Accounting for correlated error in the assimilation of high‐resolution sounder data

By Peter Weston, William Bell, John Eyre. 2014

149 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/3ffe9775643c05f851cf2757f3e7cd2e1c04076f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

In Global and Planetary Change

Citations in the corpus

The growing impact of satellite observations sensitive to humidity, cloud and precipitation (2017, methodology): “…example of the difficulties is that the allsky observation-error model will have to simultaneously model inter-channel error correlations, which have proved important in clear-sky infrared assimilation (e.g. Weston et al., 2014; Bormann et al., 2016), and also inflate errors in cloudy conditions.”
Error covariance estimation methods based on analysis residuals: theoretical foundation and convergence properties derived from simplified observation networks (2016, background): “Bormann and Bauer (2010), Bormann et al. (2010), Desroziers et al. (2011), Todling (2014) and Weston et al. (2014), among others, have used this approach to estimate the observation-error variances and cross-channel error correlations of high spectral radiance measurements.”
The benefits of correlated observation errors for small scales (2015, methodology): “However, if we were to use a diagonal observationerror covariance matrix, as is common operationally (a notable exception being Weston et al., 2014), the results would be suboptimal.”
On the representation error in data assimilation (2018, unknown): “For example, the diagnostic has also been applied to calculate satellite interchannel error covariances (Stewart et al., 2009; 2014; Bormann and Bauer, 2010; Bormann et al., 2010; Weston et al., 2014; Waller et al., 2016a) and spatial error covariances (Cordoba et al.”
On the interaction of observation and prior error correlations in data assimilation (2018, unknown): “…centres to account for Infrared Atmospheric Sounding Interferometer (IASI) inter-channel error correlations (which previously relied on variance inﬂation) have been shown to lead to an improvement in forecast skill scores (Weston et al. , 2014; Bormann et al. , 2016; Campbell et al. , 2017).”