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Toward the assimilation of time‐averaged observations
Author(s) -
Dirren Sébastien,
Hakim Gregory J.
Publication year - 2005
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2004gl021444
Subject(s) - data assimilation , assimilation (phonology) , ensemble kalman filter , kalman filter , meteorology , environmental science , precipitation , climatology , ideal (ethics) , remote sensing , computer science , algorithm , atmospheric sciences , geology , extended kalman filter , physics , artificial intelligence , philosophy , linguistics , epistemology
A novel algorithm is described for the assimilation of time‐averaged observations. A demonstration of this algorithm in an ideal model using an ensemble Kalman filter technique suggests the potential for resolving dynamical features that have a characteristic time‐scale longer than the averaging time of the observations. This technique may offer new perspectives in climate reconstruction and in the assimilation of integrated meteorological quantities such as accumulated precipitation.