An Empirical Imaging Model for Sar Ocean Wave Measurements

نویسنده

  • A. Niedermeier
چکیده

Continuous ocean wave measurements on a global basis are still only possible using spaceborne synthetic aperture radar. For more than a decade the European satellites ERS-1 and ERS-2 have acquired about 1500 globally distributed SAR images dayly. ENVISAT is capable of recording some 3000 imagettes. However strong uncertainties in the SAR ocean wave imaging models used so far are well known. These models are either purely theoretical or semi-empirical. A new empirical model for the SAR ocean wave imaging process is proposed within this study. It is derived based on a global data set of ERS-2 wave mode spectra and colocated two-dimensional ocean wave spectra from the numerical ocean wave model WAM. A least-square minimisation approach is used to fit a quasi-linear model function calculated as an optimal estimate of the ocean to SAR transfer function. The empirical transfer function is compared to the theoretical expression used in the literature. Comparing simulated and observed SAR spectra the quality of the empirical model is tested. Furthermore the model is used to evaluate significant wave heights based on a quasi-linear inversion approach. Both statistics and global maps of wave parameters are presented. The study is a contribution to the optimization of the operational use of global SAR data for the assimilation of numerical wave forecast models, especially using ENVISAT data.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Statistical Analysis of Ocean Wave and Wind Parameters Retrieved with an Empirical Sar Algorithum

A global dataset of two years (September 1998 to December 2000) of ERS SAR data was reprocessed to more than one million SAR imagettes. Met ocean Parameters like significant ocean wave height (Hs), wind speed (U10) and mean wave period (Tm-10) are derived from the SAR images using a new empirical algorithm CWAVE [1]. The results are compared to collocated ERS altimeter data and in Situ measurem...

متن کامل

The Sar Measurement of Ocean Waves: Wave Session Whitepaper

Remote sensing techniques enable the measurement of ocean wave fields with both high resolution and large coverage. As the acquisition of active radar data is independent of daylight and cloud conditions, these data are therefore believed to be most suited for operational use at weather centers and governmental agencies, as well as for many ongoing scientific investigations. In the present over...

متن کامل

Ocean Wave Measurements from Envisat Asar Data Using a Parametric Inversion Scheme

Two-dimensional ocean wave spectra are measured from ENVISAT ASAR wave mode cross spectra on a global scale. The measurement is performed using a parametric retrieval scheme, which makes use of prior information taken from numerical wave models. The Partition Rescale and Shift algorithm (PARSA) is based on a partitioning technique, which splits an a prior wave spectrum into its wave system comp...

متن کامل

Sar Imaging Simulation for Composite Model of Ship on Dynamic Ocean Scene

An efficient double superimposition model (DSM) is proposed to generate two-dimensional (2-D) ocean surface waves. On the basis of this efficient model, a modulated slope-deterministic facet model (MSDFM) is developed to compute the radar cross section (RCS) of synthetic aperture radar (SAR) for the generated ocean surface. Then, the properties of the SAR imaging mechanism for wind seas are dis...

متن کامل

Wind-wave-induced velocity in ATI SAR ocean surface currents: First experimental evidence from an airborne campaign

Conventional and along-track interferometric (ATI) Synthetic Aperture Radar (SAR) senses the motion of the ocean surface by measuring the Doppler shift of reflected signals. Measurements are affected by a Wind-wave-induced Artifact Surface Velocity (WASV) which was modeled theoretically in past studies and has been estimated empirically only once before with Envisat ASAR by Mouche et al. (2012)...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004