Download Modeling Land and atmosphere interactions - Asian G-WADI

Modeling Land and atmosphere interactions
Yongkang Xue
Dept. Geography and
Dept. Atmospheric &Oceanic Sciences
University of California, Los Angeles, USA
The 2nd Summer School on Land Surface Observing, Modeling
and Data Assimilation, 13-16 July 2010
Beijing Normal University, Beijing, China
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AEROSOL
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More variable than ocean for coupling processes:
(1) Moisture variability.
(2) Low heat capacity leads to high diurnal and seasonal
variations; more response to net radiation.
(3) Absorbed solar radiation varies with surface albedo.
(4) Heterogeneity.
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Shortcomings of the early modeling approaches:
(1) Independent specification of surface attributes;
(2) Unrealistic specification of surface albedo;
(3) Unrealistic specification of roughness length, confusion of
momentum and heat/vapor transfer pathways;
(4) Unrealistic specification of soil hydrology;
(5) Unrealistic description of the evapotranspiration processes
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Motivation for better land surface modeling
1) Considerable advances in the 1970s – 1990s in
understanding of land surface processes in the presence of
vegetation
2) GCM studies show considerable sensitivity of model
simulations to drastic changes in the formulation of land
evaporation
3) More land data available from remote sensing and field
measurements
4) Environmental concerns about the consequences of land
cover changes and global warming.
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Land surface process studies:
1.Development, validation, and calibration of land surface
processes parameterization
2.land data development and application
3. land surface atmosphere interactions studies
(1). Land/atmosphere coupling
(2). Sensitivity studies (including land use & land cover
changes)
(3). Prediction studies
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Land surface process studies:
1.Development, validation, and calibration of land surface
processes parameterization
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The Climatic System
Biophysical feedback
Temperature, humidity, precipitation,
and atmospheric circulation
Radiation balance
Momentum transfer
Heat transfer
Water cycle (Snow,
Frozen soil)
Distribution
Structure
Terrestrial ecosystems
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Schematic Diagram of Simplified Simple Biosphere Model
(SSiB)
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ECOPHYSIOLOGY
LINKING THE RATE OF
CARBON DIOXIDE
AND WATER EXCHANGE
EvapoTranspiration α gc
gc = Ahs/cs
ET=PLANT-WATER EXCHANGE
A
=
PAR UPTAKE = FAPARxPAR
hs = SURFACE RELATIVE HUMIDITY
cs = SURFACE CO2 CONCENTRATION
C12H4O6
PAR = PHOTOSYNTHETICALLY
ACTIVE RADIATION
Piers J. Sellers, Mark D. Heiser and Forrest G. Hall, “Relations Between Surface
Conductance and Spectral Vegetation Indices at Intermediate (100m2 -15km2)
Length Scales”, Journal of Geophysical Research, 97:-D17,19,033-19,061.
10µm
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The Climatic System
Biophysical feedback
Temperature, humidity, precipitation,
and atmospheric circulation
Greenhouse gases (CO2)
Radiation balance
Momentum transfer
Photosynthesis
Respiration
Heat transfer
Water cycle
Distribution
Structure
Terrestrial ecosystems
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Schematic diagram of SSiB
evaporation
Sensible
heat flux
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Carbon flux
The Climatic System
Greenhouse gases (CO2,
CH4, N2O) and aerosols
Radiation balance
Nutrient cycles
Momentum transfer
Biomass burning
Heat transfer
Photosynthesis
Respiration
Decomposition
Water cycle
Distribution
Composition
Terrestrial ecosystems
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Structure
Biogeochemical feedback
Biophysical feedback
Temperature, humidity, precipitation,
and atmospheric circulation
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OFF-Line tests
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Land surface process studies:
1.Development, validation, and calibration of land surface
processes parameterization
2.land data development and application
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Initial Conditions for Simplified Simple Biosphere Model version 1
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13 land cover types
1
2
3
4
5
6
7
8
9
10
11
12
13
tropical rainforest
broadleaf deciduous trees
broadleaf and needleaf trees
needleaf evergreen trees
needleaf deciduous trees
broadleaf trees with ground cover
groundcover only
broadleaf shrubs with ground cover
broadleaf shrubs with bare soil
dwaft trees with ground cover
bare soil
crops
land ice
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SURFACE PARAMETERS
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
LEAF TRANSMITTANCE
LEAF REFLECTANCE
SOIL REFLECTANCE
LEAF ANGLE DISTRIBUTION FACTOR
OPTIMUM TEMPERATURE FOR STOMATAL FUNCTIONING
LOWER TEMPERATURE LIMIT FOR STOMATAL FUNCTIONING
UPPER TEMPERATURE LIMIT FOR STOMATAL FUNCTIONING
VAPOR PRESSURE DEFICIT PARAMETER
WILTING POINT
SOIL MOISTURE “SLOP” PARAMETER
ROOTING DEPTH
SOIL WETNESS EXPONENT
SOIL TENSION AT SATURATION
HYDRAULIC CONDUCTIVITY AT SATURATION
SOIL POROSITY
DEPTH OF 3 SOIL MOISTURE LAYERS
ROUGHNESS LENGTH
ZERO PLANE DISPLACEMENT
LEAF AREA INDEX (LAI)
GREEN LEAF FRACTION
VEGETATION COVER FRACTION
VMAX MAXIMUM RUBISCO CAPACITY
C REFERENCE HEIGHT FOR WIND, HYMIDITY, & TEMPERATURE
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Simplified Simple Biosphere Model (SSiB) output variables
Canopy temperature
Soil surface temperature
Deep soil temperature
Surface albedo (visible, NIR, diffuse, direct)
Surface skin temperature
Water interception by canopy
Soil moisture at three layers
Snow water equivalent at canopy and on ground (up to three
layers)
Snow temperature (up to three layers)
Latent heat flux: interception loss, transpiration, evaporation
from soil
Sensible heat flux
Ground heat flux
Momentum flux
Carbon flux and net photosynthesis rate
Surface runoff and drainage
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Coordinated Enhanced Observing Period
Three Unique Capabilities
A Prototype of the Global
Water Cycle Observation
System of Systems
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RSLAI (summer)
FASIR
GIMMS
Kang et al., 2007
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Land surface process studies:
1.Development, validation, and calibration of land surface
processes parameterization
2.land data development and application
3. land surface atmosphere interactions studies
(1). Land/atmosphere coupling
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Radiation transfer
Net Radiation = (1-α) SW↓ +(LW↓-εσTs4)
1). Surface Albedo (for diffuse and direct
radiation at different wavelength with
diurnal variation)
2). Upward long wave radiation
(1)LWt+1↑= εσ(Tts)4 +4εσ(Tts)3(Tt+1s – Tts)
(2) LWt+1↑= εσ(Tts + (∆Tst+1))4
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In a surface layer with constant momentum flux, where U* is the friction velocity.
k is the von Karman constant, 0.35-0.4. Z0 is the roughness length. Z0 is the
intercept of the line with the vertical axis scale (the height above the surface at
which the wind speed would go to zero if the turbulence layer extended
completely to the ground), d is the zero plane displacement height. It is a datum
level and is determined experimentally.

U*  z − d
−
1
−
1
U=
− ψ 1 = U (C U0 + C un )
 Ln
*
k 
z0

ρ U (U − 0) ρ (U − 0)
*
τ = ρU
=
=
*
−1
ra
C −1 + Cun
u0
2
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(Tsfc − Tref )
H = ρair C P
ra
−
1
−
1
C u0 + C un (Ri)
ra =
U
*
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−
1
−
1
C u0 + C un (Ri)
ra =
U
*
k
C =
u0
z−d
Ln( z 0 )
0
 0.315Ri,− 10 < Ri < 0
−
1
C un = 
 66.86,0 < Ri < 0.16
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How to couple with PBL
∂Θ / ∂t = ∂τθ / ∂z
∂ Tc
= R nc − H C − λ E c
∂t
C gs
∂ Tgs
∂t
= Rngs − H gs − λE gs − G s
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(T jsfc − T i lowest PBLlayer )
H = ρair C P
ra
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t =t
t +1
Hc = Hc
+
t =t
∂ ( H c c ) t =t
∂q s
t =t
∂Hc
∂Hc
t +1
t
t +1
t
(Tc −Tc ) +
(Tgs −Tgs)
+
∂Tgs
∂Tc
( q st +1
t =t
∂
(
H
)
c
− q st ) +
(θ
∂θ
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t +1
−θ t)
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Land surface process studies:
1.Development, validation, and calibration of land surface
processes parameterization
2.land data development and application
3. land surface atmosphere interactions studies
(1). Land/atmosphere coupling
(2). Sensitivity studies (including land use & land cover
changes).
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A. Different mechanisms
Mechanisms I
Albedo, Soil Moisture, Surface
Roughness effect
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Net Radiation = SW ↓− albedo×SW ↓ +LW ↓ −εTs
Net Radiation = LH + SH + GH
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4
Albedo feedback
Net Radiation = SW ↓− albedo× SW ↑ +LW ↓ −εTs
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4
Soil Moisture feedback
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Surface roughness feedback
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Mechanisms II
Land surface induced low
atmospheric heating and moisture
flux convergence change
(Xue, 1996; Xue et al., 2004)
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Type 7: grasslands
Type 11: bare ground
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Mechanisms III
Changes in geostrophic balance
Xue et al., 2004 (JGR)
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*Surface Scheme
– 2 Layer soil model with monthly mean
vegetation albedo and surface roughness
– SSiB
– Two scheme use the same initial soil moisture
and surface albedo
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Mechanisms IV
Changes in moisture static energy
Xue et al., 2006 (J. Climate)
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B. Assess the effects of land/atmosphere
interaction in global climate system
Xue et. al., 2010
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(2008).
Based on NDVI
How to make assessment based on models?
.
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Global and Regional Atmospheric Conditions
Specified albedo,
soil wetness
UCLA land scheme
No interactions
Specified Bare ground
vegetation hydrology
albedo & Z0
NCEP GCM soil model
Partial interactions
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Vegetation & Soil
dynamics
SSiB
VBP/Climate
interactions
The choice of land models is crucial. Those models
should incorporate physical principles in representing
specific land surface processes and have been tested
extensively and evaluated in AGCMs with reasonable
results that this type of land processes can achieve.
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Method: Two AGCM (UCLA AGCM and NCEP AGCM) coupled
with three land surface schemes :
1). No Interaction model: The UCLA GCM Land Scheme:
Prescribing monthly-mean land surface characteristics such as
surface albedo, roughness, and ground wetness, but without any
interactions with the atmosphere.
2). Partial Interaction model: The NCEP Two Layer Soil model
(SOIL): simulated ground soil moisture exchange, using
prescribed monthly mean distribution of vegetation albedo and
surface roughness.
3). The VBP model: Simplified Simple Biosphere Model (SSiB)
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Criteria
Should VBP is important in a real climate system
and the VBP model properly presents the VBP
process, the simulations should be improved. VBP
effect is identified by the statistically significant
reduction of bias and RMSE.
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UCLA GCM with two
surface schemes (processes)
– LA-NOVBP: Specified monthly mean soil moisture
with monthly mean vegetation albedo (in the original
UCLA GCM)
– LA-VBP: SSiB: radiative transfer at canopy,
transpiration, interception loss, vegetation-modified
surface resistance, vegetation and soil property based
on vegetation types, etc.
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Observed and the simulated JJA precipitation (mm day-1)
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Observed and simulated JJA precipitation (mm day-1)
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Differences of absolute bias of annual mean precipitation
(mm day-1) between LA-VBP and LA-VBP
-2.5
Monsoon regions
Midlatitude Regs. H L
-2.0
EA
-1.5
TP
-1.0
-1
-0.5
-0.5
0.0
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HL: High latitudes
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US
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(2008, JGL).
Based on
NDVI
assessment based on models
For the Partial VBP effects (excluding soil moisture and
vegetation albedo), our study shows that its effect on
annual precipitation over land were about 13% (Xue et
al., 2010)
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Land surface process studies:
1.Development, validation, and calibration of land surface
processes parameterization
2.land data development and application
3. land surface atmosphere interactions studies
(1). Land/atmosphere coupling
(2). Sensitivity studies (including land use & land cover
changes)
(3). Prediction studies
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