which increases their survivability. We examined the spatial variability of ice melt for different types of ice from in situ drilling, coring, and multibeam sonar scans of the remotely operated underwater vehicle. Six sonar scans performed from 24 June to 21 July were analyzed and validated using seven ice drilling transects. The area investigated by the sonar (0.4 km by 0.2 km) consisted of several ice ridges, surrounded by first- and second-year ice. We show a substantial difference in melt rates for sea ice with a different draft. We also show how ridge keels decay depending on the keel draft, width, steepness, and location relative to the surrounding ridge keel edges. We also use temperature buoy data to distinguish snow, ice surface, and bottom melt rates for both ridges and level ice. These results are important for quantifying ocean heat fluxes for different types of ice during the advanced melt and for estimating the ridge contribution to the total ice mass and summer meltwater balances of the Arctic Ocean.

How to cite: Salganik, E., Lange, B., Katlein, C., Matero, I., Divine, D., Itkin, P., Høyland, K., and Granskog, M.: The rapid life of Arctic sea-ice ridge consolidation and melt, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-775, https://doi.org/10.5194/egusphere-egu24-775, 2024.

Skillful Arctic sea ice forecast for the melting season remains a great challenge because there is no reliable pan-Arctic sea ice thickness (SIT) data set for the summertime. A new summer Cryosat-2 SIT observation data set based on an artificial intelligence algorithm may mitigate the situation. We assess the impact of this new data set on the initialization of both short-term and long-term sea ice forecasts in the melting seasons of 2015 and 2016 in a sea-ice couple model with data assimilation. We find that the assimilation of the new summer CryoSat-2 SIT observations can reduce the summer ice edge prediction error. Further, adding SIT observations to an established forecast system with sea ice concentration assimilation leads to a more realistic short-term summer ice edge forecast in the Arctic Pacific sector. The long-term Arctic-wide SIT prediction is also improved especially before the onset of freezing. In spite of remaining uncertainties,  summer CryoSat-2 SIT observations have the potential to enhance Arctic sea ice forecast on multiple time scales.

How to cite: Song, R., Mu, L., Chen, X., Kauker, F., Loza, S., and Losch, M.: Potential effects of summer Cryosat-2 sea ice thickness observations on sea ice forecast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-929, https://doi.org/10.5194/egusphere-egu24-929, 2024.

The Arctic is one of Earth’s regions most susceptible to climate change. Climate models show that in a warming climate, the Arctic Ocean warms much faster than the global ocean mean, mainly due to the rapid warming of the Atlantic layer, which is called 'Arctic Ocean Amplification.' However, climate models still encounter challenges with large biases and considerable inter-model spread in the Arctic Ocean. For example, the Atlantic layer in the Arctic Ocean, simulated by the climate models, is too thick and too deep. This leads to the warming trend, and inter-annual variability of the simulated Atlantic Water that are too small compared to the observations. Here, we present Arctic Ocean dynamical downscaling simulations and projections based on a high-resolution ice-ocean coupled model, FESOM, and a climate model, FIO-ESM. The historical results demonstrate that the root mean square errors of temperature and salinity in the downscaling simulations are much smaller than those from CMIP6 climate models. The common biases, such as the overly deep and thick Atlantic layer in climate models, are significantly reduced by dynamical downscaling. Dynamical downscaling projections show that the Arctic Ocean may warm faster than the projections made by CMIP6 fully-coupled climate models.

How to cite: Shu, Q. and Wang, Q.: Dynamical downscaling simulations and future projections of the Arctic Ocean based on FESOM and FIO-ESM., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1921, https://doi.org/10.5194/egusphere-egu24-1921, 2024.

The North Water Polynya (NOW) is the largest recurrent Arctic coastal polynya. The formation of the NOW is critically dependent on the development of an ice arch that defines its northern boundary. In this study, high-resolution ENVISAT Advanced Synthetic Aperture Radar data, Sentinel-1A data, and Moderate Resolution Imaging Spectroradiometer data were employed to identify the spatio-temporal characteristics of the ice arch during 2006–2019. Polynya pixels were identified based on the thin ice thickness (TIT), using a threshold of TIT <0.2 m, from which the polynya extent, heat flux, and ice production (IP) were estimated. The results show the different locations of the ice arch in different years, with a mean duration of 132 ± 69 days. The average annual polynya extent over the 14 years is ∼38.8 ± 8 × 10³ km², and we found that it is more closely correlated with wind speed during the winter and air temperature during early spring. The average heat flux drops from about 248 W/m² in the winter months to about 34 W/m² in May. The average accumulated IP varies significantly every year, with an average of 144 ± 10³ km³, and peak values in March in most years. No apparent interannual trends are shown for the polynya area, heat flux, and IP during 2006–2019. The results also show that IP calculated based on the ice arch data is approximately 25% lower than that obtained by assuming a fixed time, location, and duration for the polynya.

How to cite: Hui, F., Ren, H., Shokr, M., Cheng, X., Li, X., and Zhang, Z.: Estimation of Sea Ice Production in the North Water Polynya Based on Ice Arch Duration in Winter During 2006–2019, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1922, https://doi.org/10.5194/egusphere-egu24-1922, 2024.

As sea ice disappears, the emergence of open ocean deep convection in the Arctic, which would enhance ice loss, has been suggested. Here, using 36 state-of-the-art climate models and up to 50 ensemble members per model, we show that Arctic deep convection is rare under the strongest warming scenario. Only 5 models have convection by 2100, while 11 have had convection by the middle of the run. For all, the deepest mixed layers are in the eastern Eurasian basin. When the models convect, that region undergoes a salinification and increasing wind speeds; it is freshening otherwise. The models that do not convect have the strongest halocline and most stable sea ice, but those that lose their ice earliest -because of their strongly warming Atlantic Water- do not have a persistent deep convection: it shuts down mid-century. Halocline and Atlantic Water changes urgently need to be better constrained in models.  

How to cite: Heuzé, C. and Liu, H.: No emergence of deep convection in the Arctic Ocean across CMIP6 models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3080, https://doi.org/10.5194/egusphere-egu24-3080, 2024.

The drastic decline of Arctic sea ice due to global warming and polar amplification of environmental changes in the Arctic basin profoundly alter primary production with consequences for polar ecosystems and the carbon cycle. In this study, we use highly branched isoprenoids (HBIs), brassicasterol, dinosterol and terrestrial biomarkers (n-alkanes and campesterol) in surface sediments to assess sympagic and pelagic algal production with changing sea-ice conditions along a latitudinal transect from the Bering Sea to the high latitudes of the western Arctic Ocean. Suspended particulate matter (SPM) was also collected in surface waters at several stations of the Chukchi Sea to provide snapshots of phytoplankton communities under various sea-ice conditions for comparison with underlying surface sediments. Our results show that sympagic production (IP₂₅ and HBI-II) increased northward between 62°N and 73°N, with maximum values at the sea-ice edge in the Marginal Ice Zone (MIZ) between 70°N and 73°N in southeastern Chukchi Sea and along the coast of Alaska. They were consistently low at northern high latitudes (>73°N) under extensive summer sea-ice cover and in the Ice-Free Zone (IFZ) of the Bering Sea. Enhanced pelagic sterols and HBI-III occurred in the IFZ across the Bering Sea and in southeastern Chukchi Sea up to 70°N-73°N in the MIZ conditions that marks a shift of sympagic over pelagic production. In surface water SPM, pelagic sterols display similar patterns as Chl a, increasing southwards with higher amounts found in the Chukchi shelf pointing out the dominance of diatom production. Higher cholesterol values were found in the mid-Chukchi Sea shelf where phytosterols were also abundant. This compound prevailed over phytosterols in sediments, compared to SPM, reflecting efficient consumption of algal material in the water column by herbivorous zooplankton.

How to cite: Bai, Y., Sicre, M.-A., Ren, J., Klein, V., Jin, H., and Chen, J.: Latitudinal distribution of biomarkers across the western Arctic Ocean and the Bering Sea: an approach to assess sympagic and pelagic algal production, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3752, https://doi.org/10.5194/egusphere-egu24-3752, 2024.

Leads in sea ice cover are almost linear fractures within the pack ice, and are commonly observed in the polar regions. In winter, leads promote energy flux from the underlying ocean to the atmosphere. Synthetic aperture radar (SAR) can monitor leads with a fine spatial resolution, regardless of solar illumination and atmospheric conditions. In this paper, we present an approach for automatic sea ice lead detection (SILDET) in the Arctic wintertime using Sentinel-1 SAR images. SILDET is made up of four modules: 1) a segmentation module; 2) a balance module; 3) an optimization module; and 4) a mask module. The validation results presented in this paper show that SILDET has the capability of detecting open and frozen leads at different stages of freezing. The lead map obtained from SILDET was compared to a lead dataset based on Moderate Resolution Imaging Spectroradiometer (MODIS) data and validated by the use of Sentinel-2 images. This shows that SILDET can provide a more detailed distribution of leads and better estimation of lead width and area. Compared with visual interpretation of Sentinel-1 images, the overall detection accuracy is 97.80% and the Kappa coefficient is 0.88 (for all types). The pyramid scene parsing network (PSPNet) in the segmentation module shows a better performance in detecting frozen leads, compared with the deep learning methods of UNet and DeepLabv3+. The optimization module utilizing shape features also improves the precision in detecting frozen leads. SILDET was applied to present the Arctic lead distribution in January and April 2023 with a spatial resolution of 40 m. The Arctic-wide lead width distribution follows a power law with an exponent of 1.64 ± 0.07. SILDET can be expected to provide long-term high-resolution lead distribution records.

How to cite: Chen, S., Shokr, M., Zhang, L., Zhang, Z., Hui, F., Cheng, X., and Qin, P.: Arctic Wintertime Sea Ice Lead Detection from Sentinel-1 SAR Images, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3959, https://doi.org/10.5194/egusphere-egu24-3959, 2024.

The surface Arctic Ocean is subject to rapidly changing freshwater inputs, from increasing ice melt and riverine inputs. Close monitoring of inflow waters from the Pacific and Atlantic is also needed for understanding the balance of geochemical cycles and making future predictions in the Arctic.  However, our knowledge of ocean biogeochemical data is very limited, necessitating an expansion of spatial and temporal coverage. However, the acquisition of ocean samples is hindered by the intricate sampling and analytical procedures employed both at sea and on land.

In our recent work [Hatta et al, 2021; 2023], a miniaturized, automated, microfluidic analyzer for nutrient analysis was developed using the programmable flow injection (pFI) technique.  This innovative system achieves accurate measurements with minimal reagent use, computer-controlled manipulations, and auto-calibration techniques, thus it is a promising oceanographic tool for increasing sample acquisition and determination, as well as minimizing human error.  For the pFI technique, the traditional silicate (Si) molybdenum blue method was modified by combining oxalate and ascorbic acid into a single reagent. This new method obtained a limit of detection of 514 nM Si, r.s.d. 2.1%, sampling frequency rate of 40 samples per hour, reagent consumption of 700 microliters per sample, and use of deionized (DI) water as a carrier solution. Phosphate (P) does not interfere significantly in this technique if the Si:P ratio is 4:1 or larger. Additionally, since there is no salinity influence, samples collected from the open ocean, coastal areas, or rivers can all be determined accurately using a DI water-based standard calibration covering a single small range by diluting samples to fall within this limited range.

In this contribution, this new shipboard method using programmable Flow Injection will be presented along with high-resolution Si data from the Chukchi shelf.  These data were obtained every 10-20 minutes by directly connecting the pFI platform to the underway water sampling system during the RV Mirai summer cruises. This new analytical platform will allow us to significantly expand our database and thus help to constrain and quantify geochemical processes and budgets in the Arctic Ocean.

How to cite: Hatta, M., Davis, M., and Measures, C.: Surface silicate distribution in the Chukchi-shelf region during the Arctic summer cruises using programmable flow injection technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6998, https://doi.org/10.5194/egusphere-egu24-6998, 2024.

Mesoscale eddies play a crucial role in shaping the dynamics of the Arctic Ocean, making them essential for understanding future Arctic changes and the ongoing 'Atlantification' of the region. In this study, we use simulations generated by the unstructured-mesh Finite volumE Sea ice-Ocean Model (FESOM2) with a 1-km horizontal resolution in the Arctic Ocean.

Our investigation includes multiple simulations, namely a seven-year run representing the present-day climate and a slice simulation for the end of the 21st century, representative for a 4°C warmer world. Through these simulations, we evaluate changes in Eddy Kinetic Energy (EKE) within the Eurasian Basin and analyze their correlation with factors like sea-ice cover, baroclinic conversion rate, and stratification. To deepen our understanding, we combine Eulerian properties like EKE and baroclinic conversion rate with Lagrangian properties obtained from an algorithm that automatically identifies and tracks eddies using vector geometry.

Our findings from the end-of-century slice simulation indicate a significant increase in Arctic eddy activity in the future, accompanied by retreating sea ice. The present-day simulation reveals that the seasonality of EKE is mainly influenced by changes in sea ice, with distinct drivers at different depth levels for monthly anomalies. The mixed layer shows a robust connection to sea ice variability, while deeper levels, protected by stratification, are more significantly influenced by baroclinic conversion.

How to cite: Müller, V., Wang, Q., Koldunov, N., Danilov, S., Li, X., Liu, C., and Jung, T.: Changes of mesoscale eddy activity in the Eurasian Basin from 1-km simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8828, https://doi.org/10.5194/egusphere-egu24-8828, 2024.

Accelerated melting of Arctic sea ice, a consequence of global warming, is being exacerbated by increased freshwater inputs. This has led to a significant reduction in the halocline layer within the Fram Strait, enhancing ocean stratification and creating a feedback loop that further accelerates sea ice loss. This process is critical for the formation of North Atlantic Deep Water (NADW), where the West Spitsbergen Current (WSC) plays an essential role in recirculation.

Our study delves into the characteristics and influences of mesoscale eddies in the Fram Strait, particularly focusing on their impact on the WSC recirculation and NADW formation. Conducted over three years (2021-2023) during the months of minimal sea ice cover (August to October), the research involved deploying 36 specialized surface mini buoys across the strait. Analytical methods such as horizontal dispersion coefficients, finite-size Lyapunov exponents (FSLE), Lagrangian eddy identification, and sea surface temperature (SST) e-folding time were employed to assess WSC surface dynamics, eddy activities, and air-sea heat exchange.

Notably, we observed WSC bifurcation and intense mesoscale seawater mixing in the southwest Yermak Plateau and east of Molloy Deep (MD), areas marked by a rise in SST e-folding scale time gradient and considerable heat loss to the atmosphere (approximately 120 W/m²). Surface water convergence and sinking were detected near the western side of Molloy Deep and the Hovgaard (HG) regions, coinciding with high vorticity zones. Analysis of the buoy trajectories identified 682 eddy samples, forming the basis for a statistical examination of their size, period, intensity, and cyclonic features. This analysis was complemented by correlating eddy trajectories with sea surface height anomaly (SSHA) data, showing notable alignment.

Our results reveal a predominance of anticyclonic eddies in the Fram Strait, accounting for nearly 65% of the total eddies. Further, a consistency analysis between these eddies and wind stress curl indicated that about 66% of the anticyclonic eddies in the Molloy Deep region correlate with wind stress curl patterns, suggesting wind influence in their formation

How to cite: Chien, H., Chen, Y.-C., Chang, H.-M., Fu, K.-H., and Wang, B.-S.: Analyzing Mesoscale Eddy Impact on the West Spitsbergen Current in the Fram Strait, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9293, https://doi.org/10.5194/egusphere-egu24-9293, 2024.

Polynyas, open water regions within the sea ice cover, have been observed by satellites intermittently in the Arctic region over the past few decades. Their formation is complex, requiring various drivers to precondition and trigger the opening, which then influences local and regional weather significantly. Therefore, understanding Arctic polynyas’ spatial and temporal distribution is crucial to studying the polynyas’ impacts on climate. To date, most research is local and short-term, focusing on the major active Arctic polynyas or specific events; there is a need for pan-Arctic, long-term studies of all polynyas. Here, we use all available sea ice satellite data products to investigate all Arctic polynya events since 1979, in particular their locations for each day. The location preciseness and robustness are examined by sensitivity tests, varying the sea ice concentration (20 – 40%) and thickness (10 – 30 cm) thresholds. In the meantime, polynyas’ daily area extent, event duration, and recurrence are also obtained. The results indicate that the Franz-Josef Land, Eastern Kara Sea, and Nares Strait are the most active polynya formation-prone regions during wintertime. In addition, there is an increasing trend of polynya formation across the observation period. In future work, we plan to use the retrieved locations to determine whether thermodynamics or dynamic forcings contribute most to the Arctic polynyas’ opening.

How to cite: Wong, H. M., Heuzé, C., Ickes, L., and Zhou, L.: Spatial and temporal distribution of all Arctic Polynyas since 1979, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9400, https://doi.org/10.5194/egusphere-egu24-9400, 2024.

The polar sea ice cover exhibits narrow bands of increased deformation, resulting in the formation of leads and pressure ridges. They are referred to as linear kinematic features (LKFs). They are important features of the sea ice field as they directly influence the heat and momentum exchange between ocean and atmosphere. By doing so, they influence the development of not only the sea ice cover but also the ocean and the local climate. Conversely, LKFs are also influenced by climate changes as the sea ice cover will be affected by changes in atmospheric and ocean temperature. In this work, the LKFs in the Arctic sea ice cover in current climate are compared to those in a warmer world. An LKF detection and tracking algorithm will be used to create a climate change signal. For this, the number of LKFs as well as their lifetimes are taken into account. The data analyzed in this work is created by the ocean-sea ice model FESOM. As LKFs are highly localized features, using a high spatial resolution is crucial. The resolution used in the analyzed runs is 1km. They span over five years starting at 2010, 2050, and 2090.

How to cite: Gärtner, J.: Detecting Linear Kinematic Features in Arctic Sea Ice in a Warmer World Using High Resolution Model Output, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10598, https://doi.org/10.5194/egusphere-egu24-10598, 2024.

The intensifying influence of warmer Atlantic Ocean waters in the Arctic, known as Arctic Atlantification, amplifies climate change effects by accelerating sea ice melting and altering ecosystems. Long-term data series are indispensable for discerning nuances in climate changes, especially when occurring in the deep ocean. They also provide a crucial temporal foundation for accurate modeling, useful to predict future scenarios and formulate effective strategies to address the challenges of climate change.

Here, we present oceanographic data collected from June 2014 to June 2023 at mooring site S1 (76°N, 14°E, 1040 m water depth), above the continental slope on the southwestern margin of Svalbard Archipelago (Fram Strait). There, the main branch of the West Spitsbergen Current transports Atlantic Water (in the upper layer) and Norwegian Sea Deep Water (below 900 m depth) poleward into the Arctic Ocean. Site S1 strategically lies at the convergence of Atlantic waters, the Arctic Ocean heat source, with waters from Storfjorden (Spitsbergen largest fjord) and shelf waters from the West Spitsbergen continental shelf. The oceanographic mooring S1 is part of the SIOS marine infrastructure network (Svalbard Integrated Arctic Earth Observing System, https://sios-svalbard.org/), and has undergone progressive instrument improvement over time, adding data collection at the intermediate layer since the summer 2022.

We focus on exploring short-term and seasonal variations in thermohaline properties, ocean currents, and particulate fluxes recorded in the deep layer over the last nine years. This analysis is undertaken in conjunction with meteorological conditions and trends in sea ice concentration. Oceanographic mooring data together with repeated Conductivity-Temperature-Depth (CTD) casts during summer surveys, show that the period 2014-2021 was characterized by the absence of dense shelf water exported at the near bottom on the slope, probably due to a limited production of dense water in the fjords, while the wind-induced vertical mixing and the resulting internal oscillations were probably favoured. During this period, a gradual decline in sea ice cover in winter is observed in the S1 area and adjacent fjords. The only exception is the winter 2020, when the sea ice extent returned apparently to pre-2013 levels, and at 1000m depth there were weak signals of cascading of dense shelf water, probably originated in the Storfjorden polynya.

Contrary to what is clearly evident in the literature regarding the increasing propagation of Atlantic waters northwards, temperature and salinity at mooring S1 showed no, or very little, positive trends over the investigated period. However, sporadic intrusions of relatively warm and saline water into the deep layer were observed. These occur most frequently in winter and are associated with the passage of internal waves that promote turbulent mixing of intermediate Atlantic waters with deep waters, facilitating the heat diffusion into the ocean depths.

How to cite: Giordano, P., Bensi, M., Kovacevic, V., Russo, A., and Langone, L.: Weak signals of dense shelf water cascading in 2020 during a persisting phase of sporadic Atlantic water intrusions into the deep layer of the SW-Svalbard slope, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11226, https://doi.org/10.5194/egusphere-egu24-11226, 2024.

We present a feasibility assessment of using several publicly available C-band wide-swath SAR datasets to derive sea ice type maps in the Atlantic sector of the Arctic Ocean from 1991 to present. This region is characterized by highly variable and dynamic sea ice conditions, and temporally consistent, large-scale monitoring of sea ice parameters is only possible through satellite remote sensing. We use data from C-band sensors including Sentinel-1, RADARSAT-2, Envisat ASAR and ERS-1/2, which have similar central frequencies and spatial resolution, to cover the study period. We evaluate comparative image classification performances and classification consistency using these datasets with common training datasets in geographically and temporally overlapping scenes and a sea ice classifier correcting for per-class incidence angle (IA) effects. Through this evaluation, we demonstrate the differences in these datasets affecting sea ice classification and the feasibility of using legacy sensors including Envisat ASAR and ERS-1/2 to extend the time series of sea ice type maps back to 1991 in our study area. This study provides theoretical support for the establishment of a multi-decadal SAR-based sea ice type product, which will contribute to the assessment of seasonal and inter-annual sea ice variations, especially the variability in new ice formation, which strongly influences physical and biogeochemical processes across the ocean-ice-atmosphere interface. This study is part of the collaborative project INTERAAC (air-snow-ice-ocean INTERactions transforming Atlantic Arctic Climate) between Norway and China, which aims at generating a reconciled multi-mission Climate Data Record (CDR) for Atlantic Arctic sea ice.

How to cite: Guo, W., Doulgeris, A. P., Lohse, J., Johansson, M., Itkin, P., Eltoft, T., Landy, J., and Xu, S.: Feasibility of using C-band Synthetic Aperture Radar datasets for long term (1991-present) sea ice monitoring: towards multi-decadal analysis of sea ice type changes in the Atlantic sector of the Arctic Ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12174, https://doi.org/10.5194/egusphere-egu24-12174, 2024.

In this study, we investigate the interannual variability of the sea ice area (SIA) in the Barents-Kara Sea (BKS) region. We explore the contributing factors to this variability, primarily focusing on oceanic influences evident in the Barents Sea Opening (BSO). The BSO, characterized by eastward warm Atlantic Water (AW) inflow, plays a crucial role in shaping the BKS SIA. While the inflow has been extensively studied, the westward-directed outflow known as Bear Island Slope Current (BISC), remains insufficiently observed. Being fed by relatively warm recirculating modified AW (mAW), the BISCs impact on the overall ocean heat transport (OHT) variability is uncertain.

Utilizing the global Finite Volume Sea Ice and Ocean Model (FESOM2.1), we derive estimates of the interannual volume transport and temperature variability of the BISC, filling the observational gap. We find that whereas the variability of BSO inflow/BISC volume transport is similar in magnitude, the temperature variability of the BISC exceeds the BSO inflow temperature variability. By linking the simulated BISC variability to BKS SIA, our findings reveal a yet unknown, strong co-variation between the volume transport of the BISC and the BKS SIA at the end of the freezing season, with a short lead time of zero to three months. We thus further examine the role of the BISC in generating interannual anomalies in the BKS SIA. Our model simulations illustrate that the volume transport of the BISC can be modified by the emergence of a secondary mAW recirculation downstream the northern AW path through the BS in the months preceding anomalously large BKS SIA. This secondary mAW recirculation is thereby increasing the volume transport of mAW leaving the BS via the BISC, reducing the amount of AW reaching the northern Barents Sea ice edge downstream. Additionally, we identify a connection between the atmospheric forcing pattern associated with the volume transport variability of the BISC and anomalous sea ice advection into the BKS as a second cause for the BISC volume transport/BKS SIA co-variability.

In general, our study emphasizes the co-variability between BKS SIA and the BISC. We highlight the role of the mAW recirculations in altering the amount of AW, and consequently ocean heat, reaching the ice edge in the northwestern Barents Sea.

How to cite: Heukamp, F. and Wekerle, C.: Variability of the Barents-Kara Sea Sea Ice Area and its Correlation with Atlantic Water Recirculation through the Barents Sea Opening, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12688, https://doi.org/10.5194/egusphere-egu24-12688, 2024.

The Pacific gateway to the Arctic has a vast continental shelf spanning the northern Bering and the Chukchi Seas. Within this shelf region, diatoms are crucial in sustaining high primary production and facilitating the sinking particulate organic carbon flux from spring to summer. Consequently, the bottom sediments have abundant viable diatoms, including resting stages. Despite the importance of diatoms, our understanding of the dynamics of this organism in sediments and their capacity to initiate primary production in the Pacific Arctic shelf remains limited.

In this study, we delved into the photophysiological capabilities of diatoms in the surface sediments collected from the Chukchi Sea in autumn through a laboratory incubation experiment at 3°C under the light conditions of 300 or 30 µmol photons m^-2 s^-1 for seven days. This experiment revealed that diatoms, mainly Chaetoceros, quickly resumed photosynthesis after light exposure and reached the maximum photosynthetic carbon fixation rates within only several days. These results suggest that diatoms in sediments have a significant potential to function as “seeds” for bloom formation in the sunlit water column. We further examined diatom communities, including resting spores, in the water column of the Chukchi Sea during autumn using scanning electron microscopy (SEM) and DNA metabarcoding techniques, as well as environmental parameters. Consequently, intense winds and subsequent water turbulence in the shallow Chukchi caused the predominance of Chaetoceros resting spores, probably derived from the sediments, in the diatom assemblages. As speculated from the incubation experiment mentioned above, diatom resting spores from the sediments can germinate immediately in the water column. Thus, settled diatoms could work as seeds for subsequent autumn blooms by being supplied from the seafloor along with nutrient-rich water.

The recent delayed sea ice formation in the autumn Arctic leads to increased storm occurrence over open water and enhanced vertical mixing, resulting in more frequent autumn blooms. Therefore, diatoms in sediments could be one of the critical contributors to autumn blooms in the shallow Pacific Arctic.

How to cite: Fukai, Y., Fujiwara, A., Nishino, S., Matsuno, K., and Suzuki, K.: Potential of diatoms in sediments as seeds for autumn blooms in the Pacific Arctic shelf, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14215, https://doi.org/10.5194/egusphere-egu24-14215, 2024.

Ocean acidification induced by the absorption of anthropogenic CO2 and its consequences pose a potential threat to marine ecosystems around the globe. The Arctic Ocean, particularly vulnerable to acidification, provides an ideal region to investigate the progression and impacts of acidification before they manifest globally. Recent documentation of undersaturated surface waters in carbonate minerals in the Sherard Osborn fjord in northwest Greenland, a region visited for the first time in summer 2019, reveals inherent variability in biogeochemical processes. Associated with highly acidic surface waters, the partial pressure of CO2 (pCO2) was undersaturated relative to the atmosphere, indicating this study area as a CO2 sink. To comprehend variations in pCO2 in the northwest Greenland fjords and identify its drivers, we conducted a comparative study between two fjords in the region (Petermann and Sherard Osborn fjords) and used carbonate system data from the temperature minimum layer to examine the winter-to-summer evolution of pCO2 and influencing factors. Additionally, we evaluated pCO2 variations (δpCO2) concerning temperature, freshwater inputs, biological activity, and air-sea CO2 uptake to quantitatively assess the seasonal influencing factors on surface ocean pCO2. In the Sherard Osborn fjord, despite a substantial increase in surface temperature from winter to summer potentially increasing pCO2 and causing CO2 supersaturation relative to the atmosphere, freshwater inflow and biological activity reduced pCO2, resulting in CO2 undersaturation relative to the atmosphere. In the Petermann fjord, pCO2 remained lower than atmospheric levels due to a slight seasonal variation in surface temperature and significant biological activity, reducing pCO2 in surface water.

How to cite: Akhoudas, C., Stranne, C., Ulfsbo, K. A., Thornton, B., and Jakobsson, M.: Winter to summer evolution of pCO2 in surface water of northern Greenland fjords , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14505, https://doi.org/10.5194/egusphere-egu24-14505, 2024.

Large model spread and biases exist in simulating the Arctic Ocean water mass and circulations from the latest CMIP6 coupled and ocean-sea ice-only simulations. This can be at least partly attributed to large uncertainties due to unresolved key processes in this region, and it is hoped that high resolution can - to a certain extent - come to the rescue.

In this work, we first examined two high-resolution simulations by two CMIP6-class models: 1) a multi-centennial integration of CESM (CESM-HR; ocean resolution 1/10-deg), and 2) a 50-year integration of NorESM (NorESM-MX; ocean resolution 1/8-deg). The two models show clear signs of improvements in simulating the Arctic Ocean compared to their standard 1-deg resolution counterparts, but certain biases remain, such as the incorrect pathway of the Atlantic Water and the too-deep mixed layer depth in NorESM-MX.

We then performed and analysed a similar NorESM-MX simulation, but this time with a newly developed hybrid vertical coordinate (z-density) in the ocean model (the default is isopycnal/density coordinate). ​​Experience from hybrid coordinate testing runs in standard 1-deg resolution shows e.g. much-improved water masses and sea ice extent in the Southern Ocean, mixed layer depths, and importantly more rapid equilibration to energy balance in coupled simulations. When applied in the high-resolution NorESM-MX configuration, the results with the new coordinate show a much-improved representation of the pathway of Atlantic water and the distribution of mixed layer depth in the Arctic Ocean. 

How to cite: Guo, C., Bentsen, M., Nummelin, A., Ilicak, M., Gupta, A., and Klocker, A.: Arctic Ocean simulations in two high-resolution coupled climate models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18118, https://doi.org/10.5194/egusphere-egu24-18118, 2024.

Near‐inertial waves are waves propagating in the interior of the ocean. Created by surface storms, they have the potential to influence the ocean environment by inducing vertical mixing. Compared to other oceans, the Arctic Ocean has low near-inertial wave activity, but might be changing. It is a challenge, however, to predict near-inertial wave activity in the Arctic Ocean due to its intricate vertical salinity and temperature stratification. Our in-situ campaign has obtained the first direct deep current measurements revealing notable temporal and spatial variability of deep near-inertial waves in the western Arctic Ocean. These observations are an important step towards a clearer depiction of the evolving energy budget, and concomitant mixing, associated with potentially high impact near-inertial wave activity in an increasingly ice-free Arctic Ocean.

How to cite: Jeon, C., Boury, S., Cho, K.-H., Lee, E.-J., Park, J.-H., and Peacock, T.: Observation of temporal and spatial variability of deep near-inertial waves in the western Arctic Ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18702, https://doi.org/10.5194/egusphere-egu24-18702, 2024.

How to cite: Vuollekoski, H., Lensu, M., and Haapala, J.: Extreme sea ice motion -- analysis of ice drifter buoy data in the Gulf of Bothnia , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18990, https://doi.org/10.5194/egusphere-egu24-18990, 2024.

The Greenland Sea is a key player in the Atlantic Meridional Overturning Circulation (AMOC), crucial for forming dense waters through open-water convection and influencing global climate dynamics. Recent changes, such as decreasing sea ice concentration (SIC) and the shoaling of the mixed layer depth (MLD), have spurred detailed research into their impact on the AMOC. Our study, using the latest TOPAZ reanalysis, explores these changes from 1991 to 2021.

To strengthen our findings, we meticulously compare a 10-year observational dataset, validating TOPAZ's ability to reproduce processes like dense water formation and MLD evolution in the Greenland Sea. We find notable agreement, with the MLD reaching intermediate depths, and TOPAZ's overflow water density aligning with observations. Results show a decrease in SIC and a shallowing of the MLD, linked to rising surface water temperatures.

While our results indicate a similar trend, we're not ready to draw final conclusions. Further analysis is needed to understand how observational data compares to TOPAZ findings. Although reanalysis data provides valuable insights, it's crucial to validate everything with observational data. The comprehensive dataset and almost daily temporal resolution of our observational platforms significantly bolster the reliability of our conclusions.

Understanding Greenland Sea variability is vital not only for decoding its role in the AMOC but also for grasping broader implications for the global climate system. By highlighting the intricate relationship between SIC, MLD, temperature, and salinity, our research contributes to the ongoing dialogue on climate change dynamics.

How to cite: Domingo, S., Horrach, J. M., Izquierdo, A., and Rodriguez, Á.: Exploring links between Mixed-Layer depth and Sea Ice concentration variability in the Greenland Sea., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19973, https://doi.org/10.5194/egusphere-egu24-19973, 2024.

Sea ice types, e.g., first-year ice (FYI) and multi-year ice (MYI), can be discriminated based on their radiometric and scattering signatures. However, changes in ice surfaces caused by factors such as ice deformation and melt-refreeze events can lead to extensive ice type misclassification. To solve this problem, a new sea ice type concentration (SITC) algorithm from microwave observations (SITCAM) is proposed in this study. It builds upon a previous algorithm, namely ECICE, but improves from two perspectives. Firstly, a new cost function is employed, with weights indicating the separation efficiencies of microwave parameters. Secondly, a pre-classification scheme is incorporated to account for the bimodal distributions in microwave characteristics. With SITCAM, daily Arctic SITCs are retrieved for the winters of 2002–2011 using passive (AMSR-E) and active (QuikSCAT and ASCAT) microwave data. The results are compared with a sea ice age product (SIA) and evaluated with ice type samples and SAR images. Overall, SITCAM performs well on mitigating the misclassifications induced by the aforementioned factors. The Arctic MYI area agrees well with that from SIA. Compared to ECICE, the retrieval accuracy for MYI and FYI samples increases to 96% and 90%, respectively (increasing by 5% and 15%, respectively), in SITCAM. The bias in MYI concentration between the SITC retrievals and SAR-based results has reduced from 15% to 4%. Furthermore, instead of being limited to specific observations (e.g., Ku-band scatterometer data), SITCAM performs well with various combinations of microwave data, even solely passive microwave data. This universality allows for a long-term record of SITC, which enables the potential of dating SITC back to late 1970s.

How to cite: Ye, Y., Luo, Y., Shokr, M., Chen, Z., and Cheng, X.: A New Sea Ice Type Concentration Retrieval Algorithm from Microwave Remote Sensing Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20571, https://doi.org/10.5194/egusphere-egu24-20571, 2024.