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The presence of melt ponds on the surface of Arctic Sea ice affects its albedo, thermal properties, and overall melting rate; thus, the detection of melt pond onset is of significant importance for understanding the Arctic's changing climate. This study investigates the utility of a novel method for detecting the onset of melt ponds on sea ice using a satellite-based, dual-sensor C-band approach, whereby Sentinel-1 provides horizontally polarized (HH) data and Advanced SCATterometer (ASCAT) provides vertically polarized (VV) data. The co-polarized ratio (VV/HH) is used to detect the presence of melt ponds on landfast sea ice in the Canadian Arctic Archipelago in 2017 and 2018. ERA-5 air temperature and wind speed re-analysis datasets are used to establish the VV/HH threshold for pond onset detection, which have been further validated by Landsat-8 reflectance. The co-polarized ratio threshold of three standard deviations from the late winter season (April) mean co-pol ratio values are used for assessing pond onset detection associated with the air temperature and wind speed data, along with visual observations from Sentinel-1 and cloud-free Sentinel-2 imagery. In 2017, the pond onset detection rates were 70.59% for FYI and 92.3% for MYI. Results suggest that this method, because of its dual-platform application, has potential for providing large-area coverage estimation of the timing of sea ice melt pond onset using different earth observation satellites. [ABSTRACT FROM AUTHOR]

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This paper presents a case study of C-band backscatter observations of snow during a Chinook event. A surface-based C-band polarimetric data set collected in February 2006 is used to contrast the polarimetric response to sampled conditions of bare frozen ground, cold snow-covered ground, and snow during a Chinook event. Chinook activity is inherently spatially and temporally variable across the region in winter and produces considerable spatial variability of snow-cover physical properties associated with snow--water-equivalent (SWE) estimates. A temporal analysis of polarimetric backscatter sensed during a Chinook-induced ablation event on February 27, 2006 is used to describe the associated changes in snow conditions and scattering mechanisms. Analysis reveals that the polarimetric surface-based C-band scatterometer data respond to changes in snow parameters associated with the specific ground and snow conditions and to the temporal Chinook ablation event. Use of the copolarizations, cross-polarization, depolarization ratio, copolarization ratio, complex copolarization correlation coefficient, and the copolarized phase difference information show promise in describing changes in snow physical parameters, differing ground and snow conditions, and transitional ablation events, based on differing scattering mechanisms. This paper infers that an increase in volume scattering and fluctuations in surface scattering during the Chinook ablation event may be associated with specific physical changes such as density, crystal structure, and permittivity caused by wind speed. This paper has implications for remotely sensed estimations of snow-covered area (SCA) and SWE. Association of SCA and SWE with backscatter coefficients is not explicit in this paper; however, changes in SWE and snow properties are inferentially linked to changes in backscatter. Index Terms--Chinook, radar polarimetry, radar scattering, snow ablation, snow-covered area (SCA), snow--water equivalent (SWE).

Wind transport alters the snow topography and microstructure on sea ice through snow redistribution controlled by deposition and erosion. The impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution on Arctic sea ice from Ka- and Ku-band radar signatures. Measurements were obtained during two wind events in November 2019 during the MOSAiC expedition. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coincident with surface height changes measured from a terrestrial laser scanner are observed. At both frequencies, snow redistribution events increased the dominance of the air/snow interface at nadir as the dominant radar scattering surface, due to wind densifying the snow surface and uppermost layers. The radar waveform data also detect 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 radar altimeters. The relative scattering contribution of the air/snow interface decreases, and the snow/sea ice interface increases with increasing incidence angles. Relative to pre-wind conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Binned backscatter within 5° azimuth bins reveals substantial backscatter variability in the radar footprint at all incidence angles and polarizations. The sensitivity of the co-polarized phase difference is linked to changes in snow settling and temperature-gradient induced grain metamorphism, demonstrating the potential of the radar to discriminate between newly deposited and older snow on sea ice. Our results reveal the importance of wind, through its geophysical impact on Ka- and Ku-band radar signatures of snow on sea ice and has implications for reliable interpretation of airborne and satellite radar measurements of snow-covered sea ice. [ABSTRACT FROM AUTHOR]

The thermodynamic state of sea ice is important to accurately and remotely monitor in order to provide improved geophysical variable parameterizations in sea ice thermodynamic models. Operationally, monitoring the thermodynamic state of sea ice can facilitate eased ship navigation routing. SeaWinds/QuikSCAT (QuikSCAT) dual-polarization [i.e., horizontal (HH) and vertical (VV)] active microwave data are available at a sufficiently large spatial scale and high temporal resolution to provide estimates of sea ice thermodynamics. This analysis evaluated the temporal evolution of the backscatter coefficient ([[sigma].sup.[degrees]]) and VV/HH copolarization ratio from QuikSCAT for estimating sea ice thermodynamics. QuikSCAT estimates were compared against RADARSAT-1 synthetic aperture radar (SAR) imagery and the Canadian Ice Service (CIS) prototype operational ice strength algorithm. In situ data from the Collaborative Interdisciplinary Cryospheric Experiment (C-ICE) for 2000, 2001, and 2002 were used as validation. Results indicate that the temporal evolution of [[sigma].sup.[degrees]] from QuikSCAT is analogous to RADARSAT-1. The QuikSCAT ([[sigma].sup.[degrees]] temporal evolution has the ability to identify winter, snow melt, and ponding thermodynamic states. Moreover, the copolarization VV/HH ratio of QuikSCAT could provide a second estimate of the ponding state in addition to identifying the drainage state that is difficult to detect by single-polarization SAR. QuikSCAT detected thermodynamic states that were found to be in reasonable agreement to that of in situ observations at the C-ICE camp for all years. Operational implications of this analysis suggest QuikSCAT is a more effective and efficient medium for monitoring ice decay compared to RADARSAT-1 and can be utilized to provide more robust modeled ice strength thresholds. Index Terms--Canadian Ice Service (CIS), copolarization, ice decay, QuikSCAT, RADARSAT-1, remote sensing, sea ice, SeaWinds, synthetic aperture radar (SAR).