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https://issues.apache.org/jira/browse/CLIMATE-643?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14647870#comment-14647870
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ASF GitHub Bot commented on CLIMATE-643:
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Github user huikyole commented on the pull request:
https://github.com/apache/climate/pull/210#issuecomment-126383587
@MJJoyce I understand your concerns. However, updating examples was
impossible without adding new modules to the dataset_processor. CLI is also
using the code based on examples. I will try to separate these into three
tickets.
> Updating some of examples
> -------------------------
>
> Key: CLIMATE-643
> URL: https://issues.apache.org/jira/browse/CLIMATE-643
> Project: Apache Open Climate Workbench
> Issue Type: Improvement
> Components: general
> Affects Versions: 1.0.0
> Reporter: Huikyo Lee
> Assignee: Huikyo Lee
> Fix For: 1.0.0
>
>
> Paul L. suggested some ideas to update examples. For example,
> "knmi_to_cru_full_bias.py" needs to be updated with better description. The
> model to model bias could be replaced by model to observation data bias. The
> goal is providing 5 examples all based on an actual published papers.
> Currently, OCW examples generate wrong results when there is missing data in
> observational datasets. It is important to mask those grid points with
> missing values in model datasets so that no metrics calculation is done at
> those grid points. In other words, if any of observation/model dataset has
> missing value at a grid point, we need to propagate the missing information
> to the other datasets.
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