Data Assimilation Meetings at Reading

Date Meeting type Speakers
13 November 2013 Internal Speaker Oscar Martinez-Alvarado (University of Reading)
Implications of model error for numerical weather and climate prediction (pdf )
Numerical weather and climate models constitute the best available tools to tackle the problems of weather and climate prediction. Two assumptions lie at the heart of their suitability: (1) a climate attractor exists, and (2) the model attractor lies on the climate attractor. Instead of jumping into the extreme complexity of climate models, in this talk I take a big step back and use the Lorenz '63 and Lorenz '96 systems both as prototype systems and as imperfect models to investigate the implications of the second assumption. By comparing results drawn from these systems and from numerical weather and climate models, the implications of using imperfect models for the prediction of weather and climate are discussed. It is shown that the imperfect model's attractor and the system's attractor are essentially different, purely due to model error and not to sensitivity to initial conditions. Furthermore, if the model was perfect, its attractor would be invariant to forecast lead time. This conclusion provides an alternative to the assessment of climate models.

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