Improving the information content of IASI assimilation for numerical weather prediction
SmithFiona Isobel
2015
The Infrared Atmosperhic Sounding Interferometer (IASI) provides significant
impact to numerical weather prediction systems despite current assimilation schemes
using less than 2% of the channels. The current system does not achieve the information
content predicted by earlier theoretical studies and results presented here show
that the information content could be doubled if the full spectrum were exploited.
There is potential to improve the vertical resolution of the humidity analysis and
the stratospheric temperature in particular.
This thesis explores principal component (PC) compression and radiance reconstruction
to compress the spectrum by over 90% whilst retaining almost the full
information content. Theoretical calculations are shown that indicate PC scores and
reconstructed radiances achieve close to the maximum information content, making
them promising approaches for better exploitation of IASI. However, care must be
taken because neglected error terms and matrix conditioning are problematic due to
the way the information in the compressed observations is coupled in the vertical.
New methods for choosing reconstructed radiance channels for assimilation are developed
and tested, generating channel selections suitable for implementation in the
Met Office operational system.
The final section is concerned with the interaction between the observation information
and the background error covariance matrix. This matrix can only ever
be estimated, which causes the analysis to be suboptimal. If the differences between
true and assumed errors are large enough, the analysis may be degraded relative
to the background. Guarding against exaggeration of background errors is therefore
important, and for water vapour in particular, spurious vertical structures in
the stratosphere must be avoided. Increasing the spectral coverage increases the
information content and reduces exposure to analysis degradation. This result is
encouraging because it means that there is no greater risk to the analysis if more
spectral information is provided, paving the way for assimilation of reconstructed
radiances.