The Philosophy of TeraGrid: Building an Open, Extensible, Distributed TeraScale Facility
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
The Globus Striped GridFTP Framework and Server
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
The Computational and Storage Potential of Volunteer Computing
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Short communication: GRID computing approach for multireservoir operating rules with uncertainty
Environmental Modelling & Software
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
A parallelization framework for calibration of hydrological models
Environmental Modelling & Software
Environmental Modelling & Software
Forecasting ENSO with a smooth transition autoregressive model
Environmental Modelling & Software
Distributed computation of large scale SWAT models on the Grid
Environmental Modelling & Software
Environmental Modelling & Software
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Grid computing is nowadays an established technology in fields such as High Energy Physics and Biomedicine, offering an alternative to traditional HPC for several problems; however, it is still an emerging discipline for the climate community and only a few climate applications have been adapted to the Grid to solve particular problems. In this paper we present an up-to-date description of the advantages and limitations of the Grid for climate applications (in particular global circulation models), analyzing the requirements and the new challenges posed to the Grid. In particular, we focus on production-like problems such as sensitivity analysis or ensemble prediction, where a single model is run several times with different parameters, forcing and/or initial conditions. As an illustrative example, we consider the Community Atmospheric Model (CAM) and analyze the advantages and shortcomings of the Grid to perform a sensitivity study of precipitation with SST perturbations in El Nino area, reporting the results obtained with traditional (local cluster) and Grid infrastructures. We conclude that new specific middleware (execution workflow managers) is needed to meet the particular requirements of climate applications (long simulations, checkpointing, etc.). This requires the side-by-side collaboration of IT and climate groups to deploy fully ported applications, such as the CAM for Grid (CAM4G) introduced in this paper.