Wind field models and classification

Charles G. Brown; Paul E. Johnson; Steve L. Richards; David G. Long

doi:10.1117/12.278917

18 September 1997 Wind field models and classification

Charles G. Brown, Paul E. Johnson, Steve L. Richards, David G. Long

Proceedings Volume 3117, Earth Observing Systems II; (1997) https://doi.org/10.1117/12.278917
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Traditional scatterometer wind estimation inverts the model function relationship between the wind and backscatter at each resolution element, yielding a set of ambiguities due to the many-to-one mapping of the model function. Field-wise wind estimation dramatically reduces the number of ambiguities by estimating the wind for many resolution elements, simultaneously, using a wind field model that constrains the spatial variability of the wind. In this paper four wind field models are presented or use in field- wise wind estimation. The models considered include tow standard expansions, a data-driven model, and a model based on geophysical constraints on the pressure field. Model accuracy, as a function of the number of model parameters, is reported for each model. This accuracy is evaluated using NSCAT JPL nudged L2.0 data. Because of the inherent compromise between computational complexity of high-order models and the imprecise fit of low-order models, automated classification schemes are developed to identify a priori whether a region will be well modeled by a simple wind model. Classification is performed through hypothesis testing on raw NSCAT data and point-wise estimates.

Citation Download Citation

Charles G. Brown, Paul E. Johnson, Steve L. Richards, and David G. Long "Wind field models and classification", Proc. SPIE 3117, Earth Observing Systems II, (18 September 1997); https://doi.org/10.1117/12.278917

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Fourier transforms

Backscatter

Error analysis

Affine motion model

Statistical modeling

Chemical elements

Show All Keywords

Keywords/Phrases

Search In:

Publication Years