5 resultados para Channel Modelling

em Publishing Network for Geoscientific


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State-of-the-art process-based models have shown to be applicable to the simulation and prediction of coastal morphodynamics. On annual to decadal temporal scales, these models may show limitations in reproducing complex natural morphological evolution patterns, such as the movement of bars and tidal channels, e.g. the observed decadal migration of the Medem Channel in the Elbe Estuary, German Bight. Here a morphodynamic model is shown to simulate the hydrodynamics and sediment budgets of the domain to some extent, but fails to adequately reproduce the pronounced channel migration, due to the insufficient implementation of bank erosion processes. In order to allow for long-term simulations of the domain, a nudging method has been introduced to update the model-predicted bathymetries with observations. The model-predicted bathymetry is nudged towards true states in annual time steps. Sensitivity analysis of a user-defined correlation length scale, for the definition of the background error covariance matrix during the nudging procedure, suggests that the optimal error correlation length is similar to the grid cell size, here 80-90 m. Additionally, spatially heterogeneous correlation lengths produce more realistic channel depths than do spatially homogeneous correlation lengths. Consecutive application of the nudging method compensates for the (stand-alone) model prediction errors and corrects the channel migration pattern, with a Brier skill score of 0.78. The proposed nudging method in this study serves as an analytical approach to update model predictions towards a predefined 'true' state for the spatiotemporal interpolation of incomplete morphological data in long-term simulations.

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The "SESAME_IT3_ZooAbundance_0-50-100m_SZN" dataset contains data of mesozooplankton species composition and abundance (ind. m-3) from samples collected in the Sicily Channel in the early spring of 2008 (17,18 March) during the SESAME-WP2 cruise IT3. Samples were collected by vertical tows with a closing WP2 net (56 cm diameter, 200 µm mesh size) in the following depth layers: 100-200 m, 50-100 m, 0-50 m. Sampling was always performed in light hours with the exception of station S-IT3-03 where zooplankton were collected in dark hours. A flowmeter was applied to the mouth of the net, however, due to its malfunctioning, the volume of filtered seawater was calculated by multiplying the the area by the height of the sampled layer from winch readings. After collection, each sample was split in two halves (1/2) after careful mixing with graduated beakers. Half sample was immediately fixed and preserved in a formaldehyde-seawater solution (4% final concentration) for species composition and abundance. The other half sample was kept fresh for biomass measurements (data already submitted to SESAME database in different files).Here, only the zooplankton abundance of samples in the upper layers 0-50 m and 50-100 m are presented. The abundance data of the samples in the layer 50-100 m will be submitted later in a separate file. The volume of filtered seawater was estimated by multiplying the the area by the height of the sampled layer from winch readings. Identification and counts of specimens were performed on aliquots (1/20-1/5) of the fixed sample or on the total sample (half of the original sample) by using a graduate large-bore pipette. Copepods were identified to the species level and separated into females, males and juveniles (copepodites). All other taxa were identified at the species level when possible, or at higher taxonomic levels. Taxonomic identification was done according to the most relevant and updated taxonomic literature. Total mesozooplankton abundance was computed as sum of all specific abundances determined as explained above.