Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)
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Transcript of Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)
![Page 1: Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)](https://reader036.fdocuments.us/reader036/viewer/2022062404/55178ac55503460e6e8b5774/html5/thumbnails/1.jpg)
Land surface in climate models
Parameterization of surface fluxes
Parameterization of surface fluxes
Bart van den Hurk(KNMI/IMAU)
![Page 2: Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)](https://reader036.fdocuments.us/reader036/viewer/2022062404/55178ac55503460e6e8b5774/html5/thumbnails/2.jpg)
Land surface in climate models
Orders of magnitudeOrders of magnitude
• Estimate the energy balance of a given surface type– What surface?– What time averaging? Peak during day?
Seasonal/annual mean?– How much net radiation?– What is the Bowen ratio (H/LE)?– How much soil heat storage?– Is this the complete energy balance?
• The same for the water balance– How much precipitation?– How much evaporation?– How much runoff?– How deep is the annual cycle of soil storage?– And the snow reservoir?
![Page 3: Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)](https://reader036.fdocuments.us/reader036/viewer/2022062404/55178ac55503460e6e8b5774/html5/thumbnails/3.jpg)
Land surface in climate models
General form of land surface schemes
General form of land surface schemes
• Energy balance equation
K(1 – a) + L – L + E + H = G
• Water balance equation
W/t = P – E – Rs – D
Q*H E
G
P E
Infiltration
Rs
D
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Land surface in climate models
Structure of a land-surface scheme (LSS or SVAT)
Structure of a land-surface scheme (LSS or SVAT)
• 6 fractions (“tiles”)• Aerodynamic coupling• Vegetatie
– Verdampingsweerstand– Wortelzone– Neerslaginterceptie
• Kale grond• Sneeuw
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Land surface in climate models
Structure of a land-surface scheme (LSS or SVAT)
Structure of a land-surface scheme (LSS or SVAT)
• 6 fractions (“tiles”)• Aerodynamic coupling
– Wind speed– Roughness– Atmospheric stability
• Vegetatie– Verdampingsweerstand– Wortelzone– Neerslaginterceptie
• Kale grond• Sneeuw
![Page 6: Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)](https://reader036.fdocuments.us/reader036/viewer/2022062404/55178ac55503460e6e8b5774/html5/thumbnails/6.jpg)
Land surface in climate models
Structure of a land-surface scheme (LSS or SVAT)
Structure of a land-surface scheme (LSS or SVAT)
• 6 fractions (“tiles”)• Aerodynamic coupling
– Wind speed– Roughness– Atmospheric stability
• Vegetation– Canopy resistance– Root zone– Interception
• Kale grond• Sneeuw
![Page 7: Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)](https://reader036.fdocuments.us/reader036/viewer/2022062404/55178ac55503460e6e8b5774/html5/thumbnails/7.jpg)
Land surface in climate models
Structure of a land-surface scheme (LSS or SVAT)
Structure of a land-surface scheme (LSS or SVAT)
• 6 fractions (“tiles”)• Aerodynamic coupling
– Wind speed– Roughness– Atmospheric stability
• Vegetation– Canopy resistance– Root zone– Interception
• Bare ground• Sneeuw
![Page 8: Land surface in climate models Parameterization of surface fluxes Bart van den Hurk (KNMI/IMAU)](https://reader036.fdocuments.us/reader036/viewer/2022062404/55178ac55503460e6e8b5774/html5/thumbnails/8.jpg)
Land surface in climate models
Structure of a land-surface scheme (LSS or SVAT)
Structure of a land-surface scheme (LSS or SVAT)
• 6 fractions (“tiles”)• Aerodynamic coupling
– Wind speed– Roughness– Atmospheric stability
• Vegetation– Canopy resistance– Root zone– Interception
• Bare ground• Snow
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Land surface in climate models
Specification of vegetation typesSpecification of vegetation types
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Land surface in climate models
Vegetation distributionVegetation distribution
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Land surface in climate models
Aerodynamic exchangeAerodynamic exchange
• Turbulent fluxes are parameterized as (for each tile):
• Solution of CH requires iteration:– CH = f(L)– L = f(H)– H = f(CH)
2UC
TqqE
TgzTUCcH
Ma
sksatsaaa
sklaHpa
aHH rUC /1
L = Monin-Obukhov length
s
a Ta+gz
s
a
H
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Land surface in climate models
More on the canopy resistanceMore on the canopy resistance
• Active regulation of evaporation via stomatal aperture
• Two different approaches– Empirical (Jarvis-Stewart)
rc = (rc,min/LAI) f(K) f(D) f(W) f(T)
– (Semi)physiological, by modelling photosynthesis
An = f(W) CO2 / rc
An = f(K, CO2)
CO2 = f(D)
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Land surface in climate models
Jarvis-Stewart functionsJarvis-Stewart functions
• Shortwave radiation:
• Atmospheric humidity deficit (D):f3 = exp(-cD) (c depends on veg.type)
0.00.1
0.20.30.40.5
0.60.70.8
0.91.0
0 200 400 600
Shortwave radiation (W/m2)
f1(R
s)
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Land surface in climate models
Jarvis-Stewart functionsJarvis-Stewart functions
• Soil moisture (W = weighted mean over root profile):
• Standard approach: linear profilef2 = 0 (W < Wpwp)
= (W-Wpwp)/(Wcap-Wpwp) (Wpwp<W<Wcap)
= 1 (W > Wcap)
• Alternative functions (e.g. RACMO2)
Lenderink et al, 2003
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Land surface in climate models
Effective rooting depthEffective rooting depth
• Amount of soil water that can actively be reached by vegetation
• Depends on– root depth (bucket depth)– stress function– typical time series of precip & evaporation
• See EXCEL sheet for demo
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Land surface in climate models
Numerical solutionNumerical solution
• Solution of energy balance equation
• With (all fluxes positive downward)
• Express all components in terms of Tsk (with Tp = Tskt
-1)
GEHQ *
)(
)1(* 4
soilsksk
sksatsaaa
sklaHpa
skTs
TTG
TqqE
TgzTUCcH
TRRaQ
net radiation
sensible heat flux
latent heat flux
soil heat flux
)()()(
)(4 344
pskT
satpsatsksat
pskppsk
TTT
qTqTq
TTTTT
p
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Land surface in climate models
Numerical solutionNumerical solution
• Substitute linear expressions of Tsk into energy balance equation
• Sort all terms with Tsk on lhs of equation
• Find Tsk = f(Tp , Tsoil , CH , forcing, coefficients)
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Land surface in climate models
Carbon exchangeCarbon exchange
• Carbon & water exchange is coupled
• Carbon pathway:– assimilation via photosynthesis– storage in biomass
• above ground leaves• below ground roots• structural biomass (stems)
– decay (leave fall, harvest, food)– respiration for maintenance, energy etc
• autotrophic (by plants)• heterotrophic (decay by other organisms)
CO2
H2O
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Land surface in climate models
The gross vegetation carbon budget
The gross vegetation carbon budget
GPP = Gross Primary Production
NPP = Net Primary Production
AR = Autotrophic Respiration
HR = Heterotrophic Respiration
C = Combustion
GPP120 AR
60HR55NPP
60
C4
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Land surface in climate models
The coupled CO2 – H2O pathway in vegetation models
The coupled CO2 – H2O pathway in vegetation models
• qin = qsat(Ts)
• Traditional (“empirical”) approach:rc = rc,min f(LAI) f(light) f(temp) f(RH) f(soil
m)
ca
airina rr
qqE
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Land surface in climate models
Modelling rc via photosynthesisModelling rc via photosynthesis
• An = f(soil m) CO2 / rc
• Thus: rc back-calculated from
– Empirical soil moisture dependence
– CO2-gradient CO2
• f(qsat – q)
– Net photosynthetic rate An
• An,max
• Photosynthetic active Radiation (PAR)• temperature
• [CO2]
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Land surface in climate models
Parameterization of soil and snow hydrology
Parameterization of soil and snow hydrology
Bart van den Hurk(KNMI/IMAU)
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Land surface in climate models
Soil heat fluxSoil heat flux
• Multi-layer scheme• Solution of diffusion equation
• with C [J/m3K] = volumetric heat capacity T [W/mK] = thermal diffusivity
• with boundary conditions– G [W/m2] at top– zero flux at bottom
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Land surface in climate models
Heat capacity and thermal diffusivity
Heat capacity and thermal diffusivity
• Heat capacity
sCs 2 MJ/m3K, wCw 4.2 MJ/m3K
• Thermal diffusivity depends on soil moisture– dry: ~0.2 W/mK; wet: ~1.5 W/mK
wwsssataaawwwssssoil CCCxCxCxC )1(
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Land surface in climate models
Soil water flowSoil water flow
• Water flows when work is acting on it– gravity: W = mgz– acceleration: W = 0.5 mv2
– pressure gradient: W = m dp/ = mp/• Fluid potential (mechanical energy / unit mass)
= gz + 0.5 v2 + p/p = gz g(z+z) = gh
• h = /g = hydraulic head = energy / unit weight = – elevation head (z) +– velocity head (0.5 v2/g) + – pressure head ( = z = p/g)
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Land surface in climate models
Relation between pressure head and volumetric soil moisture content
Relation between pressure head and volumetric soil moisture content
strong adhesy/capillary forces dewatering from
large to small pores
retention curve
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Land surface in climate models
Parameterization of K and DParameterization of K and D
• 2 ‘schools’– Clapp & Hornberger ea
• single parameter (b)
– Van Genuchten ea• more parameters describing curvature better
• Defined ‘critical’ soil moisture content– wilting point ( @ = -150m or -15 bar)– field capacity ( @ = -1m or -0.1 bar)
• Effect on water balance: see spreadsheet
32
)(
b
satsatKK
bsat
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Land surface in climate models
pF curves and plant stresspF curves and plant stress
• Canopy resistance depends on relative soil moisture content, scaled between wilting point and field capacity
pF curve
0.01
0.1
1
10
100
1000
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
Volumetric soil moisture (m3/ m3)
Pre
ssu
re h
ead
(h
Pa)
txsture 1texture 2texture 3texture 4texture 5texture 6
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Land surface in climate models
Boundary conditionsBoundary conditions
• Top:F [kg/m2s] = T – Esoil – Rs + M
• Bottom (free drainage)F = Rd = wK
• with– T = throughfall (Pl – Eint – Wl/t)– Esoil = bare ground evaporation– Eint = evaporation from interception reservoir– Rs = surface runoff– Rd = deep runoff (drainage)– M = snow melt– Pl = liquid precipitation– Wl = interception reservoir depth– S = root extraction
Sz
FFS
z
F
t wbottop
ww
Pl
TEint
Wl
MEsoilRs
Rd
S
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Land surface in climate models
Parameterization of runoffParameterization of runoff
• Simple approach– Infiltration excess runoff
Rs = max(0, T – Imax), Imax = K()
– Difficult to generate surface runoff with large grid boxes
• Explicit treatment of surface runoff– ‘Arno’ scheme
Infiltration curve(dep on W andorograpy)
Surface runoff
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Land surface in climate models
Snow parameterizationSnow parameterization
• Effects of snow– energy reflector– water reservoir acting as buffer– thermal insolator
• Parameterization of albedo– open vegetation/bare ground
• fresh snow: albedo reset to amax (0.85)
• non-melting conditions: linear decrease (0.008 day-1)
• melting conditions: exponential decay
– (amin = 0.5, f = 0.24)
– For tall vegetation: snow is under canopy• gridbox mean albedo = fixed at 0.2
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Land surface in climate models
Parameterization of snow waterParameterization of snow water
• Simple approach– single reservoir– with
• F = snow fall• E, M = evap, melt• csn = grid box fraction with snow
• Snow depth
– with sn evolving snow density (between 100 and 350
kg/m3)• More complex approaches exist (multi-layer,
melting/freezing within layers, percolation of water, …)
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Land surface in climate models
Snow energy budgetSnow energy budget
• with
– (C)sn = heat capacity of snow
– (C)i = heat capacity of ice
– GsnB = basal heat flux (T/r)
– Qsn = phase change due to melting (dependent on Tsn)
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Land surface in climate models
Snow meltSnow melt
• Is energy used to warm the snow or to melt it? In some stage (Tsn 0C) it’s both!
• Split time step into warming part and melting part
– first bring Tsn to 0C, and compute how much energy is needed
– if more energy available: melting occurs– if more energy is available than there is
snow to melt: rest of energy goes into soil.
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Land surface in climate models
ExerciseExercise
• Given:
• Derive the Penman-Monteith equation:
aas
s
a
asp
ca
ass
qTqD
ALEHGQTq
rTT
cH
rrqTq
LLE
)(
*
)(
a
cp
ap
rr
L
c
rcDALE
1
/
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Land surface in climate models
More informationMore information
• Bart van den Hurk– [email protected]