Dr Andrew Barrett - Post Doctoral Research Assistant
||Dr Andrew Barrett|
Department of Meteorology
Room 506, 5th Floor, Philip Lyle Building
University of Reading
a.i.barrett -at- reading.ac.uk
Andrew Barrett is a Post-doc researcher within the Meteorology Department at the University of Reading. His research interests include:
- What size are snowflakes inside clouds and how fast do they fall?
- Can we predict where and when intense but localised thunderstorms form?
- How can we better represent clouds and their radiative impact in climate projections?
Using radars to determine the size and fall speed of snow in clouds
The size and fall speed of ice particles and snow determine when and where it will rain and how long ice clouds exist for. By using 3 radars at different frequencies (3, 35 and 94 GHz) we can detect particles of different sizes and determine whether current assumptions about the size and fall speed of ice particles used to predict the weather are correct. For more information about Andrew's research, follow the 'Research' link.
Stationary convective orographic rain bands
Stationary rain bands form over variable orography (rough, mountainous terrain) and can remain stationary and persistent for a number of hours. Convective rain bands, particularly stationary ones over elevated orography are responsible for a number flash flooding cases. Research to understand the mechanisms of stationary convective orographic rain bands is conducted using high-resolution ensemble simulations using the Met Office Unified Model. The aim of this work is to better understand the mechanisms and predictability of stationary convective orographic rain bands and improve our understanding and ability to forecast their impacts i.e. flash flooding.
Representing mixed-phase altocumulus in NWP models
Mixed-phase altocumulus clouds are typically thin and occur in the mid-troposphere. They are mixed-phase (meaning they contain water particles in both liquid and ice phase) with a thin layer of liquid water at the top of a mainly ice cloud. This liquid layer is highly reflective to sunlight and these clouds can persist for many hours; it is therefore important to model these clouds correctly to predict the weather and future climate. Our typical understanding of cloud microphysics is that liquid water will be converted to ice when the two phases co-exist due to the Bergeron-Findeison process. However, contrary to these expectations, these clouds persist for a long time. A very large vertical resolution sensitivity is found where changing the vertical resolution from 50 metres to 500 metres removes 95% of the liquid water in simulations of these clouds, on average. This occurs because models are unable to resolve the vertical profile of temperature and ice water content at cloud top and therefore overestimate the rate of conversion of liquid to ice. A new parameterization has been developed to reduce the conversion rate near the cloud top and enables coarse resolution models to simulate mixed-phase clouds. A similar scheme is now operational in the ECMWF model.