On the potential of mapping sea level anomalies from satellite altimetry with Random Forest Regression

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Title:: On the potential of mapping sea level anomalies from satellite altimetry with Random Forest Regression
Document type:: Zeitschriftenaufsatz
Author(s):: Passaro, Marcello ; Juhl, Marie-Christin
Keywords:: Article ; Sea level anomalies ; Satellite altimetry ; Spatio-temporal interpolation ; Machine learning ; Random Forest Regression ; Engineering
Journal title:: Ocean Dynamics
Year:: 2023
Journal volume:: 73
Journal issue:: 2
Pages contribution:: 107-116
Fulltext / DOI:: doi:10.1007/s10236-023-01540-4
Publisher:: Springer Berlin Heidelberg
E-ISSN:: 1616-7341 ; 1616-7228
Date of publication:: 27.02.2023
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