TY - JOUR ID - PaulSterlini2018Seas T1 - Sea surface height variability in the North East Atlantic from satellite altimetry AU - Paul Sterlini AU - Hylke de Vries; AU - Caroline Katsman JO - Climate Dynamics VL - 47 IS - 3-4 SP - 1285 EP - 1302 PY - 2018/08/27/ UR - https://npdc.nl/publication/936aa423-cca1-5197-8d11-17ad8ad5dccf N2 - Data from 21 years of satellite altimeter meas-urements are used to identify and understand the majorcontributing components of sea surface height variability(SSV) on monthly time-scales in the North East Atlantic.A number of SSV drivers is considered, which are catego-rised into two groups; local (wind and sea surface tempera-ture) and remote (sea level pressure and the North Atlanticoscillation index). A multiple linear regression model isconstructed to model the SSV for a specific target area inthe North Sea basin. Cross-correlations between candidateregressors potentially lead to ambiguity in the interpreta-tion of the results. We therefore use an objective hierarchi-cal selection method based on variance inflation factors toselect the optimal number of regressors for the target areaand accept these into the regression model if they can beassociated to SSV through a direct underlying physicalforcing mechanism. Results show that a region of high SSVexists off the west coast of Denmark and that it can be rep-resented well with a regression model that uses local wind,sea surface temperature and sea level pressure as primaryregressors. The regression model developed here helps tounderstand sea level change in the North East Atlantic.The methodology is generalised and easily applied to otherregions. ER -