Wind retrieval over the ocean using synthetic aperture radar with C-band HH polarization

Horstmann, Jochen; Koch, Wolfgang; Lehner, Susanne; Tonboe, Rasmus

doi:10.1109/36.868871

Cited by 201 publications

(100 citation statements)

References 18 publications

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“…In all but one of the wind speed intervals the directional error is larger when only the land is filtered out. The large impact of the filtering at low wind speeds is due to the high frequency of disturbing image features in these situations (Donelan and Pierson 1987;Lehner et al 2000). In total, the increase of the standard deviation for all wind speeds seems to be small, but the additional variance introduced by omission of the filtering accounts for approximately 15°s tandard deviation.…”

Section: ) Effect Of Image Filteringmentioning

confidence: 99%

Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

Koch

Feser

2006

Monthly Weather Review

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Wind vectors over the ocean were extracted from a large number of synthetic aperture radar (SAR) images from the European Remote Sensing Satellites (ERS-1 and ERS-2). The wind directions are inferred from the orientation of wind streaks that are imaged by the SAR, while the wind speeds are retrieved by inversion of the C-band model CMOD4. The derived wind directions and speeds were compared to wind vectors from the numerical Regional Model (REMO) that are available hourly on a 55-km grid. The large number of comparisons and independent weather situations allowed for an analysis of subsets that are classified by SAR-derived wind speed. A strong decrease of the standard deviation of directional differences with increasing wind speed was found. Biases of directional differences depend on SAR wind speed as well. Furthermore, the influence of the temporal difference between SAR overflight and model and an automatic image filtering on the directional error is demonstrated. Overall, reasonable fields of wind vectors were extracted from SAR imagery in 70 of 80 cases. These fields provide valuable information for validation of numerical models of the atmosphere and case studies of coastal wind fields.

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Section: ) Effect Of Image Filteringmentioning

confidence: 99%

Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

Koch

Feser

2006

Monthly Weather Review

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“…The SOP which is an open software (http://sar.kangwon.ac.kr/sop.htm) works at cygwin (www.cygwin.com) environment and the output files of the SOP are produced separately for the wind, wave, and current information. The SOP implemented the existing algorithms such as the CMOD4 [1], [2], CMOD-IFR2 [6] models, and a polarization ratio conversion [7] for the retrieval of wind speed, the wave-SAR transforms and interlook cross-spectra [5] for the extraction of wavelength and propagation direction of wave, and the Doppler shift approach [3] for the estimation of the surface current velocity. Only the surface current velocity is extracted by the SOP and evaluated in this paper as it is a dominant oceanic phenomenon in this study area driven by the strong tidal current.…”

Section: Methodsmentioning

confidence: 99%

Estimation of Ocean Current Velocity in Coastal Area Using Radarsat-1 SAR Images and HF-Radar Data

Kang

Lee

Yang

et al. 2008

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium

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This paper presents the results of the surface current velocity estimation using 6 Radarsat-1 SAR images and high frequency (HF) radar data acquired in west coastal area near Incheon, Korea. We extracted the surface velocity from SAR images based on the Doppler shift approach in which the azimuth frequency shift is related to the motion of surface target in the radar direction. The extracted SAR current velocities were statistically compared with the current velocities from the HF-radar data. The corrected SAR current velocity inherits the average of HF-radar while maintaining high-resolution mature of the original SAR data.

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“…Especially at incidence angles lower than 35 degrees, the HV imagery contains complementary sea ice information [28]. In low-to-moderate wind conditions, backscattering from open-water is typically strong at co-polarized channels (HH or VV), but low at cross-polarized channels, thereby allowing improvement in open water detection [29,30]. Better SIC estimation results can be achieved by using a combination of HH and HV (or VV and VH) channels, radar incidence angle information, and texture features (contextual information), such as auto-correlation (AC) [10,11,31].…”

Section: Sea Ice Concentrationmentioning

confidence: 99%

Bohai Sea Ice Parameter Estimation Based on Thermodynamic Ice Model and Earth Observation Data

et al. 2017

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Abstract:We estimate two essential sea ice parameters-namely, sea ice concentration (SIC) and sea ice thickness (SIT)-for the Bohai Sea using a combination of a thermodynamic sea ice model and Earth observation (EO) data from synthetic aperture radar (SAR) and microwave radiometer. We compare the SIC and SIT estimation results with in-situ measurements conducted in the study area and estimates based on independent EO data from near-infrared/optical instruments. These comparisons suggest that the SAR-based discrimination between sea ice and open-water works well, and areas of thinner and thicker ice can be distinguished. A larger comprehensive training dataset is needed to set up an operational algorithm for the estimation of SIC and SIT.

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Wind retrieval over the ocean using synthetic aperture radar with C-band HH polarization

Cited by 201 publications

References 18 publications

Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

Relationship between SAR-Derived Wind Vectors and Wind at 10-m Height Represented by a Mesoscale Model

Estimation of Ocean Current Velocity in Coastal Area Using Radarsat-1 SAR Images and HF-Radar Data

Bohai Sea Ice Parameter Estimation Based on Thermodynamic Ice Model and Earth Observation Data

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