Ms. Yan Liu Profile

Yan Liu

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 14 October 2015

Spectral separation of wind sea and swell based on buoy observations

Yan Liu, Zengzhou Hao, Fang Gong, Tianyu Wang, Jianyu Chen

Proc. SPIE. 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015

KEYWORDS: Data modeling, Satellites, Wave propagation, Solids, Wind energy, Oceanography, Data centers, Algorithm development, Climatology, Environmental sensing

Read Abstract +

Coexistence of swells from distant sources and wind seas generated by local wind field results in complex surface wave condition. Identification and separation analysis of wave components of the wind sea and swell provide a more realistic depiction of the sea state and is important for understanding of the mechanisms of climate variability in the wave field. Spectral separating is one of the most important methods in partitioning waves. Two separating methods including the initial wave steepness method (STPN) and modified wave steepness method (MSTPN) that proposed by the National Data Buoy Center (NDBC) are described in this paper. And the NDBC buoy observations are applied in this study to investigate STPN and MSTPN. Although MSTPN method is improved from the STPN method, it is still not fit for the swell effect. Considering limitations mentioned above, we use spectral energy proportion (SEP) to describe the swell effect and abstract the valid data according to this index. Finally, we give a description of correlation between significant wave height (SWH) and wind speed under the wind sea condition. From results, it is shown that SWH and wind speed of wind sea have a quasiquadratic fitting relationship. In addition, it shows that MSTPN is a better performance in application as expected. Our work for spectral partitioning algorithms could provide a reference for the future work in satellite spectral data. And a practical method for deriving the SWHs from wind speed of scatterometer will be realized on the basis of the empirical wind and sea relationship.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print format on SPIE.org.

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Institutional Access:

PURCHASE THIS CONTENT

INTERESTED IN A FREE CORPORATE TRIAL?

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:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years