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Open AccessJournal ArticleDOI

Retrieval of Sea Surface Wind Speeds from Gaofen-3 Full Polarimetric Data

Tianyu Zhang, +4 more
- 01 Apr 2019 - 
- Vol. 11, Iss: 7, pp 813
TLDR
In this article, the sea surface wind speed (SSWS) retrieval from Gaofen-3 (GF-3) quad-polarization stripmap (QPS) data in vertical-vertical (VV), horizontal-horizontal (HH), and vertical-orthogonal (VH) polarizations is investigated in detail based on 3170 scenes acquired from October 2016 to May 2018.
Abstract
In this paper, the sea surface wind speed (SSWS) retrieval from Gaofen-3 (GF-3) quad-polarization stripmap (QPS) data in vertical-vertical (VV), horizontal-horizontal (HH), and vertical-horizontal (VH) polarizations is investigated in detail based on 3170 scenes acquired from October 2016 to May 2018. The radiometric calibration factor of the VV polarization data is examined first. This calibration factor generally meets the requirement of SSWS retrieval accuracy with an absolute bias of less than 0.5 m/s but shows highly dispersed characteristics. These results lead to SSWS retrievals with a small bias of 0.18 m/s, but a rather high root mean square error (RMSE) of 2.36 m/s when compared with the ERA-Interim reanalysis model data. Two refitted polarization ratio (PR) models for the QPS HH polarization data are presented. Based on a combination of the incidence angle-dependent and azimuth angle-dependent PR model and CMOD5.N, the SSWS derived from the QPS HH data shows a bias of 0.07 m/s and an RMSE of 2.26 m/s relative to the ERA-Interim reanalysis model wind speed. A linear function relating SSWS and the normalized radar cross section (NRCS) of QPS VH data is derived. The SSWS data retrieved from the QPS VH data show good agreement with the WindSat SSWS data, with a bias of 0.1 m/s and an RMSE of 2.02 m/s. We also apply the linear function to the GF-3 Wide ScanSAR data acquired for the typhoon SOULIK, which yields very good agreement with the model results. A comparison of SSWS retrievals among three different polarization datasets is also presented. The current study and our previous work demonstrate that the general accuracy of the SSWS retrieval based on GF-3 QPS data has an absolute bias of less than 0.3 m/s and an RMSE of 2.0 ± 0.2 m/s relative to various datasets. Further improvement will depend on dedicated radiometric calibration efforts.

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Citations
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Journal ArticleDOI

Deep Learning Based Sea Ice Classification with Gaofen-3 Fully Polarimetric SAR Data

TL;DR: From the results of this study, it is shown that the MSI-ResNet method performs better than the classical support vector machine (SVM) classifier for sea ice discrimination.
Journal ArticleDOI

Past, Present and Future Marine Microwave Satellite Missions in China

Mingsen Lin, +1 more
- 09 Mar 2022 - 
TL;DR: In this paper , a long-term plan has been formulated for the development of Chinese ocean satellites, as well as the construction of a constellation of ocean dynamic environmental and ocean surveillance satellites.
Journal ArticleDOI

Wind speed retrieval from the Gaofen-3 synthetic aperture radar for VV- and HH-polarization using a re-tuned algorithm

TL;DR: In this paper, a re-tuned algorithm based on the geophysical model function (GMF) C-SARMOD2 is proposed to retrieve wind speed from Synthetic Aperture Radar (SAR) imagery collected by the Chinese C...
Journal ArticleDOI

Intelligent Wind Retrieval from Chinese Gaofen-3 SAR Imagery in Quad Polarization

TL;DR: The use of the artificial neural network for wind retrieval with Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) data is proposed.
Journal ArticleDOI

Quad-polarimetric SAR sea state retrieval algorithm from Chinese Gaofen-3 wave mode imagettes via deep learning

TL;DR: In this paper , a deep residual convolutional neural network-based SAR SWH retrieval algorithm in quad-polarization was proposed to improve SAR wave height retrieval under high sea conditions.
References
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Journal ArticleDOI

Spectral and statistical properties of the equilibrium range in wind-generated gravity waves

TL;DR: In this paper, the nature of the equilibrium range is reexamined, using the dynamical insights into wave-wave interactions, energy input from the wind and wave-breaking that have been developed since 1960.
Journal ArticleDOI

Scatterometer data interpretation: Estimation and validation of the transfer function CMOD4

TL;DR: In this paper, the authors estimate the 18 coefficients of the CMOD4 σ0-to-wind transfer function using a maximum likelihood estimation (MLE) method in order to improve the prelaunch function.
Journal ArticleDOI

An improved C-band scatterometer ocean geophysical model function: CMOD5

TL;DR: In this article, a new C-band geophysical model function (GMF) is derived on the basis of measurements from the scatterometer on board of the European Remote Sensing Satellite ERS-2.
Journal ArticleDOI

The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance

TL;DR: The WindSat sensor provides risk reduction for the development of the Conical Microwave Imager Sounder, which is planned to provide wind vector data operationally starting in 2010, and is currently undergoing rigorous calibration and validation to verify mission success.
Journal ArticleDOI

Observation of tropical cyclones by high-resolution scatterometry

TL;DR: In this article, a comprehensive analysis of the backscattering measurements in the case of high winds and high sea states obtained within TCs is proposed in order to refine the interpretation of the wind vector derived from a backscatter model that is currently only calibrated up to moderate winds (< 20 m/s) in neutral conditions.
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