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Hieronymus, Jenny
Publications (3 of 3) Show all publications
Hieronymus, M., Hieronymus, J. & Hieronymus, F. (2019). On the Application of Machine Learning Techniques to Regression Problems in Sea Level Studies. Journal of Atmospheric and Oceanic Technology, 36(9), 1889-1902
Open this publication in new window or tab >>On the Application of Machine Learning Techniques to Regression Problems in Sea Level Studies
2019 (English)In: Journal of Atmospheric and Oceanic Technology, ISSN 0739-0572, E-ISSN 1520-0426, Vol. 36, no 9, p. 1889-1902Article in journal (Refereed) Published
Abstract [en]

Long sea level records with high temporal resolution are of paramount importance for future coastal protection and adaptation plans. Here we discuss the application of machine learning techniques to some regression problems commonly encountered when analyzing such time series. The performance of artificial neural networks is compared with that of multiple linear regression models on sea level data from the Swedish coast. The neural networks are found to be superior when local sea level forcing is used together with remote sea level forcing and meteorological forcing, whereas the linear models and the neural networks show similar performance when local sea level forcing is excluded. The overall performance of the machine learning algorithms is good, often surpassing that of the much more computationally costly numerical ocean models used at our institute.

National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-5442 (URN)10.1175/JTECH-D-19-0033.1 (DOI)000486481100001 ()
Available from: 2019-10-14 Created: 2019-10-14 Last updated: 2019-10-14Bibliographically approved
Hieronymus, J., Eilola, K., Hieronymus, M., Meier, M., Saraiva, S. & Karlson, B. (2018). Causes of simulated long-term changes in phytoplankton biomass in the Baltic proper: a wavelet analysis. Biogeosciences, 15(16), 5113-5129
Open this publication in new window or tab >>Causes of simulated long-term changes in phytoplankton biomass in the Baltic proper: a wavelet analysis
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2018 (English)In: Biogeosciences, ISSN 1726-4170, E-ISSN 1726-4189, Vol. 15, no 16, p. 5113-5129Article in journal (Refereed) Published
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-4957 (URN)10.5194/bg-15-5113-2018 (DOI)000442738300003 ()
Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-09-05Bibliographically approved
Hieronymus, M., Hieronymus, J. & Arneborg, L. (2017). Sea level modelling in the Baltic and the North Sea: The respective role of different parts of the forcing. Ocean Modelling, 118, 59-72
Open this publication in new window or tab >>Sea level modelling in the Baltic and the North Sea: The respective role of different parts of the forcing
2017 (English)In: Ocean Modelling, ISSN 1463-5003, E-ISSN 1463-5011, Vol. 118, p. 59-72Article in journal (Refereed) Published
National Category
Oceanography, Hydrology and Water Resources
Research subject
Oceanography
Identifiers
urn:nbn:se:smhi:diva-4315 (URN)10.1016/j.ocemod.2017.08.007 (DOI)000411466900005 ()
Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2018-01-13Bibliographically approved
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