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Publicação
Crowdsourcing de Dados Meteorologicos
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| 6.94 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Given its role as a central element, IPMA receives observations measured by Automatic Weather Stations (AWS) belonging to the AWS Network, recognized for their accuracy and reliability. However, due to the associated costs, they are limited in quantity and therefore spatially dispersed, which hinders scientific advances and service improvements. In contrast, Personal Weather Station (PWS) exist in increasing numbers, mainly due to their low cost and accessibility, whose distribution is correlated with population density, which together automatically provide data with high temporal and spatial resolution to numerous online platforms, as soon as they are configured by their owners. Thus, considering civic responsibility and intrinsic motivation, IPMA sought to respond to the underutilization of climate data resulting from the Crowdsourcing process at a national level, following the example of other initiatives, given the stigma among the scientific community regarding the inherent quality. Based on the associated value and enormous potential for application in a complementary way to the measurements received, the project emerges as an initial approach to understanding, processing and using data of this nature. With this in mind, the METEO-CROWD system was created, responsible for obtaining weather observations from multiple sources, which are then subjected to a validation process carried out by a quality control system, before being made available for viewing on the OBSERVAR platform. During the course of the work, meteorological measurements were collected from more than 1,500 stations, both public and internal, a number considered unattainable in terms of functional AWS; however, it is set to increase, due to the possible collection of private data and the general growth in the number of PWS, motivated by their characteristics and the intensification of climatic interest. In the global context, the data acquired could be a valuable resource in the future, especially for urban climate studies, local climate monitoring and weather forecasting.
Descrição
Trabalho de Projeto de Mestrado, Engenharia Informática, 2025, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Crowdsourcing Personal weather stations High resolution data Automatic weather stations Climate monitoring