How is the balance of a forecast ensemble affected by adaptive and non-adaptive localization schemes?

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Bannister, R. orcid id iconORCID: https://orcid.org/0000-0002-6846-8297 (2015) How is the balance of a forecast ensemble affected by adaptive and non-adaptive localization schemes? Monthly Weather Review, 143 (9). pp. 3680-3699. ISSN 0027-0644 doi: 10.1175/MWR-D-14-00379.1

Abstract/Summary

This paper investigates the effect on balance of a number of Schur product-type localization schemes which have been designed with the primary function of reducing spurious far-field correlations in forecast error statistics. The localization schemes studied comprise a non-adaptive scheme (where the moderation matrix is decomposed in a spectral basis), and two adaptive schemes, namely a simplified version of SENCORP (Smoothed ENsemble COrrelations Raised to a Power) and ECO-RAP (Ensemble COrrelations Raised to A Power). The paper shows, we believe for the first time, how the degree of balance (geostrophic and hydrostatic) implied by the error covariance matrices localized by these schemes can be diagnosed. Here it is considered that an effective localization scheme is one that reduces spurious correlations adequately but also minimizes disruption of balance (where the 'correct' degree of balance or imbalance is assumed to be possessed by the unlocalized ensemble). By varying free parameters that describe each scheme (e.g. the degree of truncation in the schemes that use the spectral basis, the 'order' of each scheme, and the degree of ensemble smoothing), it is found that a particular configuration of the ECO-RAP scheme is best suited to the convective-scale system studied. According to our diagnostics this ECO-RAP configuration still weakens geostrophic and hydrostatic balance, but overall this is less so than for other schemes.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/40541
Identification Number/DOI 10.1175/MWR-D-14-00379.1
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Uncontrolled Keywords Data assimilation, geostrophic balance, hydrostatic balance, localization
Publisher American Meteorological Society
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