Interações entre Clima e Vegetação na Interações entre Clima e Vegetação na Amazônia: do último período glacial Amazônia: do último período glacial
até o clima do futuroaté o clima do futuro
Carlos A. NobreCarlos A. NobreCPTEC/INPECPTEC/INPE
III CONFERÊNCIA CIENTÍFICA DO LBAIII CONFERÊNCIA CIENTÍFICA DO LBABrasília, 27-29 Julho 2004Brasília, 27-29 Julho 2004
Interações entre Clima e Vegetação na Interações entre Clima e Vegetação na Amazônia: do último período glacial Amazônia: do último período glacial
até o clima do futuroaté o clima do futuro
Carlos A. NobreCarlos A. NobreCPTEC/INPECPTEC/INPE
III CONFERÊNCIA CIENTÍFICA DO LBAIII CONFERÊNCIA CIENTÍFICA DO LBABrasília, 27-29 Julho 2004Brasília, 27-29 Julho 2004
Vegetation-Climate Interactions
Climate Vegetation
Bidirectional on various times scales
Atlantic rainforest
Map of dry season length (DSL) (data after Sombroek, 2001), expressed as the number of months with <100 mm of rain.
Steege et al., Biodiversity and Conservation 12 (in press), © 2003 Kluwer Academic Publishers
Sternberg, 2001, Global Ecology & Biogeography, 10, 369–378
Vegetation = f (climate)
Climate = f (vegetation)
Savanna
Forest
Simple Model of Biome (Savanna and Tropical Forest)-Climate Equilibrium States
Annualprecipitation
Meanclimaticequator
Arid Savanna Rainforest Savanna Arid
Growing season
Gro
win
g s
easo
n le
ng
th in
mo
nth
s
Mea
n a
nn
ual
pre
cip
itat
ion
in m
m
South Equator North Latitude
A scheme of the relationship between mean annual precipitation and growing season length in tropical climates (from Newman, 1977)
Tmean > 24 C13 C < Tcoldest month < 18 CP (3 driest months) < 50 mmP (6 wettest months) > 600 mm1000 mm < Pannual < 1500 mm
Climatic Conditions forSavannas (Nix (1983)
Nobre et al. 1991, J. Climate
Modeling Deforestation and Biogeography in AmazoniaModeling Deforestation and Biogeography in Amazonia
Current Biomes Post-deforestation
“1” Tropical Forest“6” Savanna
Geog
rafi
a
Ecolo
gia
Modelagem de Distribuição Geográfica de Biomas
Área de Ocorrência
Algoritmo Variável Ambiental AVar
iáve
l am
bien
tal B
Modelo de Biomas
Previsão da
Distribuição
Five climate parameters drive theFive climate parameters drive the potential vegetation model potential vegetation model
Oyama and Nobre, 2002
Monthly values of precipitation and temperature
Water Balance Model
Potential Vegetation Model
SSiB Biomes
Visual Comparison of CPTEC-PBM Visual Comparison of CPTEC-PBM versus Natural Vegetation Mapversus Natural Vegetation Map
CPTEC-PBM
SiB BiomeClassification
Oyama and Nobre, 2002
62% agreement on a global 2 deg x 2 deg grid
Visual Comparison of CPTEC-PBM versus Natural Vegetation Map
SiB BiomeClassification
NATURAL VEGETATION POTENTIAL VEGETATION
Oyama and Nobre, 2002
Searching for Multiple
Biome-Climate Equilibria
Vegetation = f1 (climate variables) = f1 (g0, g5, Tc, h, s)
g0 = degree-days above 0 Cg5 = degree-days above 5 CTc = mean temperature of the coldest monthh = aridity index s = sesonality index
f1 is a highly nonlinear function
Climate = f2 (vegetation) = f2 (AGCM coupled to vegetated land surface scheme)
f2 is also a nonlinear function
IC: All land points covered by desert IC: All land points covered by tropical forest
I T
E
R
A
T
I
O
N
S
Results of CPTEC-DBM for two different Initial Conditons: all land areas covered by
desert (a) and forest (b)
Oyama, 2002
Biome-climate equilibrium solution with IC as forest (a) is similar to current natural vegetation (c); when the IC is desert (b), the final equilibrium solution is different for Tropical South America
a
b
c
Initial Conditions
Oyama and Nobre, 2003
Two Biome-Climate Equilibrium States found for South America!
Soil Moisture
Rainfallanomalies
-- current state (a)-- second state (b)
Unconditional probability of a wet day. a) Threshold of 1 mm, b) Weak rainfall (rainy days: 1 mm - 5 mm) and, c) Moderate rainfall (rainy days: 5 mm - 25 mm). The daily data spans 1979 to 1993.
P > 1 mm 1 mm < P < 5 mm 5 mm < P < 25 mm
Obregon 2001
Unconditional Probability of a Wet Day
Obregon 2001
1 mm < P < 5 mm
SACZ
Sea BreezesInstability lines
Annual Precipitation
Sensitivity Analysis to ‘Savannization’ of AmazoniaSensitivity Analysis to ‘Savannization’ of Amazonia
Resolution: ~ 2ºx2º
Control 2033 All Savanna
2033 All Savanna
JJA 5,4% -21,7%
JJAS 1,9% -21,9%
Dry Season Precipitation*
* 12°S-3°N / 50°W-75°WOliveira et al., 2004
Paleovegetation Reconstructions as Validation for the Second Stable
Equilibrium?
Application of CPTEC-PBM for Past Climate Changes
Oyama, 2002
(a) PBM results with uniform cooling of 6 C and drying of 3 mm/day to emulate climate conditions of the LGM (21 ka BP);
(b) vegetation reconstruction for LGM;
a
b
Last glacial maximum: GENESIS+IBISThe importance of vegetation feedbacks
Reference: Foley, J. A.; Levis, S.; Costa, M. H., Cramer, W.; Pollard, D. 2000: Incorporating dynamic vegetation cover within global climate models. Ecological Applications, v. 10, n. 6, p. 1620-1632.
R = radiation of 21 ka BP, fixed modern vegetation, [CO2] = 180 ppmvRPV = radiation of 21 ka BP + dynamic vegetation + physiology at [CO2] = 180 ppmv
Decrease of AmazoniaRainfall!
Results for Amazonia
What are the likely biome changes in Tropical South America due to Global
Warming?
Change in Amazon Climate and Hydrology in HadCM3LC
Lat: 15oS - 0oNLon: 70oW - 50oW
Amazon forest die-back!
Cox et al., 2000
Change in Amazon Carbon Balancein HadCM3LC
Lat: 15oS - 0oNLon: 70oW - 50oW
Amazon forest die-back!
Cox et al., 2000
Change in Global Climate in HadCM3LC
Interactive CO2 and Dynamic Vegetation
2090s - 1990s
Cox et al., 2000
Geog
rafi
a
Ecolo
gia
Análise de Redistribuição de Biomas em face a Mudanças Climáticas
Área de Ocorrência
Algoritmo Precipitação
Tem
pera
tura
Modelo de Biomas
Previsão daDistribuição
Projeção de Biomas comMudançaClimática
Projeção considerando alterações climáticas
A2 High GHG Emissions Scenario B2 Low GHG Emissions Scenario
Temperature Anomalies (deg C) for 2091-2100
Nobre et al., 2004
A2 High GHG Emissions Scenario B2 Low GHG Emissions Scenario
Precipitation Anomalies (mm/day) for 2091-2100
Nobre et al., 2004
Projected Biome Distributions for South America for 2091-2100
Natural Vegetation Natural Vegetation
A2 High GHG Emissions Scenario B2 Low GHG Emissions Scenario
Nobre et al., 2004
ConclusionsThe future of biome distribution in Amazonia
in face of land cover and climate changes
• Natural ecosystems in Amazonia have been under increasing land use change pressure.
• Large-scale land cover changes could cause warming and a reduction of rainfall by themselves in Amazonia.
• The synergistic combination of regional climate changes caused by global warming and land cover change over the next several decades could tip the biome-climate state to a new stable equilibrium with ‘savannization’ of parts of Amazonia (and ‘desertification’ of parts of Northeast Brazil).
Possible stability landscape for Tropical South America. Valleys (X1, X2 and Y) and hills correspond to stable and unstable equilibrium states, respectively. Arrows represent climate state (depicted as a black circle) perturbations. State X1 refers to present-day stable equilibrium. For small (large) excursions from X1, state X2 (Y) can be found. It is suggested that the new alternative stable equilibrium state found in this work corresponds to X2. Notice that it is necessary to reach X2 before reaching state Y.
Resilience Stochastic Perturbations Gradual Perturbations affect Resilience (e.g., deforestation, fragmentation, etc.)
Biome-Climate Bi-Stability for the SahelBiome-Climate Bi-Stability for the Sahel
Current State Second State
SCHEFFER EL AL., NATURE | VOL 413 | 11 OCTOBER 2001
The second equilibriun state depend mostly on vegetation(albedo) feedback and secondarily on ocean feedbacks
Pr: rain
Ps: snow
T: sfc air temperature
Ts: soil temperature
S: soil water storage
N: overland snow storage
E: evapotranspiration
R: runoff
M: snowmelt
Pr: rain
Ps: snow
T: sfc air temperature
Ts: soil temperature
S: soil water storage
N: overland snow storage
E: evapotranspiration
R: runoff
M: snowmelt
Simple Land Surface Model
Oyama and Nobre, 2002