Dynamical and microphysical evolution of convective storms (DYMECS)

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A series of wet summers in the UK have reminded us of the devastating floods that can be caused by thunderstorms, from the iconic images of the Boscastle flood in August 2004 through to the repeated flooding events in 2007 that led to towns in Gloucestershire without mains water for up to 17 days and according to the subsequent Pitt Review, caused in excess of 3 billion pounds worth of damage. There is clearly an urgent need to improve our ability to forecast these storms from a few hours to a few days ahead. Most computer models used for weather forecasting worldwide divide the atmosphere up into boxes several tens of kilometers across. Since convective shower clouds and thunderstorms are typically only between 2 and 10 km across, these models have no chance to simulate individual clouds; rather they must try to estimate the effect of an ensemble of clouds within each box on surface rainfall. This is known as a 'convection parameterization' and is very error prone. However, there has been a continued increase in computer power in recent years, and the Met Office currently runs one of the highest resolution national weather forecast model operationally, its model having a horizontal grid-box size of 1.5 km over the whole of the UK. At this resolution it is just about able to simulate the air flows in individual clouds, and a convection parameterization is not needed. While there is evidence that this has improved the accuracy of forecasts, it is clear that there are still very significant shortcomings in the nature of convective shower clouds and thunderstorms simulated at this resolution. What we need are very detailed observations of a large number of shower clouds and thunderstorms over the UK, and how each cloud grows and decays, with which to test and improve these high resolution models. In this project we will obtain this information using the Chilbolton weather radar in Hampshire, which is able to measure all kinds of useful properties of storms at very high resolution (3D structure, surface rain rate, the occurrence of hail, the amount of ice in the upper parts of the cloud, the airflows within the storm and the levels of turbulence). A particularly innovative aspect to the project is that we will develop software to control the radar automatically, so that it can track individual thunderstorms as they evolve. Detailed information on potentially hundreds of storms will be obtained by operating the radar on 40 suitable days over an 18-month period, including the summers of 2011 and 2012. This unique dataset will be used to evaluate the evolution of storms in the forecast model in a level of detail and a range of conditions that has never been achieved before. We will rerun the model with different model configurations (e.g. different ways to describe the ways that cloud ice particles and liquid droplets grow and interact to eventually form rain), in order to determine what it is that limits the realism of shower clouds and thunderstorms in this model, and hence how to improve forecasts. These findings will be applicable to other models worldwide. We will examine the detailed way that storms evolve in the model and in reality, particularly how the airflows in one storm conspire to initiate another storm, and what it is that causes storms to rain persistently in one place, since it is often this behaviour that is responsible for flooding. A further aim of this project will be to test a number of the assumptions that are made in convection parameterizations. Although convection parameterization is not as accurate as simulating individual clouds explicitly, for making 100-year climate forecasts we do not have the computer power to do this with the 1.5-km boxes that would be required over the entire world. Our detailed dataset will help us to ensure that the assumptions about the size and properties of clouds in these parameterizations are realistic, potentially improving the accuracy of climate forecasts.