scholarly journals LG-Mod: A Modified Local Gradient (LG) Method to Retrieve SAR Sea Surface Wind Directions in Marine Coastal Areas

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Fabio M. Rana ◽  
Maria Adamo ◽  
Guido Pasquariello ◽  
Giacomo De Carolis ◽  
Sandra Morelli
Keyword(s):  
Wind Direction ◽  
Periodic Structures ◽  
Surface Wind ◽  
Estimation Method ◽  
Residual Effects ◽  
Envisat Asar ◽  
Sea Surface Wind ◽  
Sar Imagery ◽  
Complex Phenomena ◽  
Local Gradient

This paper describes a novel SAR wind direction estimation method based on the computation of local gradients over quasi-linear and quasi-periodic structures detected by SAR imagery. The method relies upon the standard LG method for the part relevant to the computation of the local gradients. The novelty is that the dominant local wind direction and related accuracy are estimated using results derived from the Directional Statistics. The LG-Mod is validated against in situ coastal wind measurements provided by instrumented buoys with 63 ENVISAT ASAR images. Results show an overall agreement with RMSE values obtained for off-shore areas, but residual effects due to the complex phenomena occurring in the proximity of shoreline may degrade the performance when running in automated mode.

scholarly journals An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery

2017 ◽  
Vol 9 (7) ◽  
pp. 671 ◽  
Author(s):  
Lizhang Zhou ◽  
Gang Zheng ◽  
Xiaofeng Li ◽  
Jingsong Yang ◽  
Lin Ren ◽  
...  
Keyword(s):  
Gradient Method ◽  
Wind Direction ◽  
Surface Wind ◽  
Sea Surface ◽  
Sea Surface Wind ◽  
Sar Imagery ◽  
Local Gradient

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.

Simulation Research about HJ-1C SAR Wind Mapping Capability

2012 ◽  
Vol 500 ◽  
pp. 550-555
Author(s):  
Feng Feng Chen ◽  
Wei Gen Huang ◽  
Jing Song Yang
Keyword(s):  
Wave Spectrum ◽  
Surface Wind ◽  
Coastal Region ◽  
Sea Surface ◽  
Surface Model ◽  
Composite Surface ◽  
Envisat Asar ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Wind Mapping

Synthetic aperture radar (SAR) on aboard Chinese Huan Jing (HJ)-1C satellite has been planed to be launched in 2010. The satellite will fly in a sun-synchronous polar orbit of about 500-km altitude. SAR will operate in S band with HH polarization. Its image mode has the incidence angles 25°and 47°at the near and far sides of the swath respectively. SAR image has a spatial resolution of 20 m with a swath of 100 km. Here, the sea surface wind mapping capability of the SAR in the Chinese Coastal Region has been examined using M4S radar imaging model developed by Romeiser et al. The model is based on Bragg scattering theory in a composite surface model expansion. It accounts for contributions of the full ocean wave spectrum to the radar backscatter from ocean surface. The model reproduces absolute normalized radar cross section (NRCS) values for wide ranges of wind speeds. The model results of HJ-1C SAR have been compared with the model results of Envisat and Radarsat SAR signals. It shows that HJ-1C SAR is as good as both Envisat ASAR and Radarsat SAR at sea surface wind mapping Capability.

scholarly journals X-band COSMO-SkyMed wind field retrieval, with application to coastal circulation modeling

Ocean Science ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 121-132 ◽  
Author(s):  
A. Montuori ◽  
P. de Ruggiero ◽  
M. Migliaccio ◽  
S. Pierini ◽  
G. Spezie
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Surface Wind ◽  
Circulation Model ◽  
Coastal Circulation ◽  
Wind Fields ◽  
Sea Surface Wind ◽  
X Band ◽  
Sar Data ◽  
Ecmwf Model

Abstract. In this paper, X-band COSMO-SkyMed© synthetic aperture radar (SAR) wind field retrieval is investigated, and the obtained data are used to force a coastal ocean circulation model. The SAR data set consists of 60 X-band Level 1B Multi-Look Ground Detected ScanSAR Huge Region COSMO-SkyMed© SAR data, gathered in the southern Tyrrhenian Sea during the summer and winter seasons of 2010. The SAR-based wind vector field estimation is accomplished by resolving both the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved by means of a SAR wind speed algorithm based on the azimuth cut-off procedure, while the sea surface wind direction is provided by means of a SAR wind direction algorithm based on the discrete wavelet transform multi-resolution analysis. The obtained wind fields are compared with ground truth data provided by both ASCAT scatterometer and ECMWF model wind fields. SAR-derived wind vector fields and ECMWF model wind data are used to construct a blended wind product regularly sampled in both space and time, which is then used to force a coastal circulation model of a southern Tyrrhenian coastal area to simulate wind-driven circulation processes. The modeling results show that X-band COSMO-SkyMed© SAR data can be valuable in providing effective wind fields for coastal circulation modeling.

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