An Objective Method for Determining Ocean Mixed Layer Depth with Applications to WOCE Data

An Objective Method for Determining Ocean Mixed Layer Depth with Applications to WOCE Data AbstractA new method is developed to identify the mixed layer depth (MLD) from individual temperature or density profiles. A relative variance profile is obtained that is the ratio between the standard deviation and the maximum variation of the temperature (density) from the sea surface, and the depth of the minimum relative variance is defined as the MLD. The new method is robust in finding the MLD under the influence of random noise (noise level ≤ 5%). A comparison with other available methods, which include the threshold (difference, difference interpolation, gradient, and hybrid methods) and objective (curvature and maximum angle methods) methods, is carried out using the World Ocean Circulation Experiment (WOCE) data. It is found that for a variety of depth sampling resolutions ranging from 0.04 to 25 dbar, the new method and the difference-interpolation method predict MLD values that are closer to the visually inspected ones than those by other methods. Moreover, the quality index (QI) of the MLD that is determined by the new method is the highest when compared with those of the available methods. Also, the application of the new method on the WOCE global dataset yields 94% of MLD values with , substantially higher than those (≤86%) of other methods. Ultimately, it is found that the new method determines very similar MLD values when applied to temperature or density profiles globally because it identifies the base of the mixed layer rather than the uppermost depth of the thermocline. This unique advantage makes the new method applicable in many cases, especially when the density profile is unavailable. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

An Objective Method for Determining Ocean Mixed Layer Depth with Applications to WOCE Data

Loading next page...
 
/lp/ams/an-objective-method-for-determining-ocean-mixed-layer-depth-with-y12A7u1cWB
Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
D.O.I.
10.1175/JTECH-D-17-0104.1
Publisher site
See Article on Publisher Site

Abstract

AbstractA new method is developed to identify the mixed layer depth (MLD) from individual temperature or density profiles. A relative variance profile is obtained that is the ratio between the standard deviation and the maximum variation of the temperature (density) from the sea surface, and the depth of the minimum relative variance is defined as the MLD. The new method is robust in finding the MLD under the influence of random noise (noise level ≤ 5%). A comparison with other available methods, which include the threshold (difference, difference interpolation, gradient, and hybrid methods) and objective (curvature and maximum angle methods) methods, is carried out using the World Ocean Circulation Experiment (WOCE) data. It is found that for a variety of depth sampling resolutions ranging from 0.04 to 25 dbar, the new method and the difference-interpolation method predict MLD values that are closer to the visually inspected ones than those by other methods. Moreover, the quality index (QI) of the MLD that is determined by the new method is the highest when compared with those of the available methods. Also, the application of the new method on the WOCE global dataset yields 94% of MLD values with , substantially higher than those (≤86%) of other methods. Ultimately, it is found that the new method determines very similar MLD values when applied to temperature or density profiles globally because it identifies the base of the mixed layer rather than the uppermost depth of the thermocline. This unique advantage makes the new method applicable in many cases, especially when the density profile is unavailable.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Mar 6, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from Google Scholar, PubMed
Create lists to organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off