Articles | Volume 23, issue 2
https://doi.org/10.5194/nhess-23-415-2023
https://doi.org/10.5194/nhess-23-415-2023
Research article
 | 
02 Feb 2023
Research article |  | 02 Feb 2023

Detecting anomalous sea-level states in North Sea tide gauge data using an autoassociative neural network

Kathrin Wahle, Emil V. Stanev, and Joanna Staneva

Related authors

Recent changes in extreme wave events in the Southwestern South Atlantic
Carolina Barnez Gramcianinov, Joanna Staneva, Celia Regina Gouveia Souza, Priscila Linhares, Ricardo de Camargo, and Pedro Leite da Silva Dias
State Planet Discuss., https://doi.org/10.5194/sp-2022-7,https://doi.org/10.5194/sp-2022-7, 2022
Revised manuscript accepted for SP
Short summary
The role of heat wave events in the occurrence and persistence of thermal stratification in the southern North Sea
Wei Chen, Joanna Staneva, Sebastian Grayek, Johannes Schulz-Stellenfleth, and Jens Greinert
Nat. Hazards Earth Syst. Sci., 22, 1683–1698, https://doi.org/10.5194/nhess-22-1683-2022,https://doi.org/10.5194/nhess-22-1683-2022, 2022
Short summary
Nitrogen cycling in the Elbe estuary from a joint 3D-modelling and observational perspective
Johannes Pein, Annika Eisele, Richard Hofmeister, Tina Sanders, Ute Daewel, Emil V. Stanev, Justus van Beusekom, Joanna Staneva, and Corinna Schrum
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-265,https://doi.org/10.5194/bg-2019-265, 2019
Revised manuscript not accepted
Short summary
Can wave coupling improve operational regional ocean forecasts for the north-west European Shelf?
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019,https://doi.org/10.5194/os-15-669-2019, 2019
Short summary
A multi-collocation method for coastal zone observations with applications to Sentinel-3A altimeter wave height data
Johannes Schulz-Stellenfleth and Joanna Staneva
Ocean Sci., 15, 249–268, https://doi.org/10.5194/os-15-249-2019,https://doi.org/10.5194/os-15-249-2019, 2019
Short summary

Related subject area

Sea, Ocean and Coastal Hazards
The effect of deep ocean currents on ocean- bottom seismometers records
Carlos Corela, Afonso Loureiro, José Luis Duarte, Luis Matias, Tiago Rebelo, and Tiago Bartolomeu
Nat. Hazards Earth Syst. Sci., 23, 1433–1451, https://doi.org/10.5194/nhess-23-1433-2023,https://doi.org/10.5194/nhess-23-1433-2023, 2023
Short summary
An interdisciplinary agent-based evacuation model: integrating the natural environment, built environment, and social system for community preparedness and resilience
Chen Chen, Charles Koll, Haizhong Wang, and Michael K. Lindell
Nat. Hazards Earth Syst. Sci., 23, 733–749, https://doi.org/10.5194/nhess-23-733-2023,https://doi.org/10.5194/nhess-23-733-2023, 2023
Short summary
Coastal extreme sea levels in the Caribbean Sea induced by tropical cyclones
Ariadna Martín, Angel Amores, Alejandro Orfila, Tim Toomey, and Marta Marcos
Nat. Hazards Earth Syst. Sci., 23, 587–600, https://doi.org/10.5194/nhess-23-587-2023,https://doi.org/10.5194/nhess-23-587-2023, 2023
Short summary
Characteristics of consecutive tsunamis and resulting tsunami behaviors in southern Taiwan induced by the Hengchun earthquake doublet on 26 December 2006
An-Chi Cheng, Anawat Suppasri, Kwanchai Pakoksung, and Fumihiko Imamura
Nat. Hazards Earth Syst. Sci., 23, 447–479, https://doi.org/10.5194/nhess-23-447-2023,https://doi.org/10.5194/nhess-23-447-2023, 2023
Short summary
Potential tsunami hazard of the southern Vanuatu subduction zone: tectonics, case study of the Matthew Island tsunami of 10 February 2021 and implication in regional hazard assessment
Jean Roger, Bernard Pelletier, Aditya Gusman, William Power, Xiaoming Wang, David Burbidge, and Maxime Duphil
Nat. Hazards Earth Syst. Sci., 23, 393–414, https://doi.org/10.5194/nhess-23-393-2023,https://doi.org/10.5194/nhess-23-393-2023, 2023
Short summary

Cited articles

Balogun, A. L. and Adebisi, N.: Sea level prediction using ARIMA, SVR and LSTM neural network: assessing the impact of ensemble Ocean-Atmospheric processes on models' accuracy, Geomat. Nat. Haz. Risk, 12, 653–674, 2021. 
Belmonte Rivas, M. and Stoffelen, A.: Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT, Ocean Sci., 15, 831–852, https://doi.org/10.5194/os-15-831-2019, 2019.  
Bonaduce, A., Staneva, J., Grayek, S., Bidlot, J. R., and Breivik, Ø.: Sea-state contributions to sea-level variability in the European Seas, Ocean Dynamics, 70, 1547–1569, 2020. 
Bruneau, N., Polton, J., Williams, J., and Holt, J.: Estimation of global coastal sea level extremes using neural networks. Environ. Res. Lett., 15, 074030, https://doi.org/10.1088/1748-9326/ab89d6, 2020. 
Climate Data Store (CDS): https://cds.climate.copernicus.eu/, last access: 20 July 2021. 
Download
Short summary
Knowledge of what causes maximum water levels is often key in coastal management. Processes, such as storm surge and atmospheric forcing, alter the predicted tide. Whilst most of these processes are modeled in present-day ocean forecasting, there is still a need for a better understanding of situations where modeled and observed water levels deviate from each other. Here, we will use machine learning to detect such anomalies within a network of sea-level observations in the North Sea.
Altmetrics
Final-revised paper
Preprint