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e-Science 2008 4th IEEE International Conference on e-Science

Exhibits, Demos & Posters

Producing and Sharing Regional Weather Forecast Data for e-Science Applications

Authors

  • Marcus Carvalho, Laboratório de Sistemas Distribuídos, Departamento de Sistemas e Computação, Universidade Federal de Campina Grande
  • Eliane Araújo, Laboratório de Sistemas Distribuídos, Departamento de Sistemas e Computação, Universidade Federal de Campina Grande
  • Renato O. Fernandes, Departamento de Engenharia Civil, Universidade Federal de Campina Grande
  • Rodolfo L. B. Nóbrega, Departamento de Engenharia Civil, Universidade Federal de Campina Grande

Abstract

Irregular rainfalls cause problems such as lack of drinking water, food, and work, mainly among the poor. The Brazilian Northeast, for example, is severely affected by this phenomenon because of its semi-arid climate. All this calls for an efficient water management policy.

The uncertainty of rain distribution makes water resources management difficult. Weather forecast analyses are extremely necessary for water resource management.Some weather organizations make data on weather conditions available, but these organizations usually operate on a global scale, generating low resolutions results.

A regional atmospheric model provides more accurate forecasts for a given area. However, the execution of these models requires high computational power, the input data of which are distributed among several providers and generates a large amount of output data.

Many users are interested in these forecast analyses: for example, meteorologists are interested in images or in raw data for climate analysis; agronomists are interested in rain information to manage food production; and hydrologists are interested in data to execute water management and distribution models. To support these e-scientists and all other possible users, forecast analyses should be shared and made available in different formats.

The present 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 for end-users.

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