Linking IA Models and ESMs - Joint Global Change … · Linking IA Models and ESMs KATE CALVIN...
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Linking IA Models and ESMs
KATE CALVIN JGCRI College Park, MD
January 6, 2016 1
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Types of IA-ESM Linkages
Method Advantages Disadvantages Examples
A Off-line information exchange, one-way
• Work with existing terminology and tools
• Transparent information exchange
• Flexibility • Separate research strategies
• Feedbacks are only captured via (one-single) iterations
• Potential inconsistencies
• CMIP • AgMIP
B Improved IAMs • Allows for good representation of uncertainty
• Model complexity tailored to question
• Detail in treatment of socio-economic processes
• Lack of detail in treatment of biophysical processes
• MAGICC calibration to CMIP
• GCAM-Albedo
C Improved ESMs • Higher resolution analyses than in IAMs
• Detail in treatment of biophysical processes
• Lack of detail in treatment of socio-economic processes
• Limitation of model runs limits representation of uncertainty
• Urban/crop component of CESM
D Full Coupling • Assessment of feedbacks • Highest degree of consistency
• Technical difficulties • Lack of representation of
uncertainty • Inflexibility • Complexity/[opaqueness] • Limitations in knowledge may
hamper progress
• iESM • IMAGE-CNRM
January 6, 2016 2
Source: van Vuuren et al. (2012)
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A. Offline One-Way Information Exchange: IAM to ESMs
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IAMs Provide Scenarios for ESMs
10
20
30
1980 2010 2040 2070 2100Year
GtC
/yr
ScenarioIS92−AIS92−BIS92−CIS92−DIS92−EIS92−F
IS92 CO2 Emissions (1994)
10
20
30
1980 2010 2040 2070 2100Year
GtC
/yr
ScenarioIS92−AIS92−BIS92−CIS92−DIS92−EIS92−FA1A1GA1TA2B1B2
SRES CO2 Emissions (2000)
0
10
20
30
1980 2010 2040 2070 2100Year
GtC
/yr
ScenarioIS92−AIS92−BIS92−CIS92−DIS92−EIS92−FA1A1GA1TA2B1B2RCP 6.0RCP 4.5RCP3−PD (2.6)RCP 8.5
RCP CO2 Emissions (2011)
0
10
20
30
1980 2010 2040 2070 2100Year
GtC
/yr
IS92−AIS92−BIS92−CIS92−DIS92−EIS92−FA1A1GA1TA2B1B2RCP 6.0RCP 4.5RCP3−PD (2.6)RCP 8.5SSP3−RefSSP4−34SSP1−26SSP1−RefSSP2−45
SSP CO2 Emissions (2016)
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A. Offline One-Way Information Exchange: IAM to ESMs via CMIP
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The CMIP5 Process
IPCC AR5 Chapter 12
GMT Rise in CMIP5
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A. Offline One-Way Information Exchange: ESMs to IAMs
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ESMs Provide Climate Information for IAMs
Zhou et al. (2014)
Hanasaki et al. (2014)
Nelson et al. (2014)
Energy
Water
Land
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A. Offline One-Way Information Exchange: ESMs to IAMs via AgMIP
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Source: Redrawn from Nelson et al. (2014) Results from the Agricultural Model Intercomparison Project
Change in Cropland Area in 2050
-2
0
2
4
6
8
10
12
14
16
18
AIM
EN
VIS
AG
E
EP
PA
FAR
M
GTE
M
MA
GN
ET
GC
AM
GLO
BIO
M
IMPA
CT
MA
gPIE
% C
hang
e fr
om R
efer
ence
IPSL - LPJmL HadGEM2 - LPJmL IPSL - DSSAT HadGEM2 - DSSAT
RCP exercise
CMIP5
ISIMIP
AgMIP
IntegratedAssessment
Models
RCPs(Global Gridded
Emissions Scenarios)
General CirculationModels
Global GriddedClimate Change
Global GriddedCrop Models
Global GriddedCrop Yields
Global EconomicModels
The AgMIP Process
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Types of IA-ESM Linkages
Method Advantages Disadvantages Examples
A Off-line information exchange, one-way
• Work with existing terminology and tools
• Transparent information exchange
• Flexibility • Separate research strategies
• Feedbacks are only captured via (one-single) iterations
• Potential inconsistencies
• CMIP • AgMIP
B Improved IAMs • Allows for good representation of uncertainty
• Model complexity tailored to question
• Detail in treatment of socio-economic processes
• Lack of detail in treatment of biophysical processes
• MAGICC calibration to CMIP
• GCAM-Albedo
C Improved ESMs • Higher resolution analyses than in IAMs
• Detail in treatment of biophysical processes
• Lack of detail in treatment of socio-economic processes
• Limitation of model runs limits representation of uncertainty
• CLM-Urban • CLM-Crop
D Full Coupling • Assessment of feedbacks • Highest degree of consistency
• Technical difficulties • Lack of representation of
uncertainty • Inflexibility • Complexity/intransparency • Limitations in knowledge may
hamper progress
• iESM • IMAGE-CNRM
January 6, 2016 7
Source: van Vuuren et al. (2012)
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B. Improved IAMs
8
ESMs are used to develop parameterized components of IAMs
Van Vuuren et al. (2009)
IAM Climate Modules
Updating IAM Climate Modules
Meinshausen et al. (2011)
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B. Improved IAMs
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Source: Jones et al. (2015)
Radiative Forcing in 2100 Used CLM to Parameterize GCAM
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Types of IA-ESM Linkages
Method Advantages Disadvantages Examples
A Off-line information exchange, one-way
• Work with existing terminology and tools
• Transparent information exchange
• Flexibility • Separate research strategies
• Feedbacks are only captured via (one-single) iterations
• Potential inconsistencies
• CMIP • AgMIP
B Improved IAMs • Allows for good representation of uncertainty
• Model complexity tailored to question
• Detail in treatment of socio-economic processes
• Lack of detail in treatment of biophysical processes
• MAGICC calibration to CMIP
• GCAM-Albedo
C Improved ESMs • Higher resolution analyses than in IAMs
• Detail in treatment of biophysical processes
• Lack of detail in treatment of socio-economic processes
• Limitation of model runs limits representation of uncertainty
• CLM-Urban • CLM-Crop
D Full Coupling • Assessment of feedbacks • Highest degree of consistency
• Technical difficulties • Lack of representation of
uncertainty • Inflexibility • Complexity/intransparency • Limitations in knowledge may
hamper progress
• iESM • IMAGE-CNRM
January 6, 2016 10
Source: van Vuuren et al. (2012)
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C. Improved ESMs
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Source: NCAR
Land Component of the CESM
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Types of IA-ESM Linkages
Method Advantages Disadvantages Examples
A Off-line information exchange, one-way
• Work with existing terminology and tools
• Transparent information exchange
• Flexibility • Separate research strategies
• Feedbacks are only captured via (one-single) iterations
• Potential inconsistencies
• CMIP • AgMIP
B Improved IAMs • Allows for good representation of uncertainty
• Model complexity tailored to question
• Detail in treatment of socio-economic processes
• Lack of detail in treatment of biophysical processes
• MAGICC calibration to CMIP
• GCAM-Albedo
C Improved ESMs • Higher resolution analyses than in IAMs
• Detail in treatment of biophysical processes
• Lack of detail in treatment of socio-economic processes
• Limitation of model runs limits representation of uncertainty
• CLM-Urban • CLM-Crop
D Full Coupling • Assessment of feedbacks • Highest degree of consistency
• Technical difficulties • Lack of representation of
uncertainty • Inflexibility • Complexity/intransparency • Limitations in knowledge may
hamper progress
• iESM • IMAGE-CNRM
January 6, 2016 12
Source: van Vuuren et al. (2012)
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D. Full Coupling
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IAMs and ESMs can be Fully Coupled IMAGE + CNRM-CM3
Voldoire et al. (2007)
GCAM CESM
Collins et al. (2015)
iESM
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D. Full Coupling
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14 14
GCAM CESM
Collins et al. (2015)
iESM Change in carbon storage when two-way feedbacks are included
!15$
!10$
!5$
0$
5$
10$
15$
2005$ 2025$ 2045$ 2065$ 2085$
Pg#C#
Year#
land$
ocean$
atm$
Jones et al. (2013)
Land Carbon Storage Across ESMs
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Ongoing & Future Research Directions
" A. Offline, one-way coupling " CMIP6 " ISI-MIP
" B. Improved IAMs " Emulators (including pattern scaling) " Natural emissions sources and other science insights
" C. Improved ESMs " Improved crop modeling " Water management
" D. Full Coupling " Continued experiments using iESM " Improved coupling
January 6, 2016 15
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Ongoing & Future Research Directions
" Workshop on IA-ESM coupling " Improved emulators
" Developing scenarios for improved climate science
January 6, 2016 16
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THANK YOU!!!
January 6, 2016 17