Adaptive turbulence modelling to improve high-impact weather forecasts in next generation atmospheric models

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.

The fellowship will benefit the following stakeholders:

a) Weather Centres: The UK Met Office has a clear strategic plan to increase the spatial resolution of its operational model to the sub-kilometric scales by 2021 in an attempt to provide more accurate forecasts of high-impact weather. The new sub-grid parametrizations and relevant diagnostics, will be developed in the Met Office operational NWP Unified Model (UM) in collaboration with Met Office scientists, with a large part of the work taking place at the Met Office to ensure the operational implementation of the new approaches. Moreover, I will collaborate closely with Meteo-France in validating the new schemes and explore ways to adapt the dynamic approach in their operational models. To further disseminate the results of this work and initiate new collaborations to increase the impact of my research, I will organise a workshop on high-resolution NWP in Exeter near the completion of this fellowship.

b) Policy-Makers: Fine spatial resolution is key in heavy rainfall prediction as torrential precipitation is often extremely localized. Flooding can have dramatic effects in people's lives and significant socioeconomic impact. Therefore, providing reliable forecasts is important in the early warning of the public and the local authorities to take necessary action in order to minimize the effects of such events. Even though the proposed project aims at heavy rainfall prediction, an improved representation of turbulence and boundary layer processes in NWP will also benefit the prediction of other phenomena that can substantially affect for example the aviation industry or the dispersion of pollutants. To maximise the impact of my research, I will organise two Breakfast Briefings to make government stakeholders, private weather companies and their customers aware of the benefits that the dynamic modelling approach brings in NWP.

c) Public: This programme of research aims at improving day-to-day weather forecasts and therefore directly affecting every day life for the general public. I will take part in a number of national and regional public engagement events with the aim to communicate my research and its impact to the public and introduce them to the fascinating world and challenges of atmospheric modelling.

d) Atmospheric Modelling Community: The proposed fellowship will develop different flavours of a novel dynamic sub-grid approach for the Met Office/NERC Cloud model (MONC) and UM model. This will benefit this community as this dynamic model can be used in a wide range of applications such as boundary layer to dispersion studies and cloud modelling. The code and diagnostics and the configurations for the models will be made available through the Met Office Science Repository Service. Furthermore, I will create a website that I will use to disseminate the results and source code to make the new parametrizations accessible to the modelling community.

e) Education: I will engage with the Exeter Mathematics School (EMS), one of only two specialist mathematics schools in the UK. The EMS provides an environment for those students with an aptitude for maths to be developed, stimulated and stretched. During the first phase of the fellowship, I will organise a mini project for pupils that will introduce them to the fascinating world of meteorology and mathematical modelling, giving the ability of hands-on experience with numerical modelling of the atmosphere.

f) Personal Development: I have outlined a mentoring programme that will provide me with the necessary skills through the course of this fellowship to become a future leader in meteorological modelling. I will attend research leadership and public engagement courses to improve my relevant skills. Moreover, I intend to visit the University of California, Berkeley and Météo-France to significantly improve my research skills and enhance links and collaboration with world-leading turbulence expert.