Publication Date:
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−1 in the North Atlantic.
Print ISSN:
1726-4170
Electronic ISSN:
1726-4189
Topics:
Biology
,
Geosciences
