Project Team Graal

Overall Objectives
Scientific Foundations
Application Domains
New Results
Partnerships and Cooperations
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Section: Application Domains

West African Monsoon Simulations

In collaboration with Team MOISE (UJF-Grenoble 1) and LGGE (Laboratoire de Glaciologie et Géophysique de l'Environnement ) we are interested in the large-scale environmental phenomenon of West African monsoon. It is the major atmospheric phenomenon, which drives the rainfall regime in Western Africa. The causes of spatio-temporal variability in monsoon rainfall have not yet been determined in an unequivocal manner. However, there is a considerable body of evidence suggesting that spatio-temporal changes in sea surface temperatures in the Gulf of Guinea and changes in the Saharan and sub-Saharan albedo are major factors. To simulate the rainfall, a regional atmospheric model (MAR) is used. The performance of the MAR was evaluated by comparison with precipitation data. One of the interest of physicists is to perform a sensitivity analysis on West African monsoon. However it cannot be realized by running the MAR, as we work on discretization grids in space and time, that is with huge dimensions. Hence an important preliminary step is the construction of a stochastic spatio-temporal metamodel approximating the MAR. The main properties required for this metamodel is the ability to be ran in a reasonable time and the consideration of the spatio-temporal dynamic of the underlying physical phenomenon. In this study we neglect the effect of albedo and focus our effort on regressing the rainfall on the sea surface temperature (SST). This simplification has been decided in agreement with the physicists.

An important point in this study is that the numerical storage and processing of model outputs, as far as the statistical description of the data, requires considerable computation resources. A grid environment can provide the required resources. Nevertheless, one main difficulty of the grid platform is the resource provisioning. How to find the best resource at a given time and the best amount of these resources? The answer should come from the middleware designed with an efficient scheduler. Moreover the middleware can give a transparent access to a distributed and heterogeneous platform as a Grid. We have used DIET on the regional Grid called CIMENT. Thus different DIET module was improved through this application. Bug fix on the workflow support. An automatic support of iRods a data grid software ( ) through DIET. And a new web interface designed for MAR.