About the Project
While the basic environmental characteristics favouring elevated convection are known, at least in some cases, the mechanisms leading to triggering are poorly understood, and there has been little observational work apart from ad hoc studies and one relatively recent US field campaign. Poor predictability may arise because local variations in e.g. convergence or humidity that cause initiation are harder to constrain in numerical models than those in layers close to the ground directly influenced by surface topography. It is also possible that models have systematic errors that are important for these clouds. This project aims to answer the question of which factor is more important, primarily through making use of the Met Office’s operational convection-permitting ensemble forecast system combined with ensemble sensitivity techniques to understand the sensitivity of the representation of elevated convection to different factors in the analysis or model formulation and resulting predictability issues.
Lower-resolution NWP and climate models cannot resolve convective clouds – they are smaller than the numerical grid. Their effects on resolved scales have to be estimated using ‘parametrization’ schemes. The Met Office is developing a new parametrization called COMORPH, that has made many improvements over its predecessors. However, poor representation of elevated convection is also a major deficiency in the performance the new parametrization. It is anticipated that the new understanding that arises from this project will therefore have broader impact through improving these models.
The student will initially study cases of elevated convection over the UK using available observational (radar, satellite etc.) and model data, with a view to understanding of deficiencies in the representation of elevated convection in convection-permitting km-scale models, such as the Met Office’s deterministic and ensemble high-resolution systems (UKV and MOGREPS-UK, respectively). The ensemble forecast system, in which many perturbed versions of the flow are generated, will then be used with techniques such as ensemble sensitivity analysis and spatial ensemble spread techniques to help deduce the nature of the predictability of elevated convection given particular environmental conditions. The option will be considered of extending the study to elevated convection events in other regions of the world, particularly where the Met Office runs convection-permitting forecasts. This includes the USA, where the model is run for the NOAA Hazardous Weather Testbed, or over India or China, where it is run for the Climate Science for Service Partnership programmes.
This project will build on proven expertise in Reading in these areas along with ongoing Met Office based work to address the forecasting problem. The CASE award supports up to 3 months working within Met Office HQ, with close involvement of operational meteorologists and mentored by one of the Deputy Chief Meteorologists. The student will develop:
- understanding of what NWP models are, why they are run and how they are used.
- develop analysis skills and the use of large datasets to gain insight into fundamental physical processes.
- understanding of the nature of predictability and hazardous weather and the practical application of forecasts and, through visits to the Met Office, the customer applications of them.
- communication skills with knowledgeable users through interaction with operational meteorologists.
- software skills – coding in Python for data analysis and FORTRAN within model.-
- expertise in the implementation and use of state-of-the art convection-permitting modelling systems.
Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree, Masters Degree with Merit, or equivalent in physics, mathematics or a closely related environmental or physical science.
To apply, please follow the instructions at https://research.reading.ac.uk/scenario/apply/
The project has CASE funding from the Met Office.
Due to UKRI rules, the DTP can only fund a very limited number of international students. We will only consider applications from international students with an outstanding academic background placing them in the top 10% of their cohort.
Clark, P., Roberts, N., Lean, H., Ballard, S. P. and Charlton-Perez, C. (2016) Convection-permitting models: a step-change in rainfall forecasting. Meteorological Applications, 23 (2). pp. 165-181. ISSN 1469-8080 doi: https://doi.org/10.1002/met.1538
Corfidi, S. F., S. J. Corfidi, and D. M. Schultz, 2008: Elevated Convection and Castellanus: Ambiguities, Significance, and Questions. Wea. Forecasting, 23, 1280–1303, https://doi.org/10.1175/2008WAF2222118.1.
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