Caring about the future

G-Cast: Application of GRID-computing in a coastal morphodynamics nowcast-forecast system
Coordinator - Anabela Oliveira
CESAM Responsible researcher - Paulo A. Silva
Programme - GRID/GRI/81733/2006
Execution dates - 2007-08-06 - 2011-08-05 (48 Months)
Funding Entity - FCT
Funding for CESAM - 30803 €
Total Funding - 166000 €
Proponent Institution - LNEC
Participating Institutions
Universidade de Aveiro

Project Description

The ability to simulate and forecast the long-term dynamics of estuarine and coastal zones is fundamental to assess the social, ecological and economical impacts of both human interventions and climate changes in these regions. A growing need to address this problem, fuelled in Europe by the Water Framework Directive and other legislation, has fostered the development of computational nowcast-forecast systems that provide predictions of several physical, chemical and biological quantities at short time scales, by integrating suites of models and field data. However, the large temporal and spatial scales involved in the long-term integrated simulation of the water and sediment dynamics of coastal regions as well as the complexity of the processes and uncertainty associated with the impact of climate changes require computational resources that were almost inexistent in the past. Grid computing is now emerging as an attractive and accessible tool for the modeling community to solve long-term, large scale problems in estuarine and coastal areas. Pilot applications are being developed in several places in the USA and Europe, but none is currently being done in Portugal. The availability of vast shared computational resources within the Grid computing community and a suite of parallel-processing models provide, for the first time, the means for an adequate scientific support for the sustainable long-term management of coastal systems. G-cast aims at combining the novel computational resources provided by Grid computing and the team expertise in the use of existing state-of-the-art numerical models to develop an exploratory analysis of the impact of climate changes on the long-term morphodynamic evolution of coastal zones. This goal will be achieved through 1) the adaptation of a suite of models within an existing morphodynamic modeling system to Grid-computing environment; 2) the integration of this modeling system in a nowcast-forecast computational system adapted for the Portuguese coast, and 3) its exploratory application to the analysis of climate change in the long-term morphodynamic dynamics of two contrasting coastal systems: the Óbidos lagoon and the Aveiro lagoon. These tasks will take advantage of the pilot Grid developed in the scope of the Rede Nacional de Computação Avançada (REDE/1513/RCA/2005), funded by FCT through the Re-equipamento Científico Program. During the course of the G-Cast project, LNEC´s node of this pilot Grid will be adapted to use middleware, a variation of the European project EGEE (Enabling Grids for E-sciencE) middleware, developed for interactive applications. The integration of these tools will provide a Grid-based pilot nowcast-forecast system for hydrodynamic and morphodynamic problems that can be applied to any Portuguese estuarine and coastal region, based on a suite of parallel-processing models, prepared to run in a Grid environment. G-cast constitutes thus the first step towards a new approach to operational oceanography in Portugal, by including both hydrodynamic and morphodynamic processes. The project will also promote the use of Grid computing in the Portuguese coastal modeling community, by demonstrating its importance in long-term morphodynamic applications to two coastal systems with distinct characteristics. These applications will analyze the impact of climate changes in the morphodynamics of the Óbidos lagoon, a small, but highly-dynamic system, with strong migration of its inlet, and in the morphodynamics of the Aveiro lagoon, a large, complex and human-modified system, whose inlet is constrained by two large breakwaters. 

CESAM members on this project
João Miguel Dias
Paulo A. Silva

CESAM Funding: UIDP/50017/2020 + UIDB/50017/2020 + LA/P/0094/2020