Project Description
Supervisors
Prof. Adrian Matthews (University of East Anglia, School of Environmental Sciences) – Contact me
Dr Ben Webber (School of Environmental Sciences, University of East Anglia)
Dr Juliane Schwendike (School of Earth and Environment, University of Leeds)
Project background
Extreme weather in the tropics, particularly in the form of heavy rainfall and strong winds, can destroy the lives and livelihoods of the local population through flooding, landslides and impacts on agriculture and local infrastructure. Such extreme weather in the tropics is primarily controlled by large scale weather patterns such as convectively coupled equatorial Kelvin waves (Figure 1), the Madden-Julian Oscillation (MJO) or El Nino-Southern Oscillation (ENSO). Although the broad features of these tropical weather patterns are known, their impact on extreme weather is not; this represents a major gap in our understanding of tropical weather.
Research methodology
You will determine the effect of tropical weather patterns on extreme weather using a combination of observational analysis, and numerical modelling. Initially, this will involve analysis of state-of-the-art satellite data sets that measure rainfall every 30 minutes across the whole planet and wind, temperature and other variables every hour. You will then analyse model forecast data from the UK Met Office available through the FORSEA (Forecasting in Southeast Asia) and K-scale projects, and conduct sets of experiments with a state-of-the-art atmospheric model to determine what factors generate and influence these tropical waves.
Training
You will join an active research group at UEA in tropical meteorology and climate. You will be trained in meteorological and climate theory, and in meteorological analysis of very large data sets, and computer modelling of weather and climate. You will have the opportunity to present your work at national and international conferences.
Person specification
We seek an enthusiastic, pro-active individual with strong scientific interests and self-motivation. You will have a degree in physics, mathematics, meteorology, oceanography or environmental science. Prior experience of programming is desirable.