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This article describes the enablement of the MM5 Meteorological model as a Computational Grid Workflow. Considering the challenges involved in converting legacy high performance scientific applications as service based workflows, this article provides an in-depth analysis and solutions thereof to design a Grid service based workflow of HPC scientific applications. It also captures the need and design...
Uncertainty quantification in climate models is challenged by the sparsity of the available climate data due to the high computational cost of the model runs. Another feature that prevents classical uncertainty analyses from being easily applicable is the bifurcative behavior in the climate data with respect to certain parameters. A typical example is the Meridional Overturning Circulation in the...
This paper describes the production and publication of regional weather forecast data processes based on both different users' needs and applications applied on the Brazilian Northeast region, highlighting the benefits brought for end-users. The process of producing weather forecasts is made up of five main phases: (i) download input data; (ii) preprocessing input data; (iii) regional atmospheric...
In this paper, we tackle the problem of scheduling an Ocean-Atmosphere application used for climate prediction on the grid. An experiment is composed of several 1D-meshes of identical DAGs composed of parallel tasks. To obtain a good completion time, we divide groups of processors into sets each working on parallel tasks. The group sizes are chosen by computing the best makespan for several grouping...
The Land Information System (LIS) is a multiscale hydrologic modeling and data assimilation framework that integrates the use of satellite and ground-based observational data products with advanced land-surface modeling tools to aid several application areas, including water resources management, numerical weather prediction, agricultural management, air quality, and military mobility assessment.
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