Statistical Model of the Ocean Surface for Wave-Scattering Theories
V. V. Tatarskii (CIRES) and V. I. Tatarskii (CIRES)

Project

Build an ocean surface model, which would make it possible to obtain all statistical characteristics of the ocean surface from a radar signal.

Outcome

Different methods of remote sensing of the ocean surface allow us to obtain different statistical characteristics of the surface. We are developing universal methods for a complete statistical description of the random ocean surface with the following properties:

The spectrum of the surface corresponds to experimental data and describes the range of surface wavelengths from fully developed wind waves to the gravity-capillary region.
The probability distribution function (PDF) of the surface elevations at any single point is non-Gaussian and corresponds to the experimental data.
The explicit analytical formulas in terms of model parameters can be derived for the scattering cross section and any mean values appearing in the wave scattering theory. This allows development of a method of obtaining ocean surface parameters based on radar remote sensing.
 
With these given statistical parameters, we present an example of the surface, generated by a Monte-Carlo simulation. The method derived easily allows us to incorporate new experimental data as they appear.

Impact

Better understanding of satellite and radar images of the ocean surface.
Use of these images in retrieving wind speed and wind direction over an ocean surface.
Detection of the internal waves over the background of wind-driven waves.
Better understanding of the interaction of the air, water flux, and tropical storm generation.
Improve weather prediction over an ocean surface.
ETL / Review / Statistical Model of the Ocean Surface for Wave-Scattering Theories / Figure: Introduction, 1, 2, 3, Arbitrary Relation, 4, Mathematical Statistical Model, 5, 6, 7, 8, 9, Conclusion