Road Map Proposal to Latin American Climate Simulations based on Artificial Intelligence
Abstract
This document presents a road map proposal to integrate the scientific community in Latin America, for sharing computational resources and implementing climatic applications to forecast events related to global warming in the region. Climatic applications are commonly developed in distributed and parallel architectures because of the amount of data to process. As an optimization procedure, we are also proposing implementing Artificial Intelligence methods as the evaluation of the application performance as the improvement of the results of climatic simulations. An advantage of using this kind of algorithm is based on the possibility of identifying relationships between different weather events, with the development of models that integrate different types of phenomena, including extreme events. Climate forecasting models use various data sources, mainly collecting images and time series. A climate prediction model can be implemented with a network of remote sensors, and it involves a geographical distribution that could be extrapolated to processing tasks. The scientific community in Latin America can share computing resources and has the talent to develop the implementation of these algorithms. Moreover, we invite the scientific community members to join us to face this challenge.
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