Title of article :
A modified rrsqrt-filter for assimilating data in atmospheric
chemistry models
Author/Authors :
A.J. Segers b، نويسنده , , *، نويسنده , , A.W. Heemink a، نويسنده , , M. Verlaan a، نويسنده , , M. van Loon b، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2000
Abstract :
The rrsqrt-filter is a special formulation of the Kalman filter for assimilation of data in large scale models. In this formulation,
the covariance matrix of the model state is expressed in a limited number of modes. Two modifications have been made to the
filter such that it is more robust when applied in combination with an atmospheric chemistry model; both act on the reduction of
the covariance matrix into modes. The first modification proposes a transformation of the state, which makes the reduction invariant
for a change in units and helps to collect the most important covariance structures in the first modes. The second modification
extracts additional information from the reduction algorithm to limit the formation of unphysical states by the filter.
Keywords :
Kalman filter , atmospheric chemistry , data assimilation
Journal title :
Environmental Modelling and Software
Journal title :
Environmental Modelling and Software