Controls on evapotranspiration (ET) and

its seasonality in select land surface models

In Support of The LBA-Model Intercomparison Project (MIP)

Brad ChristoffersenUniversity of Arizona

Motivation• Amazonian forests are a locus for potential

positive feedback to climate change.(Betts et al. 2004)

Rising atmospheric

CO2

Drought frequency

Forest dieback

Stomatal closure

Motivation• Amazonian forests are a locus for

potential positive feedback to climate change(Betts et al. 2004)

• Land surface models have typically predicted water-limited control on ET across the seasonally dry Amazon(Shuttleworth 1991, Bonan et al. 1998, Dickinson et al. 2006)

Rising atmospheric

CO2

Drought frequency

Forest dieback

Stomatal closure

Motivation• Amazonian forests are a locus for

potential positive feedback to climate change(Betts et al. 2004)

• Land surface models have typically predicted water-limited control on ET across the seasonally dry Amazon(Shuttleworth 1991, Bonan et al. 1998, Dickinson et al. 2006)

• Recent eddy tower syntheses reveal strong net radiation and little precipitation control on ET(Hasler and Avissar 2007, Juarez et al. 2007, Fisher et al. in press)

Rising atmospheric

CO2

Drought frequency

Forest dieback

Stomatal closure

LBA-MIP Participating Models

• Ecosystem Process Models:– SSiB2, SiB2, SiB3, SiB-CASA, Biome-BGC, VISIT

• Dynamic Vegetation Models:– LPJ, HyLand, Jules-TRIFFID, CLM-DGVM, Orchidee, IBIS,

LM3V

• Parameter Models:– 5PM, SPA-DALEC

• Strictly Soil-Vegetation-Atmosphere Model:– NOAH

• Corresponding GCMs or Mesoscale Models:– CSU-SiB3, SPEEDY-LPJ, HadCM3-Jules, CCSM-CLM, IPSL-

CM4-Orchidee, Eta-NOAH

Water Dynamics in Land Surface Models: Central

Questions• How do model-predicted seasonal / diurnal

patterns in ET intercompare with each other and with data?

• What is the relative importance of radiation and available soil moisture as controls on ET?

Long-term goal Identify key model mechanisms associated w/ model-model and model-data differences

Differences in ET seasonality

Subsurface runoffSurface runoff

Soil evapInterception evapTranspiration

Mo

de

l-m

od

el

Inte

rco

mp

ari

so

n

Da

ta-M

od

el I

nte

rco

mp

ari

so

nJ F M A M J J A S O N D

Site PrecipObserved ET

All

y-ax

is u

nits

are

mm

/mon

th

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

J F M A M J J A S O N D J F M A M J J A S O N D

CLM3 CLM3GW CLM3.5

NOAH IBIS

∑Fluxes + ∆SoilMoisture

J F M A M J J A S O N D

Fluxes:

Tapajós K67 Site

Differences in ET seasonality

Subsurface runoffSurface runoff

Soil evapInterception evapTranspiration

Mo

de

l-m

od

el

Inte

rco

mp

ari

so

n

Da

ta-M

od

el I

nte

rco

mp

ari

so

nJ F M A M J J A S O N D

Site PrecipObserved ET

All

y-ax

is u

nits

are

mm

/mon

th

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

J F M A M J J A S O N D J F M A M J J A S O N D

CLM3 CLM3GW CLM3.5

NOAH IBIS

∑Fluxes + ∆SoilMoisture

J F M A M J J A S O N D

Fluxes:

Tapajós K67 Site

Differences in ET seasonality

Subsurface runoffSurface runoff

Soil evapInterception evapTranspiration

Mo

de

l-m

od

el

Inte

rco

mp

ari

so

n

Da

ta-M

od

el I

nte

rco

mp

ari

so

nJ F M A M J J A S O N D

Site PrecipObserved ET

All

y-ax

is u

nits

are

mm

/mon

th

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

J F M A M J J A S O N D J F M A M J J A S O N D

CLM3 CLM3GW CLM3.5

NOAH IBIS

∑Fluxes + ∆SoilMoisture

J F M A M J J A S O N D

Fluxes:

Tapajós K67 Site

Differences in ET seasonality

Subsurface runoffSurface runoff

Soil evapInterception evapTranspiration

Mo

de

l-m

od

el

Inte

rco

mp

ari

so

n

Da

ta-M

od

el I

nte

rco

mp

ari

so

nJ F M A M J J A S O N D

Site PrecipObserved ET

All

y-ax

is u

nits

are

mm

/mon

th

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

J F M A M J J A S O N D J F M A M J J A S O N D

CLM3 CLM3GW CLM3.5

NOAH IBIS

∑Fluxes + ∆SoilMoisture

J F M A M J J A S O N D

Fluxes:

Tapajós K67 Site

Net Radiation Controls on ET – Observed and Modeled

Net Radiation Controls on ET – Observed and Modeled

Site Season

Slope.HA

Slope.MIP

Intcpt.HA

Intcpt.MIP

R2.HA R2.MIP

K34 Wet 0.63 -19.9 0.88

Dry

K67 Wet 0.61 -1.2 0.75

Dry

K83 Wet 0.65 35.5 0.74

Dry

RJA Wet 0.59 -5.10 0.85

Dry

FNS Wet 0.48 -26.8 0.83

Dry

Adapted from Hasler and Avissar 2007

Net Radiation Controls on ET – Observed and Modeled

Site Season

Slope.HA

Slope.MIP

Intcpt.HA

Intcpt.MIP

R2.HA R2.MIP

K34 Wet 0.63 0.58 -19.9 6.3 0.88 0.46

Dry

K67 Wet 0.61 0.64 -1.2 -5.4 0.75 0.53

Dry

K83 Wet 0.65 0.64 35.5 -5.4 0.74 0.53

Dry

RJA Wet 0.59 0.57 -5.10 10.62 0.85 0.45

Dry

FNS Wet 0.48 0.55 -26.8 6.7 0.83 0.31

Dry

Adapted from Hasler and Avissar 2007

Varying Strength of Rnet control on ET across models

(wet season)

Mean Daily Net Radiation (W m-2)

Mean

Daily L

E (

W m

-2)

CLM3.5 (x4)SiB3IBISLPJ

1:1

MIP LSR

H&A LSR

Most Models Lag ~2hrs behind observed diurnal cycles in LE

flux

Hour

Hou

rly L

E (

W m

-2)

CLM3.5 (x4)SiB3IBISData

Conclusions

• Considerable cross-model variance in predicted daily (and seasonal) patterns of ET

• Diurnal cycles of ET often lag those observed in data

• Controls on ET - Models in Semi-Agreement:– Net radiation exhibits dominant control on ET in

absence of water stress– Increased soil moisture storage capacity in

models shifts ET peak to dry season (in phase with net radiation)

Future Directions

• What model mechanisms give rise to these differences?

• What is the quantitative partitioning of relative controls of radiation and soil moisture on ET?

• Explore empirical bucket model capability of caputuring seasonal and interannual variability in modeled soil moisture.

Thanks!The LBA-MIP Team

GustavoNASA

BradUofA

ScottUofA

JulioINPA

LindseyUT-Austin

MargrietVrije U.

Laura

MarcosUFV

FannyPotsdam

NataliaUofA

DavidEdinburgh

Ian, CSU Ben, Potsdam

HewlleyUFV