Intermediate Scale Coastal Behaviour: Measurement, Modelling and Prediction

Abstract

Our overall goal is to achieve a better understanding and better predictions of coastal behaviour at intermediate (event/season/year/decade) scales. We aim to bring together researchers from Europe and North America to gain the best possible benefit from developments in field observation, theory and numerical modelling. We are following a four-pronged collaborative approach. Data on intermediate scale behaviour from both sides of the Atlantic are being studied and ways are being sought to project these observations onto a manageable number of descriptive parameters or basic patterns. Top-down modelling uses these data products to develop black-box (data extrapolation) and grey-box (behaviour-oriented) models for the observed behaviour. Bottom-up modelling investigates the predictive potential of process-based models, making best use of process results from US and European field campaigns, combined with existing modelling expertise. There is also a vital linking activity aimed at ensuring that the data, top-down modelling and bottom-up modelling activities interact fully, in order to bring together the most productive aspects of each into a predictive capability for intermediate-scale coastal change.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1999
Accession Number
ADA630166

Entities

People

  • David Huntley
  • Edward B. Thornton
  • Huib De Vriend
  • R. A. Holman
  • Richard Soulsby
  • Rolf Deigaard
  • Tony Bowen

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Atmospheric Sciences
  • Boundary Layer
  • Coastal Engineering
  • Engineering
  • Genetic Algorithms
  • Geography
  • Grain Size
  • Measurement
  • Neural Networks
  • New York
  • North America
  • Nova Scotia
  • Sedimentation
  • Self Organizing Systems
  • Universities

Fields of Study

  • Environmental science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Space/Atmospheric Physics.
  • Systems Analysis and Design