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English Information

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Authors
# Name
1 Bruno de Freitas(brunolf@id.uff.br)
2 Augusto Fonseca(augusto.fonseca@aluno.cefet-rj.br)
3 Eduardo Bezerra(ebezerra@cefet-rj.br)
4 Mariza Ferro(mariza@ic.uff.br)
5 Flavia Bernardini(fcbernardini@ic.uff.br)

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Reference
# Reference
1 Ferro, M., Bezerra, E., Ogasawara, E., Moraes, N., and Porto, F. (2022). Towards a definition for extreme weather events in rio de janeiro city. In Anais Estendidos do XXXVII Simpósio Brasileiro de Bancos de Dados, pages 181–186. SBC
2 Jitkajornwanich, K., Pant, N., Fouladgar, M., and Elmasri, R. (2020). A survey on spatial, temporal, and spatio-temporal database research and an original example of relevant applications using sql ecosystem and deep learning. Journal of Information and Telecommunication, 4(4):524–559
3 Marzban, C. and Sandgathe, S. (2006). Cluster analysis for verification of precipitation fields. Weather and Forecasting, 21(5):824–838
4 Salles Civitarese, D., Szwarcman, D., Zadrozny, B., and Watson, C. (2021). Extreme precipitation seasonal forecast using a transformer neural network. arXiv e-prints, pages arXiv–2107
5 Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M. M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M. (2014). Climate change 2013: The physical science basis. contribution of working group i to the fifth assessment report of ipcc the intergovernmental panel on climate change
6 Wanderley, H. and Bunhak, A. (2016). Alteration in precipitation and number of days without rain in the southern region of rio de janeiro state. rev brasil geog físic. 9. 7. 2341–2353