Assimilation of ERS-1 altimeter data in a tidal model of the continental shelf

Mouthaan, E.E.A.; Heemink, A.W.; Robaczewska, K.B.

doi:10.1007/bf02226308

Cited by 16 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This paper aims to show the improved forecasting skill of a dynamical model, by adopting an adequate data assimilation procedure based on a tide gauge observational network around the North Sea basin. While data assimilation of observed water levels is commonly applied in storm surge modelling (Verboom et al 1992;Mouthaan et al 1994;Gerritsen et al 1995;Philippart et al 1998;Canizares et al 2001) and, as a result, it is known that the assimilation of observational data into real-time operational models is a successful approach to improving forecasts, a key addition to the existing literature is the completeness of the development presented here, characterized by the following aspects.…”

Section: Introductionmentioning

confidence: 99%

Application of data assimilation for improved operational water level forecasting on the northwest European shelf and North Sea

2015

View full text Add to dashboard Cite

For the Netherlands, accurate water level forecasting in the coastal region is crucial, since large areas of the land lie below sea level. During storm surges, detailed and timely water level forecasts provided by an operational storm surge forecasting system are necessary to support, for example, the decision to close the movable storm surge barriers in the Eastern Scheldt and the Rotterdam Waterway. In the past years, a new generation operational tide-surge model (Dutch Continental Shelf Model version 6) has been developed covering the northwest European continental shelf. In a previous study, a large effort has been put in representing relevant physical phenomena in this process model as well as reducing parameter uncertainty over a wide area. While this has resulted in very accurate water level representation (root-meansquare error (RMSE) ∼7-8 cm), during severe storm surges, the errors in the meteorological model forcing are generally non-negligible and can cause forecast errors of several decimetres. By integrating operationally available observational data in the forecast model by means of real-time data assimilation, the errors in the meteorological forcing are prevented from propagating to the hydrodynamic tide-surge model forecasts. This paper discusses the development of a computationally efficient steady-state Kalman filter to enhance the predictive quality for the shorter lead times by improving the system state at the start of the forecast. Besides evaluating the model quality against shelf-wide tide gauge observations for a year-long hindcast simulation, the predictive value of the Kalman filter is determined by comparing the forecast quality for various lead time intervals against the model without a steady-state Kalman filter. This shows that, even though the process model has a water level representation that is substantially better than that of other comparable operational models of this scale, substantial improvements in predictive quality in the first few hours are possible in an actual operational setting.

show abstract

Section: Introductionmentioning

confidence: 99%

Application of data assimilation for improved operational water level forecasting on the northwest European shelf and North Sea

2015

View full text Add to dashboard Cite

show abstract

“…Later automated calibration procedures based on the variational methods were developed starting from the work of [8,31]. An overview of the development of these calibration procedures for DCSM can be found in [33].…”

Section: Parameter Identification For the New Dcsmmentioning

confidence: 99%

“…Among the developments was the increased resolution of the wind forecast input from 55 to 22 km, which could slightly increase the forecast quality in storm situations. Besides works on improving the wind input, a lot of studies had also been devoted to model calibration [8,11,31]. The last calibration was performed in 1998 using the adjoint method [32].…”

Section: Introductionmentioning

confidence: 99%

Efficient identification of uncertain parameters in a large‐scale tidal model of the European continental shelf by proper orthogonal decomposition

Altaf

Verlaan

Heemink

2011

Numerical Methods in Fluids

Self Cite

View full text Add to dashboard Cite

SUMMARYThe adjoint method can be used to identify uncertain parameters in large-scale shallow water flow models. This requires the implementation of the adjoint model, which is a large programming effort. The work presented here is inverse modeling based on model reduction using proper orthogonal decomposition (POD). An ensemble of forward model simulations is used to determine the approximation of the covariance matrix of the model variability and the dominant eigenvectors of this matrix are used to define a model subspace. An approximate linear reduced model is obtained by projecting the original model onto this reduced subspace. Compared with the classical variational method, the adjoint of the tangent linear model is replaced by the adjoint of a linear reduced forward model. The minimization process is carried out in reduced subspace and hence reduces the computational costs. In this study, the POD-based calibration approach has been implemented for the estimation of the depth values and the bottom friction coefficient in a large-scale shallow sea model of the entire European continental shelf with approximately 10 6 operational grid points. A number of calibration experiments is performed. The effectiveness of the algorithm is evaluated in terms of the accuracy of the final results as well as the computational costs required to produce these results. The results demonstrate that the POD calibration method with little computational effort and without the implementation of the adjoint code can be used to solve large-scale inverse shallow water flow problems.

show abstract

“…(b ) 1994- 2003Until 1998, several projects were aimed at further calibration of the storm surge model, DCSM. Most of these used the automated calibration package WAQAD (Mouthaan et al 1994;Verlaan et al 1996). A few local changes were made in the model to compensate for the lack of resolution.…”

Section: Historical Development Of the Dcsmmentioning

confidence: 99%

Operational storm surge forecasting in the Netherlands: developments in the last decade

Verlaan¹,

Zijderveld²,

Vries

et al. 2005

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

The accurate forecasting of storm surges is an important issue in the Netherlands. With the emergence of the first numerical hydrodynamic models for surge forecasting at the beginning of the 1980s, new demands and possibilities were raised. This article describes the main phases of the development and the present operational set-up of the Dutch continental shelf model, which is the main hydrodynamic model for storm surges in the Netherlands. It includes a brief discussion of applied data-assimilation techniques, such as Kalman filtering, the model calibration process and some thoughts on quality assurance in an operational environment. After further describing some select recent investigations, the paper concludes with some remarks on future developments in a European context.

show abstract

Assimilation of ERS-1 altimeter data in a tidal model of the continental shelf

Cited by 16 publications

References 5 publications

Application of data assimilation for improved operational water level forecasting on the northwest European shelf and North Sea

Application of data assimilation for improved operational water level forecasting on the northwest European shelf and North Sea

Efficient identification of uncertain parameters in a large‐scale tidal model of the European continental shelf by proper orthogonal decomposition

Operational storm surge forecasting in the Netherlands: developments in the last decade

Contact Info

Product

Resources

About