Conferences & Workshops

2024

Interpolação e Previsão de Precipitação por Redes Neurais Convolucionais para Grafos

14-10-2024

Augusto Fonseca, Ronaldo Goldschmidt, Eduardo Ogasawa, Mariza Ferro, Fabio Porto, Eduardo Bezerra

Abstract:

Statistical interpolation methods used to adapt data do not adequately capture the spatiotemporal dependencies of meteorological data. This work proposes the use of Graph Convolutional Neural Networks (GCNs) for precipitation interpolation and forecasting. The experiments utilized radar data and in-situ station data. Comparing GCN interpolation with the statistical Inverse Distance Weighting (IDW) method, preliminary......

2023

Precipitation Nowcasting using Data Augmentation

25-09-2023

Eduardo Bezerra, Augusto Fonseca, Adriano Cabo, Fabio Porto, Mariza Ferro

Abstract:

○ This paper proposes a simple data augmentation technique specifically designed to mitigate the data unbalancing problem in precipitation nowcasting. We consider the existence of one or more observational systems, each one comprised of a set of (either weather or rain gauge) stations. We use simulated data coming from the ERA5 numerical model to......
Diversidade de Dados Meteorológicos da Cidade do Rio de Janeiro: Uma Proposta de Arquitetura de Armazenamento e Fluxo de Dados para Modelos de Previsão

25-09-2023

Bruno L. Freitas, Augusto Fonseca, Eduardo Bezerra, Flávia C. Bernardini, Mariza Ferro

Abstract:

A precipitação nowcasting é um componente essencial dos sistemas de alerta precoce e das ações consecutivas no âmbito da gestão de crises para eventos climáticos extremos em áreas urbanas. Este artigo apresenta os trabalhos em andamento para a coleta, descrição de atributos, preparação e uso de múltiplas observações meteorológicas como fontes de dados disponíveis......

2022

Towards a Definition for Extreme Weather Events in Rio de Janeiro City

19-09-2022

Mariza Ferro, Eduardo Bezerra, Eduardo Ogasawara, Nilton Moraes, Fabio Porto

Abstract:

Extreme weather events is a new area of research that has recently attracted the attention of researchers from different disciplines. In this paper, we investigate the phenomena from a data-driven forecast standpoint for severe rainfall occurring in the city of Rio de Janeiro. We aim at a formal definition for the phenomena that can......
Evaluating ML models for lightning forecasting in Brazil

19-09-2022

Arielle dos Santos Bassanelli Pereira, Alvaro L. Fazenda, Alan James Peixoto Calheiros

Abstract:

Instruments for monitoring severe meteorological phenomena (such as lightning, flooding and landslides) can be used to assist in decision-making by state agencies, in an attempt to mitigate their possible harmful effects. These phenomena usually occur suddenly on a short-term duration, under a limited region, imposing difficulties in being predicted by regular weather forecast models,......
Analysis of precipitation data in Rio de Janeiro city using Extreme Value Theory

19-09-2022

Augusto J. M. da Fonseca, Fabio Porto, Mariza Ferro, Eduardo Ogasawara, Eduardo Bezerra

Abstract:

Every year the city of Rio de Janeiro is hit by heavy rains that cause several disasters. To be able to reduce potential damages that may arise due to extreme rainfall, it is important to make accurate estimates of such events. In this paper, we present preliminary work on using Extreme Value Theory (EVT)......
Towards a cloud-based framework for online and integrated event detection

19-09-2022

Janio Lima, Rebecca Salles, Luciana Escobar, Cristiane Géa, Pedro Alpis Fernandes, Esther Pacitti, Fabio Porto, Rafaelli Coutinho, Eduardo Ogasawara

Abstract:

Time series events detection relates to the study of techniques for detecting points in a series with special meaning which differs from the expected behavior of the dataset. In scenarios such as digital twins and IoT devices, there is natural generation and traffic of data in the cloud. Event detection is critical for timely......
Analysis and Visualization of Extreme Weather Events in the City of Rio de Janeiro

19-09-2022

Anderson Silva, Thiago Moeda, Fabio Porto

Abstract:

Extreme weather events regularly occur in different locations, causing immense social, environmental and economic impact and damage. Especially in the city of Rio de Janeiro, understanding extreme events related to heavy rains is a fundamental component for the correct prediction of new phenomena, ideally resulting in models capable of predicting when, how and where......