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Sea Ice Concentration from the RADARSAT Constellation Mission for Numerical Sea Ice Prediction

2021 IEEE 19th International Symposium on Antenna Technology and Applied Electromagnetics (ANTEM), 2021
In this study, our technique for automated extraction of sea ice concentration from RADARSAT-2 data was adapted to the recently launched RADARSAT Constellation mission (RCM). Ice concentrations were derived from more than 2,600 RCM images acquired between August 1, 2020 and March 31, 2021.
Mark Buehner, Alexander Komarov
openaire   +2 more sources

Assimilation of Satellite-Retrieved Sea Ice Concentration and Prospects for September Predictions of Arctic Sea Ice

Journal of Climate, 2021
AbstractThe current GFDL seasonal prediction system achieved retrospective sea ice extent (SIE) skill without direct sea ice data assimilation. Here we develop sea ice data assimilation, shown to be a key source of skill for seasonal sea ice predictions, in GFDL’s next-generation prediction system, the Seamless System for Prediction and Earth System ...
Mitchell Bushuk   +8 more
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Oscillatory behavior in Arctic sea ice concentrations

Journal of Geophysical Research: Oceans, 1996
We have done a frequency analysis of the 9‐year record of sea ice concentrations obtained with the NASA Nimbus 7 scanning multichannel microwave radiometer (SMMR). Because of the periodic revisit time of the SMMR, we are able to examine recurrence of shorter‐period oscillations, as aliased by the revisit frequency, and longer‐period oscillations per se.
Jun Yu   +2 more
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A Note on the Determination of Sea Ice Concentration

Journal of Offshore Mechanics and Arctic Engineering, 1991
Abstract An argument is presented for the inclusion of diffusive effects in the equation governing the redistribution of sea ice. An ice concentration equation including diffusion is derived through Reynold’s averaging. This advection-diffusion equation is solved using the Eulerian-Lagrangian time-splitting technique, which affords both ...
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SAR Algorithm for Sea Ice Concentration—Evaluation for the Baltic Sea

IEEE Geoscience and Remote Sensing Letters, 2012
A new sea ice concentration algorithm has been developed for C-band synthetic aperture radar data. Detailed autocorrelation statistics are derived and adopted by the algorithm, and a neural network is utilized for training against 41 sea ice charts. The charts are produced by ice analysts at the Swedish Ice Service and cover the Baltic Sea.
Anders Berg, Leif E. B. Eriksson
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Seasonal variations in sea ice motion and effects on sea ice concentration in the Canada Basin

Journal of Geophysical Research: Oceans, 1989
Drifting buoy data, surface pressure, and geostrophic wind analyses from the Arctic Ocean Buoy Program are used to examine seasonal features of the sea ice motion in the Canada Basin for 1979–1985. Although the 7‐year annual mean motion in this region is clockwise, the month‐to‐month motion is highly variable.
Alfred S. McLaren   +2 more
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Climatic trends of sea surface temperature and sea ice concentration in the Barents Sea

2021
<p>Sea ice loss in the Arctic region is an important indicator for climate change. Especially in the Barents Sea, which is expected to be free of ice by the mid of this century (Onarheim et al., 2018). Here, we analyze 38 years (1982-2019) of daily gridded sea surface temperature (SST) and sea ice concentration (SIC) from the Operational ...
Bayoumy Mohamed   +2 more
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Temporal mixture analysis of SMMR sea ice concentrations [PDF]

open access: possibleIGARSS '96. 1996 International Geoscience and Remote Sensing Symposium, 2002
Introduces the idea of temporal mixture analysis (TMA) for analyzing long sequences of hypertemporal remote sensing imagery. The basis of this approach is spectral mixture analysis, which the authors adapt from the spectral domain to the time domain and apply it to a 9-year record of sea ice concentrations in the Northern Hemisphere.
Derek R. Peddle   +2 more
openaire   +1 more source

Response of passive microwave sea ice concentration algorithms to thin ice

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
The influence of sea ice thickness brightness temperatures and ice concentrations retrieved from passive microwave observations is quantified, using horizontally homogeneous sea ice thickness retrievals from ESA's SMOS sensor observations at high incidence angles.
Natalia Ivanova   +4 more
openaire   +1 more source

Monthly average polar sea-ice concentration

Data Series, 1995
This data set represents the results of calculations carried out on sea-ice-concentration data from the SMMR and SSM/I instruments. The original data were obtained from the National Snow and Ice Data Center (NSIDC). The data set also contains the source code of the programs that made the calculations.
openaire   +2 more sources

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