Details of Award
NERC Reference : NE/T011351/1
Adaptive turbulence modelling to improve high-impact weather forecasts in next generation atmospheric models
Fellowship Award
- Fellow:
- Dr G Efstathiou, University of Exeter, Mathematics
- Grant held at:
- University of Exeter, Mathematics
- Science Area:
- Atmospheric
- Overall Classification:
- Panel B
- ENRIs:
- Environmental Risks and Hazards
- Global Change
- Science Topics:
- Boundary Layer Meteorology
- Cloud dynamics
- Computational fluid dynamics
- Land - Atmosphere Interactions
- Numerical weather prediction
- Tropospheric Processes
- Convective precipitation
- Extratropical cyclones
- Weather forecasting
- Regional & Extreme Weather
- Floods
- Abstract:
- High-impact weather events are often extremely localised therefore refined spatial resolution is essential for the accurate prediction of such events. However, Numerical Weather Prediction (NWP) might have hit a stalemate as meteorological models move towards the sub-kilometre grid spacing. Even though recent research has shown some improvements in the simulation of heavy rainfall events with increasing horizontal resolution, it has also revealed significant challenges as this improvement is not as pronounced as expected and very sensitive to the treatment of the unresolved turbulence length scales. Those unresolved motions correspond to the dominant scales of boundary layer turbulence and cloud development and mixing with its imminent environment. It seems that the fundamental assumptions behind the parametrization of sub-grid motions at sub-kilometre resolutions need to be revisited. The proposed fellowship aims to provide a step-change in capabilities for forecasting deep convection and subsequent heavy rainfall, through a more physical and dynamic representation of the sub-grid scales in the next generation sub-kilometric NWP models. This will be achieved by dynamically deriving the turbulence length scales in the sub-grid mixing scheme depending on the resolved flow field rather than statically specifying them beforehand. The dynamic method will be first used in an idealised framework to improve the understanding of the coupling between the atmospheric boundary layer with deep convection, by diagnosing the different length scales of mixing in the boundary and cloud layer. This approach can provide further insight on cloud-environment mixing to study the impact of turbulent mixing at the different stages of convection development and identify the feedback between turbulent transport and the synoptic disturbances. A first-order dynamic scheme will then be used prognostically and will be assessed in reproducing convection development against static conventional methods at sub-kilometre resolutions. As a next step, I will develop a novel, scale-aware and flow-adaptive dynamic sub-grid parametrization approach to better represent the unresolved scales by using the resolved scales to determine the intensity of the sub-grid mixing. It will utilise the conservation equations for sub-grid turbulent transport, to provide a more accurate representation of sub-grid motions, through reconstructing the resolved field near the grid scale to dynamically calculate the sub-grid turbulence mixing lengths. Hence, the scheme will be self-contained with minimum tuneable closure parameters. The new approach will be tested in an operational NWP model at very high, sub-kilometre resolutions to validate the ability of model dynamics to explicitly resolve deep convection in realistic case studies, under weak and strong synoptic forcing. This new method, has the potential to improve weather forecasting by enabling weather centres to provide more accurate forecasts of high-impact weather to policy makers and the general public while providing grounds for further research in atmospheric science.
- NERC Reference:
- NE/T011351/1
- Grant Stage:
- Awaiting Event/Action
- Scheme:
- Research Fellowship
- Grant Status:
- Active
- Programme:
- IRF
This fellowship award has a total value of £534,067
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DI - Staff | DA - Estate Costs | DA - Other Directly Allocated | DI - T&S |
|---|---|---|---|---|---|
| £9,836 | £203,232 | £252,792 | £39,264 | £1,912 | £27,028 |
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