| Randy,
Thanks. I guess I'm still wondering how you can validly assign a label such as "error" to a number that doesn't somehow tell you the likelihood of the variable value being within some sort of interval. Without getting too hung up on statistical formalisms, can you explain what use this number is to you?
Grace and peace,
Jim
Jim:
The magnitude of the Expected Error is a function of the calculated wind speed.
In perusing the Expected Error algorithm documentation to compose the last email, it appears the algorithm does not assume any type of an error distribution (normal or otherwise). The error estimate is absolute and is not associated with a confidence level.
The use of this algorithm is based on the results it has achieved on predecessor weather satellite programs (empirical data has been used to determine its effectiveness.) I can provide you additional information on the Expected Error algorithm if you are interested,
The point I am trying to make is that this is a specific error estimation approach that is unrelated to a sampling distribution. I would think there are others.
very respectfully,
randy
From: "Jim Biard" <[email protected]>
Sent: Friday, July 05, 2013 11:22 AM
To: "[email protected] List" <[email protected]>
Cc: "[email protected] Horne" <[email protected]>
Subject: Re: [CF-metadata] Fwd: how to represent a non-standard error
Randy,
Could you help me understand a touch more about this? You say it is an error that comes from a custom algorithm, but what defines what magnitude it has? How do you relate it to anything? Does it represent some sort of confidence interval?
Grace and peace,
Jim
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Dear Jonathan:
In the case of the GOES-R derived motion winds product, the error estimate (i.e. more formally referred to as Expected Error) is based on a custom algorithm.
This expected error algorithm is specific to atmospheric wind vectors derived from satellte data. The overarching concept of the wind algorithms generated from satellite data is doing pattern matching of phenomena (like clouds) across multiple images of the same region separated by some period of time
The GOES-R incarnation of this Expected Error approach makes use of a set of error predictors including (1) NWP model data (wind shear, temperature gradient), (2) wind speed, direction, and consistency quality indicators output from the winds algorithm proper, and (3) a wavelength dependent constants (GOES-R generates sets of wind vectors from a visible and several emissive bands)
I also found an article on the web that discusses it:
https://www.eumetsat.int/cs/idcplg?IdcService=GET_FILE&dDocName=pdf_conf_p42_s2_le_marshall&allowInterrupt=1&noSaveAs=1&RevisionSelectionMethod=LatestReleased
very respectfully,
randy
Dear all
OK, I agree that if it's useful to compare them, then they should be described
in a standardised way.
Why is this *not* a standard error? I suppose that to be described as a
standard error it should be a number you could regard as the standard deviation
of the true value around the stated value. If it's not that, are there other
ways you would use such a number?
Best wishes
Jonathan
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