On the equivalence between radiance and retrieval assimilation

Migliorini, S. (2012) On the equivalence between radiance and retrieval assimilation. Monthly Weather Review, 140 (1). pp. 258-265. ISSN 0027-0644 doi: 10.1175/MWR-D-10-05047.1

Abstract/Summary

The need for consistent assimilation of satellite measurements for numerical weather prediction led operational meteorological centers to assimilate satellite radiances directly using variational data assimilation systems. More recently there has been a renewed interest in assimilating satellite retrievals (e.g., to avoid the use of relatively complicated radiative transfer models as observation operators for data assimilation). The aim of this paper is to provide a rigorous and comprehensive discussion of the conditions for the equivalence between radiance and retrieval assimilation. It is shown that two requirements need to be satisfied for the equivalence: (i) the radiance observation operator needs to be approximately linear in a region of the state space centered at the retrieval and with a radius of the order of the retrieval error; and (ii) any prior information used to constrain the retrieval should not underrepresent the variability of the state, so as to retain the information content of the measurements. Both these requirements can be tested in practice. When these requirements are met, retrievals can be transformed so as to represent only the portion of the state that is well constrained by the original radiance measurements and can be assimilated in a consistent and optimal way, by means of an appropriate observation operator and a unit matrix as error covariance. Finally, specific cases when retrieval assimilation can be more advantageous (e.g., when the estimate sought by the operational assimilation system depends on the first guess) are discussed.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/25958
Identification Number/DOI	10.1175/MWR-D-10-05047.1
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Publisher	American Meteorological Society
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