scholarly journals A Geophysical Model Function for Wind Speed Retrieval From C-Band HH-Polarized Synthetic Aperture Radar

2019 ◽  
Vol 16 (10) ◽  
pp. 1521-1525 ◽  
Author(s):  
Biao Zhang ◽  
Alexis Mouche ◽  
Yiru Lu ◽  
William Perrie ◽  
Guosheng Zhang ◽  
...  
2018 ◽  
Vol 10 (9) ◽  
pp. 1448 ◽  
Author(s):  
He Fang ◽  
Tao Xie ◽  
William Perrie ◽  
Guosheng Zhang ◽  
Jingsong Yang ◽  
...  

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.


2015 ◽  
Vol 120 (2) ◽  
pp. 893-909 ◽  
Author(s):  
Paul A. Hwang ◽  
Ad Stoffelen ◽  
Gerd-Jan van Zadelhoff ◽  
William Perrie ◽  
Biao Zhang ◽  
...  

2012 ◽  
Vol 93 (4) ◽  
pp. 531-541 ◽  
Author(s):  
Biao Zhang ◽  
William Perrie

We present an empirical C-band Cross-Polarization Ocean (C-2PO) model for wind retrievals from synthetic aperture radar (SAR) data collected by the RADARSAT-2 satellite. The C-2PO model relates normalized radar cross section (NRCS) in cross polarization to wind speed at 10-m height. This wind retrieval model has the characteristic that it is independent of wind direction and radar incidence angle but is quite linear with respect to wind speed. To evaluate the accuracy of the proposed model, winds with a resolution on the scale of 1 km were retrieved from a dual-polarization SAR image of Hurricane Earl on 2 September 2010, using the C-2PO model and compared with CMOD5.N, the newest available C-band geophysical model function (GMF), and validated with collocated airborne stepped-frequency microwave radiometer measurements and National Data Buoy Center data. Results suggest that for winds up to 38 m s−1, C-2PO has a bias of −0.89 m s−1 and a root-meansquare error of 3.23 m s−1 compared to CMOD5.N, which has a bias of −4.14 m s−1 and an rms difference of 6.24 m s−1. Similar results are obtained from Hurricane Ike, comparing wind retrievals from C-2PO and CMOD5.N with H*Wind data. The advantage of C-2PO over CMOD5.N and other GMFs is that it does not need any external wind direction and radar incidence angle inputs. Moreover, in the presently available quad-polarization dataset, C-2PO has the feature that the cross-polarized NRCS linearly increases even for wind speeds up to 26 m s−1 and reproduces the hurricane eye structure well, thereby providing a potential technique for hurricane observations from space.


Author(s):  
Jochen Horstmann ◽  
Wolfgang Koch ◽  
Susanne Lehner

This paper introduces a recently developed algorithm to retrieve high-resolution wind fields over the ocean surface from spaceborne synthetic aperture radar (SAR) data. The algorithm consists of two parts, the first for determining wind direction and the second for wind speed retrieval. Wind directions are extracted from wind induced streaks e.g. from boundary layer rolls, Langmuir cells, or wind shadowing, which are approximately in line with the mean wind direction. Wind speed is derived from the normalized radar cross section (NRCS) and image geometry of the SAR image, together with the local retrieved wind direction. The application of SAR-wind retrieval in coastal regions is demonstrated using data acquired aboard the European satellites ERS-1 and ERS-2 and the Canadian satellite RADARSAT-1. These data allow to measure wind fields of an area of up to 500 km × 500 km with a resolution of up to 200 m. To improve and validate the set-up of numerical high-resolution models in coastal regions SAR-retrieved wind fields offer an unique opportunity. This is shown by comparisons of wind fields measured by SAR to results of the numerical model REMO, HIRLAM and GESIMA.


2006 ◽  
Vol 21 (1) ◽  
pp. 109-115 ◽  
Author(s):  
Todd D. Sikora ◽  
George S. Young ◽  
Nathaniel S. Winstead

Abstract This paper describes a product that allows one to assess the lower and upper bounds on synthetic aperture radar (SAR)-based marine wind speed. The SAR-based wind speed fields of the current research are generated using scatterometry techniques and, thus, depend on a priori knowledge of the wind direction field. The assessment product described here consists of a pair of wind speed images bounding the wind speed range consistent with the observed SAR data. The minimum wind speed field is generated by setting the wind direction field to be directly opposite to the radar look direction. The maximum wind speed field is generated by setting the wind direction field to be perpendicular to the radar look direction. Although the assessment product could be generated using any marine SAR scene, it is expected to be most useful in coastal regions where the large concentration of maritime operations requires accurate, high-resolution wind speed data and when uncertainty in the a priori knowledge of the wind direction precludes the generation of accurate SAR-based wind speed fields. The assessment product is demonstrated using a case in the northern Gulf of Alaska where synoptic-scale and mesoscale meteorological events coexist. The corresponding range of possible SAR-based wind speed is large enough to have operational significance to mariners and weather forecasters. It is recommended that the product become available to the public through an appropriate government outlet.


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