[GRASS-user] Re: [GRASS-dev] Changes to r.sun made Feb 2006 [resolved]

[Hamish]

Dylan Beaudette wrote:
> PS: with even better results from r.sun:
> http://169.237.35.250/~dylan/temp/11-yr_variation_vs_modeled.png
> 
> when using longer term averages, the R^2 goes to 0.95 ! (right hand
> sub-figure), but still working on optimal Linke turbidity values.


Did you extract the Linke turbidity values from the app. on the EU web
site, derive it from measured in situ values, or are you tweaking that
variable as a calibration to get r.sun to match your measured radiation
values?

I see you have a bit of sawtooth noise in your plots. FWIW to avoid
introducing this monthly jump I wrote a little app some time ago which
interpolated daily Linke value from the monthly Linke averages (for use
in r.sun bash script loop) [assume monthly averages are for day 15 of
each month and interpolate for the days in between]. I'd have to dig it
out, & it's probably a mix of Matlab+C. Maybe something for the wiki
add-ons.

How to deal with cloud cover? (coefbh= and coefdh=) Use real clear-day
measured data (find a day with a clean curve) to estimate the cloud
attenuation factors for neighboring cloudy days (theoretical curve vs
what actually happened), then generalize the cloudiness factor over your
decade long dataset?  e.g. find max (midday) light for each year's day
90, then take the max. maybe include +/-1 day. then run a smoothing
filter on the result. ?? probably want the coeffs to vary throughout
the year.

Another idea I've been playing with is getting cloud cover data from
recorded PV voltage in one of our remote solar-powered weather stations
(it lacks a real light meter). There's a pretty obvious pattern in the
voltage signal to play with. Just a matter of calibrating it..


Hamish