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Discussion papers
https://doi.org/10.5194/os-2018-124
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-2018-124
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 24 Oct 2018

Research article | 24 Oct 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Ocean Science (OS).

A multi collocation method for coastal zone observations with applications to SENTINEL-3a altimeter wave height data

Johannes Schulz-Stellenfleth and Joanna Staneva Johannes Schulz-Stellenfleth and Joanna Staneva
  • Helmholtz Zentrum Geesthacht (HZG), Institute of Coastal Research (IfK) Max-Planck-Str. 1, 21502 Geesthacht, Germany

Abstract. In many coastal areas there is an increasing number and variety of observation data available, which are often very heterogeneous in their temporal and spatial sampling characteristics. With the advent of new systems, like the radar altimeter onboard the SENTINEL-3a satellite, a lot of questions arise concerning the accuracy and added value of different instruments and numerical models. Quantification of errors is a key factor for applications, like data assimilation and forecast improvement. In the past, the triple collocation method to estimate systematic and stochastic errors of measurements and numerical models was successfully applied to different data sets. This method relies on the assumption, that three independent data sets provide estimates of the same quantity. In coastal areas with strong gradients even small distances between measurements can lead to larger differences and this assumption can become critical. In this study the triple collocation method is extended in different ways with the specific problems of the coast in mind. In addition to nearest neighbor approximations considered so far, the presented method allows to use a large variety of interpolation approaches to take spatial variations in the observed area into account. Observation and numerical model errors can therefore be estimated, even if the distance between the different data sources is too big to assume, that they measure the same quantity. If the number of observations is sufficient, the method can also be used to estimate error correlations between certain data source components. As a second novelty, an estimator for the uncertainty of the derived observation errors is derived as a function of the covariance matrices of the input data and the number of available samples.

In the first step, the method is assessed using synthetic observations and Monte Carlo simulations. The technique is then applied to a data set of SENTINEL-3a altimeter measurements, insitu wave observation, and numerical wave model data with a focus on the North Sea. Stochastic observation errors for the significant wave height, as well as bias and calibration errors are derived for the model and the altimeter. The analysis indicates a slight overestimation of altimeter wave heights, which becomes more pronounced at higher sea states. The smallest stochastic errors are found for the insitu measurements.

Different observation geometries of insitu data and altimeter tracks are furthermore analysed, considering 1D and 2D interpolation approaches. For example, the geometry of an altimeter track passing between two insitu wave instruments is considered with model data being available at the insitu locations. It is shown, that for a sufficiently large sample, the errors of all data sources, as well as the error correlations of the model, can be estimated with the new method.

Johannes Schulz-Stellenfleth and Joanna Staneva
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Johannes Schulz-Stellenfleth and Joanna Staneva
Johannes Schulz-Stellenfleth and Joanna Staneva
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Errors of observations and numerical model data are analysed with a focus on heterogeneous coastal areas. An extension of the triple collocation method is proposed, which takes into account gradients in the collocation of datasets separated by distances, which maybe not acceptable for a nearest neigbour approximation, but still be feasible for linear or higher order interpolations. The technique is applied to wave height data from insitu stations, models and the SENTINEL-3a altimeter.
Errors of observations and numerical model data are analysed with a focus on heterogeneous...
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