Spatial observation‐error correlations for AMSU‐A in all‐sky assimilation: An ECMWF and UK Met Office intercomparison

Bhatt, R., Bonavita, M., Bormann, N., Dance, S. ORCID: https://orcid.org/0000-0003-1690-3338, Fowler, A. ORCID: https://orcid.org/0000-0003-3650-3948, Holm, E., Merchant, C. ORCID: https://orcid.org/0000-0003-4687-9850, Mittaz, J., Stuart, N. and Waller, J. (2026) Spatial observation‐error correlations for AMSU‐A in all‐sky assimilation: An ECMWF and UK Met Office intercomparison. Quarterly Journal of the Royal Meteorological Society. ISSN 0035-9009 (In Press)

Abstract/Summary

Observations from microwave temperature sounders such as the Advanced Microwave Sounding Unit-A (AMSU-A) provide some of the largest contributions to forecast skill in Numerical Weather Prediction. Currently, AMSU-A radiances are assimilated under all-sky conditions at operational centres without explicitly accounting for spatial observation error correlations. To mitigate the impact of unrepresented correlated errors, strategies like spatial thinning (reducing observation density) and inflated observation error variances are commonly used. We present here new estimates of spatial observation error correlations for the AMSU-A all-sky systems from ECMWF and the Met Office, using diagnostics from background and analysis departures. Results are presented for three different cases: when all data are considered, and when data are separated by surface type and cloud cover. High spatial observation error correlations are seen particularly for tropospheric channels (4-8) over land, with correlation length scales ranging from 75 km to 125 km. We hypothesise that these correlations primarily originate from inadequacies in the modelling of surface emissivity, surface skin temperature, clouds, or precipitation. Our findings suggest an increase in forecast skill could be achieved by following a pragmatic strategy of increasing assimilated observation density for stratospheric channels (9-14) and all channels 4 to 14 over the ocean due to the negligible error correlations in these situations. In contrast, for tropospheric channels over land, fully exploiting the available data through reduced thinning requires accounting for spatial observation error correlations.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/129906
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 Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Wiley
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