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The Arctic is experiencing the greatest increase in air temperature on Earth. This significant climatic change is leading to a significant positive trend of increasing wave heights and greater coastal erosion. This in turn effects local economies and ecosystems. Increasing wave energy is one of the main drivers of this alarming trend. However, the data on spatial and temporal patterns of wave heights in the Arctic are either coarse, interpolated or limited to point measurements. The aim of this study is to overcome this shortcoming by using remote sensing data. In this study, the Synthetic Aperture Radar (SAR) satellite TerraSAR-X (TS-X) and TanDEM-X (TD-X) imagery are used to obtain sea state information with a high spatial resolution in Arctic nearshore waters in the Canadian Beaufort Sea. From the entire archive of the TS-X/TD-X StripMap mode with coverage around 30 km × 50 km acquired between 2009 and 2020 around Herschel Island, Qikiqtaruk (HIQ), all the ice-free scenes were processed. The resulting dataset of 175 collocated scenes was used to map the significant wave height ( H s ) and to link spatial and temporal patterns to local coastal processes. Sea state parameters are estimated in raster format with a 600 m step using the empirical algorithm CWAVE_EX. The statistics of the H s were aggregated according to spatial variability, seasonality and wind conditions. The results show that the spatial wave climate is clearly related to the dominant wind regime and seasonality. For instance, the aggregation of all the scenes recorded in July between 2009 and 2020 results in an average of 0.82 m H s , while in October the average H s is almost 0.40 m higher. The analysis by wind direction shows that fetch length and wind speed are likely the most important variables influencing the spatial variability. A larger fetch under NW conditions results in a mean wave height of 0.92 m, while waves generated under ESE conditions are lower at 0.81 m on average. [ABSTRACT FROM AUTHOR]

Climate change has reduced global ice mass over the last 2 decades as enhanced warming has accelerated surface melt and runoff rates. Glaciers have undergone dynamic processes in response to a warming climate that impacts the surface geometry and mass distribution of glacial ice. Until recently no single technique could consistently measure the evolution of surface flow for an entire glaciated region in three dimensions with high temporal and spatial resolution. We have improved upon earlier methods by developing a technique for mapping, in unprecedented detail, the temporal evolution of glaciers. Our software computes north, east, and vertical flow velocity and/or displacement time series from the synthetic aperture radar (SAR) ascending and descending range and azimuth speckle offsets. The software can handle large volumes of satellite data and is designed to work on high-performance computers (HPCs) as well as workstations by utilizing multiple parallelization methods. We then compute flow velocity–displacement time series for glaciers in southeastern Alaska during 2016–2021 and observe seasonal and interannual variations in flow velocities at Seward and Malaspina glaciers as well as culminating phases of surging at Klutlan, Walsh, and Kluane glaciers. On a broader scale, this technique can be used for reconstructing the response of worldwide glaciers to the warming climate using archived SAR data and for near-real-time monitoring of these glaciers using rapid revisit SAR data from satellites, such as Sentinel-1 (6 or 12 d revisit period) and the forthcoming NISAR mission (12 d revisit period). [ABSTRACT FROM AUTHOR]

Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar – SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015–2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle (>30∘) with a high topographic wetness index (TWI) (>7.0) showed correlation between SD and CPD (R2 up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types. [ABSTRACT FROM AUTHOR]

The Synthetic Aperture Laboratory at Simon Fraser University has recently acquired an experimental airborne miniature SAR sensor. The small (ca. 10x20x40 cm^3) sensor was developed to our specifications by Artemis Inc based on their SlimSAR line heritage. The SARlab's SlimSAR is a dual frequency (X- and L-band) pulsed SAR system with chirp bandwidths providing slightly better than 1 meter range resolution at both bands. There are two monostatic fully polarimetric L-band patch antennas, mounted in an along-track InSAR (ATI) configuration (2 x 4 channels), and three bi-static X-band horn antennas mounted across-track for single-pass acquisition (2 channels). The system can operate any combination of maximum 6 channels simultaneously, so e.g. we can acquire single pass X-band and fully polarimetric L-band on the same flight trajectory. Transmit power (60 W at L-band and 25 W at X-band) allows flying heights up to 2000 m above ground level with reasonable SNR for most surfaces. The system includes an IMU/GNSS module allowing accurate mocomp and after differential processing also repeat pass InSAR at L-band. A first comprehensive demonstration test of the SARlab SlimSAR using a helio courier aircraft as platform was conducted from 30 August to 3 September 2018 over areas in and around Kluane National Park, Yukon. We will present preliminary analysis results of the acquired datasets covering a variety of phenomena, glaciers, landslides, tundra and forest terrains, airfields and roads, and water surface over Kluane Lake. Data configuration examples span (alone or in combination) single pass DEMs, polarimetry, ATI, and repeat pass InSAR. We will show encountered challenges during raw data focusing with back propagation time domain processing algorithms and how they can be overcome by using differentially processed IMU/GNSS and autofocus algorithms and mocomp on multiple SAR channels simultaneously. In addition, we will present initial results of polarimetric decomposition-based classification as well as single- and repeat-pass InSAR examples. We will outline our plans for accurate calibration next field season using artificial targets and simultaneous spaceborne data acquisitions (TerraSAR-X, ALOS-2, Sentinel-1). [ABSTRACT FROM AUTHOR]