Observed vs. predicted variability in non-algal suspended particulate matter concentration in the English Channel in relation to tides and waves

Rivier, Aurélie, Gohin, Francis, Bryére, Philippe, Petus, Caroline, Guillou, Nicolas, and Chapalain, Georges (2011) Observed vs. predicted variability in non-algal suspended particulate matter concentration in the English Channel in relation to tides and waves. Geo-Marine Letters, 32 (2). pp. 139-151.

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Abstract

The study of water clarity is essential to understand variability in biological production, particularly in coastal seas. The spatial and temporal variability of non-algal suspended particulate matter (SPM) in surface waters of the English Channel was investigated and related to local forcing by means of a large satellite dataset covering the study area with a spatial resolution of 1.2 km and a daily temporal resolution. This analysed dataset is a time series of non-algal SPM images derived from MODIS and MERIS remote-sensing reflectance by application of an IFREMER semi-analytical algorithm over the period 2003–2009. In a first step, the variability of time series of MODIS images was analysed through temporal autocorrelation functions. Then, non-algal SPM concentrations were assessed in terms of site-specific explanatory variables such as tides, wind-generated surface-gravity wave amplitudes and chlorophyll-a (Chl-a), based on three statistical models with fitting parameters calibrated on a dataset of merged MERIS/MODIS images gathered from 2007 to 2009 over the whole English Channel. Correlogram analysis and the first model highlight the local patterns of the influence of the tide, especially the neap–spring cycle, on non-algal surface SPM. Its effect is particularly strong in the central and eastern English Channel and in the western coastal areas. The second model shows that waves prevail as driver at the entrance of the English Channel. The most sophisticated of the three statistical models, although involving only three explanatory variables—the tide, waves and Chl-a—is able to estimate non-algal surface SPM with a coefficient of determination reaching 70% at many locations.

Item ID: 38206
Item Type: Article (Refereed Research - C1)
ISSN: 1432-1157
Funders: European Regional Development Fund
Date Deposited: 07 Jul 2015 05:12
FoR Codes: 05 ENVIRONMENTAL SCIENCES > 0502 Environmental Science and Management > 050206 Environmental Monitoring @ 70%
04 EARTH SCIENCES > 0405 Oceanography > 040503 Physical Oceanography @ 30%
SEO Codes: 96 ENVIRONMENT > 9611 Physical and Chemical Conditions of Water > 961102 Physical and Chemical Conditions of Water in Coastal and Estuarine Environments @ 100%
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