Conference Agenda

2018 Dragon 4 Symposium

Session
WS#2 ID.32249: Parameters from Multi-sensors
Time:
Wednesday, 20/Jun/2018:
8:30am - 10:00am

Session Chair: Prof. Johnny A. Johannessen
Session Chair: Dr. Junmin Meng
Workshop: Oceans & Coastal Zones
XUST Library - Level 2 Conference Room

Presentations
Oral
ID: 256 / WS#2 ID.32249: 1
Oral Presentation
Oceans & Coastal Zones: 32249 - Synergistic Monitoring of Ocean Winds, Waves and Storm Surges from Multi-sensors

Recent Progresses of Microwave Marine Remote Sensing (ID. 32249)

Jingsong Yang1, Lin Ren1, He Wang2, Alexis Mouche3, Bertrand Chapron3, Biao Zhang4

1Second Institute of Oceanography, SOA, China; 2National Ocean Technology Center, SOA, China; 3Laboratoire d’Océanographie Physique et Spatiale, IFREMER, France; 4Nanjing University of Information Science and Technology, China

It is presented in this paper the recent progresses of ESA-MOST China Dragon Cooperation Program (ID. 32249) in the field of microwave marine remote sensing including (1) GF-3 SAR ocean wind retrieval: the first view and preliminary assessment; (2) Preliminary analysis of Chinese GF-3 SAR quad-polarization measurements to extract winds in each polarization; (3) Assessments of ocean wind retrieval schemes and geophysical model functions used for Chinese GF-3 SAR data at each polarization; (4) Combined co- and cross-polarized SAR measurements under extreme wind conditions; (5) Joint retrieval of directional ocean wave spectra from SAR and RAR; (6) The first quantitative ocean remote sensing by using Chinese interferometric imaging radar altimeter onboard TG-2.

Yang-Recent Progresses of Microwave Marine Remote Sensing_Cn_version.pdf

Oral
ID: 255 / WS#2 ID.32249: 2
Oral Presentation
Oceans & Coastal Zones: 32249 - Synergistic Monitoring of Ocean Winds, Waves and Storm Surges from Multi-sensors

Hurricane Observations with Synthetic Aperture Radar

Alexis Mouche1, Yili Zhao1,3, Biao Zhang2, He Wang3, Clement Combot1, Romain Husson4, Bertrand Chapron3, Olivier Archer1

1IFREMER, France; 2NUIST, China; 3NOTC, China; 4CLS, France

Sentinel-1, Gaofeng-3 and Radarsat-2 offer the unique possibility to observe the ocean surface at high resolution in both co- and cross- polarizations. This work shows how this new capabilities allow a new vision of the ocean surface over extreme events such as Hurricanes or Typhoon.

A database has been completed to gather all Sentinel-1 acquisitions over hurricane eyes. A collection of about 50 images now exist and a strategy to optimize the acquistitions over hurricane has been developed, proposed and tested with ESA Sentinel-1 Mission planning team.

Based on this data, an algorithm for cean surface wind speed measurements has been developped. Its performances are compared to analysis performed by hurricane experts in the hurricane centres, airborne measurements and parametric models.

SAR Radar-cross section over extreme are also directly compared to brigthness resolution from SMOS and SMAP L-band radiometer. In situation of rain rate less than 20 mm/hr, a striking linear relationship is found between both active and passive sensors. As interpreted, this can correspond to a regime change of the air-sea interactions during extreme events.

Mouche-Hurricane Observations with Synthetic Aperture Radar_Cn_version.pdf

Oral
ID: 282 / WS#2 ID.32249: 3
Oral Presentation
Oceans & Coastal Zones: 32249 - Synergistic Monitoring of Ocean Winds, Waves and Storm Surges from Multi-sensors

A C-band Geophysical Model Function for Synthetic Aperture Radar Coastal Wind Speed Retrieval

Biao Zhang, Yiru Lu, Alexis Mouche, William Perrie, Xiaofeng Li, He Wang

Nanjing University of Information Science and Technology, China

A new geophysical model function (GMF), called C_SARMOD2, has been developed to relate high resolution C-band Normalized Radar Cross Section (NRCS), acquired in VV polarization over the ocean, to the 10 m height wind speed. A total of 3078 RADARSAT-2 and Sentinel-1A VV-polarized SAR images acquired under different wind speed conditions were collocated with in situ buoy measurements. The paired dataset was used to derive transfer functions and coefficients of C_SARMOD2, and then to validate the wind speed retrievals. With almost no bias and a root mean square error of 1.84 m/s. Two representative quad- and dual-polarization SAR images acquired from coastal regions are used as case studies to examine C_SARMOD2 performances. The case study and statistical validation results suggest that the proposed C_SARMOD2 has the potential to measure coastal wind speeds at sub-kilometer resolutions. Although derived from low resolution NRCS measurements, this study also confirms the great robustness of CMOD5.N and recent CMOD7 when applied to SAR data. In addition, it shows that with the new generation of SAR satellite-borne sensors, it is no longer mandatory to rely on scatterometers in order to build a GMF that will be used for SAR applications. Such an approach is particularly important in view of the upcoming RADARSAT Constellation Mission (RCM) with new polarization configurations. Moreover, it also opens new perspectives on the derivation of GMFs in HH-polarization. However, these results also suggest that for coastal areas, the increase of the resolution to define the GMF is less important than adding other geophysical parameters to improve wind retrieval performance. This advocates for the necessity of revisiting the methodologies for ocean surface wind speed measurements in coastal areas.

Zhang-A C-band Geophysical Model Function for Synthetic Aperture Radar Coastal Wind Speed Retrieval_Cn_version.pdf

Poster
ID: 157 / WS#2 ID.32249: 4
Poster
Oceans & Coastal Zones: 32249 - Synergistic Monitoring of Ocean Winds, Waves and Storm Surges from Multi-sensors

Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

Jing Wang1,2, He Wang1, Jingsong Yang3, Jianhua Zhu1

1National Ocean Technology Center, State Oceanic Administration, China, People's Republic of; 2Marine Acoustics and Remote Sensing Laboratory, Zhejiang Ocean University, China, People's Republic of; 3State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration,China, People's Republic of

Abstract:

Gaofen-3 (GF-3), the first Chinese civil C-band synthetic aperture radar (SAR), was successfully launched by the China Academy of Space Technology on 10 August 2016. GF-3 provides many SAR images for oceanography with its high resolution and large coverage. Among its 12 imaging modes, wave mode is designed to monitor the ocean surface waves over the open ocean.

The paper proposed an empirical algorithm for significant wave height from the GF-3 wave mode data, called QPCWAVE_GF3, which contains six image and spectra parameters of radar incidence angle, normalized radar cross section, imaging normalized variance, azimuth Cut-Off, peak wavelength and direction.

The validation of the QPCWAVE_GF3 model is performed through comparisons against independent WW3 modelling hindcasts, and observations from altimeters and buoys. The assessment shows a good agreement with root mean square error from 0.5m to 0.6m, and scatter index around 20%.

Keywords: Gaofen-3; significant wave height; empirical algorithm

Wang-Empirical Algorithm for Significant Wave Height Retrieval_Cn_version.pdf

Poster
ID: 201 / WS#2 ID.32249: 5
Poster
Oceans & Coastal Zones: 32249 - Synergistic Monitoring of Ocean Winds, Waves and Storm Surges from Multi-sensors

Joint retrieval of directional ocean wave spectra from SAR and RAR

Lin Ren, Jingsong Yang, Gang Zheng, Juan Wang

Second Institute of Oceanography, State Oceanic Administration, China, People's Republic of

This study proposed a joint method to retrieve directional ocean wave spectra from synthetic aperture radar (SAR) and real aperture radar (RAR). The method broke through the limitations existed in the single-sensor wave retrieval, by combining two sensors’ characteristics. First, the Hs was estimated from the SAR cutoff using an empirical model. On the other hand, the relative wave spectra at large scale were derived from RAR modulation spectra. After that, the first guess spectra were estimated by relative wave spectra and SAR-derived Hs. Finally, the full wave spectra at small scale were retrieved from the SAR image cross spectra with the help of first guess spectra using the Max-Planck-Institute scheme. The 180° ambiguity of retrieved wave spectra was removed using the imaginary part of SAR cross spectra. Both simulation and collocated data were used to validate the joint method. This method helps to complement traditional wave retrieval methods.

Ren-Joint retrieval of directional ocean wave spectra_Cn_version.pdf
Ren-Joint retrieval of directional ocean wave spectra_ppt_present.pdf