Abstract :
[en] The Spanish surface fishery operates mainly during the summer season in the
waters of the Bay of Biscay. Sea surface temperature (SST) data recovered from
satellite images are being used to improve the operational efficiency of fishing
vessels (e.g. reduce search time and increase catch rate) and to improve the understanding
of the variations in catch distribution and rate needed to properly manage
fisheries. The images used for retrieval of SST often present gaps due to the
existence of clouds or satellite malfunction periods. The data gaps can totally or
partially affect the area of interest. Within this study, an application of a technique
for the reconstruction of missing data called DINEOF (data interpolating empirical
orthogonal functions) is analysed, with the aim of testing its applicability in
operational SST retrieval during summer months. In this case study, the Bay of
Biscay is used as the target area. Three months of SST Moderate Resolution
Imaging Spectroradiometer (MODIS) images, ranging from 1 May 2006 to 31
July 2006, were used. The main objective of this work is to test the overall
performance of this technique, under potential operational use for the support of
the fleet during the summer fishing season. The study is designed to analyse the
sensitivity of the results of this technique to several details of the methodology used
in the reconstruction of SST, such as the number of empirical orthogonal functions
(EOFs) retained, the handling of the seasonal cycle or the length (number of
images) of the SST database used. The results are tested against independent
SST data from International Comprehensive Ocean–Atmosphere Data Set
(ICOADS) ship reports and standing buoys and estimations of the error of the
reconstructed SST fields are given.
Conclusions show that over this area three months of data are enough for
efficient SST reconstruction, which yields four EOFs as the optimal number
needed for this case study. An extended EOF experiment with SST and SST with
a lag of one day was carried out to analyse whether the autocorrelation of the SST
data allows better performance in the SST reconstruction, although theexperiment did not improve the results. The validation studies show that the
reconstructed SSTs can be trusted, even when the amount of missing data is very
high. The mean absolute deviation maps show that the error is greatest near to the
coast and mainly in the upwelling areas close to the French and north-western
Spanish coasts.
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