Jack C. Landy
University of Manitoba
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Publication
Featured researches published by Jack C. Landy.
Journal of Geophysical Research | 2014
Jack C. Landy; Jens K. Ehn; Megan Shields; David G. Barber
The evolution of landfast sea ice melt pond coverage, surface topography, and mass balance was studied in the Canadian Arctic during May–June 2011 and 2012, using a terrestrial laser scanner, snow and sea ice sampling, and surface meteorological characterization. Initial melt pond formation was not limited to low-lying areas, rather ponds formed at almost all premelt elevations. The subsequent evolution of melt pond coverage varied considerably between the 2 years owing to four principle, temporally variable factors. First, the range in premelt topographic relief was 0.5 m greater in 2011 (rougher surface) than in 2012 (smoother surface), such that a seasonal maximum pond coverage of 60% and maximum hydraulic head of 204 mm were reached in 2011, versus 78% and 138 mm in 2012. A change in the meltwater balance (production minus drainage) caused the ponds to spread or recede over an area that was almost 90% larger in 2012 than in 2011. Second, modification of the premelt topography was observed during mid-June, due to preferential melting under certain drainage channels. Some of the lowest-lying premelt areas were subsequently elevated above these deepening channels and unexpectedly became drained later in the season. Third, ice interior temperatures remained 1–2°C colder later into June in 2012 than in 2011, even though the ice was 0.35 m thinner at melt onset, thereby delaying permeability increases in the ice that would allow vertical meltwater drainage to the ocean. Finally, surface melt was estimated to account for approximately 62% of the net radiative flux to the sea ice cover during the melt season.
IEEE Transactions on Geoscience and Remote Sensing | 2014
Dustin Isleifson; R. J. Galley; David G. Barber; Jack C. Landy; Alexander S. Komarov; Lotfollah Shafai
A focused study on the C-band polarimetric scattering and physical characteristics of frost-flower-covered sea ice was conducted at the Sea-Ice Environmental Research Facility over a three day period. Sea ice was grown in an outdoor pool outfitted with automated sensors to monitor environmental conditions. C-band polarimetric scattering measurements were conducted continuously at a range of incidence angles, and surface roughness statistics were obtained at discrete times using a laser scanner system LiDAR. Four stages of development were identified that exhibited notably different physical and scattering characteristics: 1) initial formation; 2) surface brine expulsion; 3) frost flower growth; and 4) decimation. An optimal polarization and incidence angle is not readily apparent for the purposes of identifying the frost flower development Stages I-III; however, the lower incidence angles (25° and 35°) appear to be most sensitive to the surface brine expulsion. Only the dual-polarization measurements at low incidence angles (e.g., 25°) could be used to identify the onset of the decimation stage. Backscatter increased rapidly during the initial formation, with a local maximum corresponding to ~ 80% areal coverage of frost flowers, followed by a local minimum when the surface was covered by a brine-rich surface layer, connoting that surface brine expulsion may be identified using polarimetric scatterometry.
IEEE Transactions on Geoscience and Remote Sensing | 2015
Jack C. Landy; Dustin Isleifson; Alexander S. Komarov; David G. Barber
Microwave scattering from sea ice is partially controlled by the ice surface roughness. In this paper, we propose a technique for calculating 2-D centimeter-scale surface roughness parameters, including the rms height, correlation length, and form of autocorrelation function, from 3-D terrestrial light detection and ranging data. We demonstrate that a single scale of roughness can be extracted from complex sea ice surfaces, incorporating multiple scales of topography, after sophisticated 2-D detrending, and calculate roughness parameters for a wide range of artificial and natural sea ice surface types. The 2-D technique is shown to be considerably more precise than standard 1-D profiling techniques and can therefore characterize surface roughness as a stationary single-scale process, which a 1-D technique typically cannot do. Sea ice surfaces are generally found to have strongly anisotropic correlation lengths, indicating that microwave scattering models for sea ice should include surface spectra that vary as a function of the azimuthal angle of incident radiation. However, our results demonstrate that there is no fundamental relationship between the rms height and correlation length for sea ice surfaces if the sampling area is above a threshold minimum size.
IEEE Transactions on Geoscience and Remote Sensing | 2015
Jack C. Landy; Alexander S. Komarov; David G. Barber
Terrestrial light detection and ranging (LiDAR) offers significant advantages over conventional techniques for measuring the centimeter-scale surface roughness of natural surfaces, such as sea ice. However, the laser scanning technique is inherently limited, principally by the following: 1) the high inclination scanning angle of the sensor with respect to nadir; 2) the precision of the laser ranging estimate; and 3) the beam divergence of the laser. In this paper, we introduce a numerical model that has been designed to simulate the acquisition of LiDAR data over a regular rough surface. Results from the model compare well (r2 = 0.97) with LiDAR observations collected over two experimental surfaces of known roughness that were constructed from medium-density fibreboard using a computer numerical control three-axis router. The model demonstrates that surface roughness parameters are not sensitive to minor variations in the LiDAR sensors range and laser beam divergence, but are slightly sensitive to the precision of the ranging estimate. The model also demonstrates that surface roughness parameters are particularly sensitive to the inclination angle of the LiDAR sensor. The surface RMS height is underestimated, and the correlation length is overestimated as either the inclination angle of the sensor or the true roughness of the surface increases. An isotropic surface is also increasingly observed as an anisotropic surface as either the inclination angle or the true surface roughness increases. Based on the model results, we propose a set of calibration functions that can be used to correct in situ LiDAR measurements of surface roughness.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | 2015
Nariman Firoozy; Alexander S. Komarov; Jack C. Landy; David G. Barber; Puyan Mojabi; Randall K. Scharien
For the microwave remote sensing of snow-covered sea ice dielectric profiles, the sensitivity of the normalized radar cross-section data with respect to the complex permittivity and thickness values is investigated. Our results show that the data collected closer to the nadir in monostatic setups, and the data collected closer to the specular angle in bistatic setups represent higher sensitivity values. Using both synthetically and experimentally collected data sets, we demonstrate that the inversion of data sets having higher sensitivity values results in enhanced reconstruction accuracy.
IEEE Journal of Oceanic Engineering | 2016
Nariman Firoozy; Alexander S. Komarov; Puyan Mojabi; David G. Barber; Jack C. Landy; Randall K. Scharien
This paper utilizes an electromagnetic inverse-scattering algorithm to quantitatively reconstruct the vertical temperature and salinity profiles of snow-covered sea ice from time-series monostatic polarimetric normalized radar cross-section (NRCS) data. The reconstructed profile at a given time step is utilized to provide a priori information for the profile reconstruction at the subsequent time step. This successive use of a priori information in the inversion algorithm results in achieving high reconstruction accuracy over the time period of interest. This inversion scheme is evaluated against the experimental data collected from snow-covered sea ice grown in an Arctic ocean mesocosm facility. It will be shown that the time evolution of the temperature, salinity, and density profiles of an artificially grown snow-covered sea ice can be quantitatively reconstructed using single-frequency time-series radar cross-section data assuming that these profiles are initially known with sufficient accuracy.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | 2016
Nariman Firoozy; Puyan Mojabi; Jack C. Landy; David G. Barber
The inversion of the monostatic normalized radar cross section (NRCS) data collected by an on-site C-band scatterometer and also RADARSAT-2 satellite are investigated to reconstruct some parameters of interest associated with landfast snow-covered sea ice in Cambridge Bay, Nunavut, Canada. The parameters of interest are temperature, density, salinity, and snow grain size. To this end, this remote sensing problem is cast as an inverse scattering problem in which a data misfit cost functional is to be minimized using a differential evolution algorithm. This minimization requires repetitive calls to an appropriate electromagnetic forward solver. The utilized electromagnetic forward solver attempts to model both surface and volume scattering components associated with the irradiated rough multilayered medium under investigation. The reconstruction results demonstrate the ability of this inversion algorithm to retrieve the parameters of interest with reasonable accuracy. In particular, the best performance of the inversion algorithm occurs when both the scatterometer and satellite NRCS data are simultaneously used in the inversion process.
Geophysical Research Letters | 2017
Karley Campbell; C. J. Mundy; Michel Gosselin; Jack C. Landy; A. Delaforge; Søren Rysgaard
The balance of photosynthesis and respiration by organisms like algae and bacteria determines whether sea ice is net heterotrophic or autotrophic. In turn this clarifies the influence of microbes on atmosphere-ice-ocean gas fluxes, and their contribution to the trophic system. In this study we define two phases of the spring bloom based on bottom-ice net community production and algal growth. Phase I was characterized by limited algal accumulation and low productivity, which at times resulted in net heterotrophy. Greater productivity in Phase II drove rapid algal accumulation that consistently produced net autotrophic conditions. The different phases were associated with seasonal shifts in light availability and species dominance. Results from this study demonstrate the importance of community respiration on spring productivity, as respiration rates can maintain a heterotrophic state independent of algal growth. This challenges previous assumptions of a fully autotrophic sea ice community during the ice-covered spring
IEEE Transactions on Geoscience and Remote Sensing | 2017
Nariman Firoozy; Thomas Neusitzer; Durell Desmond; Tyler Tiede; Marcos Lemes; Jack C. Landy; Puyan Mojabi; Søren Rysgaard; Gary A. Stern; David G. Barber
This paper presents a multidisciplinary case study on a crude oil injection experiment in an artificially grown young sea ice environment under controlled conditions. In particular, the changes in the geophysical and electromagnetic responses of the sea ice to oil introduction are investigated for this experiment. Furthermore, we perform a preliminary study on the detection of oil spills utilizing the normalized radar cross section (NRCS) data collected by a C-band scatterometer is presented. To this end, an inversion scheme is introduced that retrieves the effective complex permittivity of the domain prior and after oil injection by comparing the simulated and calibrated measured NRCS data, while roughness parameters calculated using lidar are utilized as prior information. Once the complex permittivity values are obtained, the volume fraction of oil within the sea ice is found using a mixture formula. Based on this volume fraction, a binary detection of oil presence seems to be possible for this test case. Finally, the possible sources of error in the retrieved effective volume fraction, which is an overestimate of the actual value, are identified and discussed by macrolevel and microlevel analyses through bulk salinity measurements and X-ray imagery of the samples, as well as a brief chemical analysis.
Remote Sensing | 2018
Dustin Isleifson; R. J. Galley; Nariman Firoozy; Jack C. Landy; David G. Barber
A dedicated study on the physical characteristics and C-band scattering response of frost-flower-covered sea ice was performed in an artificial sea ice mesocosm over a 36-h period in January 2017. Meteorological conditions were observed and recorded automatically at the facility when the sea ice grew and frost flowers formed while the C-band scattering measurements were conducted continuously over a range of incidence angles. Surface roughness was characterized using a LiDAR. During the experiment, frost flowers did not initially form on the extremely smooth ice surface even though suitable meteorological conditions prevailed during their development (low air temperature, low near-surface wind speed, and high near-surface relative humidity). This provides evidence that both the presence of (i) liquid brine at the surface and (ii) raised nodules as nucleation points are required to enable frost flower initiation. As the ice thickened, we observed that raised nodules gradually appeared, frost flowers formed, and flowers subsequently spread to cover the surface over a six-hour period. In contrast to previous experiments, the frost flower layer did not become visibly saturated with liquid brine. The C-band scattering measurements exhibited increases as high as 14.8 dB (vertical polarization) in response to the frost flower formation with low incidence angles (i.e., 25°) showing the largest dynamic range. Co-polarization ratios responded to the physical and thermodynamic changes associated with the frost flower formation process. Our results indicate that brine expulsion at the sea ice surface and frost flower salination can have substantial temporal variability, which can be detected by scatterometer time-series measurements. This work contributes towards the operational satellite image interpretation for Arctic waters by improving our understanding of the highly variable C-band microwave scattering properties of young sea ice types.