Sea ice mapping method for SeaWinds

Anderson, Hyrum S.; Long, D.G.

doi:10.1109/tgrs.2004.842017

Cited by 45 publications

(10 citation statements)

References 13 publications

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“…Earlier, the factor of anisotropy k a [28] or backscatter derivative k d [29] have been used for that. Later discrimination methods using the lowest statistical distance between the measured NRCS values and GMFs of the sea ice or water [30], or Bayesian approaches [10,31,32] have also been proposed.…”

Section: Methodsmentioning

confidence: 99%

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

et al. 2020

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Following the mission science plan of EPS/Metop-SG C-band scatterometer for 2023–2044, we consider the potential application of the sea ice/water discrimination method based on the minimum statistical distance of the measured normalized radar cross sections (NRCS) to the geophysical model functions (GMF) of the sea ice and water, respectively. The application of the method is considered for the classical spacecraft scatterometer geometry with three fixed fan-beam antennas and the hypothetical prospective scatterometer geometry with the five fixed fan-beam antennas. Joint vertical (VV) and horizontal (HH) transmit and receive polarization are considered for the spaceborne scatterometer geometries. We show explicitly that the hypothetical five fixed fan-beam antenna geometry combined with the dual VV and HH polarization for all antennas provides better estimates of the sea wind speed and direction as well as sea ice/water discrimination during single spacecraft pass. The sea ice/water discrimination algorithms developed for each scatterometer geometry and dual VV/HH polarization are presented. The obtained results can be used to optimize the design of new spaceborne scatterometers and will be beneficial to the forthcoming satellite missions.

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Section: Methodsmentioning

confidence: 99%

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

et al. 2020

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“…Bayesian statistics has been applied, e.g., for the QuikSCAT, ASCAT, and ERS scatterometers, to suggest and implement sea ice detection algorithms based on this approach [3,14,25]. Another Bayesian approach, developed earlier for the SeaWinds instrument, can be found in earlier work [26].…”

Section: Methodsmentioning

confidence: 99%

On Sea Ice Measurement by a C-Band Scatterometer at VV Polarization: Methodology Optimization Based on Computer Simulations

et al. 2019

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We consider sea ice and water microwave backscatter features at the C-band with vertical transmit and receive polarization and present a method for sea ice/water discrimination using a multiple fixed fan-beam satellite scatterometer. The method is based on the criterion of the minimum statistical distance of measured backscatter values to the sea ice and water (CMOD7) geophysical model functions. Implementation of the method is considered both for a typical three fan-beam geometry as well as for a potential five fan-beam geometry of a satellite scatterometer. By using computer simulations, we show explicitly that the number of looks at the same cell from different azimuthal directions needs to be increased to provide better (unambiguous) retrieval of the wind vector and sea ice/water discrimination. The algorithms for sea ice/water discrimination are described, and the results obtained are also discussed along with recommendations for the number of different azimuthal looks (beams) at the same cell from the point of view of sea ice/water discrimination as well as unambiguous wind direction retrieval during the satellite’s single pass.

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“…Discrimination of the sea ice from water and estimation of both sea ice age and extent are based on differences between their NRSCs [12]. To perform the sea ice/water discrimination, there are several previously developed approaches, based on the anisotropy factor analysis [13], on the backscatter derivative estimate [14], on the minimum statistical distance between the measured NRCS values and the ice or water GMFs [15], as well as Bayesian-based approaches [16], [17] that are utilized either separately or in combination. Most of these methods have been implemented for the spaceborne scatterometers only.…”

Section: B Sea Ice/water Discriminationmentioning

confidence: 99%

On Sea Ice/Water Discrimination by Airborne Weather Radar

et al. 2020

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We consider a conceptual approach for the applicability of airborne weather radar for the sea ice/water discrimination and estimation of the sea ice age. The sea ice/water discrimination method suited for the airborne weather radar utilization is based on finding the minimum statistical distance of the measured normalized radar cross sections within a wide azimuth sector to the geophysical model functions of the sea ice and water, respectively. The sea ice age classification is based on the comparison of the normalized radar cross section value at a given incidence angle to the lower normalized radar cross section boundaries for the first-, second-, and multi-year ice. Implementation of the proposed methodology is considered for the C-band airborne weather radar operated in the ground mapping mode as a scatterometer scanning in a wide azimuth sector up to ±100°. We show explicitly that the proposed approach provides the enhancement of the conventional airborne weather radar functionality for the sea ice/water discrimination and sea ice age estimation either using stand-alone or joint measurements.

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Sea ice mapping method for SeaWinds

Cited by 45 publications

References 13 publications

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

Towards the Sea Ice and Wind Measurement by a C-Band Scatterometer at Dual VV/HH Polarization: A Prospective Appraisal

On Sea Ice Measurement by a C-Band Scatterometer at VV Polarization: Methodology Optimization Based on Computer Simulations

On Sea Ice/Water Discrimination by Airborne Weather Radar

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