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National Institute for Space Research – INPE
Earth System Science Center – CCST
“Climate modeling, INPE's projections for
the 21st century, and the distribution of
Brazilian biomes”
Gilvan Sampaio
[email protected]
Workshop Dimensions US-BIOTA São Paulo
A multidisciplinary framework for biodiversity prediction in the Brazilian Atlantic forest hotspot
February 10th 2014
FAPESP – Rua Pio XI, 1500, Alto da Lapa, São Paulo, SP
What are the likely biome changes in Tropical South America due
to a suite of environmental drivers of change?
Environmental Drivers of Change
Climate Change:
CO2,temperature,
rainfall
Droughts
Short term
(interannual to
interdecadal)
Long term
(interdecadal to
centennial)
Land Cover Change:
Deforestation, Forest
Degradation
Forest Fires
Primary Drivers
Secondary
Drivers
Ecosystem Responses
“Secondarization”
Changes in Species
Composition
Tree Mortality x
Tree Growth
Savannization/
forest dieback
“Savannization” in this context is a statement on regional climate change and not intended to
describe complex ecological processes of vegetation substitution.
What are the likely biome changes in Tropical South America due
to a suite of environmental drivers of change?
Environmental Drivers of Change
Climate Change:
CO2,temperature,
rainfall
Droughts
Short term
(interannual to
interdecadal)
Long term
(interdecadal to
centennial)
Land Cover Change:
Deforestation, Forest
Degradation
Forest Fires
Primary Drivers
Secondary
Drivers
Ecosystem Responses
“Secondarization”
Changes in Species
Composition
Tree Mortality x
Tree Growth
Savannization/
forest dieback
“Savannization” in this context is a statement on regional climate change and not intended to
describe complex ecological processes of vegetation substitution.
How well can CMIP5 models simulate the
precipitation over tropical South
America?
CMIP5 - Bias in model precip (1971-2000 model-CRU)
Kay et al., 2013
CMIP5 - Temperature Anomalies – RCP 4.5 – 2015-2034
CMIP5 - Temperature Anomalies – RCP 8.5 – 2015-2034
Source: Sampaio et al., 2013, in preparation
CMIP5 - Temperature Anomalies – RCP 4.5 – 2040-2059
CMIP5 - Temperature Anomalies – RCP 8.5 – 2040-2059
Temperature change
2071-2100
Kay et al., 2013
CMIP5 - Precipitation Anomalies – RCP 8.5 – 2015-2034
Source: Sampaio et al., 2013, in preparation
CMIP5 - Precipitation Anomalies – RCP 8.5 – 2040-2059
Indicator of CMIP5 model
consensus in precipitation
changes – 2071-2100
• wetter conditions in DJF
Brown colours indicate model
agreement for a drying signal and
greens for a wetting signal.
Kay et al., 2013
CMIP5 - BESM RCPs Scenarios
Surface Temperature over Brazil
RCP 8.5: 0.235 C/decade
RCP 4.5: 0.134 C/decade
Fonte: Nobre et al (2013)
INPE-Eta model – RCP4.5
Lyra and Chou, 2013
INPE-Eta model – RCP4.5
Lyra and Chou, 2013
Source: Sillmann et al., 2013
LAND USE AND COVER
CHANGE
What are the likely biome changes in Tropical South America due
to a suite of environmental drivers of change?
Environmental Drivers of Change
Climate Change:
CO2,temperature,
rainfall
Droughts
Short term
(interannual to
interdecadal)
Long term
(interdecadal to
centennial)
Land Cover Change:
Deforestation, Forest
Degradation
Forest Fires
Primary Drivers
Secondary
Drivers
Ecosystem Responses
“Secondarization”
Changes in Species
Composition
Tree Mortality x
Tree Growth
Savannization/
forest dieback
“Savannization” in this context is a statement on regional climate change and not intended to
describe complex ecological processes of vegetation substitution.
(Foley et al., 2003)
EFFECTS OF LARGE SCALE DEFORESTTION
Numerical simulations of deforestation
• Increase in surface temperature: 0.3°C to 3.0°C
• Decrease in evapotranspiration: 15% to 30%
• Decrease in precipitation: 5% to 20%
• Increases the length of the dry season
Sources: Lean e Warrilow-1989; Nobre, et al.-1991; Henderson-Sellers et al.-1993; Lean et al.-1993, Sud et al.1996, Lean et al.-1996, Manzi e Planton-1996, Rocha et al.-1996, Hahmann e Dickinson.-1997, Costa e Foley2000, Rocha-2001, Werth e Avissar-2002, Voldoire e Royer-2004 e Correia-2005, Sampaio et al., 2007, Costa et
al., 2007.
Effect of regional deforestation
• Enhance local circulation
• Increase rainfall amounts
• Different impact on cloudiness in the dry
and wet seasons
Biomes of tropical South America and precipitation seasonality
Biomes of South America
Tropical Forest-Savanna
Boundary
Number of consecutive months
with less than 50 mm rainfall
Tropical Forest
Shrubland
Savanna
Annual Rainfall
Sombroek 2001, Ambio
The importance of rainfall seasonality
(short dry season) for maintaining
tropical forests all over Amazonia
“Terrestrial biosphere models are competent at
predicting plant and ecosystem carbon fluxes
under the present climate, but still require
substantial development for predicting the
consequences of severe drought scenarios”Powell et al, 2013.
Biomes for South America.
Forest
Is the current ClimateVegetation
equilibrium in
Amazonia the only
stable equilibrium
possible?
After Olsen et al. (2001).
Biome-Climate Equilibrium
variabilidade
Regime2
Regime1
Tipping points of the Earth System – Application to Amazonia
Tropical forest
Savanna state
triggered by climate
change or
deforestation
Tipping points: temperature, rainfall and deforestation area
Stability of savanna
enhanced by increased
droughts and fires
Cardoso and Borma, 2010
Biome changing – bi-stability in the Amazon
(a) First State - Biome-climate
equilibrium starting from forest
land cover as initial condition
for the Dynamic Vegetation
Model. These results are
similiar to current natural
vegetation.
(b) Second State - Biomeclimate equilibrium starting
from desert land cover as
Initial Condition for the
Dynamic Vegetation Model
‘Savannization’ of Amazonia and ‘desertification’ in NE Brazil
Oyama and Nobre, 2003
What does it take to tip the equilibrium between
the two stable states?
?
Climate Change Consequences on the Biome distribution in
tropical South America
Projected distribution of natural biomes in South America for 2090-2099 from 15
AOGCMs for the A2 emissions scenarios.
Savanas in the Amazon and Semi-Desert in the Northeast of Brazil
“Savannization” in this context is a statement on regional climate change and not intended to
Salazar et al., 2007
describe complex ecological processes of vegetation substitution.
Climate change
How does the forest respond to increased atmospheric CO2?
Only
Climate
CO2
760 ppm
½ CO2
“fertilization”
effect
Taking into account the potential positive effect of CO2 on forest resilience
Lapola et al. GBC, 2009
Preliminary attempt at determining quantitative ‘tipping’
points for collapse of the Amazon forests
Tentatively, thresholds for the maintenance of the
rainforests are:
• ∆TGlobal Warming < 3 C (3.5 C in the Amazon)
• Total Deforested Area < 40%
• Forest fires decrease even further the resilence of
tropical forests in the Amazon
• The role of CO2 “fertilization” is unkown and could
increase resilience
Ecosystems of Amazonia - environmental drivers of change
Complex Earth System Models are needed to study
all these interacting and simultaneous drivers
LUCC
Climate
Change
Fire
Climate
Extremes
Projeto PROVEG
Vieira et al., 2013
Canavesi et al. 2012
Percentage of deforestation
Deforestation maps in scenario C
INPE’s Brazilian Scenarios + AMAZALERT Project
Aguiar et al. (2013, submitted)
http://www.eu-amazalert.org/home
Impacts of deforestation, climate
change and fire on the future biomes
distribution and climate in Amazonia
Projected distribution of natural biomes in South America where more than 66,7% of the models used (>=6
models) coincide for 2050 from 9 Earth System Models for the RCP 2.6, 4.5 and 8.5 emission scenarios
Deforestation = 20% or 40% or 50% + Fire effect
Tropical Seasonal Forest
Savanna
Tropical Evergreen Forest
Savanna/Seasonal
forest replaces Forest
Sampaio et al., 2014, in preparation
Brazilian Earth System Model - BESM
BESM is a fully-coupled, global climate model that provides
state-of-the-art computer simulations of the Earth’s past,
present, and future climate states.
BESM is an evolution of previous versions of the Center for
Weather Forecasting and Climate Studies (CPTEC) coupled
ocean-atmosphere model.
The creation of the Brazilian Earth System Model is a goal of
various projects, among them the National Institute of
Science and Technology on Climate Change (INCT-MC) and
projects such as the FAPESP-Global Climate Change
Program, which represents a large collaboration between
INPE and various other national and foreign institutions and
universities.
Brazilian Earth System Model - BESM
ATMOS CHEMISTRY (Max Planck)
CO2
Trace Gases
Particles
ATMOSPHERE (INPE/CPTEC)
Heat
H2O
2080-2099 A1B
2080-2099 A1B
CO2
FMS
COUPLER
INLAND
Hydrology
Land Use
OCEAN (NOAA/GFDL – MOM4)
RIVER
ICE
Fire
RIVERS
BioChemistry
Predictability
INLAND – Integrated Land Surface Model
• We developed our integrated model on the top of the
Integrated Biosphere Simulator (IBIS) v. 2.6
• INLAND is a submodel of the Brazilian Earth System Model
(BESM).
• Represent processes that are important to us (South America)
and may be considered secondary in other models
• Collaboration with advanced climate change centers abroad
• INLAND: land surface processes parameterization
• INLAND is a community model.
40
INLAND – Processes represented
Fluxes of radiation, energy and mass
IBIS 2.6/INLAND 1
Complete terrestrial carbon cycle
IBIS 2.6/INLAND 1
Phenology and vegetation dynamics
IBIS 2.6/INLAND 1
Recovery of abandoned lands
IBIS 2.6/INLAND 1
Croplands representation
Agro-IBIS/INLAND 2
River discharge and seasonally flooded areas
THMB 2/INLAND 3
Specific representation of South American ecosystems
INLAND 2
Fires (ignition, combustion, spreading, emissions)
INLAND 2
Anthropogenic land use (deforestation)
INLAND 2
Soil fertility (P)
INLAND 2
Continental ice sheets
Subgrid tiling
INLAND 2
INLAND 2
Additional processes to be discussed
INLAND 3
CMIP5-INLAND
Results
Vegetation Type – 2050: RCP4.5, LandUSE – OFF, FIRE - OFF
CCSM4
CSIRO-Mk-3-6-0
GFDL-ESM2M
GISS-E2-R
HadGEM2-ES
IPSL-CM5A-LR
MIROC5
MRI-CGCM3
NorESM1-M
1-Tropical 2-Tropical 3-Temp. 4-Temp.
5-Temp. 6-Boreal
evergreen deciduous evergreen evergreen deciduous evergreen
broadleaf conifer
7-Boreal
deciduous
8-Mixed
forest
910-Grass.
Savanna Steppe
11-Dense 12-Open 13-Tundra 14-Desert
shrubland shrubland
15-Polar
desert /
rock / ice
Vegetation Type – 2050: RCP4.5, LandUSE – ON, FIRE - ON
CCSM4
CSIRO-Mk-3-6-0
GFDL-ESM2M
GISS-E2-R
HadGEM2-ES
IPSL-CM5A-LR
MIROC5
MRI-CGCM3
NorESM1-M
1-Tropical 2-Tropical 3-Temp. 4-Temp.
5-Temp. 6-Boreal
evergreen deciduous evergreen evergreen deciduous evergreen
broadleaf conifer
7-Boreal
deciduous
8-Mixed
forest
910-Grass.
Savanna Steppe
11-Dense 12-Open 13-Tundra 14-Desert
shrubland shrubland
15-Polar
desert /
rock / ice
Biomass – 2050: RCP4.5, LandUSE – OFF, FIRE - OFF
CCSM4
CSIRO-Mk-3-6-0
GFDL-ESM2M
GISS-E2-R
HadGEM2-ES
IPSL-CM5A-LR
MIROC5
MRI-CGCM3
NorESM1-M
Biomass – 2050: RCP4.5, LandUSE – ON, FIRE - ON
CCSM4
CSIRO-Mk-3-6-0
GFDL-ESM2M
GISS-E2-R
HadGEM2-ES
IPSL-CM5A-LR
MIROC5
MRI-CGCM3
NorESM1-M
BESM-INLAND
Results
Temperature
RCP4.5 - 2050
No fire and LU
+ fire and LU
Precipitation
RCP4.5 - 2050
No fire and LU
+ fire and LU
Dry season length
RCP4.5 - 2050
No fire and LU
+ fire and LU
Biomass
RCP4.5 - 2050
No fire and LU
+ fire and LU
reduction of upper-canopy biomass
More grasses, less trees
In Summary
•
Climate change will very likely affect most biomes in South America during this
century, but the intensity of the change is uncertain, in part because of
differences in rainfall projections.
•
Drivers of change: global warming, deforestation, fire, droughts
•
There are many uncertainties associated with the long-term effect of CO2, SST,
land use changes, aerosols, etc…
•
The role of CO2 “fertilization” is unkown and could increase resilience
•
We need to calibrate the INLAND model for Brazilian Atlantic forest
•
How to combine predictions of biodiversity with climate projections?
•
There are many issues and improvements to do!
Muito
Obrigado !