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Characterising observed patterns of suspended particulate matter and relationships with oceanographic and meteorological variables: studies in Liverpool Bay

By V. Krivtsov, M. J. Howarth and Jones

Abstract

Suspended particulate matter (SPM) in the marine environment is represented by a mixture of organic and inorganic particles, and is characterised by complex structural and dynamical transformations. This paper describes our SPM studies in Liverpool Bay (UK), and identifies (using Stepwise Regression Modelling) the meteorological and oceanographic variables especially important for the characterisation of the SPM at this site. By analysing data sets from 9 cruises conducted between September 2004 and February 2006, it was found that the highest number of significant relationships (25) was shown by Salinity and Temperature. It is therefore evident, that the most important factors influencing SPM-related variables are related to the inshore-offshore gradient. This influence has also been reflected in the importance of such variables as Density (10) relationships and Depth (9). Another very important factor appears to relate to wind waves, with the cubed amplitude of orbital velocity at the bed demonstrating 23 significant relationships, TKE due to wind showing 13 relationships, dominant wave direction 11, and average wave period 9. These figures appear to exceed the numbers of significant relationships shown by the variables related to tides (e.g. tidal level 15, tide direction 9, TKE at the surface due to the tidal current 4). Hence waves appear to matter more than tides. The Matlab function used for stepwise regression modelling is particularly suitable for the analysis of large amounts of repetitive information (e.g. for processing data from a number of cruises where the same or similar protocol was used for data collection and storage), with the results being stored in Excel files. This facilitates the analysis and enables an easy exchange of the results (i.e. due to the widespread use of Microsoft Excel). The Matlab function is provided online as a supplementary appendi

Topics: Marine Sciences
Publisher: Elsevier
Year: 2009
OAI identifier: oai:nora.nerc.ac.uk:9730
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