A Machine Learning Approach for Rainfall Nowcasting Using Numerical Model and Observational Data

Author:

Kyros Georgios12ORCID,Manolas Ioannis1ORCID,Diamantaras Konstantinos1ORCID,Dafis Stavros2ORCID,Lagouvardos Konstantinos2

Affiliation:

1. Department of Information and Electronic Engineering, International Hellenic University, 57400 Thessaloniki, Greece

2. Institute of Environmental Research and Sustainable Development, National Observatory of Athens, 11810 Athens, Greece

Publisher

MDPI

Reference24 articles.

1. Olawoyin, A.M., Leung, C.K., Hryhoruk, C.C.J., and Cuzzocrea, A. (2023, January 29–31). Big Data Management for Machine Learning from Big Data. Proceedings of the 37th International Conference on Advanced Information Networking and Applications (AINA-2023), Juiz de Fora, Brazil.

2. Hussein, E., Sadiki, R., Jafta, Y., Sungay, M.M., Ajayi, O., and Bagula, A. (2019, January 3–4). Big Data Processing Using Hadoop and Spark: The Case of Meteorology Data. Proceedings of the 11th EAI International Conference, AFRICOMM 2019, Porto-Novo, Benin. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

3. (2023, April 25). World Health Organization: Climate Change and Human Health: Risks and Responses. World Health Organization, January 2003. Available online: https://apps.who.int/iris/handle/10665/42749.

4. (2023, April 26). WMO Atlas of Mortality and Economic Losses from Weather, Climate and Water Extremes (1970–2019) (WMO-No. 1267). Available online: https://library.wmo.int/index.php?lvl=notice_display&id=21930#.ZGJGDs5ByUm.

5. Pörtner, H.-O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., and Möller, V. (2022). Climate Change 2022: Impacts, Adaptation and Vulnerability, Cambridge University Press. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.

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