Name
Abstract | ||
|---|---|---|
Enhancing the quality of weather and climate forecasts are central scientific research objectives worldwide. However, simulations of the atmosphere, usually demand high processing power and large storage resources. In this context, we present the GBRAMS project, that applies grid computing to speed up the generation of a regional model climatology for Brazil. A grid infrastructure was built to perform long-term integrations of a mesoscale numerical model (BRAMS), managing a queue of up to nine independent jobs submitted to three clusters spread over Brazil. Three distinct middlewares, Globus Toolkit, OurGrid and OAR/CIGRI, were compared in their ability to manage these jobs, and results on the usage of each node of the grid are provided. We analyze the impact of the resulted climatology in the accuracy of climate forecast, showing model bias removal which indicates correctness of the generated climatology. Our central contribution are how to use grid computing to speed-up climatology generation and the middleware impact on this enterprise. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/CCGRID.2007.86 | CCGrid |
Keywords | Field | DocType |
grid environment,climatology generation,regional model climatology,grid computing,model bias removal,middleware impact,processing mesoscale climatology,grid infrastructure,climate forecast,central contribution,mesoscale numerical model,central scientific research objective,atmosphere,climatology,middleware,atmospheric modeling,computational modeling,weather forecasting,context modeling,scientific research,demand forecasting,mesh generation | Middleware,Weather and climate,Grid computing,Computer science,Correctness,Mesoscale meteorology,Climatology,Grid,Distributed computing,OurGrid,Speedup | Conference |
ISBN | Citations | PageRank |
0-7695-2833-3 | 2 | 0.40 |
References | Authors | |
2 | 13 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. P. Souto | 1 | 2 | 1.07 |
| R. B. Avila | 2 | 2 | 0.40 |
| Philippe Olivier Alexandre Navaux | 3 | 3 | 0.81 |
| M. X. Py | 4 | 2 | 0.40 |
| T. A. Diverio | 5 | 2 | 0.40 |
| H. F. Campos Velho | 6 | 2 | 0.73 |
| S. Stephany | 7 | 3 | 1.12 |
| Airam Jonatas Preto | 8 | 5 | 1.88 |
| J. Panetta | 9 | 2 | 0.73 |
| E. R. Rodrigues | 10 | 2 | 0.73 |
| E. S. Almeida | 11 | 2 | 0.40 |
| P. L. Silva Dias | 12 | 2 | 0.73 |
| A. W. Gandu | 13 | 2 | 0.40 |