Improved description of sea level in the North Sea

Abstract

[1] The scope of this paper is to merge in situ sea level observations with satellite altimetry observations to give a consistent view of the nontidal sea level fluctuations in the North Sea. The detided sea level variability is dominated by climate induced surges that propagate counterclockwise around the North Sea with speeds of $25 m/s and spatial scales of 100-1000 km. The individual sea level recorders agree very well with the satellite observations off the coast with correlation coefficients of 0.9. The sampling characteristics of the satellite and the in situ observations are used to construct a regression model. Regression of TOPEX/POSEIDON sea surface height data onto coastal sea level observations gives a mean hindcast skill of 0.7 and RMS errors of 8.2 cm for the North Sea. Validation of the model against independent ERS satellite crossover observations yields a mean RMS difference of 13 cm including the 4-7 cm noise in the satellite observations. The modeling of the true sea level is most likely better than 10 cm. The performance is presently better than the Danish storm surge model, suggesting that much can be gained by including the spatial information from the satellite observations in the models.

Near‐coastal satellite altimetry: Sea surface height variability in the North Sea–Baltic Sea area

“…The Cromer tide gauge has been excluded; it is located in the southern North Sea where strong non-linear tidal effects makes this method unsuitable. The model performance in the North Sea is comparable to that of Høyer and Andersen [2003]. In the IDW and the Baltic Sea, the model performs better than in the North Sea, showing a successful extension of the model to these near-coastal areas.…”

“…[11] To combine the high spatial coverage of the satellite data with the hourly resolution of the tide gauge measurements, a statistical model based on multivariate regression analysis is set up [Høyer and Andersen, 2003;Emery and Thomson, 2001]. This model calculates the best weighted sum (least squares sense) of data from a range of surrounding tide gauges and a constant offset, to fit the altimetry data time series in each satellite measuring point.…”

“…The use of satellite altimetry observations in this region is limited due to coastal effects and a discrepancy between the satellite repeat period and the time scale of the SSH variability. Høyer and Andersen [2003] showed that a statistical model, based on multivariate regression analysis of satellite altimetry and tide gauge data, can estimate the real-time sea surface height in the North Sea to within 10 cm's accuracy. In this study we recover satellite data as close as 10 km from the coast using an ECMWF based wet tropospheric correction and extend the statistical model to the coastal regions of the Inner Danish Waters (IDW) and the Baltic Sea.…”

Progress in satellite remote sensing for studying physical processes at the ocean surface and its borders with the atmosphere and sea ice

“…In addition, the spatial spread of information from the coastal tide gauges is implicit in the field, which makes it easier for hydrodynamic models to assimilate. The original approach used standard altimetry observations (Høyer and Andersen, 2003;Madsen et al, 2007), but improved performance was recently obtained through the use of coastal specific altimetry data (Madsen et al, 2015).…”

“…Høyer and Andersen (2003)) has been shown to produce a real-time hourly 2-D SSH field for the North Sea and Baltic Sea. These data are attractive as their accuracy is independent of the quality of the atmospheric forecast.…”