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 
  Jim Biard
Research Scholar
 Cooperative Institute for Climate and Satellites
Remote Sensing and Applications Division
 National Climatic Data Center
151 Patton Ave, Asheville, NC 28801-5001 

[email protected]
828-271-4900  
 Follow us on Facebook! 
 On Jul 5, 2013, at 9:28 AM, "[email protected]" 
<[email protected]> wrote:    

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=LatestRe
leased   

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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