The Best of Both Worlds: Connecting Remote Sensing and Arctic Communities for Safe Sea Ice Travel

  Northern communities are increasingly interested in technology that provides information about the sea ice environment for travel purposes. Synthetic aperture radar (SAR) remote sensing is widely used to observe sea ice independently of sunlight and cloud cover, however, access to SAR in northern communities has been limited. This study 1) defines the sea ice features that influence travel for two communities in the Western Canadian Arctic, 2) identifies the utility of SAR for enhancing mobility and safety while traversing environments with these features, and 3) describes methods for sharing SAR-based maps. Three field seasons (spring and fall 2017 and spring 2018) were used to engage residents in locally guided research, where applied outputs were evaluated by community members. We found that SAR image data inform and improve sea ice safety, trafficability, and education. Information from technology is desired to complement Inuit knowledge-based understanding of sea ice features, including surface roughness, thin sea ice, early and late season conditions, slush and water on sea ice, sea ice encountered by boats, and ice discontinuities. Floe edge information was not a priority. Sea ice surface roughness was identified as the main condition where benefits to trafficability from SAR-based mapping were regarded as substantial. Classified roughness maps are designed using thresholds representing domains of sea ice surface roughness (smooth ice/maniqtuk hiku, moderately rough ice/maniilrulik hiku, rough ice/maniittuq hiku; dialect is Inuinnaqtun). These maps show excellent agreement with local observations. Overall, SAR-based maps tailored for on-ice use are beneficial for and desired by northern community residents, and we recommend that high-resolution products be routinely made available in communities.  Les collectivités du Nord s’intéressent de plus en plus aux technologies qui leur fournissent de l’information au sujet de l’environnement de glace de mer à des fins de déplacements. La télédétection par radar à synthèse d’ouverture (SAR) est couramment utilisée pour observer la glace de mer, indépendamment de la lumière du soleil et de la nébulosité. Cependant, dans les collectivités du Nord, l’accès au SAR est restreint. Cette étude 1) définit les caractéristiques de la glace de mer qui exercent une influence sur les déplacements de deux collectivités dans l’ouest de l’Arctique canadien; 2) détermine l’utilité du SAR pour améliorer la mobilité et la sécurité quand vient le temps de traverser des environnements comportant ces caractéristiques; et 3) décrit les méthodes de partage de cartes établies à l’aide du SAR. Trois saisons sur le terrain (le printemps et l’automne de 2017, et le printemps de 2018) ont permis d’inciter les résidents à participer à une recherche locale guidée, là où les extrants appliqués ont été évalués par les membres de la collectivité. Nous avons trouvé que les données émanant des images du SAR éclairent et améliorent la sécurité de la glace de mer, l’aptitude à la circulation et l’éducation. L’information découlant de la technologie s’avère un complément désirable aux connaissances inuites en vue de la compréhension des caractéristiques de la glace de mer, dont la rugosité de la surface, la glace de mer mince, les conditions en début et en fin de saison, la bouillie de glace et la glace mouillée, la glace de mer rencontrée par les bateaux, et la discontinuité de la glace. Les données sur la glace de banc ne constituaient pas une priorité. La rugosité de la surface de la glace de mer était considérée comme la principale condition pour laquelle les avantages de la praticabilité déterminés au moyen des cartes établies à l’aide du SAR étaient substantiels. Les cartes indiquant la rugosité sont conçues en fonction de seuils représentant les caractéristiques de rugosité de la surface des glaces de mer (glace lisse/maniqtuk hiku, glace modérément rugueuse/maniilrulik hiku, glace rugueuse/maniittuq hiku; en dialecte inuinnaqtun). Ces cartes sont largement en accord avec les observations locales. Dans l’ensemble, les cartes établies à l’aide du SAR préparées en fonction des utilisations de la glace sont bénéfiques et désirées par les résidents des collectivités du Nord. Nous recommandons que des produits de haute résolution soient régulièrement mis à la disposition des collectivités

A quasi-objective single-buoy approach for understanding Lagrangian coherent structures and sea ice dynamics

Sea ice drift and deformation, namely sea ice dynamics, play a significant role in atmosphere–ice–ocean coupling. Deformation patterns in sea ice can be observed over a wide range of spatial and temporal scales, though high-resolution objective quantification of these features remains difficult. In an effort to better understand local deformation of sea ice, we adapt the trajectory-stretching exponents (TSEs), quasi-objective measures of Lagrangian stretching in continuous media, to sea ice buoy data and develop a temporal analysis of TSE time series. Our work expands on previous ocean current studies that have shown TSEs provide an approximation of Lagrangian coherent structure diagnostics when only sparse trajectory data are available. As TSEs do not require multiple buoys, we find they have an expanded range of use when compared with traditional Eulerian buoy-array deformation metrics and provide local-stretching information below the length scales possible when averaging over buoy arrays. We verify the ability of TSEs to temporally and spatially identify dynamic features for three different sea ice datasets. The ability of TSEs to quantify trajectory stretching is verified by concurrent ice fracture in buoy neighborhoods ranging from tens to hundreds of kilometers in diameter, as well as the temporal concurrence of significant storm events.</p

A Facet-Based Numerical Model for Simulating SAR Altimeter Echoes From Heterogeneous Sea Ice Surfaces

Cryosat-2 has provided measurements of pan-Arctic sea ice thickness since 2010 with unprecedented spatial coverage and frequency. However, it remains uncertain how the Ku-band radar interacts with the vast range of scatterers that can be present within the satellite footprint, including sea ice with varying physical properties and multi-scale roughness, snow cover, and leads. Here, we present a numerical model designed to simulate delay-Doppler SAR (Synthetic Aperture Radar) altimeter echoes from snow-covered sea ice, such as those detected by Cryosat-2. Backscattered echoes are simulated directly from triangular facetbased models of actual sea ice topography generated from Operation IceBridge Airborne Topographic Mapper (ATM) data, as well as virtual statistical models simulated artificially. We use these waveform simulations to investigate the sensitivity of SAR altimeter echoes to variations in satellite parameters (height, pitch, roll) and sea ice properties (physical properties, roughness, presence of water). We show that the conventional Gaussian assumption for sea ice surface roughness may be introducing significant error into the Cryosat-2 waveform retracking process. Compared to a more representative lognormal surface, an echo simulated from a Gaussian surface with rms roughness height of 0.2 m underestimates the ice freeboard by 5 cm – potentially underestimating sea ice thickness by around 50 cm. We present a set of ‘ideal’ waveform shape parameters simulated for sea ice and leads to inform existing waveform classification techniques. This model will ultimately be used to improve retrievals of key sea ice properties, including freeboard, surface roughness and snow depth, from SAR altimeter observations

Snow Property Controls on Modeled Ku-Band Altimeter Estimates of First-Year Sea Ice Thickness: Case Studies From the Canadian and Norwegian Arctic

Uncertainty in snow properties impacts the accuracy of Arctic sea ice thickness estimates from radar altimetry. On first-year sea ice (FYI), spatiotemporal variations in snow properties can cause the Ku-band main radar scattering horizon to appear above the snow/sea ice interface. This can increase the estimated sea ice freeboard by several centimeters, leading to FYI thickness overestimations. This article examines the expected changes in Ku-band main scattering horizon and its impact on FYI thickness estimates, with variations in snow temperature, salinity, and density derived from ten naturally occurring Arctic FYI Cases encompassing saline/nonsaline, warm/cold, simple/complexly layered snow (4–45 cm) overlying FYI (48–170 cm). Using a semi-empirical modeling approach, snow properties from these Cases are used to derive layer-wise brine volume and dielectric constant estimates, to simulate the Ku-band main scattering horizon and delays in radar propagation speed. Differences between modeled and observed FYI thickness are calculated to assess sources of error. Under both cold and warm conditions, saline snow covers are shown to shift the main scattering horizon above from the snow/sea ice interface, causing thickness retrieval errors. Overestimates in FYI thicknesses of up to 65% are found for warm, saline snow overlaying thin sea ice. Our simulations exhibited a distinct shift in the main scattering horizon when the snow layer densities became greater than 440 kg/m 3 , especially under warmer snow conditions. Our simulations suggest a mean Ku-band propagation delay for snow of 39%, which is higher than 25%, suggested in previous studies

Annual cycle observations of aerosols capable of ice formation in central Arctic clouds

The Arctic is warming faster than anywhere else on Earth, prompting glacial melt, permafrost thaw, and sea ice decline. These severe consequences induce feedbacks that contribute to amplified warming, affecting weather and climate globally. Aerosols and clouds play a critical role in regulating radiation reaching the Arctic surface. However, the magnitude of their effects is not adequately quantified, especially in the central Arctic where they impact the energy balance over the sea ice. Specifically, aerosols called ice nucleating particles (INPs) remain understudied yet are necessary for cloud ice production and subsequent changes in cloud lifetime, radiative effects, and precipitation. Here, we report observations of INPs in the central Arctic over a full year, spanning the entire sea ice growth and decline cycle. Further, these observations are size-resolved, affording valuable information on INP sources. Our results reveal a strong seasonality of INPs, with lower concentrations in the winter and spring controlled by transport from lower latitudes, to enhanced concentrations of INPs during the summer melt, likely from marine biological production in local open waters. This comprehensive characterization of INPs will ultimately help inform cloud parameterizations in models of all scales

Physical length scales of wind-blown snow redistribution and accumulation on relatively smooth Arctic first-year sea ice

Snow thickness measurements over relatively smooth Arctic first-year sea ice, obtained near Cambridge Bay, Nunavut, Canada (2014, 2016 and 2017) and near Elson Lagoon, Alaska, USA (2003 and 2006), are analyzed to quantify physical length-scales and their relevant scaling behaviors. We use the Multi-Fractal Temporally Weighted Detrended Fluctuation Analysis (MF-TWDFA) method to detect two major physical length-scales from both the study areas. Our results suggest that physical processes underlying the formation of snow dunes are consistent and that the wind is the main process shaping the redistribution and variability of snow thickness. One scale, around 10 m, appears to be related to the formation of the snow "dunes", while the other scale, between 30 m and 60 m, is likely associated with the various interactions of the snow dunes including merging, calving and lateral linking showing self-organized characteristics. We suggest that a simple cellular automata model can be used to generate the variability of snow thickness on smooth Arctic first-year sea ice

Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice

Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0∘ (nadir) and 50∘. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice

Analysis of surface roughness and morphology of first-year sea ice melt ponds: implications for microwave scattering

Bibliography: p. 144-157Some pages are in colour