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An instability in the Incremental Analysis Update (IAU) procedure was discovered during atmospheric model downscaling. Theoretical analysis and digital filtering offer solutions to mitigate this issue in weather forecasting models.

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Area of Science:

  • Atmospheric science
  • Numerical weather prediction
  • Data assimilation

Background:

  • The Incremental Analysis Update (IAU) is crucial for data assimilation in numerical weather prediction.
  • Downscaling MERRA-2 analyses to higher resolutions revealed an unnoticed instability in the IAU procedure.

Purpose of the Study:

  • To diagnose and address the IAU instability encountered during model downscaling.
  • To propose methods for avoiding this instability in various atmospheric modeling contexts.

Main Methods:

  • Theoretical analysis using a damped harmonic oscillator model.
  • Investigating three approaches: optimizing IAU step ratios, time averaging background fields, and digital filter modulation.
  • Testing methods with NASA/GMAO atmospheric general circulation model at different resolutions.

Main Results:

  • The IAU instability can be controlled across various resolutions using the proposed methods.
  • Combining IAU with ensemble re-centering in hybrid 4D-EnVar systems also leads to instability.
  • Digital filter modulation effectively mitigates instability in ensemble IAU tendencies.

Conclusions:

  • The identified IAU instability is a significant issue in high-resolution atmospheric modeling.
  • Theoretical insights and practical methods, particularly digital filtering, provide effective solutions.
  • Further research is needed to fully analyze and improve 4D-IAU implementations.