Convective storms cause numerous hazards to life and property, including heavy rain, lightning and hail. These hazards become particularly acute when a storm or series of storms is sustained over a fixed location for several hours, which dramatically increases the flash-flooding risk. While the basic ingredients for convective storms (instability, moisture, and lifting) are well known, the physical mechanisms that anchor storms to specific locations are varied and often subtle. Storms may be rooted to features such as a mountain, coastline, or slow-moving front, or may develop internal circulations that lead to self-organization or ``back-building''. The importance of one or more of these mechanisms has previously been highlighted in specific case studies, but the relative importance of different mechanisms has not been systematically addressed. This project aims to build the understanding of quasi-stationary storms through two primary objectives:
This will involve analyses of numerous events from recent years using a combination of observations and archived model data. Selected events will be analyzed in detail using high-resolution numerical simulations with the Met Office's Unified Model (MetUM). This will allow us to pinpoint the primary physical mechanisms that caused the observed behaviour and allow simple theoretical models to be developed that isolate these mechanisms and capture their dominant sensitivities. An important related goal is to develop new algorithms for automatically detecting stationary storms, which may be highly valuable for operational forecasters.
This will involve ensembles of MetUM simulations of selected events, where the ensemble members are all identical except for small differences in their initial conditions and/or parameter settings. These ensembles will quantify the contributions of different sources of uncertainty, and will help to establish whether probabilistic prediction of stationary convection events is feasible with state-of-the-art NWP.