SEA SURFACE WIND SPEED INVERSION USING LOW INCIDENT NRCS

被引:1
|
作者
Bao, Qingliu [1 ,2 ]
Zhang, Youguang [1 ]
An, Wentao [1 ]
Cui, Limin [1 ]
Lang, Shuyan [1 ]
Lin, Mingsen [1 ]
Gong, Peng [2 ]
机构
[1] Natl Satellite Ocean Applicat Serv, Beijing 100081, Peoples R China
[2] Tsinghua Univ, Ctr Earth Syst Sci, Beijing 100084, Peoples R China
来源
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2016年
关键词
wind speed inversion; low incident angle NRCS; mean square slop; GMF model;
D O I
10.1109/IGARSS.2016.7730205
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As the launch of radars, such as the Precipitation Radar (PR) on Tropical Rainfall Measuring Mission (TRMM)[1] satellite and the Surface Wave Investigation and Monitoring (SWIM) on China France Oceanography SATellite (CFOSAT)[2], that operate in low incident angles, more and more NRCS data at low incident angle will be obtained. In order to retrieve the sea surface wind speed using low incident angle NRCS, the empirical GMF of NRCS with wind speed is established. The empirical nadir reflection coefficient |R(0)(2)| are calculated and the empirical relationship between mean square slop s(u) and wind speed is established. The mean square slop s(u) can be retrieved by fitting the NRCS at certain incident angles with the theoretical Gaussian GMF model. Then the wind speeds are calculated using the empirical corresponding relation between mean square slop and wind speed. The retrieved wind speeds are compared with Tao and NDBC buoy. The results show that the standard deviation (STD) and bias of retrieved wind speeds are smaller than 1.7m/s and 0.1m/s respectively.
引用
收藏
页码:4619 / 4622
页数:4
相关论文
共 50 条
  • [41] Observing seasonal variations of sea surface wind speed and significant wave height using TOPEX altimetry
    Chen, G
    Lin, H
    CHINESE SCIENCE BULLETIN, 2000, 45 (14): : 1323 - +
  • [42] A Dynamic Constraint Method for Retrieving Sea Surface Wind Speed Using High-Frequency Radars
    Li, Xue
    Shi, Junqiang
    Guo, Wenling
    Shao, Qiuli
    Liu, Hao
    Chen, Xueen
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025, 63
  • [43] Observing seasonal variations of sea surface wind speed and significant wave height using TOPEX altimetry
    CHEN Ge & LIN Hui1. Laboratory of Remote Sensing Information Science
    2. Ocean Remote Sensing Institute
    3. CAS/CUHK Joint Laboratory for Geo-Information Science and Department of Geography
    Chinese Science Bulletin, 2000, (14) : 1323 - 1328
  • [44] Determination of sea surface wind speed using the polarimetric and multidirectional properties of satellite measurements in visible bands
    Harmel, Tristan
    Chami, Malik
    GEOPHYSICAL RESEARCH LETTERS, 2012, 39
  • [45] Economic Feasibility of Wind Farm Using Low Wind Speed Turbine
    Sangpanich, U.
    Ault, G. A.
    Lo, K. L.
    UPEC: 2009 44TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE, 2009, : 346 - 350
  • [46] Correlation between sea surface temperature and wind speed in Greenland Sea and their relationships with NAO variability
    Qu, Bo
    Gabric, Albert J.
    Zhu, Jing-nan
    Lin, Dao-rong
    Qian, Feng
    Zhao, Min
    WATER SCIENCE AND ENGINEERING, 2012, 5 (03) : 304 - 315
  • [47] Correlation between sea surface temperature and wind speed in Greenland Sea and their relationships with NAO variability
    Albert J. GABRIC
    WaterScienceandEngineering, 2012, 5 (03) : 304 - 315
  • [48] DEPENDENCY OF BACKSCATTERING F ROM OCEAN SURFACE ON WIND DIRECTION BY USING AIRBORNE SAR - LOW WIND SPEED CASE -
    Nadai, Akitsugu
    Umehara, T.
    Matsuoka, T.
    Satake, M.
    Kobayashi, T.
    Uratsuka, S.
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 2053 - 2056
  • [49] An empirical model for wind speed inversion by HFSWR
    Li, Lun
    Wu, Xiongbin
    Xu, Xing'an
    Liu, Bin
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2012, 37 (09): : 1096 - 1099
  • [50] ResNet Deep Learning-Based Inversion Method for Sea Surface Wind Field
    Li, Ziwei
    Guo, Jianzhong
    Zhang, Baowei
    JOURNAL OF SENSORS, 2024, 2024