A modified shallow water model for inexpensive data assimilation research
Duration: 18 mins 12 secs
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| Description: | Presentation by Luca Cantarello (University of Leeds) at online meeting on 'Data Assimilation in Fluid Mechanics', organised by the UK Fluids Network Special Interest Group 'Flow instability, modelling and control', 27th May 2020. |
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| Created: | 2020-06-16 10:19 |
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| Collection: | Data Assimilation in Fluid Mechanics - 1st online meeting of UKFN SIG 'Flow instability, modelling and control' |
| Publisher: | University of Cambridge |
| Copyright: | Luca Cantarello |
| Language: | eng (English) |
| Abstract: | A modified shallow water model able to mimic convection and precipitation has been developed at the University of Leeds to conduct idealised forecast-assimilation experiments, facilitating inexpensive data assimilation research in an operational context. Exploiting a twin-setting configuration, pseudo-observations are derived from a high-resolution 'nature run' simulation and subsequently combined with lower-resolution model runs by means of an Ensemble Kalman Filter. Idealised satellite data assimilation constitutes the current focus of our research, which has required both a partial model revision and the development of a more complex pseudo-observing system, including a non-linear observation operator. |
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