A new methodology for using buoy measurements in sea wave data assimilation

Abstract

One of the main drawbacks in modern sea wave data assimilation models is the limited temporal and spatial improvement obtained in the final forecasting products. This is mainly due to deviations coming either from the relevant atmospheric input or from the dynamics of the wave model, resulting to systematic errors of the forecasted fields of numerical wave models, when no observation is available for assimilation. A potential solution is presented in this work, based on a combination of advanced statistical techniques, data assimilation systems, and wave models. More precisely, Kalman filtering algorithms are implemented into the wave model WAM and the results are assimilated by an Optimum Interpolation Scheme, in order to extend the beneficial influence of the latter in time and space. The case studied concerns a 3-month period in an open sea area near the SouthWest coast of the USA (Pacific Ocean).

Wave data assimilation using a hybrid approach in the Persian Gulf

“…Their approach led to the extension of the assimilation impact to the whole forecasting period. A significant reduction of the magnitude and variability of the discrepancies between final forecasts and observations was achieved in this way (Emmanouil et al 2010). Similar results are reported in Galanis et al (2009) in that they employed some statistical tools to extend the impact of data assimilation on ocean wave prediction.…”

“…Since the numerical model errors are not the same for different output variables (Moeini and Etemad-Shahidi 2007), the last assimilation procedure can be used to modify different wave characteristics separately. Emmanouil et al (2010) employed the Kalman filter in combination with the optimum interpolation data assimilation scheme to improve forecasted wave heights in an open ocean area (southwest US coast). In this study, the Kalman filters were implemented in the WAM model after the time integration of the two-dimensional frequency-direction wave spectra and before the data assimilation.…”

Joint Environmental Data at Five European Offshore Sites for Design of Combined Wind and Wave Energy Devices

“…Assimilation techniques are applied for the correction of initial wind and wave conditions [9,10]. By comparing with measurements, the results from the numerical model are generally correlated to the measurements.…”

Adjoint-Free Variational Data Assimilation into a Regional Wave Model

“…Their method was capable of reducing the forecast errors by 30%-60% over 12-24-h forecast periods. Operationally oriented sequential KF methods were also considered by Emmanouil et al (2010Emmanouil et al ( , 2012, who employed WAM in combination with the second-order KF and optimal interpolation schemes to improve the model's performance in the North Atlantic.…”