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Representativity error for temperature and humidity using the Met Office high-resolution model

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Waller, J. A., Dance, S. L., Lawless, A. S., Nichols, N. K. and Eyre, J. R. (2014) Representativity error for temperature and humidity using the Met Office high-resolution model. Quarterly Journal of the Royal Meteorological Society, 140 (681). pp. 1189-1197. ISSN 1477-870X

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To link to this article DOI: 10.1002/qj.2207

Abstract/Summary

The observation-error covariance matrix used in data assimilation contains contributions from instrument errors, representativity errors and errors introduced by the approximated observation operator. Forward model errors arise when the observation operator does not correctly model the observations or when observations can resolve spatial scales that the model cannot. Previous work to estimate the observation-error covariance matrix for particular observing instruments has shown that it contains signifcant correlations. In particular, correlations for humidity data are more significant than those for temperature. However it is not known what proportion of these correlations can be attributed to the representativity errors. In this article we apply an existing method for calculating representativity error, previously applied to an idealised system, to NWP data. We calculate horizontal errors of representativity for temperature and humidity using data from the Met Office high-resolution UK variable resolution model. Our results show that errors of representativity are correlated and more significant for specific humidity than temperature. We also find that representativity error varies with height. This suggests that the assimilation scheme may be improved if these errors are explicitly included in a data assimilation scheme. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > National Centre for Earth Observation (NCEO)
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:34166
Publisher:Royal Meteorological Society

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