气候变化领域集成服务门户(CCPortal): Estimation of global coastal sea level extremes using neural networks

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DOI	10.1088/1748-9326/ab89d6
	Estimation of global coastal sea level extremes using neural networks
	Bruneau N.; Polton J.; Williams J.; Holt J.
发表日期	2020
ISSN	17489318
卷号	15 期号:7
英文摘要	Accurately predicting total sea-level including tides and storm surges is key to protecting and managing our coastal environment. However, dynamically forecasting sea level extremes is computationally expensive. Here a novel alternative based on ensembles of artificial neural networks independently trained at over 600 tide gauges around the world, is used to predict the total sea-level based on tidal harmonics and atmospheric conditions at each site. The results show globally-consistent high skill of the neural networks (NNs) to capture the sea variability at gauges around the globe. While the main atmosphere-driven dynamics can be captured with multivariate linear regressions, atmospheric-driven intensification, tide-surge and tide-tide non-linearities in complex coastal environments are only predicted with the NNs. In addition, the non-linear NN approach provides a simple and consistent framework to assess the uncertainty through a probabilistic forecast. These new and cheap methods are relatively easy to setup and could be a valuable tool combined with more expensive dynamical model in order to improve local resilience. © 2020 The Author(s). Published by IOP Publishing Ltd.
英文关键词	extremes; GESLA database; machine learning; sea water anomaly; storm surges
语种	英语
scopus关键词	Coastal zones; Forecasting; Sea level; Tide gages; Uncertainty analysis; Atmospheric conditions; Coastal environments; Coastal sea level; Dynamical model; Multivariate linear regressions; Neural networks (NNS); Probabilistic forecasts; Tidal harmonics; Neural networks; artificial neural network; coastal zone management; estimation method; extreme event; global change; sea level change; storm surge
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/153936
作者单位	National Oceanography Centre, Joseph Proudman Building, Liverpool, L3 5DA, United Kingdom; Reask UK Ltd, 49 Greek Street, London, W1D 4EG, United Kingdom
推荐引用方式 GB/T 7714	Bruneau N.,Polton J.,Williams J.,et al. Estimation of global coastal sea level extremes using neural networks[J],2020,15(7).
APA	Bruneau N.,Polton J.,Williams J.,&Holt J..(2020).Estimation of global coastal sea level extremes using neural networks.Environmental Research Letters,15(7).
MLA	Bruneau N.,et al."Estimation of global coastal sea level extremes using neural networks".Environmental Research Letters 15.7(2020).