Mining meteorological data

The book, based on the author's research, aims to propose a computational model that combines meso- and micro-scale meteorological observations to identify and forecast, one hour in advance, the formation of heavy rains that may be considered a risk to a given region, based on historical data. The data used were recorded by the surface meteorological station maintained by the Center for Environmental Technology (Cetema) located at the Polytechnic Institute of the State University of Rio de Janeiro (IPRJ/Uerj), observed between November 2008 and April 2012, in the city of Nova Friburgo-RJ, as well as output data from the numerical forecast provided by the Eta regional model of Cptec/Inpe. Data mining techniques were applied to this data in order to identify patterns of behavior and relationships between them.

Autorentext

Friburguense, magister modelowania komputerowego Uniwersytetu Stanowego w Rio de Janeiro (Uerj), gdzie zajmowä si eksploracj danych meteorologicznych w ramach badä z zakresu matematyki stosowanej i informatyki naukowej, oraz absolwent analizy i rozwoju systemów na Faculdade Santa Dorotéia.

Klappentext

The book, based on the author's research, aims to propose a computational model that combines meso- and micro-scale meteorological observations to identify and forecast, one hour in advance, the formation of heavy rains that may be considered a risk to a given region, based on historical data. The data used were recorded by the surface meteorological station maintained by the Center for Environmental Technology (Cetema) located at the Polytechnic Institute of the State University of Rio de Janeiro (IPRJ/Uerj), observed between November 2008 and April 2012, in the city of Nova Friburgo-RJ, as well as output data from the numerical forecast provided by the Eta regional model of Cptec/Inpe. Data mining techniques were applied to this data in order to identify patterns of behavior and relationships between them.