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Ensemble-based data assimilation and the localisation problem

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Petrie, R. E. and Dance, S. L. (2010) Ensemble-based data assimilation and the localisation problem. Weather, 65 (3). pp. 65-69. ISSN 0043-1656

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To link to this article DOI: 10.1002/wea.505

Abstract/Summary

The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly flaps its wings in Brazil, it may cause a tornado in Texas. This essentially describes how weather forecasts can be extremely senstive to small changes in the given atmospheric data, or initial conditions, used in computer model simulations. In 1961 Edward Lorenz found, when running a weather model, that small changes in the initial conditions given to the model can, over time, lead to entriely different forecasts (Lorenz, 1963). This discovery highlights one of the major challenges in modern weather forecasting; that is to provide the computer model with the most accurately specified initial conditions possible. A process known as data assimilation seeks to minimize the errors in the given initial conditions and was, in 1911, described by Bjerkness as “the ultimate problem in meteorology” (Bjerkness, 1911).

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
Faculty of Science > School of Mathematical and Physical Sciences > National Centre for Earth Observation (NCEO)
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
ID Code:4725
Publisher:Wiley

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