Landfast Sea Ice Research Articles

Evaluating Landfast Sea Ice Ridging near UtqiaġVik Alaska Using TanDEM-X Interferometry

Seasonal landfast sea ice stretches along most Arctic coastlines and serves as a platform for community travel and subsistence, industry operations, and as a habitat for marine mammals. Landfast ice can feature smooth ice and areas of m-scale roughness in the form of pressure ridges. Such ridges can significantly hamper trafficability, but if grounded can also serve to stabilize the shoreward ice. We investigate the use of synthetic aperture radar interferometry (InSAR) to assess the formation and movement of ridges in the landfast sea ice near Utqiaġvik, Alaska. The evaluation is based on the InSAR-derived surface elevation change between two TanDEM-X bistatic image pairs acquired during January 2012. We compare the results with backscatter intensity, coastal radar data, and SAR-derived ice drift and evaluate the utility of this approach and its relevance for evaluation of ridge properties, as well as landfast sea ice evolution, dynamics, and stability.

Microplastic contamination in east Antarctic sea ice

The durability of plastics in the marine environment has led to concerns regarding the pervasiveness of this debris in remote polar habitats. Microplastic (MP) enrichment in East Antarctic sea ice was measured in one ice core sampled from coastal land-fast sea ice. The core was processed and filtered material was analyzed using micro Fourier-Transform Infrared (μFTIR) spectroscopy. 96 MP particles were identified, averaging 11.71 particles L−1. The most common MP polymers (polyethylene, polypropylene, and polyamide) were consistent with those most frequently represented in the majority of marine MP studies. Sea-ice MP concentrations were positively related with chlorophyll a, suggesting living biomass could assist in incorporating MPs in sea ice. Our preliminary results indicate that sea ice has the potential to serve as a reservoir for MP debris in the Southern Ocean, which may have consequences for Southern Ocean food webs and biogeochemistry.

Intermittent structural weakening and acceleration of the Thwaites Glacier Tongue between 2000 and 2018

AbstractEvolving conditions at the terminus of Thwaites Glacier will be important in determining the rate of its future sea-level contribution over the coming decades. Here, we use remote-sensing observations to investigate recent changes (2000–2018) in the structure and velocity of Thwaites Glacier and its floating tongue. We show that the main trunk of Thwaites Glacier has accelerated by 38% over this period, while its previously intact floating tongue has transitioned to a weaker mélange of fractured icebergs bounded by sea ice. However, the rate of structural weakening and acceleration was not uniform across the observational period and we identify two periods of rapid acceleration and structural weakening (2006–2012; 2016–2018), separated by a period of deceleration and re-advance of the structurally-intact shear margin boundary (2012–2015). The timing of these accelerations/decelerations strongly suggests a link to variable ocean forcing. The weakened tongue now has some dependency on landfast sea ice for structural integrity and is vulnerable to changes in landfast ice persistency. Future reductions in landfast sea ice could manifest from changes in climate and/or the imminent removal of the B-22A iceberg from the Thwaites embayment. Such changes could have important implications for the integrity of the ice tongue and future glacier discharge.

Spatial Heterogeneity as a Key Variable Influencing Spring-Summer Progression in UVR and PAR Transmission Through Arctic Sea Ice

The transmission of ultraviolet (UVR) and photosynthetically available radiation (PAR) through sea ice is a key factor controlling under-ice phytoplankton growth in seasonally ice-covered waters. The increase towards sufficient light levels for positive net photosynthesis occurs concurrently with the sea ice melt progression in late spring when ice surface conditions shift from a relatively homogeneous high-albedo snow cover to a less reflective mosaic of bare ice and melt ponds. Here, we present a detailed dataset on the spatial and temporal progression of transmitted UVR and PAR in relation to changing quantities of snow, sea ice and melt ponds. Data were collected with a remotely operated vehicle (ROV) during the GreenEdge landfast sea ice campaign in June-July 2016 in southwestern Baffin Bay. Over the course of melt progression, there was a 10-fold increase in spatially averaged UVR and PAR transmission through the sea ice cover, reaching a maximum transmission of 31% for PAR, 7% for UVB and 26% for UVA radiation. The depth under the sea ice experiencing spatial variability in light levels due to the influence of surface heterogeneity in snow, white ice and melt pond distributions increased from 7 +/- 4 to 20 +/- 6 m over our study. Phytoplankton drifting in under-ice surface waters were thus exposed to variations in PAR availability of up to 43%, highlighting the importance to account for spatial heterogeneity in light transmission through melting sea ice. Consequently, we demonstrate that spatial averages of PAR transmission provided more representative light availability estimates to explain under-ice bloom progression relative to single point irradiance measurements during the sea ice melt season. Encouragingly, the strong dichotomy between white ice and melt pond PAR transmittance and surface albedo permitted a very good estimate of spatially averaged light transmission from drone imagery of the surface and point transmittance measurements beneath different ice surface types.

Object-based landfast sea ice detection over West Antarctica using time series ALOS PALSAR data

Landfast sea ice (fast ice) is an important feature prevalent around the Antarctic coast, which is affected by climate change and energy exchanges with the atmosphere and ocean. This study proposed a method for detection of the West Antarctic fast ice using the Advanced Land Observing Satellite Phased Array L-band SAR (ALOS PALSAR) images. The algorithm has combined image segmentation, image correlation analysis, and machine learning techniques (i.e., random forest (RF), extremely randomized trees (ERT), and logistic regression (LR)). We used SAR images with a baseline of 5 days that are not in the same orbit but overlap each other as overlaps between swaths in adjacent orbits are often available in the polar regions. The underlying assumption for the proposed fast ice detection algorithm is that fast ice regions in SAR images with a time interval of 5 days are highly correlated. The object-based approach proposed in this study was well suited to high-resolution SAR images in deriving spatially homogeneous fast ice regions. The image segmentation results using the optimized parameters showed a distinct difference in the backscatter temporal evolution between fast ice and pack ice regions. Correlation and STD of backscattering coefficients were found to be the most significant variables for the object-based fast ice detection from two temporally separated images. In overall, the quantitative and qualitative evaluation demonstrated that the algorithm was an effective approach to detect fast ice with high accuracies. The models well detected various fast ice regions in the West Antarctica but misclassified some objects. The misclassifications occurred toward the edge of fast ice regions with relatively rapid changes in backscattering between both data acquisitions. On the other hand, few fast ice objects were misclassified as uniform backscattering over time occurred by chance on very small objects far from the coast. Very old multi-year fast ice regions with high backscattered signals were also a source for some misclassifications. This may be due to the sensitivity of L-band to snow structure to some extent and a thinner ice over the region with either ice growth (no deformation) or closing (slight deformation) between both images. Heavy snow load on the ice could be another error source for some misclassification as well. The approach allowed for the reliable detection of fast ice regions by using L-band SAR images with a small local incidence angle difference.

Green Edge ice camp campaigns: understanding the processes controlling the under-ice Arctic phytoplankton spring bloom

Abstract. The Green Edge initiative was developed to investigate the processes controlling the primary productivity and fate of organic matter produced during the Arctic phytoplankton spring bloom (PSB) and to determine its role in the ecosystem. Two field campaigns were conducted in 2015 and 2016 at an ice camp located on landfast sea ice southeast of Qikiqtarjuaq Island in Baffin Bay (67.4797∘ N, 63.7895∘ W). During both expeditions, a large suite of physical, chemical and biological variables was measured beneath a consolidated sea-ice cover from the surface to the bottom (at 360 m depth) to better understand the factors driving the PSB. Key variables, such as conservative temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured at the ice camp. Meteorological and snow-relevant variables were also monitored. Here, we present the results of a joint effort to tidy and standardize the collected datasets, which will facilitate their reuse in other Arctic studies. The dataset is available at https://doi.org/10.17882/59892 (Massicotte et al., 2019a).

An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice

Sea-ice biophysical properties are characterized by high spatio-temporal variability ranging from the meso- to the millimeter scale. Ice coring is a common yet coarse point sampling technique that struggles to capture such variability in a non-invasive manner. This hinders quantification and understanding of ice algae biomass patchiness and its complex interaction with some of its sea ice physical drivers. In response to these limitations, a novel under-ice sled system was designed to capture proxies of biomass together with 3D models of bottom topography of land-fast sea-ice. This system couples a pushbroom hyperspectral imaging (HI) sensor with a standard digital RGB camera and was trialed at Cape Evans, Antarctica. HI aims to quantify per-pixel chlorophyll-a content and other ice algae biological properties at the ice-water interface based on light transmitted through the ice. RGB imagery processed with digital photogrammetry aims to capture under-ice structure and topography. Results from a 20 m transect capturing a 0.61 m wide swath at sub-mm spatial resolution are presented. We outline the technical and logistical approach taken and provide recommendations for future deployments and developments of similar systems. A preliminary transect subsample was processed using both established and novel under-ice bio-optical indices (e.g., normalized difference indexes and the area normalized by the maximal band depth) and explorative analyses (e.g., principal component analyses) to establish proxies of algal biomass. This first deployment of HI and digital photogrammetry under-ice provides a proof-of-concept of a novel methodology capable of delivering non-invasive and highly resolved estimates of ice algal biomass in-situ, together with some of its environmental drivers. Nonetheless, various challenges and limitations remain before our method can be adopted across a range of sea-ice conditions. Our work concludes with suggested solutions to these challenges and proposes further method and system developments for future research.

Empirical prediction of snow and land-fast sea ice temperature from surface meteorology on Pistolet Bay, Northern Newfoundland

Abstract The temperature of sea ice and snow cover on the ice surface is a critical component of thermodynamic models of sea ice. Ice temperature is also an important factor in the sea ice strength and therefore in the potential loads the ice can exert on ships, ports, bridges, and offshore structures. The snow layer, while remaining distinct from the sea ice in its physical properties, can become compacted on the ice and contribute to the effective ice thickness and strength. The temperature of sea ice is governed by the atmospheric energy flux balance at the snow surface and the ocean energy flux at the ice base. In addition, snow cover acts as an insulator to sea ice, buffering it against temperature changes due to changes in surface meteorological conditions. The average internal ice temperature and total thickness (through its impact on ice salinity and brine volume) significantly affect ice strength parameters used in the calculation of loads on engineered structures. In February 2017–2019, three field campaigns were carried out on the land-fast ice on Pistolet Bay, north of St. Anthony, Newfoundland in Atlantic Canada. For approximately five days in 2017 and about four days in 2018–2019, surface air temperatures, wind speeds, and snow and ice temperature profiles were continuously measured. Dew point temperatures were obtained from the North American Regional Reanalysis (NARR) dataset. The datasets from the three field campaigns were used to develop empirical linear regression models of snow and ice surface and depth-mean temperatures as a function of the air temperature alone, and of the air and dew point temperatures and wind speed. In this paper, the meteorological data from the three field campaigns are presented, along with the snow and ice thickness and temperature data. The linear models of snow and ice temperature are presented, tested using the observed field data from the Pistolet Bay campaigns, and compared with results obtained from previously published models of snow and sea ice temperature. The results show that the models of snow and ice temperature as a function of the three meteorological variables are modestly more robust than the models as a function of air temperature alone, with R2 values of up to 0.90. The models presented in this paper have potential usefulness in improved prediction of site-specific snow/ice temperatures and associated temperature-dependent ice properties, such as strength at sites where gridded weather data or in-situ meteorological measurements are available, but in-situ snow/ice temperature measurements are nonexistent.

Landfast ice controls on sea-ice production in the Cape Darnley Polynya: A case study

Antarctic coastal polynyas serve as crucially-important sea-ice “factories” and are (in certain cases) of global significance as sites of Antarctic Bottom Water (AABW) formation e.g., the Cape Darnley Polynya (CDP) in East Antarctica. As such, understanding change and variability in their behaviour, and the factors responsible, is a high priority in climate (change) science. One such important factor that is both poorly understood and quantified is their linkage with adjacent landfast sea ice (fast ice). Here, we present a first detailed analysis that identifies and quantifies key linkages between the dynamics/behaviour of the CDP and fast ice. By forming a barrier to the incursion of pack ice at the eastern boundary, fast ice immediately upstream of the CDP (associated with the distribution of grounded icebergs) plays a crucially-important role in the polynya formation, maintenance and variability. This satellite data-based study builds upon earlier conceptual work on polynya-fast ice feedback mechanisms in the Mertz Glacier region by showing that statistical estimation of the rates of sea ice production (and hence AABW formation) in the CDP is significantly improved through inclusion of two key fast-ice metrics, compared to use of atmospheric covariates alone. These two metrics are the meridional extent of fast ice upstream of the polynya and total fast ice area within the region of high sea ice production. The work highlights the importance of accurate representation of the coupled Antarctic coastal polynya-fast ice system in global climate models.

Observation and thermodynamic modeling of the influence of snow cover on landfast sea ice thickness in Prydz Bay, East Antarctica

The observed snow depth and ice thickness on landfast sea ice in Prydz Bay, East Antarctica, were used to determine the role of snow in (a) the annual cycle of sea ice thickness at a fixed location (SIP) where snow usually blows away after snowfall and (b) early summer sea ice thickness within the transportation route surveys (TRS) domain farther from coast, where annual snow accumulation is substantial. The annual mean snow depth and maximum ice thickness had a negative relationship (r = −0.58, p < .05) at SIP, indicating a primary insulation effect of snow on ice thickness. However, in the TRS domain, this effect was negligible because snow contributes to ice thickness. A one-dimensional thermodynamic sea ice model, forced by local weather observations, reproduced the annual cycle of ice thickness at SIP well. During the freeze season, the modeled maximum difference of ice thickness using different snowfall scenarios ranged from 0.53–0.61 m. Snow cover delayed ice surface and ice bottom melting by 45 and 24 days, respectively. The modeled snow ice and superimposed ice accounted for 4–23% and 5–8% of the total maximum ice thickness on an annual basis in the case of initial ice thickness ranging from 0.05 to 2 m, respectively.

Exploring Spatial Heterogeneity of Antarctic Sea Ice Algae Using an Autonomous Underwater Vehicle Mounted Irradiance Sensor

Sea ice algae represent a key energy source for many organisms in polar food webs, but estimating their biomass at ecologically appropriate spatiotemporal scales remains a challenge. Attempts to extend ice-core derived biomass to broader scales using remote sensing approaches has largely focused on the use of under-ice spectral irradiance. Normalized Difference Index (NDI) based algorithms that relate the attenuation of irradiance by the snow-ice-algal ensemble at specific wavelengths to biomass have been used to explain up to 79% of the biomass of algae in limited areas. Application of these algorithms to datasets collected using tethered Remotely Operated Vehicles (ROVs) has begun, generating methods for spatial sampling at scales and spatial resolution not achievable with ice-core sampling. Successful integration of radiometers with untethered Autonomous Underwater Vehicles (AUVs) offers even greater capability to survey broader regions to explore the spatial heterogeneity of sea ice algal communities. This work describes the pilot use of an AUV fitted with a multispectral irradiance sensor to estimate ice-algal biomass along transects beneath land-fast sea ice (~2 m thick with minimal snow cover) in McMurdo Sound, Antarctica. The AUV obtained continuous, repeatable, multi-band irradiance data, suitable for NDI-type approaches, over transects of 500 m, with an instrument footprint of 4 m in diameter. Algorithms were developed using local measurements of ice algae biomass and spectral attenuation of sea ice and were able to explain 40% of biomass variability. Relatively poor performance of the algorithms in predicting biomass limited the confidence that could be placed in biomass estimates from AUV data. This was attributed to the larger footprint size of the optical sensors integrating small-scale biomass variability more effectively than the ice core in the platelet-dominated ice algal habitat. Our results support continued development of remote-sensing of sea ice algal biomass at m – km spatial scales using optical methods, but caution that footprint sizes of calibration data (e.g. coring) must be compatible with optical sensors used. AUVs offer autonomous survey techniques that could be applied to better understand the horizontal variability of sea ice algae from nearshore ice out to the marginal ice zone.

DNA barcoding of Cirripedia larvae reveals new knowledge on their biology in Arctic coastal ecosystems

Pelagic larvae of benthic organisms comprise a substantial part of the coastal Arctic zooplankton community in spring–summer. We studied the timing, growth, and pelagic duration of Cirripedia larvae in Adventfjorden, a high-Arctic fjord in Spitsbergen, Svalbard. Two distinct abundance peaks were found: one in early May (~ 25.000 ind. m−3) and another one in late May (~ 35,580 ind m−3). DNA barcoding based on the COI gene was used to identify the barnacle larvae to species. Whereas both Balanus balanus and Semibalanus balanoides were present, the first one dominated (50–100%) the barnacle abundance. High resolution sampling and size measurements of Cirripedia larvae revealed that these larvae most likely originated from a single spawning event. Development of the larvae suggested a pelagic residence time of roughly 2 months for B. balanus and at least 1 month for S. balanoides in the Arctic. Long pelagic residence time, large potential for biofouling on ships and larger plastic debris, combined with the disappearance of landfast sea ice and less ice scouring opens up new opportunities for barnacles to colonize the high-Arctic littoral zone. In a future warmer Arctic, we therefore expect establishment of new, more temperate Cirripedia species in Svalbard.

Loss of floating glacier tongues from the Yelverton Bay region, Ellesmere Island, Canada

ABSTRACTA total of eight floating glacier tongues have shrunk in area by &gt;85% from the Yelverton Bay region of Northern Ellesmere Island since 1959, with unusually large losses since 2005. To better understand the causes of these losses, this study undertakes the first examination of ice tongue changes in this region, including an assessment of changes in surrounding marine ice (i.e. sea ice, sikussak and mélange), and atmospheric and oceanographic forcings. From 1959 to 2017, the total ice tongue area decreased by 49.07 km2, with the majority of this loss occurring from 2005 to 2009 (34.68 km2). The loss of ice tongues since 2005 occurred when open water replaced multi-year landfast sea ice (MLSI) and first-year sea ice in the regions adjacent to the ice tongues. These changes were accompanied by an increase in mean annual mid-depth (i.e. 100 and 200 m) ocean temperatures from −0.29°C from 1999 to 2005 to 0.67°C from 2006 to 2012. Despite the recent return of ocean temperatures to below pre-2006 levels, atmospheric summer temperatures have continued to rise (+0.15°C decade−1 between 1948 and 2016), with open water continuing to occur. Without the sustained presence of MLSI in this region the ice tongues are unable to stabilize, making it unlikely that they will re-form in the current climate.

Resolving Fine-Scale Surface Features on Polar Sea Ice: A First Assessment of UAS Photogrammetry Without Ground Control

Mapping landfast sea ice at a fine spatial scale is not only meaningful for geophysical study, but is also of benefit for providing information about human activities upon it. The combination of unmanned aerial systems (UAS) with structure from motion (SfM) methods have already revolutionized the current close-range Earth observation paradigm. To test their feasibility in characterizing the properties and dynamics of fast ice, three flights were carried out in the 2016–2017 austral summer during the 33rd Chinese National Antarctic Expedition (CHINARE), focusing on the area of the Prydz Bay in East Antarctica. Three-dimensional models and orthomosaics from three sorties were constructed from a total of 205 photos using Agisoft PhotoScan software. Logistical challenges presented by the terrain precluded the deployment of a dedicated ground control network; however, it was still possible to indirectly assess the performance of the photogrammetric products through an analysis of the statistics of the matching network, bundle adjustment, and Monte-Carlo simulation. Our results show that the matching networks are quite strong, given a sufficient number of feature points (mostly &gt; 20,000) or valid matches (mostly &gt; 1000). The largest contribution to the total error using our direct georeferencing approach is attributed to inaccuracies in the onboard position and orientation system (POS) records, especially in the vehicle height and yaw angle. On one hand, the 3D precision map reveals that planimetric precision is usually about one-third of the vertical estimate (typically 20 cm in the network centre). On the other hand, shape-only errors account for less than 5% for the X and Y dimensions and 20% for the Z dimension. To further illustrate the UAS’s capability, six representative surface features are selected and interpreted by sea ice experts. Finally, we offer pragmatic suggestions and guidelines for planning future UAS-SfM surveys without the use of ground control. The work represents a pioneering attempt to comprehensively assess UAS-SfM survey capability in fast ice environments, and could serve as a reference for future improvements.

Mapping pan-Arctic landfast sea ice stability using Sentinel-1 interferometry

Abstract. Arctic landfast sea ice has undergone substantial changes in recent decades, affecting ice stability and including potential impacts on ice travel by coastal populations and on industry ice roads. We present a novel approach for evaluating landfast sea ice stability on a pan-Arctic scale using Synthetic Aperture Radar Interferometry (InSAR). Using Sentinel-1 images from spring 2017, we discriminate between bottomfast, stabilized, and nonstabilized landfast ice over the main marginal seas of the Arctic Ocean (Beaufort, Chukchi, East Siberian, Laptev, and Kara seas). This approach draws on the evaluation of relative changes in interferometric fringe patterns. This first comprehensive assessment of Arctic bottomfast sea ice extent has revealed that most of the bottomfast sea ice is situated around river mouths and coastal shallows. The Laptev and East Siberian seas dominate the aerial extent, covering roughly 4100 and 5100 km2, respectively. These seas also contain the largest extent of stabilized and nonstabilized landfast ice, but are subject to the largest uncertainties surrounding the mapping scheme. Even so, we demonstrate the potential for using InSAR for assessing the stability of landfast ice in several key regions around the Arctic, providing a new understanding of how stability may vary between regions. InSAR-derived stability may serve for strategic planning and tactical decision support for different uses of coastal ice. In a case study of the Nares Strait, we demonstrate that interferograms may reveal early-warning signals for the breakup of stationary sea ice.

Response of the Arctic Marine Inorganic Carbon System to Ice Algae and Under‐Ice Phytoplankton Blooms: A Case Study Along the Fast‐Ice Edge of Baffin Bay

AbstractPast research in seasonally ice‐covered Arctic seas has suggested that ice algae play a role in reducing dissolved inorganic carbon (DIC) during spring, preconditioning surface waters to low dissolved CO2 (pCO2sw), and uptake of atmospheric CO2 during the ice‐free season. The potential role of under‐ice phytoplankton blooms on DIC and pCO2sw has not often been considered. In this study we examined the inorganic carbon system beneath landfast sea ice starting midway through a bottom ice algae bloom and concluding in the early stages of an under‐ice phytoplankton bloom. During most of the ice algae bloom we observed a slight increase in DIC/pCO2sw in surface waters, as opposed to the expected reduction. Biomass calculations confirm that the role of ice algae on DIC/pCO2sw in the study region were minor and that this null result may be widely applicable. During snow melt, we observed an under‐ice phytoplankton bloom (to 10 mg/m3 Chl a) that did reduce DIC and pCO2sw. We conclude that under‐ice phytoplankton blooms are an important biological mechanism that may predispose some Arctic seas to act as a CO2 sink at the time of ice breakup. We also found that pCO2sw was undersaturated at the study location even at the beginning of our sampling period, consistent with several other studies that have measured under‐ice pCO2sw in late winter or early spring. Finally, we present the first measurements of carbonate saturation states for this region, which may be useful for assessing the vulnerability of a local soft‐shelled clam fishery to ocean acidification.

Environmental factors influencing the seasonal dynamics of spring algal blooms in and beneath sea ice in western Baffin Bay

Arctic sea ice is experiencing a shorter growth season and an earlier ice melt onset. The significance of spring microalgal blooms taking place prior to sea ice breakup is the subject of ongoing scientific debate. During the Green Edge project, unique time-series data were collected during two field campaigns held in spring 2015 and 2016, which documented for the first time the concomitant temporal evolution of the sea ice algal and phytoplankton blooms in and beneath the landfast sea ice in western Baffin Bay. Sea ice algal and phytoplankton blooms were negatively correlated and respectively reached 26 (6) and 152 (182) mg of chlorophyll a per m2 in 2015 (2016). Here, we describe and compare the seasonal evolutions of a wide variety of physical forcings, particularly key components of the atmosphere–snow–ice–ocean system, that influenced microalgal growth during both years. Ice algal growth was observed under low-light conditions before the snow melt period and was much higher in 2015 due to less snowfall. By increasing light availability and water column stratification, the snow melt onset marked the initiation of the phytoplankton bloom and, concomitantly, the termination of the ice algal bloom. This study therefore underlines the major role of snow on the seasonal dynamics of microalgae in western Baffin Bay. The under-ice water column was dominated by Arctic Waters. Just before the sea ice broke up, phytoplankton had consumed most of the nutrients in the surface layer. A subsurface chlorophyll maximum appeared and deepened, favored by spring tide-induced mixing, reaching the best compromise between light and nutrient availability. This deepening evidenced the importance of upper ocean tidal dynamics for shaping vertical development of the under-ice phytoplankton bloom, a major biological event along the western coast of Baffin Bay, which reached similar magnitude to the offshore ice-edge bloom.

Average cosine coefficient and spectral distribution of the light field under sea ice: Implications for primary production

The Arctic spring phytoplankton bloom has been reported to commence under a melting sea ice cover as transmission of photosynthetically active radiation (PAR; 400–700 nm) suddenly increases with the formation of surface melt ponds. Spatial variability in ice surface characteristics, i.e., snow thickness or melt pond distributions, and subsequent impact on transmitted PAR makes estimating light-limited primary production difficult during this time of year. Added to this difficulty is the interpretation of data from various sensor types, including hyperspectral, multispectral, and PAR-band irradiance sensors, with either cosine-corrected (planar) or spherical (scalar) sensor heads. To quantify the impact of the heterogeneous radiation field under sea ice, spectral irradiance profiles were collected beneath landfast sea ice during the Green Edge ice-camp campaigns in May–June 2015 and June–July 2016. Differences between PAR measurements are described using the downwelling average cosine, μd, a measure of the degree of anisotropy of the downwelling underwater radiation field which, in practice, can be used to convert between downwelling scalar, E0d, and planar, Ed, irradiance. A significantly smallerμd(PAR) was measured prior to snow melt compared to after (0.6 vs. 0.7) when melt ponds covered the ice surface. The impact of the average cosine on primary production estimates, shown in the calculation of depth-integrated daily production, was 16% larger under light-limiting conditions when E0d was used instead of Ed. Under light-saturating conditions, daily production was only 3% larger. Conversion of underwater irradiance data also plays a role in the ratio of total quanta to total energy (EQ/EW, found to be 4.25), which reflects the spectral shape of the under-ice light field. We use these observations to provide factors for converting irradiance measurements between irradiance detector types and units as a function of surface type and depth under sea ice, towards improving primary production estimates.

Dried, closed-path eddy covariance method for measuring carbon dioxide flux over sea ice

Abstract. The Arctic marine environment plays an important role in the global carbon cycle. However, there remain large uncertainties in how sea ice affects air–sea fluxes of carbon dioxide (CO2), partially due to disagreement between the two main methods (enclosure and eddy covariance) for measuring CO2 flux (FCO2). The enclosure method has appeared to produce more credible FCO2 than eddy covariance (EC), but is not suited for collecting long-term, ecosystem-scale flux datasets in such remote regions. Here we describe the design and performance of an EC system to measure FCO2 over landfast sea ice that addresses the shortcomings of previous EC systems. The system was installed on a 10 m tower on Qikirtaarjuk Island – a small rock outcrop in Dease Strait located roughly 35 km west of Cambridge Bay, Nunavut, in the Canadian Arctic Archipelago. The system incorporates recent developments in the field of air–sea gas exchange by measuring atmospheric CO2 using a closed-path infrared gas analyzer (IRGA) with a dried sample airstream, thus avoiding the known water vapor issues associated with using open-path IRGAs in low-flux environments. A description of the methods and the results from 4 months of continuous flux measurements from May through August 2017 are presented, highlighting the winter to summer transition from ice cover to open water. We show that the dried, closed-path EC system greatly reduces the magnitude of measured FCO2 compared to simultaneous open-path EC measurements, and for the first time reconciles EC and enclosure flux measurements over sea ice. This novel EC installation is capable of operating year-round on solar and wind power, and therefore promises to deliver new insights into the magnitude of CO2 fluxes and their driving processes through the annual sea ice cycle.

Chlorophyll‐a in Antarctic Landfast Sea Ice: A First Synthesis of Historical Ice Core Data

AbstractHistorical sea ice core chlorophyll‐a (Chla) data are used to describe the seasonal, regional, and vertical distribution of ice algal biomass in Antarctic landfast sea ice. The analyses are based on the Antarctic Fast Ice Algae Chlorophyll‐a data set, a compilation of currently available sea ice Chla data from landfast sea ice cores collected at circum‐Antarctic nearshore locations between 1970 and 2015. Ice cores were typically sampled from thermodynamically grown first‐year ice and have thin snow depths (mean = 0.052 ± 0.097 m). The data set comprises 888 ice cores, including 404 full vertical profile cores. Integrated ice algal Chla biomass (range: &lt;0.1–219.9 mg/m2, median = 4.4 mg/m2, interquartile range = 9.9 mg/m2) peaks in late spring and shows elevated levels in autumn. The seasonal Chla development is consistent with the current understanding of physical drivers of ice algal biomass, including the seasonal cycle of irradiance and surface temperatures driving landfast sea ice growth and melt. Landfast ice regions with reported platelet ice formation show maximum ice algal biomass. Ice algal communities in the lowermost third of the ice cores dominate integrated Chla concentrations during most of the year, but internal and surface communities are important, particularly in winter. Through comparison of biomass estimates based on different sea ice sampling strategies, that is, analysis of full cores versus bottom‐ice section sampling, we identify biases in common sampling approaches and provide recommendations for future survey programs: for example, the need to sample fast ice over its entire thickness and to measure auxiliary physicochemical parameters.