[PyCAMA] update filters for HCHO (possibly others) to exclude data with QA value < 0.5
Isabelle made a request to exclude retrievals with a QA value smaller than 0.5 from the PyCAMA analysis. At this moment we include everything that is not a fill value in the analysis, it is not hard to add a filter on the QA value, and start to monitor only the 'good' values. Please note that this also means that some problems may be masked by this choice, problems that only show up in retrievals 'with issues'. This is also the reason I haven't implemented this before. I will only implement this on request. The event counter will remain as is, but all retrievals with a small QA value will be removed here, if requested.
Let me know below if you want your product to be filtered, and in what way.
#3 Updated by Maarten Sneep almost 2 years ago
Isabelle responded via email:
I agree that it is important to keep monitoring all the data.
If we can have different filters, and I heard you saying that it was possible, then it would be very nice to have all the data for SCD, corrected SCD and AMFs.
And only filter the tropospheric HCHO VCD + HCHO VCDE random + HCHO VCDE systematic with the QA values.
Or alternatively, apply a filter for the clouds, again only for HCHO VCDs. Because large cloud artifacts in the AMFs mask all other possible problems.
I will set up the new filters and provide a test report based on a single day from DDS2B. Because of other obligations this will take some time.