Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.envsoft.2013.12.006
Title: Ensemble based prediction of water levels and residual currents in Singapore regional waters for operational forecasting
Authors: Karri, R.R. 
Wang, X.
Gerritsen, H.
Keywords: Data assimilation
Ensemble Kalman filter
Malacca Strait
Sea level anomaly
Singapore regional model
Steady state Kalman filter
Issue Date: Apr-2014
Citation: Karri, R.R., Wang, X., Gerritsen, H. (2014-04). Ensemble based prediction of water levels and residual currents in Singapore regional waters for operational forecasting. Environmental Modelling and Software 54 : 24-38. ScholarBank@NUS Repository. https://doi.org/10.1016/j.envsoft.2013.12.006
Abstract: Singapore Strait located between the South China Sea and Andaman Sea is driven by tides coming from both sides and the hydrodynamics in this area is complex. From the viewpoint of long term forecasting, however, models developed for this area suffer from limitations introduced by parametric uncertainty, absence of data for appropriate specification of forcing and lateral boundary conditions. For improving the model forecasts, a data assimilation technique based on ensemble Kalman filter is implemented and applied. Based on the latter, an ensemble based steady state Kalman filter is derived to address the computational limitation for daily operational forecasting. Via a twin experiment on a simulation period that includes a significant storm surge event (sea level anomaly) the skills of both data assimilation schemes are assessed and compared. © 2013 Elsevier Ltd.
Source Title: Environmental Modelling and Software
URI: http://scholarbank.nus.edu.sg/handle/10635/92855
ISSN: 13648152
DOI: 10.1016/j.envsoft.2013.12.006
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