General Curvilinear Ocean Model (GCOM)
From Advanced Computing Environments Lab
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Project Title:
Development of Computational Environments for the General Coastal Ocean Model (GCOM)
Project Link
Project Overview
In this project we focus on the development of a computational environment (CE) for the General Coastal Ocean Model (GCOM) project based on:
- improvements to the codebase used by the model
- middleware that will facilitate the use of cyberinfrastructure and advanced computing resources
- integration of appropriate Web 2.0/emerging technologies to facilitate the computation, analysis and access to the model by other projects
A long-term objective of this research is to also develop an end-to-end gateway for the coastal ocean modeling and monitoring communities, based on the General Curvilinear Ocean Model (GCOM) and advanced cyberinfrastructure technologies.
Model improvements include migration from F77 to F90, adoption of a simple component design, and parallelization of the model.
Through the use of the component design, new models are being incorporated including biogeochemical, pollution, and sediment transport. The computational environment is designed to allow various client interactions via secure Web applications (portal, Web services, and Web 2.0 gadgets). Features include:
- building jobs, managing and interacting with long running jobs;
- managing input and output files;
- quick visualization of results;
- publishing of Web services to be used by other systems such as larger climate models.
The CE is based mainly on Python tools including a grid-enabled Pylons Web application Framework for Web services, pyWSRF (python-Web Services-Resource Framework), pyGlobus based web services, SciPy, and various Google code tools.
The General Coastal Ocean Model (GCOM)
GCOM differs significantly from the traditional approach, where the use of Cartesian coordinates forces the model to simulate terrain as a series of steps. GCOM utilizes a full three-dimensional curvilinear transformation, which has been shown to have greater accuracy than similar models and to achieve results more efficiently. GCOM has been validated for several types of water bodies, different coastlines and bottom shapes, including the Alarcon Seamount, Southern California Coastal Region, the Valencia Lake in Venezuela, and more recently the Monterey Bay. The GCOM grid generation technique allows grid points to be clustered in any region of the computational domain. The resulting model equations are more complex than the original Cartesian ones but the advantage is that the boundary conditions are easier to implement and there is no need to interpolate near solid boundaries. The benefits of this approach include a more efficient algorithm and increased resolution. GCOM has been validated for several types of water bodies, with different coastlines and bottom shapes, among them the Monterey Bay (MB) in California, the Alarcon Seamount in the Gulf of California, and the Valencia Lake in Venezuela.
