University of Konstanz
Graduiertenkolleg / PhD Program
Computer and Information Science
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 Data assimilation techniques for numerical weather forecast
 
speaker     Vladimir Bondarenko
 
date    January 19, 2005
 
abstract    Data assimilation is a procedure of production of an accurate "image" of the true state of the atmosphere at a given time. This image is used then as the initial state (or input parameters) for a numerical weather prediction (NWP) system. Basically data assimilation process may be divided into three parts:
  1. gathering of measurements obtained by various observation systems;
  2. reduction of the observation data sets (data thinning);
  3. combination of the observations with an a priory estimate of the model state, i.e. previous wheather forecast, to produce a most accurate numerical description of the atmosphere.
The main goal of this talk is to give a brief overview of the the assimilation process concentrating on the 1st and 3d parts. The main kinds of observation systems and several most important assimilation techniques will be presented. With respect to the data thinning (the 2d part) only the necessity of such data reduction will be demonstrated, whereas data thinning algorithms are reserved as a subject of subsequent talks.