The project seeks to investigate the behaviour of atmospheric circulation patterns and the occurrence of extreme hydro-meteorological events at the mesoscale with the aim to improve forecasting, early warning and planning.
This PhD position is in the Tyndall Centre for Climate Change Research, starting October 2011. The topic of the PhD is "Circulation patterns, extreme events and resource optimisation".
Supervisor(s): Dr.-Ing. Yi He (Helen) Prof. Dr. rer.nat. Dr.-Ing. András Bárdossy
Application Deadline: April 20th 2011
http://ueasciweb.uea.ac.uk/Resproject/show.aspx?ID=234
Around the world recent weather has shown a tendency towards the extreme. Be it floods in Pakistan or China, record breaking winters in Europe and north America, landslides in South America and erratic rainfall patterns in West Africa, there is ample evidence to suggest deviation from the norm as far as the weather is concerned. As the impacts of climate change begin to be felt throughout the world a critical issue will be the response of the research community, governments, policymakers and civil society at large to increasing levels of risk.
The project seeks to investigate the behaviour of atmospheric circulation patterns and the occurrence of extreme hydro-meteorological events at the mesoscale with the aim to improve forecasting, early warning and planning. As the economic down turn creates dilemmas in allocation of human and financial sources both the public and private sectors, there is an increasing need for scientifically sound tools to support optimal allocation of resources.
Additionally such tools can potentially be used to sensitize end-users or assist in deliberation to ensure stakeholders 'buy into' adaptation policies and management proposals without significant controversy. The aim of the work is thus to: 1. Identify and quantify the relationship between circulation patterns (CPs) and the occurrence of extreme hydro-meteorological events at the mesoscale; 2. Assess how this relationship can be used to improve ensemble flood forecasting systems; 3. Assess if the information can be used in short, medium or long term planning; and 4. Identify and quantity the costs or benefits of incorporating the relationship in optimum resource allocation in the public and/or private sectors.
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