Using Biophysical Models to Ask (and Answer) Questions About Biosphere-Atmosphere
Interactions
Dennis BaldocchiAlexander Knohl
James Dorsey
Biometeorology LabUniversity of California, Berkeley
ILEAP MeetingBoulder, COJan, 2006
Isotopicexchange
ILEAPS Paradigm
Sub-Grid Variability:What are Errors in ET Scaling?
Answering Questions with Models
• Diffuse Radiation– Light Use Efficiency– Isoprene emission– Water Use Efficiency– Stable Isotopes
• Sub-Grid Parameterization, Energy Balance Closure and Scaling– Insights from a 2-D, ‘Wet’ DaisyWorld
Physiology
Photosynthesis
Stomatal Conductance
Transpiration
Micrometeorology
Leaf/Soil Energy Balance
Radiative Transfer
Lagrangian Turbulent Transfer
Albedo
LEH
Gsoil
FCO2
CANVeg MODEL
Key Attributes of CanVeg
• Seasonality– Leaf Area Index– Photosynthetic Capacity (Vcmax)
• Model parameters based on Site Measurements and EcoPhysiological Rules and Scaling
– Stomatal Conductance scales with Photosynthesis– Jmax and Rd scale with Vcmax
• Multilayer Framework– Computes Fluxes (non-linear functions) on the basis of a leaf’s local environment– Considers
• Sun and Shade Leaf Fraction• Leaf Clumping• Leaf Inclination Angle• Non-local Turbulent Transport and Counter-Gradient Transfer
0 100 200 300 400 500 600 700
NE
E ( m
ol
m-2 s
-1)
-25
-20
-15
-10
-5
0
5
10
15
measuredcalculated
1997 Walker Branch Watershed
NEE measured (mol m-2 s -1)
-30 -25 -20 -15 -10 -5 0 5 10 15 20
NE
E c
om
pu
te
d (
mo
l m-2 s
-1)
-30
-20
-10
0
10
20
b[0] 0.908b[1] 1.085r ² 0.815
CO2 Flux Model Test: Hourly to Annual Time Scales
Another Form of Model Testing: Reproducing Spectral Fidelity
n, cycles per hour
0.0001 0.001 0.01 0.1 1
nS
wc(
n)/
w'c
'
0.0001
0.001
0.01
0.1
1
10
canoakdata
1997
Baldocchi et al, 2001 Ecological Modeling
Results and Discussion
PPFD (mol m-2 s-1)
0 500 1000 1500 2000
NE
E ( m
ol
m-2 s
-1)
-40
-35
-30
-25
-20
-15
-10
-5
0
5
10Sunny daysdiffuse/total <= 0.3
Cloudy daysdiffuse/total >= 0.7
Temperate Broad-leaved ForestSpring 1995 (days 130 to 170)
How Sky Conditions Affect Net Carbon Exchange (NEE)?: Data
Baldocchi, 1997 PCE
CO2 Flux and Diffuse Radiation:Data from AmeriFlux
Niyogi et al., GRL 2004
Volcanoes, Aerosols + NEE
How do Changes in Diffuse Radiation affect Canopy Fluxes?:Case: Mt Pinatubo Explosion, ~ 10% of beam -> diffuse
Gu et al, 2003, Science
dire
ct b
eam
diff
use
Sol
ar r
adia
tion
[W m
-2]
Solar elevation angle [°]
Year of Mt. Pinatuboeruption
Canopy Photosynthesis and Aerosols:Impact on Daily & Annual Scales, I
PAR (mol m-2 d-1)
0 10 20 30 40 50 60
Ac
(gC
m-2
d-1
)
2
4
6
8
10
12
base: 1478 gC m-2 y-1
Diffuse += 10% Beam: 1527 gC m-2 y-1
Canopy Photosynthesis may increase by +50 gC m-2 y-1
increase diffuse by 10% beam: 1527 gC m-2 y-1
Conventional Wisdom:More Light Absorption with Diffuse Radiation
Diffuse/Total
0.0 0.2 0.4 0.6 0.8 1.0
fAp
ar
0.90
0.91
0.92
0.93
0.94
0.95
WHY?
PPFD (mol m-2 s-1)
0 500 1000 1500 20000
5
10
15
20
Inte
gra
ted
ph
oto
sy
nth
es
is ( m
ol m
-2 s
-1)
Deciduous forest
shaded leavessunlit leavestotal
More Efficient Use of Light by Shade Leaves?
Oak Ridge, TN 1997 Growing Season, 10 to 16 hrs
Diffuse Fraction
0.0 0.2 0.4 0.6 0.8 1.0
vpd
(m
b)
0
5
10
15
20
25
30
vpd is Correlated with Diffuse Fraction:Less Physiological Stress (?)
Temperature Deciduous Forest
Day
0 50 100 150 200 250 300 350
Flu
x D
ensi
ty (
gC
m-2
d-1
)
0.01
0.1
1
10
Canopy Photosynthesis : 1478 gC m-2 y-1
Isoprene Efflux : 17.19 gC m-2 y-1
Isoprene and Diffuse Radiation
PAR (mol m-2 d-1)
0 10 20 30 40 50 60
Fis
o (g
C m
-2 d
-1)
0.1
0.2
0.3
0.4
base: 17.19 gC m-2 y-1
Diffuse += 10% Beam: 17.33 gC m-2 y-1
Stable Isotope Discrimination and Diffuse Light
Preference of photosynthesis for light 12CO2 vs. heavier 13CO2
Hainich, GermanyD160-290, 2002
Diffuse/Total PAR
0.2 0.4 0.6 0.8 1.0
p
er m
il d
aily
ave
rage
20
21
22
23
24
25
26
4 4 27 5 4 4000
000. ( . . )
C
Ci
a
Autocorrelations among Ci/Ca, vpd and diffuse/Total
Hainich, GermanyD160-290, 2002
vpd (hPa)
0 5 10 15 20
Ci/C
a
0.65
0.70
0.75
0.80
0.85
0.90
0.95
Hainich, GermanyD160 -290, 2002
Diffuse/Total PAR
0.2 0.4 0.6 0.8 1.0
vpd
(hP
a)
0
5
10
15
20
25
Hainich, GermanyD160-290, 2002
vpd (hPa)
0 5 10 15 20
p
er
mil
da
ily a
vera
ge
20
21
22
23
24
25
26
Water Use Efficiency (A/T) and diffuse light
PAR: diffuse/total
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
A/T
(m
mol
mo
l-1)
0
2
4
6
8
10
A
T
CCCD
ai
a
( )
.
1
16
Simple Model suggests A/T decreases with or Ci/Ca
)( fT
A
)))]((([( aiai CCDCCfT
A
But Complex feedbacks need to be considered!
e.g. A/T of C4 > C3
How Do Changes in vpd and Ci/Ca conspire to affect A/T?
A
T
CCCD
ai
a
( )
.
1
16
Ci/Ca
0.5 0.6 0.7 0.8
Fac
tor
0.01
0.1
1
10
100
1-Ci/Ca
1/D:(f(Ci/Ca))
A/T
A
T
C C C
C Ca i a
i a
( / )
. . /
1
2832 332
D a bC
Ci
a
19 20 21 22 23 24
A/T
(m
mo
l m
ol-1
)
0
5
10
15
20
25
30
In toto (considering coupled energy balance feedbacks) A/T increases with Ci/Ca
Ci/Ca
0.60 0.65 0.70 0.75 0.80 0.85
A/T
(m
mo
l m
ol-1
)
0
5
10
15
20
25
CANISOTOPEA/T=f(Ci/Ca, D)
A/T = f(Ci/Ca)
Sub-Grid Variability:Lessons Derived from Wet DaisyWorld
Latent Heat Exchange Map
Newly developed 3d Lagrangian stochastic footprint model was run for a 1 m canopy and 3 m measurement height. Half a million trajectories
were integrated to calculate the source probability density.
Footprint representation
Eddy covariance footprints and ecosystem representativeness
The footprint calculation was run using the same grid geometry as
the DaisyWorld simulation to allow convolution of the results.
The EC “tower” was placed in different locations in the
simulated ecosystem, and the EC system's view of the ecosystem
was calculated.
Each histogram shows 500 separate tower locations within the simulated ecosystem.
Eddy covariance footprints and ecosystem representativeness
Errors in ET Scaling
Conclusions
• Biophysical Model aids in understanding the impact of diffuse light on photosynthesis, isoprene emission, water use efficiency and stable isotope discrimination
• A cellular automata, energy balance model shows that spatial averaging of energy balance drivers can produce huge errors in grid-scale energy fluxes and can explain lack of energy balance closure
Acknowledgements
• Funding – NASA, DOE/TCP, NIGEC/WESTGEC
• Diffuse Light and Carbon– Lianhong Gu
• Isoprene– Peter Harley, Jose Fuentes, Dave Bowling, Russ Monson & Alex
Guenther
• 13C Isotopes– Dave Bowling, Russ Monson
• Footprints & DaisyWorld– Monique Leclerc, Tess Krebs, Joon Kim, Peter Levy, HaPe
Schmid, Brian Amiro
Canopy Photosynthesis and Aerosols:Impact on Daily & Annual Time Scales, II
PAR (mol m-2 d-1)
0 10 20 30 40 50 60
Ac
(gC
m-2
d-1
)
2
4
6
8
10
12
base: 1478 gC m-2 y-1
diffuse * 1.2: 1550 gC m-2 y-1
Role of Diffuse Light on Water Use Efficiency: A/E
PPFD (mol m-2 s-1)
0 500 1000 1500 2000
NE
E ( m
ol m-2
s-1)
-40
-35
-30
-25
-20
-15
-10
-5
0
5
10Sunny daysdiffuse/total <= 0.3
Cloudy daysdiffuse/total >= 0.7
Temperate Broad-leaved ForestSpring 1995 (days 130 to 170)
Tc (mmol m-2 s-1)
0 2 4 6 8 10
Ac
(m
ol m
-2 s
-1)
0
5
10
15
20
25
30
35
40
Temperate Forest, 1997
Rnet (W m-2)
-200 0 200 400 600 800T
c (m
mol
m-2
s-1
)
0
2
4
6
8
10
Daisy World
Window (m)
0.1 1 10 100 1000
T/<
Tsf
c>
0.00001
0.0001
0.001
0.01
0.1
Window (m)
0.1 1 10 100 1000
/<
E>
0.0001
0.001
0.01
0.1
1
Rwet =50 s m-1
Rdry = 1000 s m-1
Rsoil =2000 s m-1
Coefficients:b[0] -1.846b[1] -1.02r ² 0.996
Coefficients:b[0] -0.279b[1] -1.025r ² 0.982
(a)
(b)
Baldocchi et al, 2005 Tellus
E f x f xf x
xx[ ( )] ( )
( )( )
1
2
2
22
(z)r+(z)r
)C-(C(z) a(z) -=z)S(C,
z
F
sb
i
Quantifying Sources and Sinks
• Biology:– Leaf area density, a(z)– internal conc, Ci
– stomatal resistance, rs
• Physics: – Boundary layer resistance, rb
– Scalar conc, C(z)
Partial Explanation:Fiso is very sensitive to Leaf Temperature, which changed little in
response to the imposed direct to diffuse partitioning
Oak Ridge, TN, 1997
<Tleaf>, base
-20 -10 0 10 20 30
<T
leaf
>,
diff
use
+ 1
0% b
eam
-20
-10
0
10
20
30
b[0] 0.015b[1] 0.998r ² 0.999