Measurement of Sea Surface Wind Direction Using Bistatic High-Frequency Radar

2012 ◽  
Vol 50 (10) ◽  
pp. 4117-4122 ◽  
Author(s):  
Weimin Huang ◽  
Eric Gill ◽  
Xiongbin Wu ◽  
Lun Li
Keyword(s):  
Wind Direction ◽  
High Frequency ◽  
Surface Wind ◽  
Sea Surface ◽  
High Frequency Radar ◽  
Sea Surface Wind

Effectiveness of WRF wind direction for retrieving coastal sea surface wind from synthetic aperture radar

Wind Energy ◽  
2012 ◽  
Vol 16 (6) ◽  
pp. 865-878 ◽  
Author(s):  
Yuko Takeyama ◽  
Teruo Ohsawa ◽  
Katsutoshi Kozai ◽  
Charlotte Bay Hasager ◽  
Merete Badger
Keyword(s):  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Surface Wind ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Sea Surface Wind ◽  
Coastal Sea ◽  
Aperture Radar

scholarly journals Sea Surface Wind Correction Using HF Ocean Radar and Its Impact on Coastal Wave Prediction

2017 ◽  
Vol 34 (9) ◽  
pp. 2001-2020 ◽  
Author(s):  
Yukiharu Hisaki
Keyword(s):  
Wind Direction ◽  
Surface Wind ◽  
Hf Radar ◽  
Sea Surface ◽  
Wave Parameter ◽  
Simple Method ◽  
Wind Speeds ◽  
Wave Prediction ◽  
Sea Surface Wind ◽  
The Impact

AbstractBoth wind speeds and wind directions are important for predicting wave heights near complex coastal areas, such as small islands, because the fetch is sensitive to the wind direction. High-frequency (HF) radar can be used to estimate sea surface wind directions from first-order scattering. A simple method is proposed to correct sea surface wind vectors from reanalysis data using the wind directions estimated from HF radar. The constraints for wind speed corrections are that the corrections are small and that the corrections of horizontal divergences are small. A simple algorithm for solving the solution that minimizes the weighted sum of the constraints is developed. Another simple method is proposed to correct sea surface wind vectors. The constraints of the method are that corrections of wind vectors and horizontal divergences from the reanalysis wind vectors are small and that the projection of the corrected wind vectors to the direction orthogonal to the HF radar–estimated wind direction is small. The impact of wind correction on wave parameter prediction is large in the area in which the fetch is sensitive to wind direction. The accuracy of the wave prediction is improved by correcting the wind in that area, where correction of wind direction is more important than correction of wind speeds for the improvement. This method could be used for near-real-time wave monitoring by correcting forecast winds using HF radar data.

scholarly journals Editorial for Special Issue “Ocean Radar”

2019 ◽  
Vol 11 (7) ◽  
pp. 834
Author(s):  
Weimin Huang ◽  
Björn Lund ◽  
Biyang Wen
Keyword(s):  
High Frequency ◽  
Wind Wave ◽  
Surface Wind ◽  
Sea Surface ◽  
Special Issue ◽  
Sea Surface Wind ◽  
Control Schemes ◽  
New Methodologies ◽  
Ocean Monitoring ◽  
Ocean Radar

This Special Issue hosts papers related to ocean radars including the high-frequency (HF) surface wave and sky wave radars, X-, L-, K-band marine radars, airborne scatterometers, and altimeter. The topics covered by these papers include sea surface wind, wave and current measurements, new methodologies and quality control schemes for improving the estimation results, clutter and interference classification and detection, and optimal design as well as calibration of the sensors for better performance. Although different problems are tackled in each paper, their ultimate purposes are the same, i.e., to improve the capacity and accuracy of these radars in ocean monitoring.

scholarly journals Wind Direction Retrieval Using Support Vector Machine from CYGNSS Sea Surface Data

2021 ◽  
Vol 13 (21) ◽  
pp. 4451
Author(s):  
Yun Zhang ◽  
Xu Chen ◽  
Wanting Meng ◽  
Jiwei Yin ◽  
Yanling Han ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Wind Direction ◽  
Surface Wind ◽  
Sea Surface ◽  
Support Vector ◽  
Navigation Satellite ◽  
Feature Parameters ◽  
Sea Surface Wind ◽  
Global Navigation ◽  
Global Navigation Satellite

In view of the difficulty of wind direction retrieval in the case of the large space and time span of the global sea surface, a method of sea surface wind direction retrieval using a support vector machine (SVM) is proposed. This paper uses the space-borne global navigation satellite systems reflected signal (GNSS-R) as the remote sensing signal source. Using the Cyclone Global Navigation Satellite System (CYGNSS) satellite data, this paper selects a variety of feature parameters according to the correlation between the features of the sea surface reflection signal and the wind direction, including the Delay Doppler Map (DDM), corresponding to the CYGNSS satellite parameters and geometric feature parameters. The Radial Basis Function (RBF) is selected, and parameter optimization is performed through cross-validation based on the grid search method. Finally, the SVM model of sea surface wind direction retrieval is established. The result shows that this method has a high retrieval classification accuracy using the dataset with wind speed greater than 10 m/s, and the root mean square error (RMSE) of the retrieval result is 26.70°.

scholarly journals A new research on sea surface wind direction retrieval of synthetic aperture radar image

2011 ◽  
Vol 60 (10) ◽  
pp. 108402
Author(s):  
Jiang Zhu-Hui ◽  
Huang Si-Xun ◽  
Shi Han-Qing ◽  
Zhang Wei ◽  
Wang Biao
Keyword(s):  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Surface Wind ◽  
Synthetic Aperture Radar Image ◽  
Sea Surface ◽  
Radar Image ◽  
Synthetic Aperture ◽  
Sea Surface Wind ◽  
New Research ◽  
Aperture Radar
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