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Four-dimensional variational data assimilation for mesoscale and storm-scale applications

Title
Four-dimensional variational data assimilation for mesoscale and storm-scale applications
Authors
Park S.K.Zupanski D.
Ewha Authors
박선기
SCOPUS Author ID
박선기scopus
Issue Date
2003
Journal Title
Meteorology and Atmospheric Physics
ISSN
0177-7971JCR Link
Citation
vol. 82, no. 1-4, pp. 173 - 208
Indexed
SCI; SCIE; SCOPUS WOS scopus
Abstract
The status and progress of the four-dimensional variational data assimilation (4DVAR) are briefly reviewed focusing on application to prediction of mesoscale/storm-scale atmospheric phenomena. Theoretical background is provided for each important component of the 4DVAR system - forecast and adjoint models, observations, background, cost function, preconditioning, and minimization. An overview of practical issues specific for mesoscale/storm-scale 4DVAR is then presented in terms of high-resolution observations, nonlinearity and discontinuity problem, model error, errors from lateral boundary condition, and precipitation assimilation. Practical strategies for efficient and simplified 4DVAR are also introduced, e.g., incremental 4DVAR, poor man's 4DVAR, and inverse 3DVAR. A new concept on hybrid approach is proposed to combine an efficient 4DVAR scheme and the standard 4DVAR scheme aiming at reducing computational demand required by the standard 4DVAR while improving the accuracy of the simplified 4DVAR. Applications to both hydrostatic and nonhydrostatic models are illustrated and our vision on opportunities and directions for future research is provided.
DOI
10.1007/s00703-001-0586-7
Appears in Collections:
엘텍공과대학 > 환경공학전공 > Journal papers
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