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Expert Crowdsourcing for Semantic Annotation of Atmospheric Phenomena
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  • Margarida Liberato,
  • Hugo Paredes,
  • Alexandre Ramos,
  • Arsénio Reis,
  • Riccardo Hénin,
  • João Barroso
Margarida Liberato
Escola de Ciências e Tecnologia

Corresponding Author:[email protected]

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Hugo Paredes
INESC Technology and Science (INESC TEC)
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Alexandre Ramos
Instituto Dom Luiz (IDL)
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Arsénio Reis
Escola de Ciências e Tecnologia
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Riccardo Hénin
Instituto Dom Luiz (IDL)
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João Barroso
Escola de Ciências e Tecnologia
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Abstract

Weather extremes have gained great attention to the general public and policy makers recently. Extratropical cyclones, frontal systems and atmospheric rivers are central components of weather over mid latitudes. These phenomena are associated with compound weather conditions, including dramatic changes in temperature, wind and extreme precipitation. In fact, wind extremes and heavy precipitation events occurring in the winter over land in the mid latitudes are mostly associated with extratropical cyclones. It is well known that the Iberian Peninsula, due to its location, is prone to the occurrence of these compound extreme events and associated hazards (Liberato et al., 2013; 2014). In this project our aim is to explore the usage of expert crowdsourcing for annotating weather systems associated to compound hydrometeorological extreme events over the Euro-Atlantic region, so automated methods and computational resources can be optimized in a future hybrid approach. This approach allows a sharing of lessons learned and a common design ground. Atmospheric phenomena annotation aims at bringing new dimensions to current big data problems in climate and atmospheric sciences. Today big data full potential in weather and climate science domain is still restricted by the poor semantic knowledge of data gathered and the inability to correlate data with other domains. Acknowledgements: This work is supported by the Portuguese Science and Technology Foundation (Fundação para a Ciência e Tecnologia – FCT), under the projects UID/GEO/50019/2013 – Instituto Dom Luiz and CMU/CS/0012/2017 – “eCSAAP - expert Crowdsourcing for Semantic Annotation of Atmospheric Phenomena”. Liberato et al. 2013 Nat. Hazards Earth Syst. Sci., 13:2239-2251 doi: 10.5194/nhess-13-2239-2013 Liberato 2014 Weather and Climate Extremes, 5-6: 16-28 doi: 10.1016/j.wace.2014.06.002