The documentation regarding the expected behavior of adaptive inflation needs to be improved. This includes what the scientific recommendation is for the application of inflation in regards to either prognostic versus diagnostic variables within the DART state. The guidance should reflect that inflation is applied to only 'UPDATED' DART variables. In addition, more explicit guidance on how to apply inflation settings (i.e. prior, posterior, damping settings) is needed as well as more discussion on diagnosing the inflation based on its time-varying behavior. This is a continuation of a discussion from a previous issue on github #276, and also based on recent standup discussions held within DAReS.
There are a number of issues, but to name of few, the introduction is outdated -- it refers to the outdated Manhattan naming system and also the deprecated 'observation' space inflation. The documentation should immediately address the purpose of inflation which is to handle both systematic biases (e.g. structural model errors) and sampling errors (e.g. low ensemble member count). It should directly state that inflation is applied to only 'UPDATED' variables in the DART state, whereas 'NO_COPY_BACK' variables are left alone (inflation = 1). It needs better guidance for evaluating proper behavior of time-varying inflation behavior. See next section for more details.
Suggestions for improvement
1) The documentation should state that inflation is only applied to 'UPDATED' variables in the DART state, and not 'NO_COPY_BACK' variables. 'NO_COPY_BACK' variables by definition have no impact on the assimilation forecast, however, are required for the calculation of the forward operator.
2) The section that refers to adaptive inflation recommendations based on Gharamti et al.,. 2019 should be expanded. For example, this could include the Lorenz 63 figure where various inflation approaches are used to address model bias and sampling error. (AI-b: prior inflation only; AI-a: posterior inflation only; AI-ab: both)
This is subjective, but could be then followed by a recommendation table based on assimilation applications:
What's the issue?
The documentation regarding the expected behavior of adaptive inflation needs to be improved. This includes what the scientific recommendation is for the application of inflation in regards to either prognostic versus diagnostic variables within the DART state. The guidance should reflect that inflation is applied to only 'UPDATED' DART variables. In addition, more explicit guidance on how to apply inflation settings (i.e. prior, posterior, damping settings) is needed as well as more discussion on diagnosing the inflation based on its time-varying behavior. This is a continuation of a discussion from a previous issue on github #276, and also based on recent standup discussions held within DAReS.
Where did you find the issue?
The core inflation documentation is located here . This section also refers to the fill_inflation_restart documentation.
What needs to be fixed?
There are a number of issues, but to name of few, the introduction is outdated -- it refers to the outdated Manhattan naming system and also the deprecated 'observation' space inflation. The documentation should immediately address the purpose of inflation which is to handle both systematic biases (e.g. structural model errors) and sampling errors (e.g. low ensemble member count). It should directly state that inflation is applied to only 'UPDATED' variables in the DART state, whereas 'NO_COPY_BACK' variables are left alone (inflation = 1). It needs better guidance for evaluating proper behavior of time-varying inflation behavior. See next section for more details.
Suggestions for improvement
1) The documentation should state that inflation is only applied to 'UPDATED' variables in the DART state, and not 'NO_COPY_BACK' variables. 'NO_COPY_BACK' variables by definition have no impact on the assimilation forecast, however, are required for the calculation of the forward operator.
2) The section that refers to adaptive inflation recommendations based on Gharamti et al.,. 2019 should be expanded. For example, this could include the Lorenz 63 figure where various inflation approaches are used to address model bias and sampling error. (AI-b: prior inflation only; AI-a: posterior inflation only; AI-ab: both)
This is subjective, but could be then followed by a recommendation table based on assimilation applications:
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