Exponential leap-forward gradient scheme for determining the isothermal layer depth from profile data
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Authors
Chu, P.C.
Fan, C.W.
Subjects
Mixed layer
Mixed layer depth
Isothermal layer
Isothermal layer depth
Difference
Gradient
Maximum curvature
Maximum angle
Optimal linear tting
Exponential leap-forward gradient (ELG)
Quality index
Skill score
Shannon information entropy
Mixed layer depth
Isothermal layer
Isothermal layer depth
Difference
Gradient
Maximum curvature
Maximum angle
Optimal linear tting
Exponential leap-forward gradient (ELG)
Quality index
Skill score
Shannon information entropy
Advisors
Date of Issue
2017
Date
Publisher
Springer
Language
Abstract
Two distinct layers usually exist in the upper ocean. The rst has a near-zero vertical gradient in temperature (or density) from the surface and is called the iso-thermal layer (or mixed layer). Beneath that is a layer with a strong vertical gradient in temperature (or density), called the thermocline (or pycnocline). The isothermal layer depth (ILD) or mixed layer depth (MLD) for the same pro le var- ies depending on the method used to determine it. Also, whether they are subjective or objective, existing methods of determining the ILD do not estimate the thermocline (pycnocline) gradient. Here, we propose a new exponen- tial leap-forward gradient (ELG) method of determining the ILD that retains the strengths of subjective (simplicity) and objective (gradient change) methods and avoids their weaknesses (subjective methods are threshold-sensitive and objective methods are computationally intensive). This new method involves two steps: (1) the estimation of the ther- mocline gradient Gth for an individual temperature pro le, and (2) the computation of the vertical gradient by averag- ing over gradients using exponential leap-forward steps. Such averaging can lter out noise in the pro le data. Five existing methods of determining the ILD (difference, gra- dient, maximum curvature, maximum angle, and optimal linear tting methods) as well as the proposed ELG method were veri ed using global expendable bathythermograph (XBT) temperature and conductivity–temperature–depth (CTD) datasets. Among all the methods considered, the ELG method yielded the highest skill score and the lowest Shannon information entropy (i.e., the lowest uncertainty).
Type
Article
Description
The article of record as published may be found at http://dx.doi.org/10.1007/s10872-017-0418-0.
Series/Report No
Department
Oceanography
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Chu, P.C., and C.W. Fan, 2017: Exponential leap-forward gradient scheme for determining the isothermal layer depth from profile data. Journal of Oceanography, DOI 10.1007/s10872-017-0418-0.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.