Seasonal Ice Research Articles

Accelerated Sea Ice Loss from Late Summer Cyclones in the New Arctic

Abstract Synoptic-scale cyclones in the Arctic are an important source of short-term sea ice variability during the melt season. This study examines whether recent changes to the Arctic environment have made Arctic cyclones during the summer months more destructive to sea ice on short time scales. We compare the 1–7-day changes in sea ice area and thickness following days in each month with and without cyclones from two decades: 1991–2000 and 2009–18. Only in August do cyclones locally accelerate seasonal sea ice loss on average, and the ability of August cyclones to accelerate ice loss has become more pronounced in the recent decade. The recent increase in ice loss following August cyclones is most evident in the Amerasian Arctic (140°E–120°W), where reanalyses indicate that the average upper-ocean temperature has increased by 0.2°–0.8°C and the average ice thickness has decreased by almost 1 m between the two decades. Such changes promote cyclone-induced ocean mixing and sea ice divergence that locally increase the likelihood for rapid ice loss near cyclones. In contrast, June cyclones in both decades locally slow down seasonal sea ice loss. Moreover, the 7-day sea ice loss in June has increased from the early to the recent decade by 67% more in the absence of cyclones than in the presence of cyclones. The largest increases in June ice loss occur in the Eurasian Arctic (0°–140°E), where substantial reductions in average surface albedo in the recent decade have allowed more of the abundant insolation in the absence of cyclones to be absorbed at the sea surface. Significance Statement This study determines whether Arctic storms during summer have become more destructive to sea ice in recent years. In comparing storms from two periods (1991–2000 vs 2009–18), we find that only storms in August have become more destructive to sea ice in the recent period, because of warmer upper-ocean temperatures and thinner ice, which strong winds move around more easily. In June, clear-sky conditions have become more destructive to sea ice in recent years because declining ice cover has allowed more sunlight to be absorbed at the sea surface, favoring further ice melt. These results suggest that sunny conditions in June followed by stormy conditions in August could cause the first ice-free summer in the Arctic.

The Role of Summer Snowstorms on Seasonal Arctic Sea Ice Loss

AbstractIn the Arctic, short‐lived summer snowstorms can provide snow cover that can increase surface reflectivity and heat capacity. Despite their potential importance, little research has been done to understand the impact of summer snowstorms on basin‐scale Arctic sea ice cover. Our observational analysis shows that a summer snowstorm event is accompanied by cyclonic ice drift, increases in surface albedo and surface air cooling that can persist for up to ∼2 weeks, dampening sea ice loss. Specifically, multiple snowstorm events in a summer, on average, results in net increase in sea ice extent of ∼0.2 × 106 km2 by early September. Experiments with a sophisticated ice‐ocean model framework indicate that the initial expansion of sea ice extent is driven by cyclonic wind‐driven ice drifts driving sea ice southwards and increasing albedo around the summer ice edge, however the thermal effects from the associated snowfall and atmospheric conditions result in a stronger overall impact on basin‐averaged sea ice extent at seasonal scales. Additional model experiments were carried out to isolate the physical processes contributing to the thermal response of Arctic sea ice to summer snowstorms. Our results show the impact of surface air cooling on sea ice extent is about 3.5 times larger than the snowfall/albedo response. However, our simulated albedo response is weaker than the observed response, likely due to the negligible difference in surface albedo between old snow and freshly fallen snow—a limiting factor in our analysis and a topic worthy of future focus.

Anthropogenic and natural hydrocarbons in water and sediments of the Kara Sea.

The results on the content and composition of aliphatic (AHСs) and polycyclic aromatic hydrocarbons (PAHs) at the geochemical barrier between the Kara Sea and the Ob and Yenisei Rivers are discussed in comparison with those in the mouth areas of the Lena, Khatanga, Indigirka and Kolyma. It has been established that hydrocarbon concentrations sharply decrease in the river-sea mixing zones, and their composition, and the ratio of their dissolved and suspended forms change. Besides, the research season plays a great role, as the highest content of hydrocarbons and particulate matter was found in the Ob Gulf during the flood, when the concentrations of AHCs in surface waters reached 325μg/L, PAHs -15ng/L, particulate matter-15.5mg/L. In the Kara Sea itself, AHC concentrations increased on average from 20 to 59μg/L, that is most likely associated with the melting of seasonal ice and floods. Anthropogenic influence was found in river waters, where the proportion of naphthalenes, which marks oil products, and pyrene, which marks pyrogenic PAHs, is increased. In the Ob Gulf is linked to an increase in navigation along the Northern Sea Route and the functioning of the port of Sabetta. In the mouth area of the Yenisei, the concentrations of both AHC and PAH in surface waters and sediments varied in a smaller range than in the mouth area of the Ob, which is due to the nature of the rocks that make up the catchment areas of these rivers, as well as the regulation of the Yenisei runoff. The hydrological features of the estuarine areas can lead to increased AHC concentrations (the mouth of the Khatanga, up to 189μg/L, 2.6μg/mg SPM). The minimum AHC content in SPM and sediments in the river transects was established in the East Siberian rivers (Indigirka, Kolyma), associated with the decreasing productivity in waters from the Western Arctic seas to the Eastern.

The Interannual Variability of Sea Ice Area, Thickness, and Volume in the Southern Sea of Okhotsk and Its Likely Factors

AbstractThe lowest latitude sea ice in the world (excluding coastal freezing) is in the southern Sea of Okhotsk (south of 46°N), where it has significant impacts on freshwater input and primary production. This region is subject to climate change, and accordingly the monitoring of sea ice conditions is important. However, the interannual variability of the region's sea ice is poorly understood due to its logistical challenges. Sea ice observations have been conducted in this region every winter for the period 1996–2020. The interannual variability of the ice conditions and the likely factors responsible for it were investigated using visual observations following the international ASPeCt protocol, combined with satellite SSM/I‐SSMIS ice concentration data (1988–2020). AMSR‐derived ice drift data sets and ERA5 meteorological reanalysis data sets were also analyzed to examine the effects of dynamic and thermodynamic processes. Our analysis revealed that (a) sea ice area in this region varies differently from that in the central and northern Sea of Okhotsk, where decreasing trends are reported, (b) sea ice volume has remarkable interannual variation and the peaks appeared much to more affected by dynamically deformed ice than freezing conditions, and (c) prominently deformed ice can be explained by taking shear components into account based on sea ice rheology. These results suggest the importance of including the proper sea ice rheology in numerical sea ice models to reproduce the realistic sea ice volume and deformation processes, for all seasonal ice zones.

Feeding Ecology of Odontaster validus under Different Environmental Conditions in the West Antarctic Peninsula.

To study how Odontaster validus can influence the spatial structure of Antarctic benthic communities and how they respond to disturbance, it is necessary to assess potential dietary shifts in different habitats. We investigated the diets of O. validus from Maxwell Bay and South Bay in the West Antarctic Peninsula. A multifaceted approach was applied including in situ observations of cardiac stomach everted contents, isotopic niche, and trophic diversity metrics. Results confirm the flexible foraging strategy of this species under markedly different environmental conditions, suggesting plasticity in resource use. The data also showed evidence of isotopic niche expansion, high δ15N values, and Nacella concinna as a common food item for individuals inhabiting a site with low seasonal sea ice (Ardley Cove), which could have significant ecological implications such as new trophic linkages within the Antarctic benthic community. These results highlight the importance of considering trophic changes of key species to their environment as multiple ecological factors can vary as a function of climatic conditions.

The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment

Abstract. While advanced computational capabilities have enabled the development of complex ocean general circulation models (OGCMs) for marginal seas, systematic comparisons of regional ocean models and their setups are still rare. The Baltic Sea Model Intercomparison Project (BMIP), introduced herein, was therefore established as a platform for the scientific analysis and systematic comparison of Baltic Sea models. The inclusion of a physically consistent regional reanalysis data set for the period 1961–2018 allows for standardized meteorological forcing and river runoff. Protocols to harmonize model outputs and analyses are provided as well. An analysis of six simulations performed with four regional OGCMs differing in their resolution, grid coordinates, and numerical methods was carried out to explore intermodel differences despite harmonized forcing. Uncertainties in the modeled surface temperatures were shown to be larger at extreme than at moderate temperatures. In addition, a roughly linear increase in the temperature spread with increasing water depth was determined and indicated larger uncertainties in the near-bottom layer. On the seasonal scale, the model spread was larger in summer than in winter, likely due to differences in the models' thermocline dynamics. In winter, stronger air–sea heat fluxes and vigorous convective and wind mixing reduced the intermodel spread. Uncertainties were likewise reduced near the coasts, where the impact of meteorological forcing was stronger. The uncertainties were highest in the Bothnian Sea and Bothnian Bay, attributable to the differences between the models in the seasonal cycles of sea ice triggered by the ice–albedo feedback. However, despite the large spreads in the mean climatologies, high interannual correlations between the sea surface temperatures (SSTs) of all models and data derived from a satellite product were determined. The exceptions were the Bothnian Sea and Bothnian Bay, where the correlation dropped significantly, likely related to the effect of sea ice on air–sea heat exchange. The spread of water salinity across the models is generally larger compared to water temperature, which is most obvious in the long-term time series of deepwater salinity. The inflow dynamics of saline water from the North Sea is covered well by most models, but the magnitude, as inferred from salinity, differs as much as the simulated mean salinity of deepwater. Marine heat waves (MHWs), coastal upwelling, and stratification were also assessed. In all models, MHWs were more frequent in shallow areas and in regions with seasonal ice cover. An increase in the frequency (regionally varying between ∼50 % and 250 %) and duration (50 %–150 %) of MHWs during the last 3 decades in all models was found as well. The uncertainties were highest in the Bothnian Bay, likely due to the different trends in sea ice presence. All but one of the analyzed models overestimated upwelling frequencies along the Swedish coast, the Gulf of Finland, and around Gotland, while they underestimated upwelling in the Gulf of Riga. The onset and seasonal cycle of thermal stratification likewise differed among the models. Compared to observation-based estimates, in all models the thermocline in early spring was too deep, whereas a good match was obtained in June when the thermocline intensifies.

Rates and timing of chlorophyll-aincreases and related environmental variables in global temperate and cold-temperate lakes

Abstract. Lakes are key ecosystems within the global biogeosphere. However, the environmental controls on the biological productivity of lakes – including surface temperature, ice phenology, nutrient loads, and mixing regime – are increasingly altered by climate warming and land-use changes. To better characterize global trends in lake productivity, we assembled a dataset on chlorophyll-a concentrations as well as associated water quality parameters and surface solar radiation for temperate and cold-temperate lakes experiencing seasonal ice cover. We developed a method to identify periods of rapid net increase of in situ chlorophyll-a concentrations from time series data and applied it to data collected between 1964 and 2019 across 343 lakes located north of 40∘. The data show that the spring chlorophyll-a increase periods have been occurring earlier in the year, potentially extending the growing season and increasing the annual productivity of northern lakes. The dataset on chlorophyll-a increase rates and timing can be used to analyze trends and patterns in lake productivity across the northern hemisphere or at smaller, regional scales. We illustrate some trends extracted from the dataset and encourage other researchers to use the open dataset for their own research questions. The PCI dataset and additional data files can be openly accessed at the Federated Research Data Repository at https://doi.org/10.20383/102.0488 (Adams et al., 2021).

A regional-scale approach for modeling primary production and biogenic silica export in the Southern Ocean

Persistent uncertainties in the representations of net primary production (NPP) and silicate in the Southern Ocean have been noted in recent assessments ofthe ocean biogeochemical components of Earth system models (ESMs). Consequently, more mechanistic studies at the regional scale are required. To reduce these uncertainties, we applied a one-dimensional (1D) marine ecosystem model to different bioregions in the Southern Ocean: the Polar Frontal Zone in the Pacific sector, the seasonal sea ice zone in the northwestern Ross Sea, and the inner shelf of Terra Nova Bay. To make the existing ecosystem model applicable to the Southern Ocean, we modified the phytoplankton physiology (stoichiometry depending on species) and the silicate cycle (dissolution rate of biogenic silica (BSi) depending on latitude) in the model. We quantified and compared seasonal variations in several limitation factors of NPP, namely, iron, irradiance, silicate and temperature, in the three regions. The simulation results showed that dissolved iron plays the most significant role in determining the magnitude of NPP and the phytoplankton community structure during summer. Additionally, the modified model successfully reproduced the vertical flux of BSi and particulate organic carbon (POC). The POC export efficiency was high in the inner shelf zone, which had high levels of iron concentration, NPP, and Phaeocystis biomass. In contrast, BSi export occurred most efficiently in the Polar Frontal Zone, where diatoms are dominant, the BSi dissolution rate is low, and NPP is extremely low. Our results from the integrated mechanistic framework at the regional scale demonstrate which specific processes should be urgently included in ESMs for better representation of the biogeochemical dynamics in the Southern Ocean.

The prediction of mid-winter and spring breakups of ice cover on Canadian rivers using a hybrid ontology-based and machine learning model

Mid-winter breakups (MWBs) are an increasingly common event on Canadian rivers resulting in the early breakup of river ice cover, with complex and numerous drivers. This study focuses on the development of an MWB Ontology which allows the key data, events, and relationships in an ice season to be defined and analyzed. The MWB Ontology is applied to a national case study of 54 rivers in Canada. Through assessment of the MWB Ontology with network analysis techniques, a hybrid modelling framework coupling the MWB Ontology with machine learning is developed. The hybrid models produce greatly reduced errors in their forecasts of the timing breakup events, with the best performance being a mean absolute error of 12.47 days for MWBs and 10.68 days for spring breakup. The results demonstrate the utility of the MWB Ontology as a tool for collating data and a means for analysis and forecasting of these events.

Uptake of sympagic organic carbon by the Barents Sea benthos linked to sea ice seasonality

On Arctic shelves, where primary production occurs in both the pelagic and sympagic (ice-associated) habitats, sympagic organic material (OM) can constitute a disproportionate fraction of benthic diets due to higher sinking rates and lower grazing pressure than pelagic OM. Less documented is how sympagic OM assimilation across feeding guilds varies seasonally and in relation to sea ice duation. We therefore investigated the relative abundance of sympagic vs pelagic OM in Barents Sea shelf megabenthos in the summer and winter of 2018 and 2019, from 10 stations where sea ice duration ranged from 0 to 245 days per year. We use highly branched isoprenoids, which are lipid biomarkers produced with distinct molecular structures by diatoms in sea ice and the water column, to determine the ratio of sympagic-to-pelagic OM assimilated by benthic organisms. From 114 samples of 25 taxa analysed, we found that the proportion of sympagic OM assimilated ranged from 0.4% to 95.8% and correlated strongly (r2 = 0.754) with the duration of sea ice cover. The effect of sea ice duration was more evident in fauna collected during summer than winter, indicating that sympagic signals are more evident in the summer than in the winter at higher latitudes. Our data show that sympagic production can supply a high fraction of carbon for Barents Sea benthos, although this is highly variable and likely dependent on availability and patchiness of sympagic OM deposition. These results are comparable to similar studies conducted on benthos in the Pacific Arctic and highlight the variable importance of sympagic OM in the seasonal ice zone of Arctic inflow shelves, which are the Arctic regions with highest rates of sea ice loss.

Comparison of macroalgae meadows in warm Atlantic versus cold Arctic regimes in the high-Arctic Svalbard

A warmer Arctic with less sea ice will likely improve macroalgae growth conditions, but observational data to support this hypothesis are scarce. In this study, we combined hydroacoustic and video inspections to compare the depth of growth, density and thickness of macroalgae (>10 cm) meadows in two contrasting climate regimes in Svalbard 1) the warm, ice free, Atlantic influenced West Spitsbergen and 2) the cold, Arctic and seasonal ice covered East Spitsbergen. Both places had similar insolation and comparable turbidity levels. Macroalgae communities at both places were similar and were formed mainly by common north Atlantic kelp species: Saccharina latissima, Alaria esculenta, Laminaria digitata and L. hyperborea. However, the density of the bottom coverage and thalli condition were strikingly different between the two sites. Algae at the warmer site were intact and fully developed and occupied most of the available hard substrate. At the colder site, only patchy macroalgae canopies were found and most thallies were physically damaged and trimmed at a uniform height due to physical ice scouring. These differences in macroalgal density and thalli condition were only found at depths down to 5 m. Deeper, no distinct differences were observed between the warm and cold sites. Sea urchins were only observed at the warm site, but in few numbers with no visible negative top-down control on macroalgae growth.

Modeling of the thermal regime of rivers subject to seasonal ice cover using data from different sources and temporal resolutions

A comprehensive picture of the spatial and temporal patterns of river thermal regimes requires temperature recorded over continuous long time series and across various environments. Unfortunately, these data are generally scarce in extended areas. In Canada, the first attempt to a general large-scale characterization of river thermal regimes was done using a standardized three-parameter Gaussian function and continuous temperature records collected in 158 Québec rivers. This model provided estimates of the river temperature annual maximum, the date of the annual maximum occurrence and the duration of the warm season, with confidence intervals linked to the duration of the available time series. This resulting thermal map was however limited spatially by the geographical location of the monitoring stations, restricted to the eastern portion of the province. It was also based on relatively short and recent temperature series, with most records shorter than five years and starting after 2010. In this work, we expanded both the space and time spans of the Québec rivers thermal map by adding new temperature data sources, namely satellite thermal data and spot measurements. Satellite data provided thermal information in remote northern regions where in situ data acquisition is difficult, from early 1980s until today. Spot measurements from the Banque de données sur la qualité des milieux aquatiques allowed to add nearly 250 rivers to the Québec thermal regimes characterization, with several stations operating since 1979. These three data sources were combined to characterize Québec rivers thermal regimes in more than 400 rivers and streams, over an extended geographical distribution. Uncertainty brought by the coarser temporal resolution of the spot and combined time series was assessed and found to result in substantially larger confidence intervals on the estimated model parameters, as compared with the confidence intervals obtained when using continuous time series of similar length.

Sea ice fluctuations in the Baffin Bay and the Labrador Sea during glacial abrupt climate changes

Sea ice decline in the North Atlantic and Nordic Seas has been proposed to contribute to the repeated abrupt atmospheric warmings recorded in Greenland ice cores during the last glacial period, known as Dansgaard-Oeschger (D-O) events. However, the understanding of how sea ice changes were coupled with abrupt climate changes during D-O events has remained incomplete due to a lack of suitable high-resolution sea ice proxy records from northwestern North Atlantic regions. Here, we present a subdecadal-scale bromine enrichment (Brenr) record from the NEEM ice core (Northwest Greenland) and sediment core biomarker records to reconstruct the variability of seasonal sea ice in the Baffin Bay and Labrador Sea over a suite of D-O events between 34 and 42 ka. Our results reveal repeated shifts between stable, multiyear sea ice (MYSI) conditions during cold stadials and unstable, seasonal sea ice conditions during warmer interstadials. The shift from stadial to interstadial sea ice conditions occurred rapidly and synchronously with the atmospheric warming over Greenland, while the amplitude of high-frequency sea ice fluctuations increased through interstadials. Our findings suggest that the rapid replacement of widespread MYSI with seasonal sea ice amplified the abrupt climate warming over the course of D-O events and highlight the role of feedbacks associated with late-interstadial seasonal sea ice expansion in driving the North Atlantic ocean-climate system back to stadial conditions.

Group 2i Isochrysidales flourishes at exceedingly low growth temperatures (0 to 6 °C)

Group 2i Isochrysidales (Haptophyta) microalgae were recently suggested to be the main producer of the C37:4 alkenone in high latitude oceans with seasonal sea ice, enabling potential quantitative sea ice reconstructions using C37:4%. However, the conditions favoring the growth of Group 2i are currently unclear. Phylogenetically based on small subunit 18S rDNA sequence data, Group 2i is indistinguishable from OTU8 and Hap-A previously reported in numerous saline lakes around the world, and has been found to bloom in the early spring season in Lake George, North Dakota. These observations suggest Group 2i may have a preference for low growth temperatures and may grow within or underneath seasonal ice. Here we performed systematic culture experiments of Group 2i RCC5486 (isolated from sea ice of Baffin Bay) at exceedingly low temperatures (0, 3, 6, 9 °C at 31 ppt) and different salinities (15, 21, 26, 31, 38 ppt at 3 °C). We found Group 2i RCC5486 displays unusually fast growth from 0 to 6 °C, but failed to grow at 10.5 and 12 °C. These data confirm that Group 2i is explicitly adapted to low temperatures in both saline lakes and high latitude ocean regions (i.e., it is a psychrophile). Salinity, on the other hand, does not significantly influence the growth rates of Group 2i RCC5486. In addition, both growth temperature and salinity show minimal influence on C37:4%, which supports the use of C37:4% as a proxy for sea ice, rather than temperature or salinity in high latitude oceans.

Planet Four: A Neural Network’s search for polar spring-time fans on Mars

Dark deposits visible from orbit appear in the Martian south polar region during the springtime. These are thought to form from explosive jets of carbon dioxide gas breaking through the thawing seasonal ice cap, carrying dust and dirt which is then deposited onto the ice as dark ‘blotches’, or blown by the surface winds into streaks or ‘fans’. We investigate machine learning (ML) methods for automatically identifying these seasonal features in High Resolution Imaging Science Experiment (HiRISE) satellite imagery. We designed deep Convolutional Neural Networks (CNNs) that were trained and tested using the catalog generated by Planet Four, an online citizen science project mapping the south polar seasonal deposits. We validated the CNNs by comparing their results with those of ISODATA (Iterative Self-Organizing Data Analysis Technique) clustering and as expected, the CNNs were significantly better at predicting the results found by Planet Four, in both the area of predicted seasonal deposits and in delineating their boundaries. We found neither the CNNs or ISODATA were suited to predicting the source point and directions of seasonal fans, which is a strength of the citizen science approach. The CNNs showed good agreement with Planet Four in cross-validation metrics and detected some seasonal deposits in the HiRISE images missed in the Planet Four catalog; the total area of seasonal deposits predicted by the CNNs was 27% larger than that of the Planet Four catalog, but this aspect varied considerably on a per-image basis.

Understanding model spread in sea ice volume by attribution of model differences in seasonal ice growth and melt

Abstract. Arctic sea ice is declining rapidly, but predictions of its future loss are made difficult by the large spread both in present-day and in future sea ice area and volume; hence, there is a need to better understand the drivers of model spread in sea ice state. Here we present a framework for understanding differences between modelled sea ice simulations based on attributing seasonal ice growth and melt differences. In the method presented, the net downward surface flux is treated as the principal driver of seasonal sea ice growth and melt. An energy balance approach is used to estimate the pointwise effect of model differences in key Arctic climate variables on this surface flux and hence on seasonal sea ice growth and melt. We compare three models with very different historical sea ice simulations: HadGEM2-ES, HadGEM3-GC3.1 and UKESM1.0. The largest driver of differences in ice growth and melt between these models is shown to be the ice area in summer (representing the surface albedo feedback) and the ice thickness distribution in winter (the thickness–growth feedback). Differences in snow and melt pond cover during the early summer exert a smaller effect on the seasonal growth and melt, hence representing the drivers of model differences in both this and in the sea ice volume. In particular, the direct impacts on sea ice growth and melt of differing model parameterisations of snow area and of melt ponds are shown to be small but non-negligible.

Emerging unprecedented lake ice loss in climate change projections

Seasonal ice in lakes plays an important role for local communities and lake ecosystems. Here we use Large Ensemble simulations conducted with the Community Earth System Model version 2, which includes a lake simulator, to quantify the response of lake ice to greenhouse warming and to determine emergence patterns of anthropogenic lake ice loss. Our model simulations show that the average duration of ice coverage and maximum ice thickness are projected to decrease over the next 80 years by 38 days and 0.23 m, respectively. In the Canadian Arctic, lake ice loss is accelerated by the cold-season polar amplification. Lake ice on the Tibetan Plateau decreases rapidly due to a combination of strong insolation forcing and ice-albedo feedbacks. Comparing the anthropogenic signal with natural variability represented by the Large Ensemble, we find that lake ecosystems in these regions may be exposed to no-analogue ice coverage within the next 4-5 decades.

Late glacial retreat of the Lancaster Sound Ice Stream and early Holocene onset of Arctic/Atlantic throughflow in the Arctic Island channels

ABSTRACT Multiple proxies in three sediment cores from Northwestern Baffin Bay document the timing of Lancaster Sound Ice Stream (LSIS) retreat that led to Arctic–Atlantic throughflow in Parry Channel, an important source of freshwater that can impact the Atlantic Meridional Overturning Circulation. The Late Glacial to Holocene timing of ice retreat and channel opening and the responses of the regional ocean environment to these events are presented. We use quantitative mineral composition, foraminiferal assemblages, biogenic silica, ice-rafted debris (IRD), and 14C-based age models to document and date the events and environmental changes occurring during deglaciation of this major marine channel. Findings show that retreat of the LSIS into Lancaster Sound occurred before ~15.3 cal ka BP, about 800 years before the onset of major iceberg calving events from the LSIS, named the Baffin Bay Detrital Carbonate events (BBDC 1 and BBDC 0). The end of BBDC 0 occurred at ~10.6 cal ka BP, which coincides with the opening of Parry Channel. A marine environment productive of calcareous benthic and planktic foraminifera, with diminished meltwater, seasonal sea ice, warmer summer temperatures, and inflowing, nutrient-rich Arctic surface water characterizes the interval between the opening of Parry Channel and the opening of Nares Strait. Paired planktic and benthic 14C ages over this 2,200-year interval show diminishing age offsets suggesting progressive mixing of the upper ~850–900 m of the water column. The opening of Nares Strait by ~8.2 cal ka BP coincides with increased biogenic silica in the form of abundant, large centric diatoms and dissolution of CaCO3. The paucity of calcareous organisms after 8.2 cal ka BP resulted in poor chronological control in the cores to interpret changing environments after 8.2 cal ka BP.

Probabilistic spatiotemporal seasonal sea ice presence forecasting using sequence-to-sequence learning and ERA5 data in the Hudson Bay region

Abstract. Accurate and timely forecasts of sea ice conditions are crucial for safe shipping operations in the Canadian Arctic and other ice-infested waters. Given the recent declining trend of Arctic sea ice extent in past decades, seasonal forecasts are often desired. In this study machine learning (ML) approaches are deployed to provide accurate seasonal forecasts based on ERA5 data as input. This study, unlike previous ML approaches in the sea ice forecasting domain, provides daily spatial maps of sea ice presence probability in the study domain for lead times up to 90 d using a novel spatiotemporal forecasting method based on sequence-to-sequence learning. The predictions are further used to predict freeze-up/breakup dates and show their capability to capture these events within a 7 d period at specific locations of interest to shipping operators and communities. The model is demonstrated in hindcasting mode to allow for evaluation of forecasted predication. However, the design allows for the approach to be used as a forecasting tool. The proposed method is capable of predicting sea ice presence probabilities with skill during the breakup season in comparison to both Climate Normal and sea ice concentration forecasts from a leading subseasonal-to-seasonal forecasting system.

Martian subsurface water ice prediction at the Tianwen-1 mission landing site

One of the important sub-tasks of China's ongoing Tianwen-1 exploration mission is to find water ice on Mars. We have predicted the distribution of shallow subsurface water ice at the Tianwen-1 landing site to provide reference information for the mission. A detailed analysis shows that only for an exceptionally favorable combination of slope, albedo, and thermal inertia would perennial near-surface ice be expected at the Tiwanwen-1 landing site and the Zhurong rover is hardly to carry out in-situ searching for ice at steep slopes with dust-mantled surfaces, while seasonal ice is very likely to be found in winter in Tianwen-1 landing area with appropriate terrain conditions. With the interaction of a hygroscopic salt, the transient diurnal ice can exist and experience phase transitions. Notably, under the influence of Ca (ClO4)2, liquid brine may exist in diurnal cycles even on the hottest day of Mars.