[gradsusr] Averaging Multiple Data sets with Different Temporal Resolutions
Jennifer M Adams
jadams21 at gmu.edu
Tue Jan 23 11:35:02 EST 2018
No zeros. Only the good data values are included in the average. If you have only one model, then that one value is your result. If you have two models, then the average of those two is your result, etc.
—Jennifer
> On Jan 23, 2018, at 10:31 AM, Perry, Aaron <Aaron.Perry at lsc.vsc.edu> wrote:
>
> Hi Jennifer!
>
> So, if some of the datasets aren't available during averaging, what happens to those data? Are 0s used in the averaging?
>
>
> Aaron D. Perry
> Class of 2016
> Lyndon State College
> Lyndonville, VT 05851
> Twitter: @arnpry
> Email: Aaron.Perry at lyndonstate.edu
> From: gradsusr <gradsusr-bounces at gradsusr.org> on behalf of Jennifer M Adams <jadams21 at gmu.edu>
> Sent: Tuesday, January 23, 2018 7:13:25 AM
> To: GrADS Users Forum
> Subject: Re: [gradsusr] Averaging Multiple Data sets with Different Temporal Resolutions
>
>
>
> > On Jan 22, 2018, at 7:49 PM, Jeff Duda <jeffduda319 at gmail.com> wrote:
> >
> >
> > Your blend would become "missing data" and you would get no plot at all once even one of the input fields dropped out.
> ^^ This is incorrect.
>
> As it calculates averages, GrADS keeps track of missing data and weights the average accordingly. You will get a missing value in the result only if *all* the values are missing. For the time steps where *some* of the models are missing, you will get an average of the available models.
> —Jennifer
>
> > On Fri, Jan 19, 2018 at 10:19 AM, Perry, Aaron <Aaron.Perry at lsc.vsc.edu> wrote:
> > I have a hypothetical question...
> >
> > If you were to blend multiple data sets together with varying temporal resolutions, (and after lterp'ing them all to the same grid) what would happen with one of the data sets if it's data time ran out before the others did?
> >
> > Ex.
> >
> > ND = No Data
> >
> > TAU 0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102 108 114 120 126 132 138 144 150 156 162 168 174 180 186 192 198 204 210 216 222 228 234 240
> > GFS - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
> > CMC - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
> > ECM - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
> > NAM3 - - - - - - - - - - - ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND
> > NAM12 - - - - - - - - - - - - - - - ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND
> >
> >
> > 'define blend = (GFS+CMC+ECM+NAM3+NAM12)/5.0'
> >
> > Would the sudden data drop-out in the average result in 0s being introduced into the average? How would you keep the data (last valid timestep) that runs out included in the overall average?
> >
> > Cheers,
> >
> >
> > Aaron D. Perry
> > Class of 2016
> > Lyndon State College
> > Lyndonville, VT 05851
> > Twitter: @arnpry
> > Email: Aaron.Perry at lyndonstate.edu
> >
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> >
> >
> >
> > --
> > Jeff Duda
> > Research Scientist
> > Cooperative Institute for Research in Environmental Sciences at the University of Colorado
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> > gradsusr at gradsusr.org
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> --
> Jennifer Miletta Adams
> Center for Ocean-Land-Atmosphere Studies (COLA)
> George Mason University
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Jennifer Miletta Adams
Center for Ocean-Land-Atmosphere Studies (COLA)
George Mason University
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