1Hadley Centre for Climate Prediction and Research

Biophysical forcing of climate by anthropogenic vegetation change

Richard A. Betts & Pete Falloon

Hadley Centre for Climate Prediction and ResearchMet Office

Expert Meeting on the Contribution of Agriculture to the State of Climate

Ottawa, Canada28 September 2004

2Hadley Centre for Climate Prediction and Research IPCC 2001

3Hadley Centre for Climate Prediction and ResearchPhoto: Centre for Ecology and Hydrology

4Hadley Centre for Climate Prediction and ResearchPhoto: Tim Hewison

5Hadley Centre for Climate Prediction and Research

Fraction of land used by agriculture(crops + grazing)

Ramankutty & Foley 1999 Klein Goldewijk 2000

6Hadley Centre for Climate Prediction and Research

Forest and grassland albedo Delta Junction, Alaska, 1991-1993

Sharratt 1998

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Modelling surface albedo α

α = α0 + (αD - α0)(1 - e-0.2S)

α0 = snow-free albedoForest: 0.15 Grassland: 0.2

αD = deep-snow albedo

Forest: 0.25 Grassland: 0.8(also some temperature dependence)

S = snow amount (kg m-2)

Hansen et al 1983

8Hadley Centre for Climate Prediction and Research

Radiative forcing (Wm-2) by surface albedo change:“actual” - “natural” vegetation

Global mean: - 0.24 Wm-2

9Hadley Centre for Climate Prediction and Research

Vegetation-atmosphere interactions

Surface albedo

Latent heat / moisture Sensible

heat LW emissivity

CO2

Aerodynamic roughness

Moisture availability

10Hadley Centre for Climate Prediction and Research

Simulated 1.5m temperature difference (K) “Actual” - “Natural” vegetation

(annual mean)

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Simulated seasonal differences“Actual” (ACT) - “Natural” (NAT) vegetation

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Simulated seasonal differencesdue to albedo change alone

“ALBNAT” = albedo of natural veg

13Hadley Centre for Climate Prediction and Research

Changes in fraction of land

disturbed by agriculture

Ramankutty & Foley 1999

Klein Goldewijk 2000

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Surface albedo forcing (Wm-2): 1750 - “natural”

Global mean: - 0.06 Wm-2

15Hadley Centre for Climate Prediction and Research Global mean: - 0.10 Wm-2

Surface albedo forcing (Wm-2): 1850 - “natural”

16Hadley Centre for Climate Prediction and Research Global mean: - 0.14 Wm-2

Surface albedo forcing (Wm-2): 1900 - “natural”

17Hadley Centre for Climate Prediction and Research Global mean: - 0.18 Wm-2

Surface albedo forcing (Wm-2): 1950 - “natural”

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Surface albedo forcing (Wm-2): 1990 - “natural”

Global mean: - 0.24 Wm-2

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1990 forcing relative to “natural”

global mean: -0.24 Wm-2

1990 forcing relative to 1750

global mean: -0.18 Wm-2

Wm-2

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Time evolution of shortwave radiative

forcings (Wm-2)

Surface albedo

Ramaswamy et al 2001

21Hadley Centre for Climate Prediction and Research

But what about

“Cool the Earth - plant a tree?”

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Carbon sink plantations:estimated sequestration potentials

From regional/national estimates of annual increment

(Nilsson & Schopfhauser 1995, Nabuurs & Mohren 1995)

Carbon uptake (trees + soil) over 1 harvest rotation period

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Radiative forcing due to carbon sequestration

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Radiative forcing due to surface albedo change

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Net forcing due to “carbon sink” plantations

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Rates of change of forest cover

Temperate forests: + 1.3 million ha yr-1

Tropical forests: - 12.6 million ha yr-1

UN Food and Agriculture Organization 1997

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Temperature change (K) due to Amazon deforestation

Kleidon and Heimann 2000

1.25

Contour interval 0.25K

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150hpa circulation response to Amazon deforestation

Streamfunction deviation from zonal mean

Contour interval 5×105 m2s-1

Gedney & Valdes 2000

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Conclusions (i)

Model results suggest that past deforestation has affected global climate mainly through surface albedo change

Radiative forcing (-0.18 Wm-2 since 1750) therefore seems to be a reasonable indicator of land use effects on global climate

Surface albedo change may affect estimates of aerosol forcing

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Conclusions (ii)

“Carbon sink” afforestation will also affect climate via surface albedo

– carbon accounting may overestimate negative forcing

– in cold regions, forcing may even be positive!

Tropical deforestation forces climate non-radiatively

– how do we quantify this?

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