Michael J. Caruso

A New Approach to Ocean Wave Parameter Estimates From C-Band ScanSAR Images

Because of their large swath widths of about 400-500 km, the ScanSAR modes of RADARSAT-1 and -2 and of the Advanced SAR (ASAR) system on Envisat have been the preferred modes of operation for hurricane and typhoon observations and similar applications. While C-band ScanSAR images have been demonstrated to be well suitable for wind retrievals, ocean wave retrievals are a more challenging problem: Because of the limited spatial resolution of 100 m (RADARSAT)/150 m (Envisat), only long waves can get imaged directly, and many images of tropical storm scenarios do not exhibit clear signatures of any waves in large areas. The interpretation of wave patterns that exist in an image is difficult because of the imaging mechanisms nonlinearities. We think we have found a promising new technique for wave parameter retrievals from C-band ScanSAR images, which determines peak wavelengths and directions from image spectra where possible but uses an empirically determined relation to estimate significant wave heights (SWHs) from local mean image intensities, which is similar to the method used for wind retrievals. This way, it is possible to obtain SWH estimates for the entire image and to account for the contributions of subresolution-scale waves. We explain how the algorithm works and how the empirical SWH model function has been determined from a set of hurricane images from RADARSAT-1 and reference wave spectra from a numerical wave model. The first independent test with a set of RADARSAT-2 and Envisat images from the 2010 Impact of Typhoons on the Ocean in the Pacific (ITOP) experiment reveals a few weaknesses but essentially confirms the feasibility of the concept.

Tropical Cyclone Winds Retrieved From C-Band Cross-Polarized Synthetic Aperture Radar

This paper presents a geophysical model function (GMF) that has been developed to describe the relation of the ocean surface wind with the normalized radar cross section (NRCS) at C-band cross polarization (cross-pol). Synthetic aperture radar (SAR) images have been simultaneously collected at copolarization (co-pol) and cross-pol at moderate to high wind speeds. Using the SAR co-pol retrieved wind fields and an uncertainty estimate of the retrieved wind speeds, the cross-pol dependencies of the NRCS are investigated with respect to wind, incidence angle, and polarization pairs. For wind speeds above 10 m/s, there is a significant dependence of the NRCS on wind speed. However, the SAR cross-pol data are also significantly affected by the noise floor and crosstalk between the channels. Estimates of the noise floor are determined and removed from the NRCS. Three GMFs are developed: the first is for transmission at horizontal (H) polarization and the second at vertical (V) polarization. A third GMF accounts for wind direction dependence. Validation of the GMFs is conducted by comparison with collocated Stepped Frequency Microwave Radiometer (SFMR) data. The resulting bias of -0.7 m/s and standard deviation of 3.7 m/s demonstrate the excellent performance for these GMFs for wind speed retrieval between 10 and 35 m/s. Furthermore, comparisons show that SAR cross-pol retrieved wind speeds are of similar quality as those of SFMR and are significantly better in the moderate to high wind speed regime than SAR co-pol retrieved winds.

A Descalloping Postprocessor for ScanSAR Images of Ocean Scenes

Due to its specific way of recording signals from multiple adjacent swaths in an alternating manner, a scanning synthetic aperture radar (SAR) (ScanSAR) cannot sample Doppler histories continuously like a SAR in stripmap mode. This can cause an effect known as azimuth scalloping, a wavelike modulation of the image intensity in near-azimuth direction. In theory, azimuth scalloping can be straightened out by using appropriate beam pattern corrections and multilooking techniques in the SAR processor. This works well over land, but lower signal-to-noise ratios and less accurate Doppler centroid estimates over water cause significant residual scalloping in many ScanSAR images of ocean scenes. The scalloping patterns hamper a correct interpretation of signatures of wind streaks, waves, and other phenomena. To overcome this problem once and for all, we have developed an algorithm that can eliminate scalloping patterns from existing ScanSAR images by postprocessing. Our algorithm detects the dominant scalloping pattern in an image automatically and eliminates most of it with very small side effects. We treat the scalloping pattern as a multiplicative effect, i.e., the amplitude spectrum of an affected image is assumed to be the convolution of the amplitude spectra of the unscalloped image and of the scalloping pattern. The proposed descalloping technique works partly in the spatial and partly in the spectral domain to approximate an exact deconvolution. We give a detailed technical description, show example results, and perform a quality analysis. We demonstrate the positive effects of the proposed descalloping treatment with a wind field retrieval example.

The 1995 Georges Bank Stratification Study and moored array measurements

Funding was provided by the National Science Foundation under Grant Numbers OCE-98-06379 and OCE-98-06445.

Significant internal waves and internal tides measured northeast of Taiwan

Author Posting.