DA | VarBC
Most data assimilation schemes assumes an unbiased observation model error.
- Berry, Tyrus, and John Harlim. "Correcting biased observation model error in data assimilation." Monthly Weather Review 145.7 (2017): 2833-2853.
- While the formulation of
most data assimilation schemes assumes an unbiased observation model error, - in real applications model error with nontrivial biases is unavoidable.
- A practical example is errors in the radiative transfer model (which is used to assimilate satellite measurements) in the presence of clouds. Together with the dynamical model error, the result is that many (in fact 99%) of the cloudy observed measurements are not being used although they may contain useful information.
- While the formulation of
- Bias correction in data assimilation | Hans Hersbach and Dick Dee | 2014
- Most assimilation systems assume unbiased models and unbiased data
- Observational bias correction in data assimilation and an overview of satellite data monitoring | Niels Bormann | 2024
DA | VarBC
https://waipangsze.github.io/2025/06/04/NWP-DA-VarBC/