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This paper addresses the problems of overlapping sea level time series measured using different technologies and sometimes from different locations inside a harbour. The renovation of the Spanish REDMAR (RED de MAReógrafos) sea level network is taken here as an example of the difficulties encountered: up to seventeen old tide gauge stations have been replaced by radar tide gauges all around the Spanish coast, in order to fulfil the new international requirements on tsunami detection. Overlapping periods between old and new stations have allowed the comparison of records in different frequency ranges and the determination of the impact of this change of instrumentation on the long-term sea level products such as tides, surges and mean sea levels. The differences encountered are generally within the values expected, taking into account the characteristics of the different sensors, the different sampling strategies and sometimes the different locations inside the harbours. However, our analysis has also revealed in some cases the presence of significant scale errors that, overlapping with datum differences and uncertainties, as well as with hardware problems in many new radar gauges, may hinder the generation of coherent and continuous sea level time series. Comparisons with nearby stations have been combined with comparisons with altimetry time series close to each station in order to better determine the sources of error and to guarantee the precise relationships between the sea level time series from the old and the new tide gauges. [ABSTRACT FROM AUTHOR]

ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast that makes use of existing storm surge or circulation models today operational in Europe, as well as near-real time tide gauge data in the region, with the following main goals: -- providing an easy access to existing forecasts, as well as to its performance and model validation, by means of an adequate visualization tool -- generation of better forecasts of sea level, including confidence intervals, by means of the Bayesian Model Average Technique (BMA) The system was developed and implemented within ECOOP (C.No. 036355) European Project for the NOOS and the IBIROOS regions, based on MATROOS visualization tool developed by Deltares. Both systems are today operational at Deltares and Puertos del Estado respectively. The Bayesian Modelling Average technique generates an overall forecast probability density function (PDF) by making a weighted average of the individual forecasts PDF's; the weights represent the probability that a model will give the correct forecast PDF and are determined and updated operationally based on the performance of the models during a recent training period. This implies the technique needs the availability of sea level data from tide gauges in near-real time. Results of validation of the different models and BMA implementation for the main harbours will be presented for the IBIROOS and Western Mediterranean regions, where this kind of activity is performed for the first time. The work has proved to be useful to detect problems in some of the circulation models not previously well calibrated with sea level data, to identify the differences on baroclinic and barotropic models for sea level applications and to confirm the general improvement of the BMA forecasts. [ABSTRACT FROM AUTHOR]