Challenges for mesoscale climatology execution on experimental grid computing systems

Abstract

This paper discusses the challenges of executing a long-term application on a computational grid, which generates the climatology of the atmospheric numerical model BRAMS (Brazilian development on Regional Atmospheric Modeling System) using ensemble members. We have developed a workflow that submits climatology to the computational grid composed by three different grid middlewares (OurGrid, OAR/CiGri and Globus) and three clusters (situated in Porto Alegre, São José dos Campos and Cachoeira Paulista-Brazil). The application characteristics demand a processing grid, rather than a data grid, due to intensive computation and data transfer between the geographically distributed grid nodes. We achieved the goal of generating the climatology using a computational grid. However, we observed problems on application performance due data transfer and non-availability of the computational grid. Questions related to data storage/transfer and grid failures must be better treated to ensure application performance.

Analysis for Precipitation Climate Prediction on South of Brazil

“…BRAMS project, andAlmeida et al (2013) show the results.Long range time integrations of BRAMS simulations will provide data for some climate analysis, and for numerical integration of different models: (a) extreme events regimes, (b) MGB-IPH (hydrological) model, (c) InfoCrop: model calibrated for Southern Brazil with three agriculture crops to be analyzed (rice, soybean, and corn). The boundary conditions are provided from CPTEC-INPE global model, where 5 members (meaning, 5 different initial conditions) are integrated for 10 years(period: 1992-2001).…”