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Surface Skin Temperature, Soil Moisture, and Turbulent Fluxes in Land Models. Xubin Zeng, Mike Barlage, Mark Decker, Jesse Miller, Cindy Wang, Jennifer Wang Dept of Atmospheric Sciences University of Arizona Tucson, AZ 85721, USA. - PowerPoint PPT Presentation
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Surface Skin Temperature, Soil Moisture, and Turbulent Fluxes in Land Models
Xubin Zeng, Mike Barlage, Mark Decker,Jesse Miller, Cindy Wang, Jennifer Wang
Dept of Atmospheric Sciences University of Arizona Tucson, AZ 85721, USA
(a) A revised form of Richards equation
(b) CLM3 simulation versus MODIS skin T Consistent (c) Treatment of turbulence below and above
canopy as well as snow burial of canopy(d) Vegetation and snow albedo data
Revised Richards Eq.
B
sat
lsatlsatwtd zz
z
zKq
Sz
zK
zt
0)(
)(
Decker andZeng (2007)
CLM3 offline tests over Sahara, southwest US and TibetFor July 1-5, 2003.
Cs = Cs,soil W + Cs,veg (1 – W) Zeng et al. (2005) W = exp(– LAI)
Dickinson et al. (2006)
Thought experiment: What would be the land zo and dIf above-ground biomass disappears?
CLM3 deficiency: zo and d depend on vegetation type only
Solution:
de = d V + (1 – V) dg
ln (zoc,e) = V ln(zoc) + (1 – V) ln (zog)
V = (1 – exp[-β min(Lt, Lcr)])/(1 – exp[- β Lcr])
Impact in CLM3
Figure C. 1 CLM3-simulated snow depth and surface fluxes from Jan. 11-13, 1996 over a boreal grassland site in Canada. Both simulation with new formulation of fv,sno and simulation with standard CLM3 are shown (52.16ºN, 106.13ºW ).
Figure C.2 The same simulation as in Fig. C. 1 but for averaged diurnal cycles of winter time (Dec. 1995, Jan. and Feb. 1996).
Wang andZeng (2007)
Figure C.4 (a) Ten-year averaged DJF differences of Tg between CLM3
with Eq.(C. 3) and the standard CLM3 global offline simulations, and (b) ten-year averaged annual cycle of Tg difference over Alaska
(59-72ºN, 170-140ºW).
Zeng et al. (2000)
NCAR/CLM3: FVC(x,y), LAI(x,y,t)
NCEP/Noah: GVF(x,y,t),LAI=Const
Validation:1-3m spy sat data,1-5m aircraft data,30m Landsat data,Surface survey data
Data Impact
Barlage and Zeng (2004)
NLDAS GVF DataNoah 1/8 degree monthly
MODIS 2km 16-day
Miller et al. (2006)
NLDAS GVF Results
crop
grass • Addition of new GVF dataset results in an increase of transpiration (up to 35W/m2) and canopy evaporation (up to 8W/m2)
• Balanced by a decrease in ground evaporation (up to 20W/m2)
• Overall increase in LHF(up to 20W/m2) is balanced by decreases in SHF(up to 10W/m2) and Lwup(5W/m2) Miller et al. (2006)
AlbedoNDSINDVILand coverIndividual bands
Red: NN filledBlue: LAT filledGreen: > 0.84
Barlage et al. (2005)
MODIS versus Noah maximum snow albedo data
Barlage et al. (2005)
Impact on NLDAS Offline Noah Tests
Application of MODIS Maximum Snow Albedo to WRF-NMM/NOAH
• up to 0.5 C decreases in 2-m Tair in regions of significant albedo change
• > 0.5 C increase in 2-m Tair in several regions
Barlage et al. (2007)
• Skin temperature and turbulent fluxes are all strongly affected by the treatment of below and
above-canpy turbulence and snow burial • They are also affected by green vegetation cover
data as well as maximum snow albedo data• While Terra/Aqua MODIS provides 4 skin Ts measurements a day, its use without constraint from Tair requires additional efforts
• The revised Richards equation should be used for land models for improved simulations of soil moisture and fluxes
Summary
Suggestions on LANDFLUX
• Try to reach some consensuses on the land boundary data to be used• Identify flux tower sites with relatively comprehensive data over different climate regimes to set up minimum criteria for
land models or model components to meet
• Try to use land-atmosphere constrained
land and atmospheric forcing data
Model Run
• Model Alterations– New Richards equation
•Including new bottom boundary condition
•NO TUNABLE PARAMETERS
– Soil texture constant with depth– Infiltration– Area of Saturated Fraction
• 1984-2004 with Qian/Dai forcing
Comparison ofCAM/CLM3 withthe Terra and AquaMODIS data
Zeng et al. (2007)
NCAR/CLM3: FVC(x,y), LAI(x,y,t)NCEP/Noah: GVF(x,y,t),LAI=Const
Validation:1-3m spy sat data,1-5m aircraft data,30m Landsat data,Surface survey data
Histogram of evergreenBroadleaf treeNDVIveg = 0.69
Fractional Vegetation Cover
Interannual variability and decadal trend ofglobal fractional vegetation cover from1982 to 2000
Zeng et al. (2003)
(a) Shading effect (b) Shadowing effect LAI is difficult to measure in winter! A = Asn fsn + Av(1-fsn)
Then the question is
(1) what is satellite snow fraction? (2) What is Asn?
Maximum Snow Albedo in the NCEP Noah Land Model
Issue: Consistency of Cx below/within canopy
Motivation: warm bias of 10 K in Tg in CCSM2
Below/within canopy in CLM Hg ~ Cs u* (Tg – Tva) Hf ~ Cf LAI u*
0.5 (Tv – Tva)
Cs = const in BATS, LSM, CLM2
Based on K-theory Cs ≈ 0.13 b exp(-0.9b)/[1 – exp(-2b/3)] b = f(LAI, stability)
Surface Skin Temperature, Soil Moisture, and Turbulent Fluxes in Land Models
Xubin ZengMike Barlage, Mark Decker,Jesse Miller, Cindy Wang, Jennifer Wang
Dept of Atmospheric Sciences University of Arizona Tucson, AZ 85721, USA
Turbulence
Energy Balance: Rnet + G + Ft + Fq ≈ 0Water Balance: P ≈ Fq + RTurbulent fluxes Fx ~ Cx U (Xa – Xs) Cx = f(Zom, Zot, stability) X: temperaure, humidity, wind, trace gas
(a) Consistent treatment of turbulence below and above canopy as well as snow burial of canopy(b) Vegetation and snow albedo data (c) CAM3/CLM3 simulation versus MODIS skin T(d) A revised form of Richards equation