Multiyear Sea Ice Research Articles

Benefits of sea ice initialization for the interannual-to-decadal climate prediction skill in the Arctic in EC-Earth3

Abstract. A substantial part of Arctic climate predictability at interannual timescales stems from the knowledge of the initial sea ice conditions. Among all sea ice properties, its volume, which is a product of sea ice concentration (SIC) and thickness (SIT), is the most responsive parameter to climate change. However, the majority of climate prediction systems are only assimilating the observed SIC due to lack of long-term reliable global observation of SIT. In this study, the EC-Earth3 Climate Prediction System with anomaly initialization to ocean, SIC and SIT states is developed. In order to evaluate the regional benefits of specific initialized variables, three sets of retrospective ensemble prediction experiments are performed with different initialization strategies: ocean only; ocean plus SIC; and ocean plus SIC and SIT initialization. In the Atlantic Arctic, the Greenland–Iceland–Norway (GIN) and Barents seas are the two most skilful regions in SIC prediction for up to 5–6 lead years with ocean initialization; there are re-emerging skills for SIC in the Barents and Kara seas in lead years 7–9 coinciding with improved skills of sea surface temperature (SST), reflecting the impact of SIC initialization on ocean–atmosphere interactions for interannual-to-decadal timescales. For the year 2–9 average, the region with significant skill for SIT is confined to the central Arctic Ocean, covered by multi-year sea ice (CAO-MYI). Winter preconditioning with SIT initialization increases the skill for September SIC in the eastern Arctic (e.g. Kara, Laptev and East Siberian seas) and in turn improve the skill of air surface temperature locally and further expanded over land. SIT initialization outperforms the other initialization methods in improving SIT prediction in the Pacific Arctic (e.g. East Siberian and Beaufort seas) in the first few lead years. Our results suggest that as the climate warming continues and the central Arctic Ocean might become seasonal ice free in the future, the controlling mechanism for decadal predictability may thus shift from sea ice volume to ocean-driven processes.

Impact of model resolution on the representation of the wind field along Nares Strait

Nares Strait is a major pathway along which multi-year sea ice leaves the Arctic, an ice class that has seen a recent dramatic reduction in extent. The winds that blow along the strait play an important role in modulating this ice export as well as in establishing the Arctic’s largest and most productive polynya, the North Water, that forms at its southern terminus. However, its remote location has limited our knowledge of the winds along the strait. Here we use automatic weather station data from Hans Island, in the middle of the strait, to assess the ability of a set of atmospheric renalyses and analyses with a common lineage but with varying horizontal resolution to represent the variability in the wind field. We find that the flow is highly bidirectional, consistent with topographic channeling, with the highest wind speeds from the north and that a model resolution of ~ 9 km is required to capture the observed variability. The wind field at Hans Island is also found to be representative of variability in the flow along much of Nares Strait.

Circumpolar phylogeography and demographic history of beluga whales reflect past climatic fluctuations.

Several Arctic marine mammal species are predicted to be negatively impacted by rapid sea ice loss associated with ongoing ocean warming. However, consequences for Arctic whales remain uncertain. To investigate how Arctic whales responded to past climatic fluctuations, we analysed 206 mitochondrial genomes from beluga whales (Delphinapterus leucas) sampled across their circumpolar range, and four nuclear genomes, covering both the Atlantic and the Pacific Arctic region. We found four well-differentiated mitochondrial lineages, which were established before the onset of the last glacial expansion ~110 thousand years ago. Our findings suggested these lineages diverged in allopatry, reflecting isolation of populations during glacial periods when the Arctic sea-shelf was covered by multiyear sea ice. Subsequent population expansion and secondary contact between the Atlantic and Pacific Oceans shaped the current geographic distribution of lineages, and may have facilitated mitochondrial introgression. Our demographic reconstructions based on both mitochondrial and nuclear genomes showed markedly lower population sizes during the Last Glacial Maximum (LGM) compared to the preceding Eemian and current Holocene interglacial periods. Habitat modelling similarly revealed less suitable habitat during the LGM (glacial) than at present (interglacial). Together, our findings suggested the association between climate, population size, and available habitat in belugas. Forecasts for year 2100 showed that beluga habitat will decrease and shift northwards as oceans continue to warm, putatively leading to population declines in some beluga populations. Finally, we identified vulnerable populations which, if extirpated as a consequence of ocean warming, will lead to a substantial decline of species-wide haplotype diversity.

The triggers of the disaggregation of Voyeykov Ice Shelf (2007), Wilkes Land, East Antarctica, and its subsequent evolution

AbstractThe weakening and/or removal of floating ice shelves in Antarctica can induce inland ice flow acceleration. Numerical modelling suggests these processes will play an important role in Antarctica's future sea-level contribution, but our understanding of the mechanisms that lead to ice tongue/shelf collapse is incomplete and largely based on observations from the Antarctic Peninsula and West Antarctica. Here, we use remote sensing of structural glaciology and ice velocity from 2001 to 2020 and analyse potential ocean-climate forcings to identify mechanisms that triggered the rapid disintegration of ~2445 km2of ice mélange and part of the Voyeykov Ice Shelf in Wilkes Land, East Antarctica between 27 March and 28 May 2007. Results show disaggregation was pre-conditioned by weakening of the ice tongue's structural integrity and was triggered by mélange removal driven by a regional atmospheric circulation anomaly and a less extensive latent-heat polynya. Disaggregation did not induce inland ice flow acceleration, but our observations highlight an important mechanism through which floating termini can be removed, whereby the break-out of mélange and multiyear landfast sea ice triggers disaggregation of a structurally-weak ice shelf. These observations highlight the need for numerical ice-sheet models to account for interactions between sea-ice, mélange and ice shelves.

Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data

Snow depth over sea ice is an essential variable for understanding the Arctic energy budget. In this study, we evaluate snow depth over Arctic sea ice during 1993–2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) against recent satellite retrievals. The CMIP6 models capture some aspects of the observed snow depth climatology and variability. The observed variability lies in the middle of the models’ simulations. All the models show negative trends of snow depth during 1993–2014. However, substantial spatiotemporal discrepancies are identified. Compared to the observation, most models have late seasonal maximum snow depth (by two months), remarkably thinner snow for the seasonal minimum, an incorrect transition from the growth to decay period, and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice. Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic. Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099. Under the SSP5-8.5 scenario, the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January. Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution, the inclusion of a high-top atmospheric model, and biogeochemistry processes are important factors for snow depth simulation.

Anomalous collapses of Nares Strait ice arches leads to enhanced export of Arctic sea ice

The ice arches that usually develop at the northern and southern ends of Nares Strait play an important role in modulating the export of Arctic Ocean multi-year sea ice. The Arctic Ocean is evolving towards an ice pack that is younger, thinner, and more mobile and the fate of its multi-year ice is becoming of increasing interest. Here, we use sea ice motion retrievals from Sentinel-1 imagery to report on the recent behavior of these ice arches and the associated ice fluxes. We show that the duration of arch formation has decreased over the past 20 years, while the ice area and volume fluxes along Nares Strait have both increased. These results suggest that a transition is underway towards a state where the formation of these arches will become atypical with a concomitant increase in the export of multi-year ice accelerating the transition towards a younger and thinner Arctic ice pack.

Erratum to: Arctic multiyear sea ice variability observed from satellites: a review

Erratum to: Arctic multiyear sea ice variability observed from satellites: a review

Fatty acids and stable isotope signatures of first-year and multiyear sea ice in the Canadian High Arctic

Ice algae are critical components to the lipid-driven Arctic marine food web, particularly early in the spring. As little is known about these communities in multiyear ice (MYI), we aimed to provide a baseline of fatty acid (FA) and stable isotope signatures of sea-ice communities in MYI from the Lincoln Sea and compare these biomarkers to first-year ice (FYI). Significant differences in the relative proportions of approximately 25% of the identified FAs and significantly higher nitrogen stable isotope values (δ15N) in bottom-ice samples of FYI (δ15N = 6.4 ± 0.7%) compared to MYI (δ15N = 5.0 ± 0.4%) reflect different community compositions in the two ice types. Yet, the relative proportion of diatom- and dinoflagellate-associated FAs, as well as their bulk and most of the FA-specific carbon stable isotope compositions (δ13C) were not significantly different between bottom FYI (bulk δ13C: –28.4% to –26.7%, FA average δ13C: –34.4% to –31.7%) and MYI (bulk δ13C: –27.6% to –27.2%, FA average δ13C: –33.6% to –31.9%), suggesting at least partly overlapping community structures and similar biochemical processes within the ice. Diatom-associated FAs contributed, on average, 28% and 25% to the total FA content of bottom FYI and MYI, respectively, indicating that diatoms play a central role in structuring sea-ice communities in the Lincoln Sea. The differences in FA signatures of FYI and MYI support the view that different ice types harbor different inhabitants and that the loss of Arctic MYI will impact complex food web interactions with ice-associated ecosystems. Comparable nutritional quality of FAs, however, as indicated by similar average levels of polyunsaturated FAs in bottom FYI (33%) and MYI (28%), could help to ensure growth and reproduction of ice-associated grazers despite the shift from a MYI to FYI-dominated sea-ice cover with ongoing climate warming.

Incidence Angle Dependence of Texture Statistics From Sentinel-1 HH-Polarization Images of Winter Arctic Sea Ice

The proliferation of synthetic aperture radar (SAR) imagery, its accessibility in open platforms like Google Earth Engine, and the development of automated classification and geophysical information extraction algorithms have prompted the need for understanding the role of incidence angle (IA) on radar scattering mechanism, backscatter intensity, and classification accuracy. This letter demonstrates the dependence of image texture parameters on SAR IA, using Arctic landfast sea ice samples extracted from C-band frequency Sentinel-1 SAR scenes collected during the winter period. Gray-level cooccurrence matrix (GLCM) derived texture parameters, and occurrence texture parameters, derived from undeformed first-year sea ice and multi-year sea ice, which are dominated by surface and volume scattering mechanisms, respectively, were analyzed. All GLCM texture parameters were found to be dependent on IA, highlighting the need for consideration of angular dependence in texture parameters, particularly in the development of image classification and inversion algorithms utilizing them. Occurrence texture parameters showed negligible influence by IA; however, feature discrimination capability was also lost. Some GLCM parameters had similar angular dependencies for both sea ice types, suggesting that, in some cases, global image normalization approaches for texture may be applied to account for the IA effect.

Local-scale variability of snow density on Arctic sea ice

Abstract. Local-scale variations in snow density and layering on Arctic sea ice were characterized using a combination of traditional snow pit and SnowMicroPen (SMP) measurements. In total, 14 sites were evaluated within the Canadian Arctic Archipelago and Arctic Ocean on both first-year (FYI) and multi-year (MYI) sea ice. Sites contained multiple snow pits with coincident SMP profiles as well as unidirectional SMP transects. An existing SMP density model was recalibrated using manual density cutter measurements (n=186) to identify best-fit parameters for the observed conditions. Cross-validation of the revised SMP model showed errors comparable to the expected baseline for manual density measurements (RMSE = 34 kg m−3 or 10.9 %) and strong retrieval skill (R2=0.78). The density model was then applied to SMP transect measurements to characterize variations at spatial scales of up to 100 m. A supervised classification trained on snow pit stratigraphy allowed separation of the SMP density estimates by layer type. The resulting dataset contains 58 882 layer-classified estimates of snow density on sea ice representing 147 m of vertical variation and equivalent to more than 600 individual snow pits. An average bulk density of 310 kg m−3 was estimated with clear separation between FYI and MYI environments. Lower densities on MYI (277 kg m−3) corresponded with increased depth hoar composition (49.2 %), in strong contrast to composition of the thin FYI snowpack (19.8 %). Spatial auto-correlation analysis showed layered composition on FYI snowpack to persist over long distances while composition on MYI rapidly decorrelated at distances less than 16 m. Application of the SMP profiles to determine propagation bias in radar altimetry showed the potential errors of 0.5 cm when climatology is used over known snow density.

The 2017 Reversal of the Beaufort Gyre: Can Dynamic Thickening of a Seasonal Ice Cover During a Reversal Limit Summer Ice Melt in the Beaufort Sea?

AbstractDuring winter 2017, the semipermanent Beaufort High collapsed and the anticyclonic Beaufort Gyre reversed. The reversal drove eastward ice motion through the Western Arctic, causing sea ice to converge against Banks Island, and halted the circulation of multiyear sea ice via the gyre, preventing its replenishment in the Beaufort Sea. Prior to the reversal, an anomalously thin seasonal ice cover had formed in the Beaufort following ice‐free conditions during September 2016. With the onset of the reversal in January 2017, convergence drove uncharacteristic dynamic thickening during winter. By the end of March, despite seasonal ice comprising 97% of the ice cover, the reversal created the thickest, roughest, and most voluminous regional ice cover of the CryoSat‐2 record. Within the Beaufort Sea, previous work has shown that winter ice export can precondition the region for increased summer ice melt, but that a short reversal during April 2013 contributed to a reduction in summer ice loss. Hence, the deformed ice cover at the end of winter 2017 could be expected to limit summer melt. In spite of this, the Beaufort ice cover fell to its fourth lowest September area as the gyre re‐established during April and divergent ice drift broke up the pack, negating the reversal's earlier preconditioning. Our work highlights that dynamic winter thickening of a regional sea ice cover, for instance during a gyre reversal, offers the potential to limit summer ice loss, but that dynamic forcing during spring dictates whether this conditioning carries through to the melt season.

Unusual drift behaviour of multi-year sea ice in the Beaufort Sea during summer 2018

In summer 2018, thick sea ice blocked the mouth of the Amundsen Gulf (AG), Canada, obstructing shipping through the North-west Passage. This study analysed multi-year ice motion to investigate the source of this thick ice and the reasons for its unusual movement. For this purpose, a daily multi-year ice distribution product was generated by ice tracking using gridded daily sea-ice velocities (2003–2018) derived from the AMSR-E and AMSR-2 data. From autumn 2017 to summer 2018, the area of multi-year ice extended westward to the Beaufort Sea and then migrated towards the AG mouth. The primary cause of the unusual ice cover was anomalous AG-ward wind in September 2018. It is known that multi-year ice has become increasingly moveable over the past decades, as indicated by the increasing wind factor (i.e., ratio of ice-drift speed and wind speed), but the unusual ice motion in the summer of 2018 cannot be explainable by the wind factor alone. Accurately, predicting monthly wind and monitoring old thick ice will reduce the risk posed by thick Arctic sea ice to shipping.

Transient benefits of climate change for a high-Arctic polar bear (Ursus maritimus) subpopulation.

Kane Basin (KB) is one of the world's most northerly polar bear (Ursus maritimus) subpopulations, where bears have historically inhabited a mix of thick multiyear and annual sea ice year-round. Currently, KB is transitioning to a seasonally ice-free region because of climate change. This ecological shift has been hypothesized to benefit polar bears in the near-term due to thinner ice with increased biological production, although this has not been demonstrated empirically. We assess sea-ice changes in KB together with changes in polar bear movements, seasonal ranges, body condition, and reproductive metrics obtained from capture-recapture (physical and genetic) and satellite telemetry studies during two study periods (1993-1997 and 2012-2016). The annual cycle of sea-ice habitat in KB shifted from a year-round ice platform (~50% coverage in summer) in the 1990s to nearly complete melt-out in summer (<5% coverage) in the 2010s. The mean duration between sea-ice retreat and advance increased from 109 to 160days (p=.004). Between the 1990s and 2010s, adult female (AF) seasonal ranges more than doubled in spring and summer and were significantly larger in all months. Body condition scores improved for all ages and both sexes. Mean litter sizes of cubs-of-the-year (C0s) and yearlings (C1s), and the number of C1s per AF, did not change between decades. The date of spring sea-ice retreat in the previous year was positively correlated with C1 litter size, suggesting smaller litters following years with earlier sea-ice breakup. Our study provides evidence for range expansion, improved body condition, and stable reproductive performance in the KB polar bear subpopulation. These changes, together with a likely increasing subpopulation abundance, may reflect the shift from thick, multiyear ice to thinner, seasonal ice with higher biological productivity. The duration of these benefits is unknown because, under unmitigated climate change, continued sea-ice loss is expected to eventually have negative demographic and ecological effects on all polar bears.

Seasonal evolution of L-band SAR backscatter over landfast Arctic sea ice

We construct and present the first baseline, time series evolution of L-band SAR microwave backscatter (σ0HH) for landfast Arctic first-year (FYI) and multi-year (MYI) sea ice from ALOS PALSAR. We compare the winter to freeze-up seasonal L-band σ0HH signatures with C-band RADARSAT-2 SAR imagery and Ku-band QuikSCAT scatterometer data. We also explored the utility of L-band σ0HH to detect FYI and MYI melt onset dates. For both ice types, L-band exhibited a similar σ0HH evolution to C- and Ku-bands. A rise in L-band σ0HH was observed from winter to melt onset, however, with a lower magnitude attributed to the larger penetration of L-band microwaves through the snow-covered sea ice medium. Over FYI, L-band σ0HH exhibited the most robust response and greater diversity in melt onset signature, compared to C- and Ku-bands. Over MYI, L-band σ0HH declined during the winter to melt onset transition contrasting the C- and Ku-band evolution of σ0HH during melt onset. Although, a distinct L-band σ0HH response was not found during pond onset, a very strong σ0HH response was found during sea ice break-up, which could operationally be utilized to identify sea ice break-up timing. During freeze-up, L-band σ0HH showed greater diversity compared to C- and Ku-bands. Our study also found that, L-band detected melt onset dates were up to 6 days later than C- and Ku-band detected dates, for both ice types. The melt response was the strongest at L-band for FYI, where C-band detected a robust melt onset date for MYI. Therefore, for operational sea ice monitoring, L-band suits better for FYI, whereas C-band is still a better choice for MYI. In the warming Arctic, where FYI has become the dominant ice type, L-band demonstrates promise to be the optimal choice for sea ice operational monitoring with high spatiotemporal data acquisition from existing, upcoming and proposed L-band SAR missions.

Impact of Synthetic Arctic Argo-Type Floats in a Coupled Ocean–Sea Ice State Estimation Framework

AbstractThe lack of continuous spatial and temporal sampling of hydrographic measurements in large parts of the Arctic Ocean remains a major obstacle for quantifying mean state and variability of the Arctic Ocean circulation. This shortcoming motivates an assessment of the utility of Argo-type floats, the challenges of deploying such floats due to the presence of sea ice, and the implications of extended times of no surfacing on hydrographic inferences. Within the framework of an Arctic coupled ocean–sea ice state estimate that is constrained to available satellite and in situ observations, we establish metrics for quantifying the usefulness of such floats. The likelihood of float surfacing strongly correlates with the annual sea ice minimum cover. Within the float lifetime of 4–5 years, surfacing frequency ranges from 10–100 days in seasonally sea ice–covered regions to 1–3 years in multiyear sea ice–covered regions. The longer the float drifts under ice without surfacing, the larger the uncertainty in its position, which translates into larger uncertainties in hydrographic measurements. Below the mixed layer, especially in the western Arctic, normalized errors remain below 1, suggesting that measurements along a path whose only known positions are the beginning and end points can help constrain numerical models and reduce hydrographic uncertainties. The error assessment presented is a first step in the development of quantitative methods for guiding the design of observing networks. These results can and should be used to inform a float network design with suggested locations of float deployment and associated expected hydrographic uncertainties.

Characterizing winter landfast sea-ice surface roughness in the Canadian Arctic Archipelago using Sentinel-1 synthetic aperture radar and the Multi-angle Imaging SpectroRadiometer

AbstractTwo satellite datasets are used to characterize winter landfast first-year sea-ice (FYI), deformed FYI (DFYI) and multiyear sea-ice (MYI) roughness in the Canadian Arctic Archipelago (CAA): (1) optical Multi-angle Imaging SpectroRadiometer (MISR) and (2) synthetic aperture radar Sentinel-1. The Normalized Difference Angular Index (NDAI) roughness proxy derived from MISR, and backscatter from Sentinel-1 are intercompared. NDAI and backscatter are also compared to surface roughness derived from an airborne LiDAR track covering a subset of FYI and MYI (no DFYI). Overall, NDAI and backscatter are significantly positively correlated when all ice type samples are considered. When individual ice types are evaluated, NDAI and backscatter are only significantly correlated for DFYI. Both NDAI and backscatter are correlated with LiDAR-derived roughness (r= 0.71 andr= 0.74, respectively). The relationship between NDAI and roughness is greater for MYI than FYI, whereas for backscatter and ice roughness, the relationship is greater for FYI than MYI. Linear regression models are created for the estimation of FYI and MYI roughness from NDAI, and FYI roughness from backscatter. Results suggest that using a combination of Sentinel-1 backscatter for FYI and MISR NDAI for MYI may be optimal for mapping winter sea-ice roughness in the CAA.

Monitoring evolution of melt ponds on first-year and multiyear sea ice in the Canadian Arctic Archipelago with optical satellite data

AbstractThe evolution of melt ponds on Arctic sea ice in summer is one of the main factors that affect sea-ice albedo and hence the polar climate system. Due to the different spectral properties of open water, melt pond and sea ice, the melt pond fraction (MPF) can be retrieved using a fully constrained least-squares algorithm, which shows a high accuracy with root mean square error ~0.06 based on the validation experiment using WorldView-2 image. In this study, the evolution of ponds on first-year and multiyear ice in the Canadian Arctic Archipelago was compared based on Sentinel-2 and Landsat 8 images. The relationships of pond coverage with air temperature and albedo were analysed. The results show that the pond coverage on first-year ice changed dramatically with seasonal maximum of 54%, whereas that on multiyear ice changed relatively flat with only 30% during the entire melting period. During the stage of pond formation, the ponds expanded rapidly when the temperature increased to over 0°C for three consecutive days. Sea-ice albedo shows a significantly negative correlation (R= −1) with the MPF in melt season and increases gradually with the refreezing of ponds and sea ice.

Arctic multiyear sea ice variability observed from satellites: a review

In comparison with seasonal sea ice (first-year ice, FY ice), multiyear (MY) sea ice is thicker and has more opportunity to survive through the summer melting seasons. Therefore, the variability of wintertime MY ice plays a vital role in modulating the variations in the Arctic sea ice minimum extent during the following summer. As a response, the ice-ocean-atmosphere interactions may be significantly affected by the variations in the MY ice cover. Satellite observations are characterized by their capability to capture the spatiotemporal changes of Arctic sea ice. During the recent decades, many active and passive sensors onboard a variety of satellites (QuikSCAT, ASCAT, SSMIS, ICESat, CryoSat-2, etc.) have been used to monitor the dramatic loss of Arctic MY ice. The main objective of this study is to outline the advances and remaining challenges in monitoring the MY ice changes through the utilization of multiple satellite observations. We summarize the primary satellite data sources that are used to identify MY ice. The methodology to classify MY ice and derive MY ice concentration is reviewed. The interannual variability and trends in the MY ice time series in terms of coverage, thickness, volume, and age composition are evaluated. The potential causes associated with the observed Arctic MY ice loss are outlined, which are primarily related to the export and melting mechanisms. In addition, the causes to the MY ice depletion from the perspective of the oceanic water inflow from Pacific and Atlantic Oceans and the water vapor intrusion, as well as the roles of synoptic weather, are analyzed. The remaining challenges and possible upcoming research subjects in detecting the rapidly changing Arctic MY ice using the combined application of multisource remote sensing techniques are discussed. Moreover, some suggestions for the future application of satellite observations on the investigations of MY ice cover changes are proposed.

Evaluating the impact of blowing-snow sea salt aerosol on springtime BrO and O&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; in the Arctic

Abstract. We use the GEOS-Chem chemical transport model to examine the influence of bromine release from blowing-snow sea salt aerosol (SSA) on springtime bromine activation and O3 depletion events (ODEs) in the Arctic lower troposphere. We evaluate our simulation against observations of tropospheric BrO vertical column densities (VCDtropo) from the GOME-2 (second Global Ozone Monitoring Experiment) and Ozone Monitoring Instrument (OMI) spaceborne instruments for 3 years (2007–2009), as well as against surface observations of O3. We conduct a simulation with blowing-snow SSA emissions from first-year sea ice (FYI; with a surface snow salinity of 0.1 psu) and multi-year sea ice (MYI; with a surface snow salinity of 0.05 psu), assuming a factor of 5 bromide enrichment of surface snow relative to seawater. This simulation captures the magnitude of observed March–April GOME-2 and OMI VCDtropo to within 17 %, as well as their spatiotemporal variability (r=0.76–0.85). Many of the large-scale bromine explosions are successfully reproduced, with the exception of events in May, which are absent or systematically underpredicted in the model. If we assume a lower salinity on MYI (0.01 psu), some of the bromine explosions events observed over MYI are not captured, suggesting that blowing snow over MYI is an important source of bromine activation. We find that the modeled atmospheric deposition onto snow-covered sea ice becomes highly enriched in bromide, increasing from enrichment factors of ∼5 in September–February to 10–60 in May, consistent with composition observations of freshly fallen snow. We propose that this progressive enrichment in deposition could enable blowing-snow-induced halogen activation to propagate into May and might explain our late-spring underestimate in VCDtropo. We estimate that the atmospheric deposition of SSA could increase snow salinity by up to 0.04 psu between February and April, which could be an important source of salinity for surface snow on MYI as well as FYI covered by deep snowpack. Inclusion of halogen release from blowing-snow SSA in our simulations decreases monthly mean Arctic surface O3 by 4–8 ppbv (15 %–30 %) in March and 8–14 ppbv (30 %–40 %) in April. We reproduce a transport event of depleted O3 Arctic air down to 40∘ N observed at many sub-Arctic surface sites in early April 2007. While our simulation captures 25 %–40 % of the ODEs observed at coastal Arctic surface sites, it underestimates the magnitude of many of these events and entirely misses 60 %–75 % of ODEs. This difficulty in reproducing observed surface ODEs could be related to the coarse horizontal resolution of the model, the known biases in simulating Arctic boundary layer exchange processes, the lack of detailed chlorine chemistry, and/or the fact that we did not include direct halogen activation by snowpack chemistry.

Recent Decrease of Summer Sea Ice in the Weddell Sea, Antarctica

AbstractIn Austral summer 2016/2017, the sea ice extent (SIE) in the Weddell Sea dropped to a near‐record value in the satellite era (1.88 × 106 km2), a large negative seasonal anomaly that persisted in an unprecedented fashion for the following three summers. Various atmospheric and oceanic factors played a part in the change. Ice loss started in September 2016 when the northern Weddell Sea experienced westerly winds of record strength, advecting multiyear sea ice from the region. In late 2016, a polynya over Maud Rise contributed to low SIE over the eastern Weddell Sea. With extensive areas of open water early in the summer, upper ocean temperatures increased by ~0.5°C, with the anomalies persisting in subsequent years. The reappearance of the Maud Rise polynya in 2017, high ocean temperatures, and storms of record depth kept the summer SIE low.