Sunlit/Shaded Scheme in SiB Model Framework
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Transcript of Sunlit/Shaded Scheme in SiB Model Framework
Explicit representation of sunlit and shaded canopy
fraction: fun modeling issues and interesting
WLEF results.
Ian Baker, Joe Berry, C. James Collatz, A. Scott Denning, YingPing Wang, Neil Suits,
Lara Prihodko, Kevin Schaefer, Andrew Philpott
Sunlit/Shaded Scheme in SiB Model Framework
Tcsunlit
e*(Tcsunlit)
Tm
em
Ta
ea
Tg
e*(Tg)
rbsun
rd
ra
rbshade
Tcshaded
e*(Tcshaded)
Replace a single vegetation value with 2 prognostic variables-sunlit and shaded canopy fraction. What changes to the model are required?
Radiation Transfer Submodel
General form of equation•Sunlit fraction= exp(-kL)•Shaded fraction = 1-exp(-kL)
k is a function of solar zenith angle and leaf angle distribution
Light is partitioned between the two canopy elements
Radiative Transfer Submodel (cont.)
0
/ 1 1 expdI dL I I K KL
0
/ 1 1 1 expdI dL I I K KL
Radiation scattered in an upward direction:
Radiation scattered in a downward direction:
These components are convolved with sunlit/shaded canopy fraction based upon Beers’ Law to give full complement of radiative transfer equations. Generally follows Sellers (1985) and Sellers et al (1996).
Canopy Radiative Transfer (cont.)
0 0
_0
T T
T
sunlit beam diffusesunlit sunlit
scattered beam sunlit
L LL L dL L L dL
LL L dL
f fI I I
fI
Sunlit leaves: beam + diffuse + scattered
_0 0
1 1T T
shaded diffuse scattered beamsunlit sunlit
L LL L dL L L dLf fI I I
Shaded leaves: diffuse + scattered
Canopy Nitrogen/Rubisco Velocity Attenuation
Nitrogen decreases with depth in a canopy, in a Beers’ Law relationship similar to LAI.
Multiple ways to represent this, but two popular techniques are:•Normalized: N(L) = N(0)exp(-kL/LT)•Non-Normalized: N(L) = N(0)exp(-KL)
Canopy Nitrogen/Rubisco Velocity Attenuation
(cont.)Does Rubisco Velocity decrease in the canopy 1:1 with Nitrogen (black line)?
Or is Nitrogen re-partitioned with depth in the canopy?•Canopy top: most resources allocated to carboxylation, light capture not as important •Canopy interior: Nitrogen re-allocated to light capture from carboxylation (blue line)
•Beam/diffuse•Saturation at high illumination
Impact of Rubisco
Assumptions on Results
Effect of Rubisco
Treatment on
ResultsWhat happens as more leaf is added to the canopy?
What have we decided to do?
•We like the ‘normalized’ Nitrogen attenuation scheme. It makes sense that the bottom of the canopy has 50% the Nitrogen at the top. Non-normalized schemes can have leaves at the bottom of a dense canopy with 2% Nitrogen compared to top leaves.
•It also makes sense to re-allocate Nitrogen from carboxylation to chlorophyll with depth in the canopy. Not doing so results in excessive photosynthesis in test cases. Caveat: we have not determined the optimal re-allocation scheme for multiple biome types. Also, we are not modifying leaf transmissivity/reflectivity characteristics with canopy depth.
SO WHAT? Or, how can we utilize this new
tool?1. More realistic fluxes of heat, moisture, carbon and momentum
when compared to flux towers2. Higher degree of biophysical
realism: Ability to perform additional botanical/ecological
experiments
But First--Energy Budget
•We know that the eddy covariance fluxes don’t close the energy budget-How should we use this when comparing modeled fluxes to obs?
•What is the diurnal/annual nature of this term?
•Rn = H + LE + G
•Correction factor: C = (Rn – G) / (H + LE)
•But this correction factor has limitations
But First--Energy Budget
Observed
Mod
eled
Limitations to Using ‘Adjusted’ Observations•Can only evaluate model:obs
on a 1:1 plot during restricted periods (i.e. H+LE > 0, Rn>0
•C = (Rn – G) / (H + LE)
•Monthly mean/Diurnal composite?
I need guidance from the observation community for determining a reasonable evaluation strategy for the
models vis-à-vis the energy closure issue!
Improved results
Monthly Mean Values•Summer H decreased•Annual cycle NEE
•Spingtime sign change•Fall return to efflux•Magnitude?
More improved
results
Monthly Mean Diurnal Composite•New code has better shape, when compared to obs•Magnitude?
Taylor Plot
Polar coordinates:
•ANGLE: cos-1(R), where R is the correlation coefficient
•Radius: standard deviation
Taylor Plot
•Correlation coeff of LE, NEE improves•Magnitude of NEE much larger•This plot for all points: how does it break out by month?
Taylor Plot: Sensible Heat
•Amplitude of summertime H decreased•Correlation coeff worse
Taylor Plot: Latent Heat
•Magnitude larger•Correlation coeff better
Taylor Plot: NEE
•Magnitude larger•Correlation coeff better
What else can we do?
Isotopes
Shaded canopy discrimination is around 4‰ smaller that sunlit fraction; this agrees well with observations
Impending projects•Species-specific
•Ewers/Mackay et al; estimate transpiration flux from sap flux data; 4 basic forest types•Model: obtain leaf/species level data from Gutshick, determine model parameters•Initial model results: variable. With new model scheme, can re-address
•Beam-diffuse•‘Global dimming’/aerosol loading (volcanic) change beam/diffuse radiation distribution•Model reproduction/resulting fluxes