Search Results (843)

The National Research Council Canada (NRC) is actively engaged in the development of an advanced autonomy system for the Bell 412 helicopter. This system’s capabilities extend to the execution of complex missions, such as arctic resupply missions. In an arctic resupply mission, the helicopter autonomously delivers supplies to a remote arctic base. During the mission it performs tasks such as takeoff, navigation, obstacle avoidance, and precise landing at its destination, all while minimizing the need for pilot intervention. The complexity of this autonomy system necessitates the inclusion of a high-level supervisory controller. This controller plays a critical role in monitoring mission progress, interacting with system components, and efficiently allocating resources. Conventionally, supervisory controllers are embedded within monolithic programs, lacking transparent state flows. This causes system modification and testing to be a significant challenge. In our research, we present an innovative approach and methodology to develop supervisory controllers for autonomous aircraft on the example of the NRC Bell 412. Using the Discrete Event System Specification (DEVS) formalism and the Cadmium simulation engine, we effectively address the challenges above. We discuss the entire development process for a state-based, event-driven supervisory controller for autonomous rotorcraft using the NRC’s Bell-412 autonomy system as a comprehensive case study. This process includes modeling, implementation, verification, validation, testing, and deployment. It incorporates a simulation phase, in which the supervisor integrates with components within a Digital Twin of the Bell 412, and a real-time operations phase, where the supervisor becomes an integral part of the actual Bell 412 helicopter. Our method outlines the smooth transition between these phases, ensuring a seamless and efficient process. Full article

During the 84th cruise of the R/V Akademik Mstislav Keldysh in August 2021, patterns of phytoplankton composition transformation were revealed along a northward gradient. The study involved three transects in the Fram Strait and adjacent Arctic waters: a southern transect (from the Barents Sea shelf to the Greenland shelf), a middle transect across the Fram Strait, and a northern transect along the ice edge. Ten species of diatoms and eleven of dinoflagellates were identified, and their ecological preferences were characterized by determining the minimum, maximum, mean, and median values for abundance, biomass, depth of the biomass maximum, salinity, temperature, and the concentrations and ratios of nitrogen, phosphorus, and silicon. Significant gradients in temperature, salinity, silicon, and nitrogen concentrations were recorded along the south–north direction in the study area. The phytoplankton community responds to these changing factors through restructuring. Dinoflagellates predominantly dominate the southern and middle transects, whereas large diatoms make a substantial contribution to the phytoplankton biomass in the northern transect. Diatom biomass is determined by nitrogen concentration. The dependence of dinoflagellate biomass on that of small flagellates confirms the importance of mixotrophic nutrition. A hypothesis is proposed that the most probable criterion for the selective selection of diatoms northward is the half-saturation constant for nitrogen uptake, while for dinoflagellates, it is temperature. Full article

Glaciers play a crucial role in shaping global hydrology and biogeochemical cycles, yet their climate-forced dynamic impact on chemical denudation and solute yields remain poorly understood. This study compiled data on 40 well-documented cationic denudation rates (CDR) from glaciers across Northwest America, the Svalbard/Arctic Canada, Iceland, Greenland, Europe, China-Tibet, Antarctica, and the Himalayas, revealing substantial spatial variability. CDRs ranged from 46 to 4160 meq m⁻² yr⁻¹. Northwest American and Himalayan glaciers exhibited the highest CDRs, with the Himalayan denudation rate exceeding the global average by more than fourfold. The exceptionally high mean chemical weathering intensity (CWI) of 801 meq m⁻³ from the Himalayan glaciers indicate a wide range of geochemical and climatic conditions within the region, while Northwest American and Greenland glaciers show comparatively lower mean intensities (273 and 247 meq m⁻³, respectively) suggesting a consistent geochemical regime. Northwest American glaciers had the highest specific discharge rates, while Svalbard/Arctic Canada glaciers had the lowest, reflecting regional disparities influenced by climatic and geological factors. A Bonferroni post hoc test highlighted significant differences in specific discharge between Northwest American glaciers and two other basins, emphasizing their distinct hydrological behavior. Predictive modeling revealed a statistically significant but weak relationship between CDR and specific discharge (R² = 57%), suggesting that much of the variability in CDR cannot be explained by specific discharge alone. A regression coefficient of 382 meq m⁻² yr⁻¹ indicates that CDR increases with glacier discharge, although basin-specific analyses showed minimal variation in this relationship across regions. Svalbard/Arctic Canada, Antarctic, Greenlandic, Icelandic, and European Alpine glaciers displayed lower CDRs, which varied depending on underlying lithology, with higher rates observed in carbonate and basaltic terrains compared to other lithologies. We hypothesize that glacier retreat enhances the downward progression of the weathering reaction front, increasing CDR, particularly in rapidly retreating glaciers. Full article

This study presents a comprehensive evaluation of the behavior of fluoroelastomer (FKM) compounds reinforced with graphene nanoplatelets of various sizes such as 15 μm (GN15) and 5 μm (GN5). The study evaluates the mechanical, dynamic mechanical, thermal, wetting, and photothermal properties of the compounds when irradiated with an 808 nm laser. The results demonstrate that the size of the graphene nanoplatelets significantly impacts the mechanical properties, with smaller sizes exhibiting a stronger reinforcing effect compared to larger nanoplatelets. Additionally, clear evidence of an influence on dynamic mechanical properties was observed, particularly through the broadening of the damping factor (tan δ) peak. This suggests modifications to the material’s viscoelastic behavior. Regarding the photothermal response, it was found that smaller nanoplatelets (GN5) dispersed in the rubber matrix allow higher temperatures to be reached and thermal equilibrium to be achieved more efficiently under irradiation. Overall, the results suggest that FKM compounds containing graphene nanoplatelets can attain high temperatures with low-energy infrared irradiation. This makes them promising materials for technological applications in extreme environments, such as the Arctic, high mountains, or space, where materials with controlled thermal responses and high mechanical performance are required. Full article

The Surface Extraction by TIN-based Search-space Minimization (SETSM) algorithm provides automatic generation of stereo-photogrammetric Digital Surface Models (DSMs) from single stereopairs of stereoscopic images (i.e., stereopairs), eliminating the need for terrain-dependent parameters. SETSM has been extensively validated through the ArcticDEM and Reference Elevation Models for Antarctica (REMA) DSM mapping projects. To enhance DSM coverage, quality, and accuracy by addressing stereopair occlusions, we expand the capabilities of the SETSM algorithm from single stereopair to multiple-pair matching. Building on SETSM’s essential components, we present a SETSM multiple-pair matching procedure (SETSM MMP) that modifies 3D voxel construction, similarity measurement, and blunder detection, among other components. A novel Three-Dimensional Kernel-based Weighted Height Estimation (3D KWHE) algorithm specialized for SETSM accurately determines optimal heights and reduces surface noise. Additionally, an adaptive pixel-to-pixel matching strategy mitigates the effect of differences in ground sample distance (GSD) between images. Validation using space-borne Worldview-2 and air-borne DMC multiple images over urban landscapes, compared to USGS lidar DSM, confirms improved height accuracy and matching success rates. The results from the DMC air-borne images demonstrate efficient elimination of occlusions. SETSM MMP enables high-quality DSM generation in urban environments while retaining the original, single-stereopair SETSM’s high performance. Full article

Reliable sea ice extent (SIE) information is essential for Arctic navigation, climate research, and resource exploration. Synthetic Aperture Radar (SAR), with its all-weather, high-resolution capabilities, is well suited for SIE extraction. This study evaluates a pan-Arctic SIE product automatically generated from over 85,000 Sentinel-1 SAR images acquired between 2020 and 2023 using an integrated stacking U-Net framework. To validate its performance, all the SIE products are converted to sea ice concentration (SIC) and compared against the 3.125 km resolution Advanced Microwave Scanning Radiometer-2 (AMSR2) SIC products. The S1-derived SIC shows strong agreement with AMSR2 SIC, yielding a Pearson correlation of 0.99 and annual mean absolute differences between 5.93% and 7.85%. Case analyses demonstrate that the S1 products effectively capture small-scale ice features, such as floes, which are often missed by AMSR2. Furthermore, we introduce an Integrated Index to quantify the relative contribution of each sub-model within the integrated stacking U-Net framework. The analysis indicates that three sub-models provide the primary contribution to the ensemble, offering insights into improving integration efficiency and guiding the design of more scientifically grounded ensemble strategies. Full article

This paper addresses the technical requirements and challenges encountered in the design and development of a customised power electronics board for a stratospheric balloon payload. This board includes power conversion and distribution to critical components (e.g., FPGAs and a ±4 kV power supply), as well as the pressurised enclosure designed to house these components along with other essential electronics. These systems were part of two scientific instruments onboard SUNRISE III, a high-altitude solar observatory launched in July 2024 from ESRANGE (Kiruna, Sweden), with a floating trajectory over the Arctic Circle. The SUNRISE III mission, based on a stratospheric balloon, was carried out by an international consortium of research institutions from Germany, Spain, Japan, and the United States, and in collaboration with NASA’s CSBF and the Swedish Space Corporation. Furthermore, this work presents telemetry data from the pressure sensing system of the electronic unit, as well as voltage and current measurements from the power electronics board outputs. These data were recorded during the floating phase of the mission, up to the balloon’s arrival in northern Canada after a successful week of scientific operations. Full article

Arctic warming is expected to alter permafrost landscapes and shift tundra ecosystems from greenhouse gas sinks to sources. We quantified plant biomass and necromass, carbon stocks, and microbial activity across five Low-Arctic tundra sites in the Yana–Indigirka Lowland (Chokurdakh, NE Siberia) during the 2024 growing season. Above- and below-ground plant biomass was measured by harvest adjacent to 50 × 50 m permanent plots; total C and N were determined by dry combustion on an elemental analyzer. Total organic carbon (TOC) stocks were calculated by horizon from TOC (%), bulk density, and thickness. Microbial basal respiration (BR), substrate-induced respiration (SIR), microbial biomass C (MBC), and the metabolic quotient (qCO₂) were assessed in litter/organic (O), peat (T), and mineral gley horizons. Mean above-ground biomass was 15.8 ± 1.5 t ha⁻¹; total living biomass averaged 43.1 ± 1.6 t ha⁻¹. Below-ground biomass exceeded above-ground by 1.73×. Carbon in above-ground, below-ground, and necromass pools averaged 7.8, 12.2, and 12.5 t C ha⁻¹, respectively. Surface organic horizons dominated ecosystem C storage: litter–peat stocks ranged from 234 to 449 t C ha⁻¹, whereas 0–30 cm mineral layers held 18–50 t C ha⁻¹; total (surface + 0–30 cm) stocks spanned 258–511 t C ha⁻¹ among sites. Key contributors to biomass and C storage were deciduous shrubs (Salix pulchra, Betula nana), bryophytes (notably Aulacomnium palustre), and the graminoids (Eriophorum vaginatum). BR and MBC were highest in O and T horizons (BR up to 21.9 μg C g⁻¹ h⁻¹; MBC up to 70,628 μg C g⁻¹) and declined sharply in mineral soil; qCO₂ decreased from O to mineral horizons, indicating more efficient C use at depth. These in situ data show that Low-Arctic tundra C stocks are concentrated in surface organic layers while microbial communities remain responsive to warming, implying high sensitivity of carbon turnover to thaw and hydrologic change. The dataset supports model parameterization and remote sensing of shrub–tussock tundra carbon dynamics. Full article

The Arctic, characterized by extensive ice and snow cover with persistent low solar elevation angles and prolonged polar nights, poses significant challenges for conventional spectral threshold methods in cloud detection and cloud-top thermodynamic phase classification. The study addressed these limitations by combining active and passive remote sensing and developing a machine learning framework for cloud detection and cloud-top thermodynamic phase classification. Utilizing the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) cloud product from 2021 as the truth reference, the model was trained with spatiotemporally collocated datasets from FY3D/MERSI-II (Medium Resolution Spectral Imager-II) and CALIOP. The AdaBoost (Adaptive Boosting) machine learning algorithm was employed to construct the model, with considerations for six distinct Arctic surface types to enhance its performance. The accuracy test results showed that the cloud detection model achieved an accuracy of 0.92, and the cloud recognition model achieved an accuracy of 0.93. The inversion performance of the final model was then rigorously evaluated using a completely independent dataset collected in July 2022. Our findings demonstrated that our model results align well with results from CALIOP, and the detection and identification outcomes across various surface scenarios show high consistency with the actual situations displayed in false-color images. Full article

The Arctic region, one of the most vulnerable areas globally, faces severe climate change impacts, with rising sea levels and temperatures threatening local communities. Modern geoinformation tools provide a reliable, cost-efficient, and time-saving method for assessing these climate changes in Arctic coastal regions. This study focuses on Finland’s Arctic and sub-Arctic diverse coastline. The Coastal Vulnerability Index (CVI) is used to assess the vulnerability of Finland’s coastlines, using advanced geoinformatics tools. Integrating high-resolution data from EMODnet, the National Land Survey of Finland Digital Elevation Model (DEM), and physical sources, the CVI includes six input parameters: geomorphology, coastal slope, shoreline change rates, mean wave height, tidal range, and relative sea-level change. The CVI results reveal pronounced spatial variability: 37% of the coastline is classified with very low vulnerability, primarily in the southern Gulf of Finland, and some northern segments, specifically part of Lapland, exhibit minimal susceptibility to coastal hazards. Conversely, the central Gulf of Bothnia shows high vulnerability (29%), with low and moderate vulnerability zones comprising 27% and 6%, respectively, and very high vulnerability at 1%. This assessment provides essential insights for sustainable coastal management in Finland by offering a replicable model for Arctic coastal assessments. This study supports policymakers and local communities in developing targeted adaptation strategies to enhance resilience against climate-driven coastal hazards. Full article

Variability in the Laptev Sea–East Siberian Sea circulation system modulates freshwater circulation in the Arctic Ocean, yet details of these wind-driven mechanisms remain poorly understood. Based on in situ observations from the 2018 Sino-Russian joint Arctic expedition, this study investigates the modulatory influence of wind on circulation structures and freshwater transport in the study area and examines the long-term variation characteristics of this circulation and its inherent connection with the Arctic wind. In situ measurements confirm two freshwater transport pathways: a coastal-current route and a geostrophic slope-current route. As the Beaufort High moves toward the Canadian Basin, it shifts wind patterns from anticyclonic to cyclonic, which regulates the transport of shelf water by influencing the prevailing wind direction. Furthermore, our analysis identifies two main modes of long-term changes in summer surface circulation: the first mode characterizes the coastal-current architecture, while the second mode delineates slope-current configurations. Crucially, large-scale modes of the Arctic wind play an important role in regulating circulation. Its first mode corresponds to the summer anticyclonic circulation pattern of the Arctic Ocean Oscillation, which drives the eastward strengthening of the coastal current, while the third mode presents a mechanism similar to the Arctic Dipole, which promotes the development of the slope current by enhancing the convergence of the polar current and wind. This has led to the long-term strengthening of the slope current. Full article

The maneuvering performance of ships in marginal ice zones is critical for navigational safety, yet most existing studies focus on icebreaking vessels. This study develops a coupled numerical framework that integrates the Non-Smooth Discrete Element Method (NDEM) for simulating ship–ice interactions with the three-degree-of-freedom MMG model for ship dynamics. The framework was applied to an S175 container ship, and numerical simulations were conducted for turning circle and Zig-Zag maneuvers under varying ice concentrations (0–60%), floe sizes, and rudder angles. NDEM efficiently handles complex, high-frequency multi-body collisions with larger time steps compared to conventional DEM or CFD–DEM approaches, enabling large-scale simulations of realistic ice conditions. Results indicate that increasing ice concentration from 0% to 60% reduces the turning diameter from 4.11L to 3.21L and decreases steady turning speed by approximately 53%. Larger floes form stable force chains that restrict lateral motion, while higher rudder angles improve responsiveness but may induce dynamic instability. These findings improve understanding of non-icebreaking ship maneuverability in ice and provide practical guidance for safe and efficient Arctic navigation. Full article

With the expansion of offshore and subsea infrastructure in Arctic and sub-Arctic regions, concerns are rising, driven by climate change and global warming, over the risk of drifting icebergs colliding with these structures in cold waters. Traditional methods for estimating iceberg underwater height and assessing subgouge soil properties, such as costly and time-consuming underwater surveys or centrifuge tests, are still used, but the industry continues to seek faster and more cost-efficient solutions. In this study, the extra tree regression (ETR) algorithm was employed for the first time to simultaneously model iceberg drafts and subgouge soil properties in both sandy and clay seabeds. The ETR approach first predicted the iceberg draft, then simulated subgouge soil reaction forces and deformations. A total of 22 ETR models were developed, incorporating parameters relevant to both iceberg draft estimation and subgouge soil characterization. The best-performing ETR models, along with the most influential input variables, were identified through a combination of sensitivity, error, discrepancy, and uncertainty analyses. The ETR model predicted iceberg draft with a high level of accuracy (R = 0.920, RMSE = 1.081), while the superior model for vertical reaction force in sand achieved an RMSE of 43.95 with 70% of predictions within 16% error. The methodology demonstrated improved prediction capacity over traditional techniques and can serve early-stage iceberg risk management. Full article

The information on the seasonal variability of the chemical composition of the Arctic rivers is necessary for the proper assessment of the status of river runoff and the influence of anthropogenic and natural factors. Spring freshet is an especially important period for the Arctic rivers with a sharp maximum of water discharge. The Kolyma River is the least studied large river with a basin located solely in the permafrost zone. The change in the concentration of dissolved organic carbon (DOC), major, trace, and rare earth (RE) elements was studied at the peak and waning of the spring freshet of 2024 in the lower reaches of the Kolyma River. The concentration of elements was determined in filtrates <0.45 μm and in suspended solids > 0.45 μm. The content of coarse colloids (0.05–0.45 μm) was estimated by the intensity of dynamic light scattering (DLS). It was shown that the freshet peak is characterized by a minimal specific conductivity, concentration of major cations, and chemical elements migrating mainly in solution (Li, Sr, and Ba). During the freshet decline, the concentration of these elements increases with dynamics depending on the water exchange. The waters from the Kolyma River main stream have a maximal content of coarse colloids and concentration of <0.45 μm forms of hydrolysates (Al, Ti, Fe, Mn, REEs, Zr, Y, Sc, and Th), DOC, P, and heavy metals (Cu, Ni, Cd, and Co) at the freshet peak. A decrease of 8–10 times for hydrolysates and coarse colloids (0.05–0.45 μm) and of 3–6 times for heavy metals was observed at the freshet waning during the first half of June. This indicates a large-scale accumulation of easy soluble forms of hydrolysates, DOC, and heavy metals in the seasonal thawing topsoil layer on the catchment upstream in the previous summer, with a flush out of these elements at the freshet peak of the current year. In the large floodplain watercourse Panteleikha River, the change in concentration of major cations and REEs, Zr, Y, Sc, and Th at the freshet is less accented compared with the Kolyma River main stream due to a slower water exchange. Yet, <0.45 μm forms of Fe, Mn, Co, As, V, and P show an increase of 4–6 times in the Panteleikha River in the second half of June compared with the freshet peak, which indicates an additional input of these elements from the thawing floodplain landscapes and bottom sediments of floodplain watercourses. The concentration of the majority of chemical elements in suspended matter (>0.45 μm) of the Kolyma River is rather stable during the high-water period. The relative stability in the chemical composition of the suspended solids means that the content of the suspension and not its composition is the key to the share of dissolved and suspended forms of chemical elements in the Kolyma River runoff. Full article

This study evaluates three wind data sources in East Iceland’s coastal environment: the high-resolution Synthetic Aperture Radar (SAR)-based Sentinel-1, the regional reanalysis Copernicus Arctic Regional Reanalysis (CARRA), and the global reanalysis ECMWF Reanalysis v5 (ERA5). We focus on assessing the advantages and limitations of each dataset, especially considering their differences in spatial and temporal resolutions. While ERA5 aligns well with CARRA and Sentinel-1 offshore, it tends to underestimate wind speeds and misrepresent wind directions near complex coastlines and fjords, with Root Mean Squared Difference (RMSD) values reaching up to 3.98 m/s in these areas. CARRA’s higher resolution allows it to better capture coastal wind dynamics and shows strong agreement with Sentinel-1. Sentinel-1 excels in revealing detailed local wind features, such as katabatic winds in fjords, highlighting the value of satellite observations in complex terrain. By combining these complementary datasets, this study enhances understanding of coastal wind variability and supports improved hazard assessment in Iceland’s challenging coastal environments. Full article