Seasonal Ice Research Articles

Approximation of ice phenology of Maine lakes using Aqua MODIS surface temperature data

AbstractStudies of lake ice phenology have historically relied on limited in situ data. Relatively few observations exist for ice out and fewer still for ice in, both of which are necessary to determine the temporal extent of ice cover. Satellite data provide an opportunity to better document patterns of ice phenology across landscapes and relate them to the climatological drivers behind changing ice phenology. We developed a model, the Cumulative Sum Method (CSM), that uses daytime and nighttime surface temperature observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Earth‐observing Aqua satellite to approximate ice in (the onset of ice cover) and ice out from training datasets of 13 and 58 Maine lakes, respectively, during the 2002/2003 through 2017/2018 ice seasons. Ice in was signaled by reaching a threshold of cumulative negative degrees following the first day of the season below 0°C. Ice out was signaled by reaching a threshold of cumulative positive degrees following the first day of the year above 0°C. The comparison of observed and remotely sensed ice‐in dates showed relative agreement with a correlation coefficient of 0.71 and a mean absolute error (MAE) of 9.8 days. Ice‐out approximations had a correlation coefficient of 0.67 and an MAE of 8.8 days. Lakes smaller in surface area and nearer the Atlantic coast had the greatest error in approximation. Application of the CSM to 20 additional lakes in Maine produced a comparable ice‐out MAE of 8.9 days. Ice‐out model performance was weaker for the warmest years; there was a larger MAE of 12.0 days when the model was applied to the years 2019–2023 for the original 58 lakes. The development of this model, which utilizes daily satellite data, demonstrates the promise of remote sensing for quantifying ice phenology over short, temporal scales, and wider geographic regions than can be observed in situ, and allows exploration of the influence of surface temperature patterns on the process and timing of ice in and ice out.

Temporal Evolution of Gaseous Mercury Across the Sea Ice‐Seawater Interface: A Mesocosm Study

AbstractIn the marine cryosphere, seasonal sea ice dynamics affect the behavior of gaseous mercury, yet the mechanism remains poorly understood. By carrying out an outdoor sea ice mesocosm study, we examine primarily the abiotic factors influencing mercury dynamics and show distinct behaviors of gaseous mercury across the sea ice‐seawater interface over the full growth‐melt cycle. The distribution of gaseous mercury in sea ice is influenced by entrapment of gaseous mercury from different sources into sea ice of different textures, transport schemes within sea ice, and in situ cryo‐processes that affect mercury speciation. In the growing sea ice sections where solar radiation penetrated, production of gaseous mercury was observed, supporting the occurrence of in‐ice cryo‐photoreduction of divalent mercury. In under‐ice seawater, concentrations of dissolved gaseous mercury decreased gradually during ice growth and increased rapidly to pre‐freezing levels as ice started to melt, suggesting that the atmosphere‐sea ice‐seawater exchange pathway of gaseous mercury could be re‐established through melting first‐year sea ice. Our results from this unique mesocosm study provide new insights on the dynamics of gaseous mercury in and around sea ice that are primarily driven by abiotic processes, assisting model parameterizations for mercury cycling in polar regions.

Two Decades of Arctic Sea-Ice Thickness from Satellite Altimeters: Retrieval Approaches and Record of Changes (2003–2023)

There now exists two decades of basin-wide coverage of Arctic sea ice from three dedicated polar-orbiting altimetry missions (ICESat, CryoSat-2, and ICESat-2) launched by NASA and ESA. Here, we review our retrieval approaches and discuss the composite record of Arctic ice thickness (2003–2023) after appending two more years (2022–2023) to our earlier records. The present availability of five years of snow depth estimates—from differencing lidar (ICESat-2) and radar (CryoSat-2) freeboards—have benefited from the concurrent operation of two altimetry missions. Broadly, the dramatic volume loss (5500 km3) and Arctic-wide thinning (0.6 m) captured by ICESat (2003–2009), primarily due to the decline in old ice coverage between 2003 and 2007, has slowed. In the central Arctic, away from the coasts, the CryoSat-2 and shorter ICESat-2 records show near-negligible thickness trends since 2007, where the winter and fall ice thicknesses now hover around 2 m and 1.3 m, from a peak of 3.6 m and 2.7 m in 1980. Ice volume production has doubled between the fall and winter with the faster-growing seasonal ice cover occupying more than half of the Arctic Ocean at the end of summer. Seasonal ice behavior dominates the Arctic Sea ice’s interannual thickness and volume signatures.

High uptake of sympagic organic matter by benthos on an Arctic outflow shelf.

On Arctic shelves, benthic food-webs are tightly linked to overlying primary production. In the seasonal ice zone, sympagic (ice-associated) primary production can be a major source of carbon for the benthos on productive inflow shelves. However, the role of sympagic organic matter is less well-understood in food webs of heavily ice-covered, less- productive outflow shelves, such as the northeast Greenland shelf. Highly branched isoprenoid biomarkers (HBIs) were used to track the relative distribution of sympagic and pelagic organic matter in the water column, sediments, and benthic fauna of the northeast Greenland shelf and fjords. Low pelagic HBI presence throughout the study area indicated a generally low production by pelagic diatoms (at the time of sampling). This was reflected in the benthos, as ~90% of their assimilated carbon was estimated to come from sympagic sources, indicating a benthic food-web highly reliant on sympagic production. This reliance was higher in coastal areas than on the open shelf, where the potentially higher pelagic productivity and shallower water on banks likely increased contributions of pelagic organic matter. As declining ice cover and reduced production of fast-sinking ice algae projected for Arctic shelves will likely result in weaker coupling between ice algae and the benthos, with possible consequences for future benthic-community structure and function.

Characterizing offshore polar ocean soundscapes using ecoacoustic intensity and diversity metrics.

Polar offshore environments are considered the last pristine soundscapes, but accelerating climate change and increasing human activity threaten their integrity. In order to assess the acoustic state of polar oceans, there is the need to investigate their soundscape characteristics more holistically. We apply a set of 14 ecoacoustic metrics (EAMs) to identify which metrics are best suited to reflect the characteristics of disturbed and naturally intact polar offshore soundscapes. We used two soundscape datasets: (i) the Arctic eastern Fram Strait (FS), which is already impacted by anthropogenic noise, and (ii) the quasi-pristine Antarctic Weddell Sea (WS). Our results show that EAMs when applied in concert can be used to quantitatively assess soundscape variability, enabling the appraisal of marine soundscapes over broad spatiotemporal scales. The tested set of EAMs was able to show that the eastern FS, which is virtually free from sea ice, lacks seasonal soundscape dynamics and exhibits low acoustic complexity owing to year-round wind-mediated sounds and anthropogenic noise. By contrast, the WS exhibits pronounced seasonal soundscape dynamics with greater soundscape heterogeneity driven in large part by the vocal activity of marine mammal communities, whose composition in turn varies with the prevailing seasonal sea ice conditions.

Microplastic Particles and Fibers in Seasonal Ice of the Northern Baltic Sea.

Microplastic pollution is a pervasive issue, with remarkably high concentrations observed even in the most remote locations such as Arctic sea ice and snow. The reason for such large microplastic abundances in sea ice is still speculative and applies mainly to saline or freshwater conditions. In this study, we investigated seasonal ice core samples collected in March 2021 from the northern Baltic Sea (Gulf of Bothnia) for their microplastic distributions. The Baltic Sea is characterized by low salinity and can be ice-covered for up to six months annually. Microplastics were analyzed in the melted ice samples using an adsorption technique and Raman microscopy to identify their abundances, colors, shapes, and sizes to calculate their masses. Due to the strong dynamic of the ice layer and the repeated melting and freezing processes during the ice formation, no discernible trends in microplastic abundances, masses, or polymer types were observed throughout the ice core length. The average microplastic abundance (±SD) in the Baltic Sea ice was determined to be 22.3 ± 8.6 N L-1, with 64.9% of the particles exhibiting a particulate shape and 35.1% having a fibrous shape. The most prevalent polymer type was polyethylene terephthalate (PET), accounting for 44.4% of all polymers. This is likely due to the high proportion of PET fibers (93.8%). The majority of particle-shaped microplastics were identified as polyethylene (PE; 37.2%), followed by PET (17.2%), polyvinyl chloride (PVC; 15.9%), and polypropylene (PP; 15.9%). No correlations were found between microplastic concentrations and proximity to land, cities, industries, or rivers, except for PP mass concentrations and particle sizes, which correlated with distances to industries in Luleå, Sweden.

Metatranscriptomic analysis reveals dissimilarity in viral community activity between an ice-free and ice-covered winter in Lake Erie.

Winter is a relatively under-studied season in freshwater ecology. The paucity of wintertime surveys has led to a lack of knowledge regarding microbial community activity during the winter in Lake Erie, a North American Great Lake. Viruses shape microbial communities and regulate biogeochemical cycles by acting as top-down controls, yet very few efforts have been made to examine active virus populations during the winter in Lake Erie. Furthermore, climate change-driven declines in seasonal ice cover have been shown to influence microbial community structure, but no studies have compared viral community activity between different ice cover conditions. We surveyed surface water metatranscriptomes for viral hallmark genes as a proxy for active virus populations and compared activity metrics between ice-covered and ice-free conditions from two sampled winters. Transcriptionally active viral communities were detected in both winters, spanning diverse phylogenetic clades of putative bacteriophage (Caudoviricetes), giant viruses (Nucleocytoviricota, or NCLDV), and RNA viruses (Orthornavirae). However, viral community activity metrics revealed pronounced differences between the ice-covered and ice-free winters. Viral community composition was distinct between winters and viral hallmark gene richness was reduced in the ice-covered relative to the ice-free conditions. In addition, the observed differences in viral communities correlated with microbial community activity metrics. Overall, these findings contribute to our understanding of the viral populations that are active during the winter in Lake Erie and suggest that viral community activity may be associated with ice cover extent.IMPORTANCEAs seasonal ice cover is projected to become increasingly rare on large temperate lakes, there is a need to understand how microbial communities might respond to changing ice conditions. Although it is widely recognized that viruses impact microbial community structure and function, there is little known regarding wintertime viral activity or the relationship between viral activity and ice cover extent. Our metatranscriptomic analyses indicated that viruses were transcriptionally active in the winter surface waters of Lake Erie. These findings also expanded the known diversity of viral lineages in the Great Lakes. Notably, viral community activity metrics were significantly different between the two sampled winters. The pronounced differences we observed in active viral communities between the ice-covered and ice-free samples merit further research regarding how viral communities will function in future, potentially ice-free, freshwater systems.

Arctic accessibility: recent trend in observed ship tracks and validation of arctic transport accessibility model

ABSTRACT The Arctic region is undergoing significant changes in maritime accessibility. This study investigates observed ship trajectories from 2013 to 2020 to demonstrate the recent trends of Arctic traffic. A notable surge in maritime activities has been observed, particularly during summer months, driven by economic interests and the increasing popularity of existing routes. Unique patterns in the northern Barents Sea have been observed where ships favour different routes based on seasonal ice conditions. Another contribution from this work is the validation of the Arctic Traffic Accessibility Model (ATAM) using the observed ship traffic data. Results show that the ATAM model underestimates the accessibility and vessel travel speed. This is largely due to outdated model parameters. The predefined ice multipliers and calculation of ice numerals used in the ATAM may not accurately reflect real-world conditions.

Response of the abundance and size of Acartia (Acartiura) hongi (Copepoda: Calanoida) copepodites to environmental variables in Laizhou Bay, Bohai Sea

Acartia hongi is an endemic brackish and coastal copepod species in the Yellow and Bohai Seas. To investigate the population structure and distribution, we examined samples of A. hongi copepodites from May 2011 to April 2012, excluding the ice season. A generalized additive model (GAM) was used to explore the response of the abundance and prosome length (PL) of A. hongi to a range of environmental variables, including temperature, salinity, chlorophyll a (Chl a) content, Yellow River runoff, pelagic fish, and phytoplankton. A. hongi occurred throughout the survey season continuously and area widely in Laizhou Bay. It was a dominant species in the copepod community and showed a maximum abundance during April and May. The CI-CIII copepodites were the primary contributors to the total population of A. hongi during the blooming months. Population densities (>10,000 ind.m−3) occurred in nearshore waters with temperatures between 10°C and 15°C and salinities between 25 and 27. Mean PLs across all copepodite stages were shortest in August or September and longest in March. The best-fitting GAMs for copepodite abundance and PL included the variables of temperature, salinity, Chl a content, and runoff. The abundance of A. hongi copepodites decreased with increasing temperature, particularly for CI and CII copepodites, when the temperature exceeded 10–15°C. Salinity and runoff showed more negative correlations with A. hongi copepodites of younger stages. The PLs across the copepodite stages demonstrated significant inverse correlations with temperature. Furthermore, the Chl a content significantly influenced the PLs of CVs and adults through interactions with temperature. Overall, this study highlights temperature as a critical factor for the abundance and size distribution of the A. hongi population. Copepodites at earlier stages are more sensitive to temperature and salinity fluctuations. These findings provide valuable insights into the environmental effects on the A. hongi population dynamics in Laizhou Bay.

Revealing the Freezing-Induced Alteration in Microplastic Behavior and Its Implication for the Microplastics Released from Seasonal Ice.

Ice can serve as a significant temporary repository and conveyance mechanism for microplastics (MPs). MPs present in the water column can become entrapped within developing ice formations, subsequently being sequestered and transported by ice floes. With changing temperatures, MPs stored in ice can be released back into the environment, while freezing conditions can alter the properties of MPs, ultimately affecting the fate of MPs in the environment. Freezing of MPs in freshwater ice results in the aggregation of MP particles due to physical compression, leading to an increase in particle size once the MPs are released from the ice. The freezing-induced aggregation enhances buoyancy effects, accelerating the settling/rising velocity of MPs in water. Additionally, freezing can lead to enhanced surface wetting alterations, thus improving the dispersion of hydrophobic MPs. The presence of salt in the water can mitigate the effect of freezing on MPs due to the formation of a brine network within the ice structure, which reduces the pressure on MPs entrapped by ice. In cold regions, numerous MPs undergo freezing and thawing, re-entering the water column.

Sedimentary ancient DNA sequences reveal marine ecosystem shifts and indicator taxa for glacial-interglacial sea ice conditions

Sedimentary ancient DNA (sedaDNA) analysis is a promising new approach for reconstructing the impact of past climate and environmental changes on marine paleobiodiversity. By recovering, amplifying, and sequencing taxonomically informative sedaDNA fragments preserved in sediments, it is possible to assess the response of a broad range of eukaryote taxa, including non-fossilizing lineages, to past climate change. Here we present a unique marine derived sedaDNA metabarcoding record, spanning the penultimate glacial-interglacial transition across Marine Isotope Stages 6 to 5d (>135–107 ka) from an Eirik Drift core-site in the Labrador Sea. We identified a range of marine groups including dinoflagellates, diatoms, coccolithophores, chlorophytes, and copepods. There were representatives of primary/secondary producers, grazers, and parasites, which may represent remnants of complex ecosystems and ancient food webs. There were significant biodiversity shifts following the penultimate deglaciation and changing sea ice conditions throughout the Last Interglacial. These shifts reflected the striking increase in community richness during periods of seasonal sea ice and reduction under extensive perennial sea ice cover and open ocean. We identify two potential sedaDNA indicator taxa sequences associated with past seasonal sea ice which are most likely pico-eukaryote representatives of Micromonas and Pyramimonas, both green algae with known sea ice associations in modern ecosystems. Our work demonstrates the importance of high resolution marine sedaDNA metabarcoding for unravelling climate-ecosystem linkages and strengthens the potential of sedaDNA signals for past sea ice reconstructions through indicator sequences.

Spatial and Temporal Evolution of Seasonal Sea Ice Extent of Hudson Strait, Canada, 1971–2018

The temporal and spatial variation in seasonal sea ice in Hudson Strait is examined using time series and spatial clustering analyses. For the period from 1971 to 2018, a time series of sea ice breakup and freeze-up dates and ice-free season length at twenty-four grid points were generated from sea ice charts derived from satellite and other data. These data were analyzed temporally and spatially. The temporal analyses indicated an unambiguous response to a warming climate with statistically significant earlier breakup dates, later freeze-up dates, and longer ice-free seasons, that were statistically linked to coincident regional surface air temperatures. The rate of change in freeze-up dates and ice-free season length was particularly strong in the early 2000s and less so in the 2010s. There was evidence that breakup date behaviour was not only coincident with regional temperatures but likely with temperature and ice conditions of the previous year. Later freeze-up dates were directly linked to earlier breakup dates using detrended time series. Spatial clustering analysis on the Hudson Strait gridded sea ice data revealed distinctive signatures for Ungava Bay, Frobisher Bay, and for grid points close to the shore and a clear linkage to the underlying circulation of Hudson Strait.

Modeling pan-Arctic seasonal and interannual landfast sea ice thickness and snow depth between 1979 and 2021

ABSTRACT Landfast sea ice (LFSI) is sensitive to local climate change, making it an important component of the cryosphere system. In this study, the LFSI around the pan-Arctic domain was simulated from 1979 to 2021 using a well-validated snow and ice thermodynamic model (HIGHTSI) under the framework of the Fast Ice Prediction System (FIPS), forced by the ERA5 reanalysis. The simulation results agree well with the in-situ observations in the Canadian Arctic, with a mean error of −0.06 ± 0.29 m for ice thickness and −0.04 ± 0.12 m for snow depth. A decrease of −2.8 ± 0.4 cm/10a in thickness and −16.2 ± 1.5 km3/a in volume for the Arctic LFSI was modeled during this period. There was significant spatial variability among the different domains, with the fastest decline found in the Vilkitsky Strait. The modeled snow depth shows large interannual and spatial variations, which was confirmed by other modeling results. The spatiotemporal variations in both air temperature and precipitation are the driving factors for the multi-decadal variations in LFSI thickness. The decreasing air temperature during the 2010s aligned with a slower thickness decrease and a slight volume increase for LFSI, which agreed with the pan-Arctic sea ice pattern.

Sea ice choke points reduce the length of the shipping season in the Northwest Passage

Arctic sea ice has shifted from a perennial (older, thicker ice) to a seasonal (younger, thinner) ice regime, leading to the increasingly common belief that shipping through Canada’s Northwest Passage is becoming more viable. Here, we use the Risk Index Outcome values derived from the Polar Operational Limit Assessment Risk Indexing System and analyze recent changes to shipping season lengths along individual sections of the Northwest Passage routes from 2007 to 2021. Results show that multi-year ice flushed southward from high-latitude regions maintains the so-called choke points along certain route sections, reducing overall shipping season length. There is considerable spatiotemporal variability in shipping season lengths along the southern and northern routes. Specifically, parts of the northern route exhibit a decrease of up to 14 weeks over the 15 years. The variability of shipping season and, in particular, the shortening of the season will impact not only international shipping but also resupply and the cost of food in many Arctic communities, which require a prompt policy response.

Improving the Estimation of Lake Ice Thickness with High-Resolution Radar Altimetry Data

Lake ice thickness (LIT) is a sensitive indicator of climate change, identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic-aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow–ice and ice–water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LIT and FFSAR_LIT retracker, respectively. We found that LIT retrievals from Sentinel-6 high-resolution SAR data at different posting rates are fully consistent with the LIT estimations obtained from thermodynamic lake ice model simulations and from low-resolution mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, demonstrating the continuity between LRM and SAR LIT retrievals. By comparing the Sentinel-6 SAR LIT estimates to optical/radar images, we found that the Sentinel-6 LIT measurements are fully consistent with the evolution of the lake surface conditions, accurately capturing the seasonal transitions of ice formation and melt. The uncertainty in the LIT estimates obtained with Sentinel-6 UFSAR data at 20 Hz is in the order of 5 cm, meeting the GCOS requirements for LIT measurements. This uncertainty is significantly smaller, by a factor of 2 to 3 times, than the uncertainty obtained with LRM data. The FFSAR processing at 140 Hz provides even better LIT estimates, with 20% smaller uncertainties. The LIT retracker analysis performed on data at the higher posting rate (140 Hz) shows increased performance in comparison to the 20 Hz data, especially during the melt transition period, due to the increased statistics. The LIT analysis has been performed over two representative lakes, Great Slave Lake and Baker Lake (Canada), demonstrating that the results are robust and hold for lake targets that differ in terms of size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions.

Evolving Arctic maritime hazards: Declining sea ice and rising waves in the Northwest Passage

The ongoing and projected retreat of Arctic sea ice has garnered international interest toward the utilization of Arctic maritime corridors for shipping, tourism, and development. Yet, with potential for increasing traffic in Arctic regions, it's important to consider additional environmental variables affected by climate change which may threaten maritime operations. Here, we use four climate model projections to produce ocean wave simulations and investigate the future magnitude and seasonality of sea ice risk coupled with wave hazards. Analyzing the potential 5 mo shipping season spanning July to November along the Northwest Passage maritime route between 2020 and 2070, our results show a substantial decline in sea ice risk over the analysis time period, resulting in near open-water conditions along the route for a 5 mo period by 2070. However, as seasonal ice coverage retreats, there is a significant upward trend in wave heights along the route during July and November, with the timing of the greatest wave height shifting away from September toward later in the season. This result is pertinent as the possibility of seasonally unprecedented extreme waves coupled with subfreezing late fall temperatures makes for an especially hazardous environment, thus emphasizing the importance of considering the interaction between evolving sea ice and interdependent hazards when predicting the risks and challenges faced by Arctic maritime operations.

Predicting September Arctic Sea Ice: A Multimodel Seasonal Skill Comparison

Abstract This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynamical models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance.

Sea Ice Interannual Variability and Sensitivity to Fall Oceanic Conditions and Winter Air Temperature in the Gulf of St. Lawrence, Canada

AbstractThe Gulf of St. Lawrence has been nearly free of sea ice in the winter six times in its recorded history, four of which have occurred since 2010. This study examines the inter‐annual variability of sea ice cover characteristics (1969–2024) and winter mixed layer heat content (1996–2024), their sensitivity to fall oceanic conditions (since fall of 1995) and to winter air temperatures. The study finds no relationship between fall oceanic conditions with either the first occurrence of sea ice, maximum seasonal estimated volume or winter mixed layer heat content. However, it shows that the first occurrence of sea ice in the northwestern Gulf is related to the timing of sea surface temperature crossing the 1°C threshold with a lag time of 30–37 days, and with air temperature dropping below −2°C with a lag of 37–44 days; longer lags have weak correlations. The seasonal maximum conditions in area or estimated volume can be estimated by the preceding measurements of the same metrics with a lead time of only 29 days for volume and 36 days for area. The average air temperature over the Gulf between December and February or March is highly correlated to seasonal maximum sea ice area and estimated volume, as well as ice season duration. The six nearly ice‐free winters correspond to the warmest December to February (or December to March) average air temperatures over the Gulf. A warming of >1.9°C–2.4°C (DJFM) or >2.2°C–2.9°C (DJF) above the 1991–2020 climatology leads to nearly ice‐free conditions.

New insights into the environmental photochemistry of common-use antibiotics in ice and in water: A comparison of kinetics and influencing factors

The photochemistry of organic contaminants present in ice is receiving growing attention, given the wide presence of ice during winter in temperate regions as well as Polar and mountain environments. Differences between ice photochemistry and aqueous photochemistry, however, influence the quantitative fate and transformation of organic chemicals present in freshwater, marine and ice-cap environments and these differences need to be explored. Here we comparatively studied the ice and aqueous photochemistry of three antibiotics [levofloxacin (LVX), sulfamerazine (SM), and chlortetracycline (CTC)] under the same simulated sunlight (λ > 290 nm). Their photodegradation in ice/water followed pseudo-first-order kinetics, whereby the photolytic rates of LVX in ice and water were found to be similar, SM photodegraded faster in ice, while CTC underwent slower photodegradation in ice. Whether individual antibiotics underwent faster photodegradation in ice or not depends on the specific concentration effect and cage effect coexisting in the ice compartment. In most cases, the fastest photodegradation occurred in freshwater ice or in fresh water, and the slowest photolysis occurred in pure-water ice or in pure water. This can be attributed to the effects of key photochemical reactive constituents of Cl−, HA, NO3− and Fe(III), that exist in natural waters. These constituents at certain levels showed significant effects (P < 0.1) on the photolysis, not only in ice but also in water. However, these individual constituents at a given concentration, serve to either enhance or suppress the photoreaction, depending on the specific antibiotic and the matrix type (e.g., ice or aqueous solution). Furthermore, extrapolation of the laboratory findings to cold environments indicate that pharmaceuticals present in ice will have a different photofate compared to water. These results are of particular relevance for those regions that experience seasonal ice cover in fresh water and coastal marine systems.

Modeling seasonal ice and its impact on the thermal regime of a shallow boreal lake using the Canadian small Lake model

At high latitudes, lake-atmosphere interactions are disrupted for several months of the year by the presence of an ice cover. By isolating the water column from the atmosphere, ice, typically topped by snow, drastically alters albedo, surface roughness, and heat exchanges relative to the open water period, with major climatic, ecological, and hydrological implications. Lake models used to simulate the appearance and disappearance of the ice cover have rarely been validated with detailed in situ observations of snow and ice. In this study, we investigate the ability of the physically-based 1D Canadian Small Lake Model (CSLM) to simulate the freeze-up, ice-cover growth, and breakup of a small boreal lake. The model, driven offline by local weather observations, is run on Lake Piché, 0.15 km2 and 4 m deep (47.32°N; 71.15°W) from 25 October 2019 to 20 July 2021, and compared to observations of the temperature profile and ice and snow cover properties. Our results show that the CSLM is able to reproduce the total ice thickness (average error of 15 cm) but not the ice type-specific thickness, underestimating clear ice and overestimating snow ice. CSLM manages to reproduce snow depth (errors less than 10 cm). However, it has an average cold bias of 2°C and an underestimation of average snow density of 34 kg m−3. Observed and model freeze-up and break-up dates are very similar, as the model is able to predict the longevity of the ice cover to within 2 weeks. CSLM successfully reproduces seasonal stratification, the mixed layer depth, and surface water temperatures, while it shows discrepancies in simulating bottom waters especially during the open water period.