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Using Ensemble Data Assimilation to Forecast Hydrological Flumes : Volume 20, Issue 6 (08/11/2013)

By Amour, I.

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Book Id: WPLBN0003990938
Format Type: PDF Article :
File Size: Pages 10
Reproduction Date: 2015

Title: Using Ensemble Data Assimilation to Forecast Hydrological Flumes : Volume 20, Issue 6 (08/11/2013)  
Author: Amour, I.
Volume: Vol. 20, Issue 6
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Kauranne, T., Bibov, A., Mussa, Z., & Amour, I. (2013). Using Ensemble Data Assimilation to Forecast Hydrological Flumes : Volume 20, Issue 6 (08/11/2013). Retrieved from

Description: Lappeenranta University of Technology, Lappeenranta, Finland. Data assimilation, commonly used in weather forecasting, means combining a mathematical forecast of a target dynamical system with simultaneous measurements from that system in an optimal fashion. We demonstrate the benefits obtainable from data assimilation with a dam break flume simulation in which a shallow-water equation model is complemented with wave meter measurements. Data assimilation is conducted with a Variational Ensemble Kalman Filter (VEnKF) algorithm. The resulting dynamical analysis of the flume displays turbulent behavior, features prominent hydraulic jumps and avoids many numerical artifacts present in a pure simulation.

Using ensemble data assimilation to forecast hydrological flumes

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