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uk.sci.weather (UK Weather) (uk.sci.weather) For the discussion of daily weather events, chiefly affecting the UK and adjacent parts of Europe, both past and predicted. The discussion is open to all, but contributions on a practical scientific level are encouraged. |
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NRL SEMINAR
3:00 PM, Tuesday, 8 September 2009 Advanced and High-resolution Data Assimilation Techniques Andrew Lorenc MET Office, Exeter, Devon, United Kingdom The review intends to shed light on possible strategies for the convective scales data assimilation (DA) of clouds and precipitations. Operational schemes are often based on quasi-linear optimal estimation theory, and use the variational technique (e.g. 3DVar/4DVar) to cope with the minimization problem. The review will try to figure out possibilities and limitations of the seamless extension of such schemes to higher resolution (Lorenc and Payne, 2007) and cloud analysis (Errico et al, 2007). Another method of solving the quasi-linear estimation problem is to discretize it with ensembles, (through the various forms of Ensemble Kalman Filters (EnKF).) Several reviews have already considered the EnKF vs. 4D-Var approaches (Dance, 2004), so we suggest the review may focus on hybrid strategies (1DVAR+4DVAR, VAR+EnKF, Lognormal+Gaussian DA systems) in conjunction with cloud VAR+analysis. At those scales and for the hydrometeors, non-linearity becomes a significant issue. It may first appear as a displacement error, requiring some specific DA schemes, such as Beezley and Mandel (2008). The review may also give some clues about the notion of fronts and vertical/horizontal displacement errors in clouds and the way alternative DA scheme could be designed to solve such problems. Just as well reallly as I usually rely on online dictionaries these days and I doubt very much it would be worth carrying my desktop through US customs. They thayer baying so quaint ayun all. Errmm.. wots an hydrometeor? |
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