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Data Assimilation for Convection

Explore the role of data assimilation in improving convection models for more accurate predictions and risk assessment. Learn about the benefits, challenges, and future advancements in assimilation science for convective events. Collaboration with Met Office enhances research outcomes. Spin-up work on high-resolution observations essential for model accuracy.

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Data Assimilation for Convection

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  1. Data Assimilation for Convection Univ: R. Bannister, S. Migliorini, P.-J. Vanleeuwen, S. Dance, S. Rennie, N. Pounder, D. Clifford, … MetO: M. Dixon, S. Ballard, D. Simonin, … Students: S. Vetra, R. Petrie, A. Fowler, … Good models will not achieve their predictive potential without appropriate data assimilation Assimilation science Convection permitting data assimilation systems Data Observations of convective events \ observation operators Assimilation benefits Validation / targeting / ensemble generation / quality assessment

  2. The MetOVar system is hydrostatic ... ... but inside resolved convection the atmosphere is not AB Rainfall rate kg m-2 s-1 B A S. Vetra Totalθ correlation Hydrostatically balanced θcorrelation

  3. Ensembles/Var at convective scales • Way forward:ensemble-Kalman-filter, an ensemble-transform-Kalman-filter, and variationalassimilation at ‘hi-res’ based on the current Met Office system • 1.5 km resolution over 70 vertical levels over southern UK • 23 forecasts + control • Development of reduced-rank-Kalman-filter in a convecting toy model • The above methods recognize the flow-dependent (ie convection dependent) nature of the assimilation problem

  4. Challenges ahead • What are the consequences of using a non-convection-permitting data assimilation system at hi-res? • How ‘non-hydrostatic’ and ‘non-geostrophic’ are forecast errors at different positions and scales? • What is the detailed design and performance of the new ‘convection permitting’ data assimilation methodologies? • Ensemble Kalman filter • Ensemble transform Kalman filter • Variational data assimilation • Reduced-rank Kalman filter • What is the effect of hi-res observations (radar)? • Important collaboration with Met Office • Spin-up work on MetO/NERC MONSooN supercomputer

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