Using ensemble data assimilation to forecast hydrological flumes
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 whic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2013-11-01
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| Series: | Nonlinear Processes in Geophysics |
| Online Access: | http://www.nonlin-processes-geophys.net/20/955/2013/npg-20-955-2013.pdf |
| _version_ | 1818205383644151808 |
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| author | I. Amour Z. Mussa A. Bibov T. Kauranne |
| author_facet | I. Amour Z. Mussa A. Bibov T. Kauranne |
| author_sort | I. Amour |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-12T03:56:16Z |
| format | Article |
| id | doaj.art-4e3bb1aeaf964b679138cfe68ebc0c10 |
| institution | Directory Open Access Journal |
| issn | 1023-5809 1607-7946 |
| language | English |
| last_indexed | 2024-12-12T03:56:16Z |
| publishDate | 2013-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Nonlinear Processes in Geophysics |
| spelling | doaj.art-4e3bb1aeaf964b679138cfe68ebc0c102022-12-22T00:39:14ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462013-11-0120695596410.5194/npg-20-955-2013Using ensemble data assimilation to forecast hydrological flumesI. Amour0Z. Mussa1A. Bibov2T. Kauranne3Lappeenranta University of Technology, Lappeenranta, FinlandLappeenranta University of Technology, Lappeenranta, FinlandLappeenranta University of Technology, Lappeenranta, FinlandLappeenranta University of Technology, Lappeenranta, FinlandData 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.http://www.nonlin-processes-geophys.net/20/955/2013/npg-20-955-2013.pdf |
| spellingShingle | I. Amour Z. Mussa A. Bibov T. Kauranne Using ensemble data assimilation to forecast hydrological flumes Nonlinear Processes in Geophysics |
| title | Using ensemble data assimilation to forecast hydrological flumes |
| title_full | Using ensemble data assimilation to forecast hydrological flumes |
| title_fullStr | Using ensemble data assimilation to forecast hydrological flumes |
| title_full_unstemmed | Using ensemble data assimilation to forecast hydrological flumes |
| title_short | Using ensemble data assimilation to forecast hydrological flumes |
| title_sort | using ensemble data assimilation to forecast hydrological flumes |
| url | http://www.nonlin-processes-geophys.net/20/955/2013/npg-20-955-2013.pdf |
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