Cyclone Wind Retrieval Based on X-Band SAR-Derived Wave Parameter Estimation

被引:19
作者
Shao, Weizeng [1 ,4 ]
Hu, Yuyi [1 ]
Nunziata, Ferdinando [2 ]
Corcione, Valeria [2 ]
Migliaccio, Maurizio [2 ]
Li, Xiaoming [3 ]
机构
[1] Zhejiang Ocean Univ, Marine Sci & Technol Coll, Zhoushan, Peoples R China
[2] Univ Napoli Parthenope, Electromagnet Fields, Naples, Italy
[3] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China
[4] Natl Satellite Ocean Applicat Serv, Beijing, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Sea state; Tropical cyclones; Wind; Algorithms; Remote sensing; SYNTHETIC-APERTURE RADAR; OCEAN SURFACE-WAVES; AZIMUTH CUTOFF; LIMITED GROWTH; MODEL; SPEED;
D O I
10.1175/JTECH-D-20-0014.1
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
In this study, a method for retrieving wind speed from synthetic aperture radar (SAR) imagery collected under extreme weather conditions is proposed. The rationale for this approach relies on the fact that, although copolarized channels exhibit saturation for wind speed > similar to 20 m s(-1), the wave growth can be successfully exploited to gather information on wind speed under extreme weather conditions. Hence, in this study, the intrinsic relationship among the wind-wave triplets [wind speed at 10 m above the sea surface, significant wave height (SWH), and peak wave period] is exploited in order to retrieve wind speeds under tropical cyclone conditions. Experiments, undertaken on actual X-band TerraSAR-X (TS-X) SAR images of tropical cyclones (Typhoon Megi, Hurricane Sandy, and Hurricane Miriam) and using collocated WAVEWATCH-III (WW3) simulations, revealed the robustness of the proposed approach, which resulted in a root-mean-square error (RMSE) of 2.54 m s(-1) when comparing the retrieved wind speeds with the values from products delivered by the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD). However, the applicability of the algorithm herein will be further confirmed at very strong storms.
引用
收藏
页码:1907 / 1924
页数:18
相关论文
共 47 条
[1]   ON THE DETECTABILITY OF OCEAN SURFACE-WAVES BY REAL AND SYNTHETIC APERTURE RADAR [J].
ALPERS, WR ;
ROSS, DB ;
RUFENACH, CL .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 1981, 86 (NC7) :6481-6498
[2]   ON THE RELATIVE IMPORTANCE OF MOTION-RELATED CONTRIBUTIONS TO THE SAR IMAGING MECHANISM OF OCEAN SURFACE-WAVES [J].
ALPERS, WR ;
BRUENING, C .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1986, 24 (06) :873-885
[3]   Weakly turbulent laws of wind-wave growth [J].
Badulin, Sergei I. ;
Babanin, Alexander V. ;
Zakharov, Vladimir E. ;
Resio, Donald .
JOURNAL OF FLUID MECHANICS, 2007, 591 (339-378) :339-378
[4]   TerraSAR-X/TanDEM-X sea state measurements using the XWAVE algorithm [J].
Bruck, Miguel ;
Lehner, Susanne .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2015, 36 (15) :3890-3912
[5]   Coastal wave field extraction using TerraSAR-X data [J].
Bruck, Miguel ;
Lehner, Susanne .
JOURNAL OF APPLIED REMOTE SENSING, 2013, 7
[6]   The TerraSAR-X Ground Segment [J].
Buckreuss, Stefan ;
Schaettler, Birgit .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2010, 48 (02) :623-632
[7]   A Novel Azimuth Cutoff Implementation to Retrieve Sea Surface Wind Speed From SAR Imagery [J].
Corcione, Valeria ;
Grieco, Giuseppe ;
Portabella, Marcos ;
Nunziata, Ferdinando ;
Migliaccio, Maurizio .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (06) :3331-3340
[8]   Megi Typhoon Monitoring by X-Band Synthetic Aperture Radar Measurements [J].
Corcione, Valeria ;
Nunziata, Ferdinando ;
Migliaccio, Maurizio .
IEEE JOURNAL OF OCEANIC ENGINEERING, 2018, 43 (01) :184-194
[9]   ON THE NONLINEAR MAPPING OF AN OCEAN WAVE SPECTRUM INTO A SYNTHETIC APERTURE RADAR IMAGE SPECTRUM AND ITS INVERSION [J].
HASSELMANN, K ;
HASSELMANN, S .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 1991, 96 (C6) :10713-10729
[10]   An improved C-band scatterometer ocean geophysical model function: CMOD5 [J].
Hersbach, H. ;
Stoffelen, A. ;
de Haan, S. .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2007, 112 (C3)