[GRASS-user] Creating turbidity raster file

Hamish hamish_b at yahoo.com
Wed Feb 11 02:15:03 EST 2009


Hamish:
>> I have worried about r.sun's Linke Turbidity factor values in areas with
>> big changes in elevation. Is turbidity value heavily dependent on
>> altitude?

Jose:
> Linke turbidity is certainly height-dependent given the higher optical
> path length at lower elevations. A simple approximated pressure correction
> might be applied if the turbidity at a given altitude z' is known:
> 
> TL(z) = TL(z') exp( -(z-z') / 8435.2)

Dylan:
> It should, as it is based on a measure of optical thickness (air mass):
> m = \frac{1}{sin(\alpha) + 0.15(\alpha + 3.885)^{-1.253}} e^{-0.0001184 \timesA}

(yay LyX, ctrl-m, paste selection, view PostScript)
 
buraq wrote:
> I took the turbidity values from soda-is.com. I entered no altitude
> value for the latitude and longitude.


I did the same, I attempted to match their model grid (approx 1x1-deg IIRC)
for an array of lat/lon extractions over my study area, then v.surf.rst to
produce a Linke layer for r.sun. I can't recall off the top of my head if
we entered an altitude or not, I think not.

I work in fjords with >1000m vertical drops (including one of the top
10 tallest waterfalls in the world). With little idea of the elevation
values used for the SODA data, I just guess that it will be very rough
and subject to a somewhat arbitrary sampling error.

I assume I'll have to use one of the above formulas with r.mapcalc to
create the Linke layer from the SODA data & a local DEM for delta-z. But
that just makes me wonder if turbidity really belongs in a 3D voxel grid,
not a 2D coverage map? i.e. I can derive a value for Linke at the
ground-surface for each raster cell in the DEM easily enough using the
above formulas, but isn't the important Linke value(s) what the beam
encounters on it's path through the atmosphere high above the ground,
not just the value at ground level at the beam's terminus?

If it helps, I do have quite a bit of PAR light meter data we collected
at sea level throughout the region over full years; and do know the air
is nearly as clear as it gets. What instrumentation could I add to our
met stations to get a better record? Deploying light loggers on mountain
peaks for the summer months may be an option (granite is beautiful stuff
to climb :).


hope that makes sense,
Hamish


ps- If anyone is interested, at one point I wrote a little C program
that fit a sine curve to the monthly data and gave you a per-day value
from per-month data, avoiding big jumps at the month changes. The same
could in theory be adapted to work with r.mapcalc to get daily maps from
the monthly raster layers, at considerable computational cost. (but you
just need to run it once(ie x365) in a dedicated mapset)



      



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