MIA: Artificial intelligence system for sub-seasonal forecast of hydrometeorological variables in Brazil

• Grant number: 21/14700-0
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: May 01, 2022
• End date: April 30, 2024
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Meteorology
• Principal Investigator: Thomas Christian Marcel Martin
• Grantee: Thomas Christian Marcel Martin
• Company: Meteoia Datascience Ltda
• CNAE: Pesquisa e desenvolvimento experimental em ciências físicas e naturais
• City: São Paulo
• Associated researchers: Edson Luiz Shoitchi Yatabe Barbosa ; Eduardo Bezerra da Silva ; Gabriel Martins Palma Perez ; Humberto Ribeiro da Rocha ; José Fernando e Toledo
• Associated research grant: 20/00566-8 - MIA: artificial intelligence system for sub-seasonal forecast of hydrometeorological variables in Brazil, AP.PIPE
• Associated scholarship(s): 22/07205-6 - MIA: artificial intelligence system for sub-seasonal hidrometerological forecast in Brazil, BP.PIPE

Abstract

The main goal of this proposal is the development of an automated artificial intelligence forecast system for hydrometeorological variables focused in the subseasonal scale, named MIA. The system will be used to make streamflow prediction at each hydropower plants of the "Sistema Interligado Nacional" (SIN). The innovations associated with this project are two-fold, both as a process and a service. As a process, the project will connect state-of-the-art artificial intelligence techniques, little explored in the climate sciences, in an end-to-end automated system of model training, forecast and hyperparameter optimization. As a service, this product of this project will be among the few subseasonal scale specialized systems, scale in which the traditional climate modelling approaches are weakest. As an outcome, we expect to reduce the uncertainties and improve the planning of the Brazilian market regarding the water variability associated with climate. We also expect to place the company in the recent frameworks of industry 4.0 and AutoML (automated machine learning). (AU)