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