Suspended particulate matter (SPM) is an important constituent of marine ecosystems, and is involved in a wide range of biogeochemical processes. Because availability of light is dependent upon the concentration of suspended solids, correct representation of SPM dynamics is paramount for simulating the dynamics of primary producers, and therefore for simulating all the other ecological variables. This paper presents a brief overview of the Irish Sea/Liverpool Bay monitoring and modelling programme, and on the basis of a case study, discusses the ways how the models’ explanatory and predictive powers may be further enhanced by taking detailed account of patterns and processes related to the SPM dynamics and particle size distribution. Here we identify (using the results of monitoring data combined with tidal predictions generated by POLPRED model, and a Matlab script specially written to carry out stepwise regression modelling on these data) the meteorological and oceanographic variables especially important for the characterisation of SPM in Liverpool Bay. In particular, in the stepwise regression models, variables related to winds, waves, and tidal currents appear to explain considerable percent of the variance observed. Tides appear to matter more during springs than neaps, but overall show weaker relationships with SPM variables than winds and waves. These results are important for further developments and applications of the POLCOMS and ERSEM models, and may have implications for a number of ecological and oceanographic issue
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