Linking IA Models and ESMs

KATE CALVIN JGCRI College Park, MD

January 6, 2016 1

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)

A. Offline One-Way Information Exchange: IAM to ESMs

January 6, 2016 3

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)

A. Offline One-Way Information Exchange: IAM to ESMs via CMIP

January 6, 2016 4

The CMIP5 Process

IPCC AR5 Chapter 12

GMT Rise in CMIP5

A. Offline One-Way Information Exchange: ESMs to IAMs

January 6, 2016 5

ESMs Provide Climate Information for IAMs

Zhou et al. (2014)

Hanasaki et al. (2014)

Nelson et al. (2014)

Energy

Water

Land

A. Offline One-Way Information Exchange: ESMs to IAMs via AgMIP

January 6, 2016 6

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

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)

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)

B. Improved IAMs

January 6, 2016 9

Source: Jones et al. (2015)

Radiative Forcing in 2100 Used CLM to Parameterize GCAM

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)

C. Improved ESMs

January 6, 2016 11

Source: NCAR

Land Component of the CESM

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)

D. Full Coupling

January 6, 2016 13

IAMs and ESMs can be Fully Coupled IMAGE + CNRM-CM3

Voldoire et al. (2007)

GCAM CESM

Collins et al. (2015)

iESM

D. Full Coupling

January 6, 2016

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

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

Ongoing & Future Research Directions

"   Workshop on IA-ESM coupling "   Improved emulators

"   Developing scenarios for improved climate science

January 6, 2016 16

THANK YOU!!!

January 6, 2016 17