modelling australian tropical savanna peter isaac 1, jason beringer 1, lindsay hutley 2 and stephen...

Modelling Australian Tropical Savanna

Peter Isaac1, Jason Beringer1, Lindsay Hutley2 and Stephen

Wood1

1 School of Geography and Environmental Science, Monash University, Melbourne

2 School of Science and Primary Industry, Charles Darwin University, Darwin

Introduction• Savanna occupies ~20% of the Earth’s

surface and ~25% of Australia

• Undisturbed Australian savanna is a sink of CO2, -3 to -4 tCha-1yr-1

• Tropical savanna is a highly dynamic ecosystem– mix of C3 and C4 plant species

– large annual variation in Fe and Fc in response to wet season/dry season climate

– large inter-annual variation due to fire

ARC Discovery Project• Title

– “Patterns and Processes of Carbon, Water and Energy Cycles Across Northern Australian Landscapes: From Point to Region”

• People– Beringer (Monash), Hacker (ARA), Paw U

(UCD), Neininger (MetAir AG), Hutley (CDU)

• MethodsFlux towers (Monash, CDU)

6 sitesRemote sensing

MODIS, LandsatAircraft (ARA, MetAir)

IOP September 2008LSM (UCD, CC)

ACASA, CABLE

Sites• Howard Springs

– open forest savanna

• Fogg Dam– wetland

• Adelaide River– woody savanna

• Daly River Uncleared– open forest savanna

• Daly River 5 year– regrowth

• Daly River 25 year– pasture

Howard Springs• Fluxes

– Fsd, Fsu, Fld, Flu, Fn, PAR– Fm, Fe, Fh, Fc, Fg

• Meteorology– Ta, RH, WS, WD

• Concentrations– CO2, H2O

• Precipitation– Rainfall

• Soil– moisture (10 & 40 cm)– temperature

• 12º 29.655S 131º 09.143E • Open forest savanna

Howard Springs

Savanna Canopy

C3 overstoreyLai 0.6 - 1.0hc 16 m

C4 understoreyLai 0.08 - 1.4hc 0.1 - 2 m

Above ground biomass 34 t ha-1

Below ground biomass 17 t ha-1

Soil organic carbon 140 t ha-1

Leaf Area Index

0.0

0.5

1.0

1.5

2.0

2.5

1 2 3 4 5 6 7 8 9 10 11 12

Month

LAI

Overstorey

Understorey

Overstorey(Fit)

Total

C4 fraction

Drivers and Cycles

0

0.5

1

1.5

2

2.5

LAI (to ta l)

LA I (U S)

C 4 fraction

-50

0

50

100

150

200

(Wm

-2)

N et radiation

Latent heat flux

C O 2 flux

- 5

0

(m

olm

-2s-1

)

0 3 6 9 12M onth

0

0.1

0.2

(m3 m

-3)

Soil m oisture (10cm )

0 3 6 9 12M onth

0

100

200

300

400(m

m)

R ainfa ll

a) b)

c) d)

Questions

To accurately model the seasonal variation in Fe and Fc over tropical savanna, is it necessary:1) for the data input to the model to resolve

the seasonal change in Lai ?

2) for the data input to the model to resolve the seasonal change in C4 ?

3) to use a multi-layer model to resolve changes in the canopy ?

CABLECSIRO Atmosphere Biosphere Land Exchange model

• Big leaf model– Kowalczyk et al. (2006), CMAR Paper 013– coupled assimilation/transpiration– one sunlit leaf, one shaded– mixed C3/C4 canopy by specifying C4 fraction

– seasonally varying Lai and C4 fraction

– radiation in IR, near IR and visible– 13 vegetation types, 9 soil types, 6 soil layers– destined to be the LSM in ACCESS

ACASAAdvanced Canopy Atmosphere Soil Algorithm

• Multi-layer model– University of California, Davis– Pyles et al., 2000, QJRMS, 126, 2951-2980– coupled assimilation/transpiration– third-order closure turbulence sub-model– 100 canopy layers for radiation– 20 canopy layers for turbulence/fluxes– 15 soil layers– no C4 pathway

Savanna canopy

C3C4

Sunlit

Shaded

CABLE C3

ACASA

C3 overstoreyLai 0.6 - 1.0hc 16 m

C4 understoreyLai 0.08 - 1.4hc 0.1 - 2 m

C4 roots shallow

C3 roots deep

Reality vs Model

Results

1) Out-of-the-box– all defaults except LAI

2) Basic Tuning– “educated guess”

3) Constant Lai

– as for 2), Lai = 1.4

4) Constant C4 fraction– as for 2), C4 fraction = 0.39

Out-of-the-box : CABLE

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

-15

-10

-5

0

5

mo

lm-2

s-1

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

W et D raw -dow n D ry R e-charge

C ABLE : H ow ard Springs ; 1 /6 /2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Out-of-the-box : ACASA

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

A C ASA

-100

0

100

200

300

Wm

-2

O bs

A C ASA

0

100

200

300

400

Wm

-2

O bs

A C ASA

-15-10

-505

1015

mo

lm-2

s-1

O bs

A C ASA

0 6 12 18 24H o u r

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

W et D raw -dow n D ry R e-charge

AC AS A : H ow ard Springs ; 1 /6/2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Basic Tuning

• Soil moisture at wilting point reduced from 0.135 to 0.08 m3m-3 based on observations

• Root fraction for E. tetradonta according to Eamus et al. (2002)

• CABLE– vcmax increased from 10 to 30 molm-2s-1

• ACASA– set soil microbial respiration to 0

Basic Tuning : CABLE

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

-15

-10

-5

0

5

mo

lm-2

s-1

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

W et D raw -dow n D ry R e-charge

C ABLE : H ow ard Springs ; 1 /6 /2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Basic Tuning : ACASA

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

A C ASA

-100

0

100

200

300

Wm

-2

O bs

A C ASA

0

100

200

300

400

Wm

-2

O bs

A C ASA

-15

-10

-5

0

5

mo

lm-2

s-1

O bs

A C ASA

0 6 12 18 24H o u r

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

W et D raw -dow n D ry R e-charge

AC AS A : H ow ard Springs ; 1 /6/2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Constant Lai : CABLE

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

-15

-10

-5

0

5

mo

lm-2

s-1

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

W et D raw -dow n D ry R e-charge

C ABLE : H ow ard Springs ; 1 /6 /2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Constant Lai : ACASA

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

A C ASA

-100

0

100

200

300

Wm

-2

O bs

A C ASA

0

100

200

300

400

Wm

-2

O bs

A C ASA

-15

-10

-5

0

5

mo

lm-2

s-1

O bs

A C ASA

0 6 12 18 24H o u r

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

W et D raw -dow n D ry R e-charge

AC AS A : H ow ard Springs ; 1 /6/2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Constant C4 fraction : CABLE

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

0

100

200

300

400

Wm

-2

O bs

C ABLE

-15

-10

-5

0

5

mo

lm-2

s-1

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

0 6 12 18 24H o u r

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

O bs

C ABLE

W et D raw -dow n D ry R e-charge

C ABLE : H ow ard Springs ; 1 /6 /2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Constant C4 fraction : ACASA

0 6 12 18 24H o u r

0

200

400

600

800

Wm

-2

O bs

A C ASA

-100

0

100

200

300

Wm

-2

O bs

A C ASA

0

100

200

300

400

Wm

-2

O bs

A C ASA

-15

-10

-5

0

5

mo

lm-2

s-1

O bs

A C ASA

0 6 12 18 24H o u r

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

O bs

A C ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

0 6 12 18 24H o u r

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

O bs

AC ASA

W et D raw -dow n D ry R e-charge

AC AS A : H ow ard Springs ; 1 /6/2004 to 31/5 /2005

N et R adiation

Sensib le

Latent

N EE

Seasonal Variation in Fe and Fc

0 3 6 9 12M o n th

0

40

80

120

160

200

Wm

-2

-5

-4

-3

-2

-1

0m

olm

-2s-1

O bs

Tuned

LA I constant

C 4 constant

0 3 6 9 12M o n th

O bs

Tuned

LA I constant

C 4 constant

C ABLE AC ASAN EE N EE

Latent

Latent

Summary• Tropical savanna is a dynamic system

– mix of C3 overstorey and C4 understorey

– Lai and C4 fraction respond mainly to soil moisture

– soil moisture driven by bi-modal rainfall

• Questions– do we need a multi-layer model ?

– do we need seasonally varying Lai ?

– do we need seasonally varying C4 fraction ?

Conclusions (ACASA)

• The multi-layer model (ACASA) did not perform better than the single layer model (CABLE) for this study– Raupach and Finnigan (1988)

• The multi-layer model did not perform well enough to make conclusions about the necessity of resolving seasonal changes in Lai and C4 fraction in the input data.

Conclusions (CABLE)• Basic tuning significantly improves model

performance.

• When tuned, CABLE over-predicts Fc in the wet season and under-predicts Fe in the dry season.

• CABLE is sensitive to both Lai and C4 fraction when predicting Fc but is not sensitive to either when predicting Fe.

• C4 fraction must vary by season to correctly predict seasonal changes in Fc.