Editorial: EVA 2019 data competition on spatio-temporal prediction of Red Sea surface temperature extremes

DOI10.1007/s10687-019-00369-9zbMath1461.00065arXiv1912.00694OpenAlexW3000316433WikidataQ126348295 ScholiaQ126348295MaRDI QIDQ2028570

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Publication date: 1 June 2021

Published in: Extremes (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.00694

zbMATH Keywords

predictionextremal dependenceextreme eventspatio-temporal processdata competitionEVA 2019 conferenceRed Sea surface temperature datathreshold-weighted continuous ranked probability score

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Proceedings, conferences, collections, etc. pertaining to statistics (62-06) Proceedings of conferences of miscellaneous specific interest (00B25)

Related Items (2)

Estimating high-resolution red sea surface temperature hotspots, using a low-rank semiparametric spatial model ⋮ Spatio-temporal prediction of missing temperature with stochastic Poisson equations. The LC2019 team winning entry for the EVA 2019 data competition

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