Oacres Function: Grid to Station Ratio

[Stephen R McMillan]

In the GrADS Documentation Index, the description for the Cressman 
objective analysis function "oacres" rightfully cautions against using too 
few stations in the analysis, relative to the number of grid points:

"The Cressman Analysis scheme can be unstable if the grid density is 
substantially higher than the station data density (ie, far more grid 
points than station data points). In such cases, the analysis can produce 
extrema in the grid values that are not realistic. It is thus suggested 
that you examine the results of oacres and compare them to the station 
data to insure they meet your needs."

I have two questions regarding use of oacres:
1.  What is an example of a grid-to-station ratio that one might consider 
unstable or unrealistic?

I have searched the GrADS User Group archives, but no luck.  Additional 
searches on the Internet suggest a grid-to-station ratio of around 81:1 is 
approaching any useful limits, based on a grid cell requiring any station 
data within four grid points of itself (thus, a 9 x 9 "box" surrounding 
it).  If you've had experience (good or bad) with using oacres, or were 
involved in its development, please let me know what might be considered 
realistic grid-to-station limits.  Of course, I could go the 
trial-and-error route to see what makes sense, but I would rather approach 
the problem based on others' success.

2.  What are the function's optional "radii of influence"?  Are they 
length units and, if so, what?  Are they number of grid cells/points?  Or 
something else?

Again, I could not find the answer, either in the Documentation Index 
description, or in the User archives.

I would be processing mainly surface temperature and precipitation station 
data across regional and continental domains.

Thanks in advance!
Stephen McMillan
Planalytics, Inc.


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