Cross-Polarized Synthetic Aperture Radar: A New Potential Measurement Technique for Hurricanes

2012 ◽  
Vol 93 (4) ◽  
pp. 531-541 ◽  
Author(s):  
Biao Zhang ◽  
William Perrie
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Incidence Angle ◽  
Microwave Radiometer ◽  
Synthetic Aperture ◽  
Cross Polarization ◽  
Potential Measurement ◽  
Wind Retrievals ◽  
Aperture Radar

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.

High Resolution Wind Fields Retrieved From Spaceborne Synthetic Aperture Radar Images in Comparison to Numerical Models

2002 ◽  
Author(s):  
Jochen Horstmann ◽  
Wolfgang Koch ◽  
Susanne Lehner
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Numerical Models ◽  
Synthetic Aperture ◽  
Wind Fields ◽  
Coastal Regions ◽  
Radar Images ◽  
Aperture Radar

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.

scholarly journals A Novel Approach to Marine Wind Speed Assessment Using Synthetic Aperture Radar

2006 ◽  
Vol 21 (1) ◽  
pp. 109-115 ◽  
Author(s):  
Todd D. Sikora ◽  
George S. Young ◽  
Nathaniel S. Winstead
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
A Priori ◽  
Gulf Of Alaska ◽  
Synthetic Aperture ◽  
A Priori Knowledge ◽  
Direction Field ◽  
Aperture Radar ◽  
Priori Knowledge

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.

scholarly journals Development of Wind Speed Retrieval from Cross-Polarization Chinese Gaofen-3 Synthetic Aperture Radar in Typhoons

Sensors ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 412 ◽  
Author(s):  
Weizeng Shao ◽  
Xinzhe Yuan ◽  
Yexin Sheng ◽  
Jian Sun ◽  
Wei Zhou ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Cross Polarization ◽  
Aperture Radar

scholarly journals US East Coast synthetic aperture radar wind atlas for offshore wind energy

2020 ◽  
Vol 5 (3) ◽  
pp. 1191-1210 ◽  
Author(s):  
Tobias Ahsbahs ◽  
Galen Maclaurin ◽  
Caroline Draxl ◽  
Christopher R. Jackson ◽  
Frank Monaldo ◽  
...  
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
East Coast ◽  
Offshore Wind ◽  
Synthetic Aperture ◽  
The Us ◽  
Wind Retrievals ◽  
Wind Resources ◽  
Us East Coast ◽  
Aperture Radar

Abstract. We present the first synthetic aperture radar (SAR) offshore wind atlas of the US East Coast from Georgia to the Canadian border. Images from RADARSAT-1, Envisat, and Sentinel-1A/B are processed to wind maps using the geophysical model function (GMF) CMOD5.N. Extensive comparisons with 6008 collocated buoy observations of the wind speed reveal that biases of the individual systems range from −0.8 to 0.6 m s−1. Unbiased wind retrievals are crucial for producing an accurate wind atlas, and intercalibration of the SAR observations is therefore applied. Wind retrievals from the intercalibrated SAR observations show biases in the range of to −0.2 to 0.0 m s−1, while at the same time improving the root-mean-squared error from 1.67 to 1.46 m s−1. The intercalibrated SAR observations are, for the first time, aggregated to create a wind atlas at the height 10 m a.s.l. (above sea level). The SAR wind atlas is used as a reference to study wind resources derived from the Wind Integration National Dataset Toolkit (WTK), which is based on 7 years of modelling output from the Weather Research and Forecasting (WRF) model. Comparisons focus on the spatial variation in wind resources and show that model outputs lead to lower coastal wind speed gradients than those derived from SAR. Areas designated for offshore wind development by the Bureau of Ocean Energy Management are investigated in more detail; the wind resources in terms of the mean wind speed show spatial variations within each designated area between 0.3 and 0.5 m s−1 for SAR and less than 0.2 m s−1 for the WTK. Our findings indicate that wind speed gradients and variations might be underestimated in mesoscale model outputs along the US East Coast.

scholarly journals Manual and Semiautomated Wind Direction Editing for Use in the Generation of Synthetic Aperture Radar Wind Speed Imagery

2007 ◽  
Vol 46 (6) ◽  
pp. 776-790 ◽  
Author(s):  
George S. Young ◽  
Todd D. Sikora ◽  
Nathaniel S. Winstead
Keyword(s):  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Numerical Weather Prediction ◽  
Wind Direction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Synthetic Aperture ◽  
Numerical Weather ◽  
Sar Imagery ◽  
Aperture Radar

Abstract Previous studies have demonstrated that satellite synthetic aperture radar (SAR) can be used as an accurate scatterometer, yielding wind speed fields with subkilometer resolution. This wind speed generation is only possible, however, if a corresponding accurate wind direction field is available. The potential sources of this wind direction information include satellite scatterometers, numerical weather prediction models, and SAR itself through analysis of the spatial patterns caused by boundary layer wind structures. Each of these wind direction sources has shortcomings that can lead to wind speed errors in the SAR-derived field. Manual and semiautomated methods are presented for identifying and correcting numerical weather prediction model wind direction errors. The utility of this approach is demonstrated for a set of cases in which the first-guess wind direction data did not adequately portray the features seen in the SAR imagery. These situations include poorly resolved mesoscale phenomena and misplaced synoptic-scale fronts and cyclones.

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.

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.

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