scholarly journals Comparison of C-Band Quad-Polarization Synthetic Aperture Radar Wind Retrieval Models

2018 ◽  
Vol 10 (9) ◽  
pp. 1448 ◽  
Author(s):  
He Fang ◽  
Tao Xie ◽  
William Perrie ◽  
Guosheng Zhang ◽  
Jingsong Yang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Synthetic Aperture ◽  
Northwest Pacific ◽  
Sar Images ◽  
Retrieval Models ◽  
Wind Retrieval ◽  
Wind Speeds ◽  
Aperture Radar

This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training and testing subsets. From the training data subset, we retrieve ocean surface wind speeds (OSWSs) from different models at each polarization and compare with reference wind speeds. The RMSEs of SAR-retrieved wind speeds are: 2.5 m/s: 2.11 m/s (VH-polarized), 2.13 m/s (HV-polarized), 1.86 m/s (VV-polarized) and 2.26 m/s (HH-polarized) and the correlation coefficients are 0.86 (VH-polarized), 0.85(HV-polarized), 0.87(VV-polarized) and 0.83 (HH-polarized), which are statistically significant at the 99.9% significance level. Moreover, we found that OSWSs retrieved using C-2PO model at VH-polarized are most suitable for moderate-to-high winds while CMOD4 GMF at VV-polarized tend to be best for low-to-moderate winds. A hybrid wind retrieval model is put forward composed of the two models, C-2PO and CMOD4 and sets of SAR test data are used in order to establish an appropriate wind speed threshold, to differentiate the wind speed range appropriate for one model from that of the other. The results show that the OSWSs retrieved using our hybrid method has RMSE of 1.66 m/s and the correlation coefficient are 0.9, thereby significantly outperforming both the C-2PO and CMOD4 models.

scholarly journals Comparison of Synthetic Aperture Radar–Derived Wind Speeds with Buoy Wind Speeds along the Mountainous Alaskan Coast

2008 ◽  
Vol 47 (5) ◽  
pp. 1365-1376 ◽  
Author(s):  
C. M. Fisher ◽  
G. S. Young ◽  
N. S. Winstead ◽  
J. D. Haqq-Misra
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Global Model ◽  
Synthetic Aperture ◽  
Retrieval Models ◽  
Wind Speed Profile ◽  
Wind Speeds ◽  
The Impact ◽  
Aperture Radar

Abstract Satellite-borne synthetic aperture radar (SAR) offers the potential for remotely sensing surface wind speed both over the open sea and in close proximity to the coast. The resolution improvement of SAR over scatterometers is of particular advantage near coasts. Thus, there is a need to verify the performance of SAR wind speed retrieval in coastal environments adjacent to very complex terrain and subject to strong synoptic forcing. Mountainous coasts present a challenge because the wind direction values required for SAR wind speed retrieval algorithms cannot be obtained from global model analyses with as much accuracy there as over the open ocean or adjacent to gentle coasts where most previous SAR accuracy studies have been conducted. The performance of SAR wind speed retrieval in this challenging environment is tested using a 7-yr dataset from the mountainous coast of the Gulf of Alaska. SAR-derived wind speeds are compared with direct measurements from three U.S. Navy Oceanographic Meteorological Automatic Device (NOMAD) buoys. Both of the commonly used SAR wind speed retrieval models, CMOD4 and CMOD5, were tested, as was the impact of correcting the buoy-derived wind speed profile for surface-layer stability. Both SAR wind speed retrieval models performed well although there was some wind speed–dependent bias. This may be either a SAR wind speed retrieval issue or a buoy issue because buoys can underestimate winds as wind speed and thus sea state increase. The full set of tests is performed twice, once using wind directions from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model analyses and once using wind direction observations from the buoys themselves. It is concluded that useful wind speeds can be derived from SAR backscatter and global model wind directions even in proximity to mountainous coastlines.

scholarly journals Analysis on the variational model of synthetic aperture radar sea surface wind retrieval

2014 ◽  
Vol 63 (14) ◽  
pp. 148401
Author(s):  
Jiang Zhu-Hui ◽  
Zhou Xiao-Zhong ◽  
You Xiao-Bao ◽  
Yi Xin ◽  
Huang Wei-Quan
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Variational Model ◽  
Wind Retrieval ◽  
Sea Surface Wind ◽  
Sea Surface Wind Retrieval ◽  
Aperture Radar

Use of Spaceborne Synthetic Aperture Radar for Offshore Wave Analysis

2004 ◽  
Author(s):  
Jose´ C. Nieto-Borge ◽  
Susanne Lehner ◽  
Tobias Schneiderhan ◽  
Johannes Schulz-Stellenfleth ◽  
Andreas Niedermeier
Keyword(s):  
Synthetic Aperture Radar ◽  
North Sea ◽  
Wave Spectrum ◽  
Surface Wind ◽  
Global Scale ◽  
Synthetic Aperture ◽  
Sar Images ◽  
The North ◽  
The North Sea ◽  
Aperture Radar

Spaceborne Synthetic Aperture Radar (SAR) is able to provide sea state information on a global scale by means of the directional wave spectrum. Recent developed algorithms have been developed to obtain additional information in the spatial domain rather than the spectral domain. These methods permit to detect of individual wave heights, wave groupiness in open sea areas, as well as surface wind fields. This work shows the capabilities of spaceborne SAR to extract offshore information about individual waves and wave grouping for areas of about 100 × 100 square kilometers. The methods are applied to ERS-2 SAR images of the North Sea over areas close to the location of some oil platforms. Results obtained in the vicinity of the Ekofisk platform are shown. In addition, ERS-2 SAR images taken on January 1, 1995 over the Draupner platform in the North Sea are analyzed. These SAR images were taken at the approximate time when the wave record known as “new year wave” was measured.

scholarly journals Mesoscale Near-Surface Wind Speed Variability Mapping with Synthetic Aperture Radar

Sensors ◽  
2008 ◽  
Vol 8 (11) ◽  
pp. 7012-7034 ◽  
Author(s):  
George Young ◽  
Todd Sikora ◽  
Nathaniel Winstead
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Synthetic Aperture ◽  
Near Surface ◽  
Aperture Radar

scholarly journals Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland

2020 ◽  
Vol 5 (3) ◽  
pp. 1023-1036 ◽  
Author(s):  
Louis de Montera ◽  
Tiny Remmers ◽  
Ross O'Connell ◽  
Cian Desmond
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Power ◽  
Surface Wind ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Average Wind ◽  
Level 2 ◽  
Aperture Radar

Abstract. In this paper, surface wind speed and average wind power derived from Sentinel-1 Synthetic Aperture Radar Level 2 Ocean (OCN) product were validated against four weather buoys and three coastal weather stations around Ireland. A total of 1544 match-up points was obtained over a 2-year period running from May 2017 to May 2019. The match-up comparison showed that the satellite data underestimated the wind speed compared to in situ devices, with an average bias of 0.4 m s−1, which decreased linearly as a function of average wind speed. Long-term statistics using all the available data, while assuming a Weibull law for the wind speed, were also produced and resulted in a significant reduction of the bias. Additionally, the average wind power was found to be consistent with in situ data, resulting in an error of 10 % and 5 % for weather buoys and coastal stations, respectively. These results show that the Sentinel-1 Level 2 OCN product can be used to estimate the wind resource distribution, even in coastal areas. Maps of the average and seasonal wind speed and wind power illustrated that the error was spatially dependent, which should be taken into consideration when working with Sentinel-1 Synthetic Aperture Radar data.

scholarly journals Ocean Surface Wind Speed Retrieval Using Simulated RADARSAT Constellation Mission Compact Polarimetry SAR Data

2019 ◽  
Vol 11 (16) ◽  
pp. 1876
Author(s):  
He Fang ◽  
William Perrie ◽  
Guosheng Zhang ◽  
Tao Xie ◽  
Shahid Khurshid ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Surface Wind ◽  
Ocean Surface ◽  
Synthetic Aperture ◽  
Ocean Surface Wind ◽  
Sar Data ◽  
Relative Wind ◽  
Aperture Radar

We investigated the use of C-band RADARSAT Constellation Mission (RCM) synthetic aperture radar (SAR) for retrieval of ocean surface wind speeds by using four new channels (right circular transmit, vertical receive (RV); right circular transmit, horizontal receive (RH); right circular transmit, left circular transmit (RL); and right circular transmit, right circular receive (RR)) in compact polarimetry (CP) mode. Using 256 buoy measurements collocated with RADARSAT-2 fine beam quad-polarized scenes, RCM CP data was simulated using a “CP simulator”. Provided that the relative wind direction is known, our results demonstrate that wind speed can be retrieved from RV, RH and RL polarization channels using existing C-band model (CMOD) geophysical model function (GMF) and polarization ratio (PR) models. Simulated RR-polarized radar returns have a strong linear relationship with speed and are less sensitive to relative wind direction and incidence angle. Therefore, a model is proposed for the RR-polarized synthetic aperture radar (SAR) data. Our results show that the proposed model can provide an efficient methodology for wind speed retrieval.

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