Satellite Applications in Estimating Earth's Surface Energy Budget
AOSC624
Class
22:
May
1,
2012
At
Issue:
How can
satellites
help
to estimate
the
Surface
Energy
Budget
(SEB)
One Component
of
SEB:
Surface
Radiation
Budget
(Review)
Other
components:
Surface
Turbulent
Fluxes
of
heat and
moisture
Heat
into
ground
How do
we
evaluate
the
turbulent
fluxes?
Overview
of
Eddy
Covariance
Principles
Radiation Balance
at
the
Earth
Surface
The net flux
of
radiation
at
the
earth’s
surface
results
from
a
balance between the solar
and
terrestrial
radiation
fluxes:
F
sfc
rad
=
F
SW
+
F
LW
The
short-wave
and
long-wave
radiation
balance
can
be
expressed:
F
SW
=
F
SW
↓
-
F
SW
↑
F
LW
=
F
LW
↓
-
F
LW
↑
The net
radiation
balance
being:
F
sfc
rad
=
F
SW
↓
-
F
SW
↑
+
F
LW
↓
-
F
LW
↑
•
The incident solar
radiation
F
SW
↓
is the sum
of
the
direct
and
diffuse
solar
radiation.
It
has
a
pronounced diurnal
and
seasonal
variation,
and
is
also
strongly
affected
by
clouds
. The outgoing
short-wave
solar
radiation
is the
part
reflected
by
the
surface
F
SW
↑=
A
sfc
F
SW
↓, where
A
sfc
is the
surface
albedo so
that
the net
short-wave
radiation
is:
F
SW
=
(1
–
A
sfc
)
F
SW
↓
•
The outgoing
long-wave
radiation
F
LW
↑
is
given by
the
Stefan-Boltzmann
law,
assuming
a
given
emissivity
є
for
the
earth’s
surface
.
•
The net
radiation
flux
at
the
surface
is then
given
by
:
F
sfc
rad
=
F
SW
↓
(1
–
A
sfc
)
–
σєT
4
s
f
c
+
F
LW
↓
Energy
Balance
at
the
Earth
Surface
The
main
part
of
the
energy
absorbed
at
the
surface
is used
to
evaporate
water
,
another part is
lost to
the
atmosphere
as
sensible heat
, and
a
smaller part is
lost to
the underlying
layers
or
used
to
melt snow and
ice
.
Thus,
there
are
essentially
four
types
of
energy
fluxes
at
the
earth’s
surface.
They
are
the net
radiation
flux
F
rad
, the
(direct) sensible heat flux
F
SH
↑,
the (indirect)
latent
heat
flux
F
LH
↑,
and the heat flux
into
the
subsurface
layers
F
G
↓.
Under
steady
conditions the balance equation
for
the
energy
is given
by
F
sfc
rad
-
F
SH
↑
-
F
LH
↑
-
F
G
↓
-
F
M
=
0
These
surface
fluxes are
associated
with
land
processes
and depend
on:
•
vertical stability;
roughness
•
surface
temperature
•
subsurface
heat
conduction
•
vegetation
•
surface
hydrological
balance
•
potential
evapotranspiration
•
radiative
flux
•
Theoretical
aspects
of
satellite remote
sensing
of
energy
balance
•
Thermal equilibrium
at
the
surface
is
maintained by
a
combination
of
thermodynamic and
physiological
processes.
•
The net
energy
absorbed
by
the
surface through
radiative
processes,
net
radiation
R
n
,
must
be
balanced
by that transported
to
the
atmosphere
and
ground
(sensible,
latent,
and
ground heat
flux):
•
R
n
= H +
LE
+
G.
(
1
)
•
R
n
is
simply the
difference
between the incident and
reflected
shortwave
radiation
and the incident and
emitted
long
wave
radiation
at
the
surface, that
is:
•
R
n
= S{1 -
}
+
L
wd
-
L
wu
,
(
2
)
•
where
S is
downwelling
shortwave
radiation energy
flux
(Wm
-2
).
Surface energy
balance
formulae
For
the sensible and
latent
heat components
in eq.
1,
closed-form
solutions
cannot
be
obtained.
Commonly
used
semi-empirical
relations
are:
For
Sensible
heat:
H =
C
p
(T
aero
-
T
a
)/r
a
(
3
)
•
where
H
sensible
heat
flux,
W
m
-2
;
density of
air,
kg
m
-3
;
•
C
p
specific
heat
of
air,
J
kg
-1
o
C
-1
;
•
T
a
reference
height
air
temperature,
o
C;
•
T
aero
canopy
temperature,
o
C;
•
r
a
aerodynamic
resistance
for
heat
and
water
vapor,
s
m
-1
.
•
In
this
formulation
the
aerodynamic
resistance,
r
a
,
relates
the
vertical
gradient
in
temperature,
T
aero
-
T
a,
to
the
sensible heat
flux.
•
The
r
a
value
is
semi-empirical
and is
intended to
characterize
the
efficiency
of
the very
complex
transfer
of
heat by turbulent
air
movement through
the
canopy
into
the air
above;
r
a
is normally
derived
using empirical arguments
to
adjust
the
surface
momentum
transfer
coefficient,
a
term
that
relates
the
vertical
gradient
in boundary
layer
wind speed
to
surface
shear
stress.
•
A
number
of
such
empirical
formulations are
available
for
r
a
(
see
Hall
et
al,.
1991),
such
as:
where
U is windspeed, m
s
-1
;
z is
reference
height
for
measurement
of
T
a
and U ; h is
height
of
canopy
(m);
and g is
gravitational
acceleration,
m
s
-2
.
For more
details
and additional
formulation
for
Aerodynamic
Resistance
see the
provided
paper:
Measurement
and
estimation
of the
aerodynamic
resistance
S.
Liu,
D.
Mao,
and
L.
Lu
a
e
ro
,
ln(
z
0.56
h
)
ln[(
z
0.56
h
)
/
(0.0189
h
)]
r
a
0.16
U
{1
[5
g
(
z
0.56
h
)(
T
T
)
/
T
U
2
]}
3/4
a
a
•
For latent
heat:
LE
=
C
p
[e
*
(T
aero
)-
e
a
)](g
c
g
a
)/
(g
c
+
g
a
),
(5
)
vapor
pressure at
reference
height,
mbar;
air
temperature at
reference
height,
o
k;
saturated
vapor
pressure
in the
canopy
air
space,
•
•
w
h
e
r
e
e
a
•
T
a
•
e
*
(
T
a
e
r
o
)
mbar;
C
p
g
c
psychometric
constant,
mbar
o
k
-1
;
as
defined
in
(2);
bulk
stomatal
conductance
of
canopy,
m
s
-1
;
bulk
aerodynamic conductance
of
canopy
(1/
r
a
),
m
•
•
•
•
g
a
s
-
1
.
•
•
These
first-order
solutions
to
the
turbulent transport equations
served as the primary model
for
investigating
relationship
between the properties of land
surface vegetation,
energy-
mass balance, and
remote
sensing of these
interactions
in
FIFE.
Sensible
heat
•
For
H
in (3),
remote
sensing
measures
of
surface
radiometric
temperature have
been
evaluated
as a
surrogate
for
T
aero
.
•
•
However,
T
aero
is
not
explicitly
T
rad
but,
as
discussed
above,
a
theoretical construct that
parameterizes
a
“convective”
temperature.
Vining and Blad
(1991)
investigated
the
relationship
between
T
aero
and
T
rad
.
Latent
heat
For latent
heat
estimation
(eq.
5)
the
main
focus
of
remote
sensing
techniques
is
the
conductance
term g
c
and
the
T
aero
term
in
estimating
canopy
air-space
vapor
pressure.
The
canopy conductance
term g
c
can
be
modeled
after
Jarvis
(1976)
as a
product
of
functions with
range
(0,
1)
where
each function
characterizes
the dependence of
g
c
on
APAR
(absorbed
PAR),
e,
T,
and
leaf
water
potential
.
•
That
is:
*
•
g
=
g
(APAR)g(
e)g(T
c
c
ae
r
o
)
g(
)
(
6
)
c
•
where
g
*
(APAR)
is
“unstressed”
canopy
conductance
and
g
(
e),
g
(T
aero
),
g
(
)
are
functions
with
ranges
(0, 1) describing the
fraction
of
stomatal
closure by
vapor pressure
deficit, leaf
temperature,
and
leaf
water
potential.
•
The
most
accurate
method
to
estimate
turbulent
fluxes
is the
“
Eddy
Correlation Method
“
to
be
explained
in
what
follows:
What
is
Flux
Flux
–
how much
of
something
moves through
a
unit
area
per
unit
time
Flux is dependent
on:
(1) number
of
things
crossing
the
area;
(2)
size
of
the
area
being
crossed,
and
(3)
the time it
takes
to
cross
this
area
Flux
Measurements
•
Flux
measurements
are
widely used
to
estimate
heat,
water,
and
CO
2
exchange,
as
well
as
methane
and
other
trace
gases
•
Eddy
Covariance
is
one of
the
most
direct
and
defensible
ways
to
measure
such
fluxes
•
The method is
mathematically complex,
and
requires
a
lot
of
care setting
up
and
processing
data
.
“
A
Brief
Practical
Guide
to
Eddy
Covariance Flux
Measurements: Principles and
Workflow
Examples
for
Scientific and
Industrial
Applications”
G.
Burba and
D.
Anderson
of
LI-COR
Biosciences
To
help a non-expert gain a basic understanding
of
the Eddy
Covariance method
and to point
out
valuable
references
To
provide
explanations in a
simplified
manner
first,
and then elaborate with specific
details
Introduction
The
Eddy
Covariance
method is
one of
the
most
accurate,
direct
and
defensible
approaches
available
to
date
for
measurements
of
gas
fluxes
and
monitoring
of
gas
emissions
from
areas
with
sizes
ranging
from
a
few
hundred
to
millions
of
square
meters
•
The method
relies
on
direct
and
very
fast
measurements
of
actual
gas
transport by
a 3-D
wind
speed in
real
time
in situ
,
resulting
in
calculations
of
turbulent
fluxes
within the atmospheric
boundary
layer
•
Modern
instruments
and
software
make
this
method
easily
available
and
potentially
widely-used
in
studies
beyond
micrometeorology,
such
as in
ecology,
hydrology,
environmental
and
industrial
monitoring,
etc.
•
Main
challenge of the
method
for
a
non-
expert
is
the shear
complexity
of
system
design,
implementation
and
processing
the
large
volume
of
data
•
The
Eddy
Covariance
method
provides
measurements
of
gas
emission
and
also
allows measurements
of
fluxes
of
sensible
heat,
latent
heat
and
momentum
,
integrated
over
an
area.
•
This method
was
widely used in
micrometeorology
for
over
30
years,
but
now,
with
firmer
methodology
and
more
advanced
instrumentation,
it
can
be
available
to
any
discipline, including science,
industry,
environmental
monitoring
and
inventory.
Several networks
have
been
established over
the globe
to
measure turbulent
fluxes
Existing
Flux
Networks:
Fluxnet, Fluxnet-Canada, AsiaFlux,
CarboEurope
and
AmeriFlux
networks
They
collect
Eddy
Covariance
information.
http://gcmd.nasa.gov/records/GCMD_AMERIFLU
X_SHIDLER-CDIAC.html
http://terraweb.forestry.oregonstate.edu/chair2.
htm
•
There
i
s
current
l
y
no
un
i
fom
[
i
no
l
ogy
or
a
s
i
ng
l
e
methodo
l
ogy
for
E
C
method
•
A
l
ot
of
effort
i
s
b
e
i
ng
p
l
aced
b
y
ne
t
wor
k
s
(e.g.,F
l
uxnet)
to
un
i
fy
var
i
ous
approaches
•
Here
we
present one
of
the
conventiona
l
ways
of
imp
l
ement
i
ng
the
Eddy
Covariance
method
WI
D
•
Ai
r
flow
can
be
imagined
as
a
hori
z
on
t
a
l
flow
of
numerous
rotat
i
ng
edd
i
es
•
Each
eddy
has
3-D
components,including
a
vert
i
cal
w
i
nd
component
•
The
d
i
agram
looks
chaotic
but
componentscan
be
measured
from
tower
t
i
m
e:i.
e
d
d
y:i.
t
i
m
e
2
eddy
2
GJ
2
W
2
t
air
,_
[;J
l
W
GJ
GJ
At
a
single
point
on
the
tower
:
Eddy
1
moves
parcel
of
air
c
down
with
the
speed
w
1
1
then
Ed
dy
2
moves
parcel
c
2
up
with
the
speed
w
2
Each
pa
ce
l
has
concentrat
i
on
,
temperature,
hum
i
dity;
i
f
we
know
these
and
the
speed
-we
know
the
flux
The
general
principle:
If
we
k
now
how
many
mo
l
ecu
l
es
went
up
with
eddies
at
t
i
me
1,
and
how
many
molecu
l
es
went
down
w
i
t
h
edd
i
es
at
t
i
me
2
at
the
same
po
i
nt
-
we
can
ca
l
cu
l
ate
vert
i
ca
l
flux
at
that
po
i
nt
and
over
that
time
pe
ri
od
Essenceof
method
:
V
er
t
i
c
a
l
f
l
ux
c
an
be
represented
as
a
c
o
va
ria
n
c
e
o
f
t
he
ver
t
i
c
a
l
ve
l
ocity
and
concentrat
i
on
of
the
ent
i
ty
of
i
nterest
In
tur
b
u
l
en
t
fl
ow,
vert
i
ca
l
fl
ux
can
b
e
presented
as
:
(s
-
p/p
a
i
s
the
m
i
x
i
ng
rat
i
o
of
substance
'c
i
n
a
i
r
)
F
=
Jlili
S
l
F
=
(pa
+
p
'
Q)
(
,..
,
+
l
t
·
'
'
)(
s
+
s
'
)
R
eyn
o
l
ds
de
c
omposit
i
on
i
s
used
then
to
br
e
a
k
i
n
t
o
m
e
an
s
a
nd
dev
i
a
t
io
n
s:
"
Ope
n
i
n
g
the
p
a
r
e
n
these
s
:
-
-
-
-
-
F
=
(
pa1
1.1
s
+
pa
'
pa
1
·
pa
1v
'
s
'+
p
a
l
p
'
a
1
1
'
+
p
'
a
1
i
"
s
+
p
'
a
1
1
-
1
)
1
Averoged
deviation
from
the
avemge
is
zem
-
-
-
-
-
-
Equa
ti
on
i
s
s
i
mp
l
ified:
F
=
(pa
l
i
1
s
+
pa
,
i
,
'
s
'
+
1
1
-
p
'
a.S
'
+
s
p
'
a
11
1
+
pi
'
,
i
,'
s
')
Now
an
im
po
rtan
t
assum
p
t
i
on
is
made
(for
c
onventiona
l
Eddy
Covaria
n
ce)-
Le.
air
density
f
l
uctua
t
i
ons
areassumed
neglig
i
ble:
!
-
-
-
-
-
-
Then
a
nothe
r
im
p
o
rta
n
t
ass
u
m
p
t
i
on
is
m
a
de
-
mean
v
rt
i
c
a
lflow
1
s
assumed
negligib
l
e
f
or
h
o
r
iz
o
n
t
a
l
hom
o
gene
o
us
te
rra
in
(no
d
i
vergence/c
o
nvergence):
'
E
d
d
y
fl
u
x'
G
e
n
e
r
al
e
q
u
a
t
i
o
n
:
I
F
:::::::
P
a
W
I
S
I
I
Se
nsib
l
e
heat
flux:
H
==
p
C
,1
,
'
T
'
a
p
L
ate
n
t
h
e
at
fl
ux:
'l
.
1
\
.
.1
.
,
..
/
J
\
f
.
a
-
-
,
,
LE
=
.11,
"
'
p
p
lt.
.
'
e
/J
C
a
1
1
b
o
n
d
i
o
x
i
de
f
l
u
x
:
F
C
l
{p
C
'
NOTE:
Instruments
usua
l
ly
do
no
t
measure
mixing
ratio
s,so
there
i
s
yet
a
no
t
h
e
r
as
s
u
m
p
t
i
o
n
i
n
t
h
e
prac
t
i
c
a
l
f
or
m
u
l
a
s
(s
u
c
h
a
s
:
p,
,
w
'
s
'
=
w
'
'
P
'
c
Measurements
at
a
pointcan
represent
an
upw
i
nd
area
Measurements
are
done
inside
t
he
boundary
l
aye
r
o
f
i
nterest
Fe
t
ch
/f
ootprint
is
adequa
t
e
-fluxes
are
me
a
sure
d
only
at
t
he
a
r
e
a
of
in
t
eres
t
F
l
ux
is
fully
turbu
l
en
t
-most
o
f
the
net
ve
rt
i
cal
tr
ans
f
e
r
i
s
d
one
by
edd
i
es
Te
r
rain
i
s
hor
i
z
ontal
and
un
i
torm:
average
of
flu
ct
ua
t
ions
i
s
z
e
r
o;
a
i
r
de
n
sity
fluctuations
,flow
convergence
&
d
i
ve
r
ge
n
ce
are
negligib
l
e
Inst
r
uments
can
detect
very
small
changes
a
t
very
high
frequency
r
-·
I
Measurements are
no
t
perfect
:
due
t
o
assumpt
i
ons,phys
i
ca
l
phenomena
,
instrument
problems
,
and
spec
ifi
c
i
ties
o
f
terra
i
n
and
se
t
up
There
could
be
a
number
of
fl
ux
e
r
rors
i
ntroduced
if
not
correc
t
ed:
Other
key
error
sources
:
System
t
i
me
response
Sensor
separa
ti
on
S
c
a
r
pa
h
ave
r
-
,
i
n
g
ub
e
l
on
1
1
K
l
lD
R
.,.,...
_
c
r
•
These
errors
are
not
trivia
l
-
they
may
combine
to
over
10o%
of
the
flux
•
To
m
i
nim
i
ze
or
avo
i
d
such
errors
a
number
o
f
procedures
cou
l
d
be
performe
d
•
Measures
fluxes
transported
by
edd
i
es
•
Req
u
i
res
t
u
r
b
u
l
e
n
t
f
l
ow
•
Re
q
ui
r
es
state
-
o
f
-
the
-
art
instruments
•
Ca
l
cula
t
ed
as
covar
i
ance
of
w'
and
c'
•
Many
assumptions
t
o
sa
t
i
sfy
•
C
o
m
p
l
ex
ca
l
c
u
l
a
t
i
o
n
s
•
Most
direct
way
to
measure
f
l
ux
•
C
o
n
t
i
n
u
o
us
n
ew
d
ev
e
l
o
p
m
e
nts
TERRESTRIAL
98%
of
applications
Designe
d
for
sta
f
onary
use
Limited
by
precip
i
tat
i
on,
fog,&
dew
<
1
%
of
ap
p
l
i
ca
t
i
ons
May need
c
u
stomized
r
e
i
nforcement
May be
affecte
d
by
extreme
tempe
r
atures
and
vibrations
OCEANOGRAPHIC
<
1
%
o
f
a
p
p
h
cabOns
May
nee
d
custom
i
zed
coating,
LPS3
May
be
affected
by
preci
p
itation,
dew,
&
gyroscopic
e
ff
ects
was
<3
0
W
a
tts,
inclu
d
in
g
Ll-n
o
o
for
C
H
4
•
The
po
w
er
c
o
n
su
mp
tion
by
t
h
e
entir
e
Edd
y
Covar
i
ance
stat
i
on
in
t
h
e
F
l
o
r
i
da
E
ve
r
gl
ad
es
,
Ll-7500
fo
r
C
0:1/
H
2
0,some
anemomet
e
r,and
air
tem
pe
ratu
re
/relative
humidity
sensors
and
barome
t
e
r
•
The
12
lb
.
(5.5
kg)
op
en
pa
t
h
me
t
hane
anatyz
er
was
c
ar
r
i
ed
In
to
the
wet
l
and
b
y
one
perso
n
inthe
backpack,
along
w
i
th
too
l
s,other
se
n
sors,and
a
la
p
top
•
Insuc
h
re
m
ote
pl
aces
occasiona
l
calibrationchecks
ca
n
be
done
us
ing
s
m
all
ha
n
d-earned
gastanks
with
known
CH
4
conce
nt
rat
i
on
and
CH
4
-free
air
•
Remote
sensing the
surface
energy
budget
•
The
First
International
Satellite
Land
Surface
Climatology Project
(ISLSCP) Field
Experiment
(FIFE)
was
an
international,
land-surface-atmosphere
experiment centered
on a 15 x 15 km
test
site
near
Manhattan,
Kansas.
•
The objectives
of
FIFE:
to
better understand
the
role
of
biology in
controlling
the
interactions
between
the
atmosphere
and the
vegetated
land
surface
and
to
investigate
the use
of
satellite
observations
for
inferring
climatologically significant
land
surface
parameters.
Specifically:
•
to
verify
the basic
flux
relationships
for
the
homogeneous
patches;
•
to
assess the
ability
to remotely
sense
parametric
inputs
to
these
relationships;
•
to
examine
how
these
relationships
and
remote
sensing
algorithms scale
from
the
patch level to
heterogeneous
collections
of
patches at
the meso-
scale
level;
•
to determine
how well
existing
calibration,
atmospheric correction,
and
radiometric
rectification
techniques
permit
to
extend
satellite
observations
between
dates
and
sensors
•
to determine to
what degree
existing
and
future
satellite
designs
satisfy
the
requirements
for
periodic
monitoring
of
surface
energy
balance
components
on a
global
scale.
•
Below are
a
few
examples
of the
sources
of
information
on the
various
methods of flux
measurements,
and specifically on
the
Eddy
Covariance
method:
•
Micrometeorology,
2009.
By
T.
Foken.
Springer-Verlag.
•
Handbook of
Micrometeorology:
A
Guide
for
Surface
Flux
Measurement
and
Analysis,
2008.
By
X. Lee;
W.
Massman; B. Law
(Eds.).
Springer-Verlag.
•
Principles of
Environmental Physics,
2007.
By J.
Monteith
and
M.
Unsworth.
Academic
Press.
•
Microclimate:
The Biological
Environment.
1983.
By
N.
Rosenberg,
B. Blad, S.
Verma.
Wiley
Publishers.
•
Baldocchi,
D.D.,
B.B.
Hicks
and
T.P.
Meyers.
1988.
'Measuring
biosphere-
atmosphere
exchanges
of biologically
related
gases
with
micrometeorological
methods',
Ecology,
69,
1331-1340
•
Verma,
S.B.,
1990.
Micrometeorological
methods
for
measuring
surface
fluxes
of mass and
energy.
Remote
Sensing
Reviews,
5:
99-115.
•
Wesely,
M.L.,
D.H.
Lenschow and
O.T.
1989.
Flux measurement techniques. In:
Global
Tropospheric Chemistry,
Chemical
Fluxes
in
the
Global
Atmosphere.
•
NCAR
Report.
Eds.
DH
Lenschow and BB
Hicks.
pp
31-46
Satellites play a crucial role in estimating the Surface Energy Budget (SEB) by providing data on various components such as Surface Radiation Budget and Surface Turbulent Fluxes. The SEB includes factors like net radiation flux, sensible and latent heat fluxes, and subsurface heat transfer. Satellites help in assessing these fluxes and understanding land processes based on factors like surface temperature, vegetation, and radiative flux. Theoretical aspects of satellite remote sensing focus on maintaining thermal equilibrium through a combination of thermodynamic and physiological processes, balancing energy absorbed by the surface with that transferred to the atmosphere and ground.
Download Presentation
Please find below an Image/Link to download the presentation.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
E N D
Presentation Transcript
AOSC624 Class 22: May 1, 2012 AtIssue: How can satellites help to estimate the Surface Energy Budget (SEB) One Component of SEB: Surface Radiation Budget (Review) Other components: Surface Turbulent Fluxes of heat and moisture Heat into ground How do we evaluate the turbulent fluxes? Overview of Eddy Covariance Principles
Radiation Balance at the Earth Surface The net flux of radiation at the earth s surface results from a balance between the solar and terrestrial radiation fluxes: Fsfcrad = FSW +FLW The short-wave and long-wave radiation balance can beexpressed: FSW = FSW - FSW FLW = FLW -FLW The net radiation balance being: Fsfcrad = FSW - FSW + FLW - FLW
The incident solar radiation FSW is the sum of the direct and diffuse solar radiation. It has a pronounced diurnal and seasonal variation, and is also strongly affected by clouds. The outgoing short-wave solar radiation is the part reflected by the surface FSW =AsfcFSW , where Asfc is the surface albedo so that the net short-wave radiation is: FSW= (1 Asfc)FSW The outgoing long-wave radiation FLW is given by the Stefan-Boltzmann law, assuming a given emissivity for the earth s surface. The net radiation flux at the surface is then given by: Fsfcrad = FSW (1 Asfc) T4sfc+ FLW
Energy Balance at the Earth Surface The main part of the energy absorbed at the surface is used to evaporate water, another part is lost to the atmosphere as sensible heat, and a smaller part is lost to the underlying layers or used to melt snow and ice. Thus, there are essentially four types of energy fluxes at the earth s surface. They are the net radiation flux Frad, the (direct) sensible heat flux FSH , the (indirect) latent heat flux FLH , and the heat flux into the subsurface layers FG . Under steady conditions the balance equation for the energy is given by Fsfcrad - FSH - FLH - FG - FM =0
These surface fluxes are associated with land processes and depend on: vertical stability; roughness surface temperature subsurface heat conduction vegetation surface hydrological balance potential evapotranspiration radiative flux
Theoretical aspects of satellite remote sensing of energy balance Thermal equilibrium at the surface is maintained by a combination of thermodynamic and physiological processes. The net energy absorbed by the surface through radiative processes, net radiation Rn, must be balanced by that transported to the atmosphere and ground (sensible, latent, and ground heat flux): Rn = H + LE + G. (1) Rn is simply the difference between the incident and reflected shortwave radiation and the incident and emitted long wave radiation at the surface, thatis: Rn = S{1 - } + Lwd -Lwu, (2) where S is downwelling shortwave radiation energy flux (Wm-2).
Surface energy balance formulae For the sensible and latent heat components in eq. 1, closed-form solutions cannot be obtained. Commonlyused semi-empirical relationsare: For Sensible heat: H = Cp (Taero -Ta)/ra (3) sensible heat flux, W m-2; density of air, kgm-3; specific heat of air, J kg-1 oC-1; reference height air temperature,oC; Taerocanopy temperature,oC; ra aerodynamic resistance for heat and water vapor, s m-1. where H Cp Ta
In this formulation the aerodynamic resistance, ra, relates the vertical gradient in temperature, Taero - Ta, to the sensible heat flux. The ra value is semi-empirical and is intended to characterize the efficiency of the very complex transfer of heat by turbulent air movement through the canopy into the air above; ra is normally derived using empirical arguments to adjust the surface momentum transfer coefficient, a term that relates the vertical gradient in boundary layer wind speed to surface shear stress. A number of such empirical formulations are available for ra ( see Hall et al,. 1991), suchas:
ln(z 0.56h)ln[(z 0.56h) / (0.0189h)] ra =0.16U {1 + [5g(z 0.56h)(T , T ) / T U2 ]}3/4 a a aero where U is windspeed, m s-1; z is reference height for measurement of Ta and U ; h is height of canopy (m); and g is gravitational acceleration, m s-2. For more details and additional formulation for Aerodynamic Resistance see the provided paper: Measurement and estimation of the aerodynamic resistance S. Liu, D. Mao, and L. Lu
For latent heat: LE = Cp[e*(Taero)- ea)](gcga)/ (gc +ga), (5) where e*(Taero) mbar; ga s-1. These first-order solutions to the turbulent transport equations served as the primary model for investigating relationship between the properties of land surface vegetation, energy- mass balance, and remote sensing of these interactions in FIFE. ea vapor pressure at reference height, mbar; air temperature at reference height,ok; saturated vapor pressure in the canopy air space, Ta psychometric constant, mbar ok-1; as defined in (2); bulk stomatal conductance of canopy, m s-1; bulk aerodynamic conductance of canopy (1/ ra), m Cp gc
Sensibleheat For H in (3), remote sensing measures of surface radiometric temperature have been evaluated as a surrogate forTaero. However, Taerois not explicitly Tradbut, as discussed above, a theoretical construct that parameterizes a convective temperature. Vining and Blad (1991) investigated the relationship between Taeroand Trad.
Latentheat For latent heat estimation (eq. 5) the main focus of remote sensing techniques is the conductance term gc and the Taero term in estimating canopy air-space vaporpressure. The canopy conductance term gc canbe modeled after Jarvis (1976) as a product of functions with range (0, 1) where each function characterizes the dependence of gc on APAR (absorbed PAR), e, T, and leaf water potential .
Thatis: g = g (APAR)g( e)g(T c c aero)g( ) * (6) where g*(APAR) is unstressed canopy conductance and g ( e), g (Taero), g ( ) are functions with ranges (0, 1) describing the fraction of stomatal closure by vapor pressure deficit, leaf temperature, and leaf water potential. The most accurate method to estimate turbulent fluxes is the Eddy Correlation Method to be explained in what follows: c
What is Flux Flux how much of something moves through a unit area per unit time Flux is dependent on: (1) number of things crossing the area; (2) size of the area being crossed, and (3) the time it takes to cross this area
Flux Measurements Flux measurements are widely used to estimate heat, water, and CO2 exchange, as well as methane and other tracegases Eddy Covariance is one of the most direct and defensible ways to measure such fluxes The method is mathematically complex, and requires a lot of care setting up and processing data.
A Brief Practical Guide to Eddy Covariance Flux Measurements: Principles and Workflow Examples for Scientific and Industrial Applications G. Burba and D. Anderson of LI-COR Biosciences To help a non-expert gain a basic understandingof the Eddy Covariance method and to point out valuablereferences To provide explanations in a simplified manner first, and then elaborate with specificdetails
Introduction The Eddy Covariance method is one of the most accurate, direct and defensible approaches available to date for measurements of gas fluxes and monitoring of gas emissions from areas with sizes ranging from a few hundred to millions of square meters The method relies on direct and very fast measurements of actual gas transport by a 3-D wind speed in real time in situ, resulting in calculations of turbulent fluxes within the atmospheric boundary layer
Modern instruments and software makethis method easily available and potentially widely-used in studies beyond micrometeorology, such as in ecology, hydrology, environmental and industrial monitoring,etc. Main challenge of the method for a non- expert is the shear complexity of system design, implementation and processing the large volume of data
The Eddy Covariance method provides measurements of gas emission and also allows measurements of fluxes of sensible heat, latent heat and momentum, integrated over an area. This method was widely used in micrometeorology for over 30 years, but now, with firmer methodology and moreadvanced instrumentation, it can be available to any discipline, including science, industry, environmental monitoring and inventory.
Several networks have been established over the globe to measure turbulent fluxes Existing Flux Networks: Fluxnet, Fluxnet-Canada, AsiaFlux, CarboEurope and AmeriFlux networks They collect Eddy Covariance information. http://gcmd.nasa.gov/records/GCMD_AMERIFLU X_SHIDLER-CDIAC.html http://terraweb.forestry.oregonstate.edu/chair2. htm
Thereiscurrently nounifom[ or asingle methodology for EC method inology Alot of effort is being placed by networks (e.g.,Fluxnet) to unify various approaches Here we present one of the conventional ways of implementing the Eddy Covariance method
WI D Airflow canbe imaginedasahorizontalflow of numerous rotating eddies Eacheddy has3-Dcomponents,includingaverticalwindcomponent Thediagramlookschaotic but componentscanbemeasuredfromtower
time:i. eddy:i. time2 eddy2 [;J l G J G J W2 t G J air ,_ W 2 At asinglepointon the tower: Eddy 1moves parcel of air c down with thespeed w then Ed dy 2 moves parcel c2 up with the speed w2 1 1 Each pa cel has concentration,temperature, humidity; if we knowthese and the speed -we knowthe flux
Thegeneralprinciple: If we know how many molecules went up with eddies at time 1, and how many molecules went down with eddies at time 2 at the same point - we can calculate verticalflux at that point and over that time period Essenceofmethod: V ertical flux can be represented as a covariance of t he vertical velocityand concentrationofthe entityof interest
In turbulent flow, vertical flux can bepresented as: (s-p/paisthemixingratioofsubstance'cin air) F = JliliS lF=(pa +p'Q)(,..,+lt '')(s+s') Reynoldsdecomposition isused then to break into means and deviations: " Opening the parentheses: - - - F =(pa11.1s+pa - - ' pa1 pa 1v's'+p al p'a11 '+p'a1i"s + p'a11-1 ) 1 Averoged deviationfrom theavemge iszem - - - - - - Equationissimplified: F =(pali1s+pa,i,'s'+11-p'a.S' + sp'a111+ pi ',i,'s')
Nowanimportantassumptionismade(forconventionalEddy Covariance)- Le. airdensityfluctuationsareassumednegligible: ! - - - - - - Thenanother important assumptionismade- meanv rticalflow 1 s assumed negligible for horizontalhomogeneous terrain (no divergence/convergence): 'Eddy flux'
Generalequation: IF : : : : : : :Pa W ISII H = =p C ,1,'T' a Sensible heatflux: p 'l .1 \ ..1. ,../ J \f. a "'p - - , , p lt..'e /J LE = .11, Latentheatflux: Ca1 1 bondioxideflux: F l { p C ' C NOTE:Instrumentsusuallydonotmeasuremixingratios,sothereisyet p,,w's'=w''P'c anotherassumptioninthepracticalformulas(suchas:
Measurementsatapointcanrepresentanupwindarea Measurementsaredoneinsidethe boundary layerof interest Fetch/footprint is adequate-fluxes are measured only at the area of interest Flux isfullyturbulent -most of the netverticaltransfer is done byeddies Terrainis horizontaland unitorm: averageof fluctuations iszero; airdensityfluctuations,flow convergence & divergence arenegligible Instrumentscandetect verysmall changes at very highfrequency r - I
Measurements are not perfect:due to assumptions,physical phenomena,instrument problems,andspecificitiesofterrainandsetup There could be a number of flux errors introduced if not corrected: Other key errorsources: Systemtime response Sensorseparation Sc arpa haver- ,ing ube 11KllDR .,.,..._ c r lon
Theseerrorsarenottrivial-they maycombinetoover10o%ofthe flux Tominimizeoravoidsucherrorsanumberofprocedurescouldbeperformed Affected fluxes Approximate Range Errorsdue to Frequencyresponse all 5-30% all T mederay 5-15% all Spikes,nose 0-15% Unleveledmstrument/flow all 0-25% H20,co>'CH.. sensibleheat Densityfluctuatton 0-50% Sonic heaterror 0..10% BandBroadeningfor NDtR mostlyC03 0..5% 0 3o96 Spectroscop..:effect forLASER anygas someH30 0 1096 Oxygen ln thepath all O Messing data fillIng
Errors Remedy frequency respo secorrections Fruency respose Time lay adjust g for delay Spikes,noise spikeremoval coord ate rotatio Unleveled inst1ument/ ow Densityfluctuation Webb..Pearman Leun ng correction Son c heaterror sonctemperature correction Ba d Broaden g forNDIR nd..broadeningcorrectton SpKtroscopic effect forLASER no uniform W1dely usedcorrecnon Oxyge int e path oxygencorrect on Miss g datafill ng Methodology/tests: Monte-Carloetc-
Measuresfluxestransported byeddies Requiresturbulent flow Requiresstate-of-the-artinstruments Calculated ascovariance of w' and c' Many assumptions to satisfy Complex calculations Most direct wayto measureflux Continuousnewdevelopments
TERRESTRIAL OCEANOGRAPHIC <1%of apphcabOns 98%of applications <1%ofapplications May needcustomized Designed forstafonary use May needcustomized reinforcement coating,LPS3 Limited byprecipitation, fog,&dew May be affected by extreme temperaturesand vibrations May be affected by precipitation,dew,& gyroscopiceffects
The power consumption bythe entire EddyCovariance station inthe Florida Everglades ,Ll-7500for C0:1/H20,some anemometer,and was<30Watts,includingLl-nooforCH4 airtemperature/relative humidity sensorsand barometer The 1 2 lb.(5.5kg)open pathmethaneanatyzerwas carried Intothewetland by onepersoninthe backpack,alongwithtools,othersensors,andalaptop Insuch remoteplacesoccasionalcalibrationcheckscanbedoneusingsmall hand-earned gastankswithknownCH4concentration andCH4-freeair
Remote sensing the surface energy budget The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) was an international, land-surface-atmosphere experiment centered on a 15 x 15 km test site near Manhattan,Kansas. The objectives ofFIFE: to better understand the role of biology in controlling the interactions between the atmosphere and the vegetated land surface and to investigate the use of satellite observations for inferring climatologically significant land surface parameters. Specifically:
to verify the basic flux relationships for the homogeneous patches; to assess the ability to remotely sense parametric inputs to theserelationships; to examine how these relationships and remote sensing algorithms scale from the patch level to heterogeneous collections of patches at the meso- scalelevel; to determine how well existing calibration, atmospheric correction, and radiometric rectification techniques permit to extend satellite observations between dates andsensors to determine to what degree existing and future satellite designs satisfy the requirements for periodic monitoring of surface energy balance components on a globalscale.
Below are a few examples of the sources of information on the various methods of flux measurements, and specifically on the Eddy Covariance method: Micrometeorology, 2009. By T. Foken. Springer-Verlag. Handbook of Micrometeorology: A Guide for Surface Flux Measurement and Analysis, 2008. By X. Lee; W. Massman; B. Law (Eds.). Springer-Verlag. Principles of Environmental Physics, 2007. By J. Monteith and M. Unsworth. AcademicPress. Microclimate: The Biological Environment. 1983. By N. Rosenberg, B. Blad, S. Verma. WileyPublishers. Baldocchi, D.D., B.B. Hicks and T.P. Meyers. 1988. 'Measuring biosphere- atmosphere exchanges of biologically related gases with micrometeorological methods', Ecology, 69, 1331-1340 Verma, S.B., 1990. Micrometeorological methods for measuring surface fluxes of mass and energy. Remote Sensing Reviews, 5: 99-115. Wesely, M.L., D.H. Lenschow and O.T. 1989. Flux measurement techniques. In: Global Tropospheric Chemistry, Chemical Fluxes in the Global Atmosphere. NCAR Report. Eds. DH Lenschow and BB Hicks. pp 31-46
