Data Assimilation and its applications to meteorology

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• Professor Chris Budd
• Friday 04 March 2016, 14:00-15:00
• Aston Webb G33 .

If you have a question about this talk, please contact David Smith.

Data assimilation is the process of systematically including (often noisy) data into a forecast. It is now widely used in numerical weather prediction and its positive impact on the accuracy of weather forecasts is unquestionable. Indeed improvements in our ability to forecast the weather over the last decade are a reflection on the increasing volume of data available, improved computational methods and (significantly) much improved algorithms for incorporating this data into the forecast. However, many problems remain, including dealing with the sheer volume of the data and the inherent complexity of the weather and climate, understanding the effects of data and model error, and of reducing spurious correlations between the data and the forecast. In this talk I will give a survey of various techniques that are used operationally to implement data assimilation procedures in weather (and climate) forecasting including the Ensemble Kalman Filter, particle filters and the 4D-Var method. I will discuss their various advantages and disadvantages, the nature of the errors and ways to minimise these. Hopefully I will show that used carefully Data Assimilation techniques can significantly improve our ability to forecast the weather.

This talk is part of the Applied Mathematics Seminar Series series.

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• Applied Mathematics Seminar Series
• Aston Webb G33
• School of Mathematics Events

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