%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16c/2020/12.15.13.05
%2 sid.inpe.br/mtc-m16c/2020/12.15.13.05.04
%@issn 2179-4847
%T Geographical Complex Networks applied to describe meteorological data
%D 2020
%A Jorge, Aurelienne Aparecida Souza,
%A Costa, Izabelly Carvalho da,
%A Santos, Leonardo B. L.,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)
%@electronicmailaddress aurelienne.jorge@inpe.br
%@electronicmailaddress izabelly.costa@inpe.br
%@electronicmailaddress santoslbl@gmail.com
%E Carneiro, Tiago Garcia de Senna (UFOP),
%E Felgueiras, Carlos Alberto (INPE),
%B Simpósio Brasileiro de Geoinformática, 21 (GEOINFO)
%C On-line
%8 30 nov. a 03 dez. 2020
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%S Anais
%K banon.
%X ComplexNetworkshavebeenwidelyappliedtoclimatedataanalysis, identifying relations and patterns in the atmosphere on a long-term scale. How- ever, a few investigations have made use of Complex Networks to study meteo- rology (dealing with short-term changes in the atmosphere). With this in mind, the purpose of the present work is to make some progress in the spatial anal- ysis of metrics in meteorological networks, specifically in precipitation events. We present some results for a study case comprising the Tamanduate ́ı basin, in which we could analyze the spatial dependence intrinsic in the network struc- ture.
%9 Geoinformação
%@language en
%3 s17.pdf