Estimating mixed layer nitrate in the North Atlantic Ocean

Here we present an equation for the estimation of nitrate in surface waters of the North Atlantic Ocean (40° N to 52° N, 10° W to 60° W). The equation was derived by multiple linear regression (MLR) from nitrate, sea surface temperature (SST) observati...

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Main Authors: T. Steinhoff, T. Friedrich, S. E. Hartman, A. Oschlies, D. W. R. Wallace, A. Körtzinger
Format: Article
Language:English
Published: Copernicus Publications 2010-03-01
Series:Biogeosciences
Online Access:http://www.biogeosciences.net/7/795/2010/bg-7-795-2010.pdf
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spelling doaj-d36ee4d5d4ce451ab561bf5d6b054f602020-11-24T23:47:34ZengCopernicus PublicationsBiogeosciences1726-41701726-41892010-03-0173795807Estimating mixed layer nitrate in the North Atlantic OceanT. SteinhoffT. FriedrichS. E. HartmanA. OschliesD. W. R. WallaceA. KörtzingerHere we present an equation for the estimation of nitrate in surface waters of the North Atlantic Ocean (40° N to 52° N, 10° W to 60° W). The equation was derived by multiple linear regression (MLR) from nitrate, sea surface temperature (SST) observational data and model mixed layer depth (MLD) data. The observational data were taken from merchant vessels that have crossed the North Atlantic on a regular basis in 2002/2003 and from 2005 to the present. It is important to find a robust and realistic estimate of MLD because the deepening of the mixed layer is crucial for nitrate supply to the surface. We compared model data from two models (FOAM and Mercator) with MLD derived from float data (using various criteria). The Mercator model gives a MLD estimate that is close to the MLD derived from floats. MLR was established using SST, MLD from Mercator, time and latitude as predictors. Additionally a neural network was trained with the same dataset and the results were validated against both model data as a "ground truth" and an independent observational dataset. This validation produced RMS errors of the same order for MLR and the neural network approach. We conclude that it is possible to estimate nitrate concentrations with an uncertainty of ±1.4 μmol L<sup>−1</sup> in the North Atlantic. http://www.biogeosciences.net/7/795/2010/bg-7-795-2010.pdf
collection DOAJ
language English
format Article
sources DOAJ
author T. Steinhoff
T. Friedrich
S. E. Hartman
A. Oschlies
D. W. R. Wallace
A. Körtzinger
spellingShingle T. Steinhoff
T. Friedrich
S. E. Hartman
A. Oschlies
D. W. R. Wallace
A. Körtzinger
Estimating mixed layer nitrate in the North Atlantic Ocean
Biogeosciences
author_facet T. Steinhoff
T. Friedrich
S. E. Hartman
A. Oschlies
D. W. R. Wallace
A. Körtzinger
author_sort T. Steinhoff
title Estimating mixed layer nitrate in the North Atlantic Ocean
title_short Estimating mixed layer nitrate in the North Atlantic Ocean
title_full Estimating mixed layer nitrate in the North Atlantic Ocean
title_fullStr Estimating mixed layer nitrate in the North Atlantic Ocean
title_full_unstemmed Estimating mixed layer nitrate in the North Atlantic Ocean
title_sort estimating mixed layer nitrate in the north atlantic ocean
publisher Copernicus Publications
series Biogeosciences
issn 1726-4170
1726-4189
publishDate 2010-03-01
description Here we present an equation for the estimation of nitrate in surface waters of the North Atlantic Ocean (40° N to 52° N, 10° W to 60° W). The equation was derived by multiple linear regression (MLR) from nitrate, sea surface temperature (SST) observational data and model mixed layer depth (MLD) data. The observational data were taken from merchant vessels that have crossed the North Atlantic on a regular basis in 2002/2003 and from 2005 to the present. It is important to find a robust and realistic estimate of MLD because the deepening of the mixed layer is crucial for nitrate supply to the surface. We compared model data from two models (FOAM and Mercator) with MLD derived from float data (using various criteria). The Mercator model gives a MLD estimate that is close to the MLD derived from floats. MLR was established using SST, MLD from Mercator, time and latitude as predictors. Additionally a neural network was trained with the same dataset and the results were validated against both model data as a "ground truth" and an independent observational dataset. This validation produced RMS errors of the same order for MLR and the neural network approach. We conclude that it is possible to estimate nitrate concentrations with an uncertainty of ±1.4 μmol L<sup>−1</sup> in the North Atlantic.
url http://www.biogeosciences.net/7/795/2010/bg-7-795-2010.pdf
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