Higher-Resolution IA Models

LEON CLARKE

November 13, 2015

Presented  at  the  Third  Mee.ng  of  the  Commi4ee  on  Assessing  Approaches  to  Upda.ng  the  Social  Cost  of  Carbon          

Higher-Resolution IA Models

Higher-Resolution Integrated Assessment (IA) Models

!   Capture interactions between complex and highly nonlinear systems

!   In the context of mitigation, they

have traditionally focused on cost-effectiveness analysis

!   They are increasingly being used to explore climate impacts, with a particular focus on energy-water-land interactions

!   They are part of a larger stream of IA research that includes multi-model approaches to bridge scales

Human Systems

Natural Earth Systems

ENERGY

Economy Security

Settlements

Food

Health

Managed Ecosystems

TechnologyScience

TransportPopulation

Sea Ice Carbon Cycle

Earth System Models

EcosystemsOceans

Atmospheric Chemistry

Hydrology

Coastal Zones

Higher-Resolution IA Models and Teams

Model   Home  Ins,tu,on  

AIM  Asia  Integrated  Model  

Na.onal  Ins.tutes  for  Environmental  Studies,  Tsukuba  Japan  

GCAM  Global  Change  Assessment  Model  

 

Joint  Global  Change  Research  Ins.tute,  PNNL,  College  Park,  MD  

IGSM  Integrated  Global  System  Model  

 

Joint  Program,  MIT,  Cambridge,  MA  

IMAGE  The  Integrated  Model  to  Assess  the  Global  

Environment    

PBL  Netherlands  Environmental  Assessment  Agency,  Bildhoven,  The  

Netherlands  

MESSAGE  Model  for  Energy  Supply  Strategy  Alterna.ves  and  

their  General  Environmental  Impact  

Interna.onal  Ins.tute  for  Applied  Systems  Analysis;  Laxenburg,  Austria  

REMIND  Regionalized  Model  of  Investments  and  Technological  

Development  

Potsdam  Ins.tute  for  Climate  Impacts  Research;  Potsdam,  Germany  

Japan: The Asia Integrated Model (AIM)

2000

2050

2100

structure  of  AIM/CGE

production  factormarket

capital

laborland

Final  demand  sector

resource

Production  sectors

produced  commoditymarket

food

serviceenergy

...

tradeJapan

China...

Energy  technology  model:  energy  efficiencyAgriculture  model:  land  productivity

...

Annual  parameter  change

GHGsemissions

GHGsemissions

climatechange

feedbackeg.  land  productivity  change  due  to  climate  changescenarios:  population,  GDP,  ...  

25 http://www.mnp.nl/image

Socio-economic system: 24 / 26 world regions

Environmental system: 0.5 x 0.5 degree

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The Energy System

Agriculture and Land Use

The EconomyRegional

Labor ForceRegional GDP

Regional Labor

Productivity

Energy Demand

Technologies

Energy Demand

Regional Resource

Bases

Regional Energy

Conversion Technologies

Energy Supply

Energy Markets

Energy Production.

Transformation & Use

GHG Emissions

Demand•Crops•LivestockForests products

SupplyRegional Land Categories and Characteristics

Ag-Land Markets

Production•Crops•Livestock•Forests products•Biomass energy

Commercial Biomass

Land Use ChangeEmissions

Technology

Land Use•Crops•Livestock•Managed Forests•Unmanaged

•Crops•Livestock•Biocrops•Foresty Products

•Land rent•Crop prices•Livestock prices•Forest product prices•Biomass prices

Terrestrial Carbon Cycle

Atmospheric Composition,

Radiative Forcing, & Climate

Ocean Carbon Cycle

Geospacially explicit land use data

Geospacially energy supply data14-region GCAM aggregations

GCAM

The Global Change Assessment Model (GCAM): A Higher-Resolution IA Model

283 Land Regions

32 Energy Economy Regions

233 Water Basins

! GCAM  is  a  global  integrated  assessment  model  ! GCAM  links  Economic,  Energy,  Land-­‐use,  Water,  and  Climate  systems  

! Meant  to  analyze  consequences  of  interdependencies  between  human  and  Earth  systems  

! Runs  in  5-­‐year  ,me-­‐steps.  ! GCAM  is  a  community  

model  ! Documenta.on  available  

at:  wiki.umd.edu/gcam  

! Socioeconomic  development  ! Effects  of  climate  ! Technology  and  resource  

developments  ! Energy  and  other  policies  

Data Development System

Disaggregation Models

GCAM Core: Dynamic Integration

   IA Models Have Become Increasingly Complex Over the Last 30 Years

283 Land Regions

32 Energy Economy Regions

233 Water Basins

Province-Level Energy Economy

Regions

Automation System

Reduced-Form Climate Model

EIA IEA

GTAP HYDE

SAGE OECD

FAO IMAGE

MIRCA Aquastat

USDA USGS

CDIAC IIASA

Papers: Houghton, Rogner, others

Others

Digital Map of Irrigated

Areas MODIS

Union of Concerned Scientists

Gridded Livestock of the World

Others

Papers: Friedl, Portmann, Sleeter, Radeloff, others

Inputs and Output

Scenario  Outputs  

!   Prices and production quantities: !   Energy sectors !   Transportation !   Primary energy resources !   Agricultural products

!   Land use !   Crops (by type) !   Pasture !   Unmanaged

!   Water demand !   Raw demand by sector !   Response to scarcity

!   Greenhouse gases !   Economic indicators

!   Economic losses !   Income transfer

Scenario  Assump,ons  

!   Socioeconomic assumptions

!   Energy, land use, and water technologies

!   Policies !   Resources

Climate and Highly-Resolved IA Models

Closing the Climate in IA Models

9  

Energy Water Land Socio-

Economics

Climate

Strategies  for  climate  mi.ga.on  

Climate  effects  on  human  systems  

The Challenges of Full-Coupling in Highly-Resolved IA Research

10  

Energy Water Land Socio-

Economics

Climate

Challenge  1.  Spa.ally-­‐  and  temporally-­‐resolved  climate  informa.on  that  effec.vely  represents  uncertainty  

Challenge  2.  Intermediate  Responses  (e.g.,  response  surfaces  for  agricultural  yields)  

Challenge  3.  “Hooks”  to  take  on  climate  or  intermediate  informa.on  in  IA  models,  incorpora.ng  higher-­‐resolu.on  phenomenon    

A Range of Ways to Treat Climate Impacts

Process  Representa,on   Parameterized  Impacts  

Large  Energy-­‐Water-­‐Land  Focus  

Producer  of  Damage  Informa,on  

Consumer  of  Damage  Informa,on  

Impact on Building Energy Expenditures

12  

!100$

!50$

0$

50$

100$

150$

200$

0$ 1000$ 2000$ 3000$ 4000$ 5000$ 6000$ 7000$ 8000$2005$USD

$per$cap

ita$

million$persons$

2100$

Brazil$ Middle$East$&$N.$Afr.$ Other$Asia$

Other$La@n$America$ USA$ India$

China$ Sub!Saharan$Africa$ Pacific$OECD$

Europe$ Russia$ Canada$

!200$ !100$ 0$ 100$ 200$ 300$ 400$

USA$Canada$Russia$Europe$

Oth.$Lat.$Amer.$Brazil$

Sub!Sah.$Afr.$Mid.$E.$&$N.$Afr.$

Other$Asia$Pacific$OECD$

India$China$

Global$average$

2005$USD$per$person$

2100$

!200$ !100$ 0$ 100$ 200$ 300$ 400$

USA$Canada$Russia$Europe$

Oth.$Lat.$Amer.$Brazil$

Sub!Sah.$Afr.$Mid.$E.$&$N.$Afr.$

Other$Asia$Pacific$OECD$

India$China$

Global$average$ 2050$

Comm.$Cooling$Comm.$HeaOng$Resid.$Cooling$Resid.$HeaOng$Net$

Change in energy expenditures for heating & cooling

Climate data from CCSM A2 scenario

Impact on Building Energy Expenditures

0.00%$

0.02%$

0.04%$

0.06%$

0.08%$

0.10%$

0.12%$

0.14%$

0.16%$

0.18%$

0.20%$

0$ 1$ 2$ 3$ 4$ 5$ 6$Degrees&C&

830:$2030$

830:$2050$

830:$2075$

830:$2100$

550:$2030$

550:$2050$

550:$2075$

550:$2100$

Figure  12:  Global  average  addi.onal  expenditures  per  unit  of  income  on  hea.ng  and  cooling  as  a  func.on  of  the  increase  in  global  average  surface  temperature  from  2010.    

Water Demands in GCAM

(1) Hejazi et al. (2013). Hydrological Sciences Journal (2) Kyle et al. (2013). Int. J. of Greenhouse Gas Control (3) Davies et al. (2013). Advances in Water Resources (4) Chaturvedi et al. (2013). Mitigation & Adaptation Strategies for Global Change. (5) Hejazi et al. (2014). Technological Forecasting and Social Change (6) Kim et al. (in review). Climatic Change

(4)    (2,3)    (1)    

(5)    (6)    

Instream  flow  requirements  

GCAM tracks water demands for several sectors, subsectors, and technologies, &

at various spatial scales

Transforming Climate Information to Streamflow

! Requires climate information from GCMs as inputs

! Monthly temporal scale ! 0.5x0.5 degree spatial

resolution

Major basins

Hejazi et al. 2014. Hydrology & Earth Sys. Sc.

! Global hydrologic model ! Modified River Transport

Model scheme ! 233 Basins

What are the Implications of Different Land Use and Bioenergy Pathways on Water Scarcity?

!  Human system dynamics have a critical influence on future water scarcity

!   The percent of global population living in grids classified as water scarce in 2095 depends substantially on the role of bioenergy in future pathways.

Δpop  =  -­‐3.6%  

Δpop  =  +8.4%  Hejazi  et  al.  2014.  Hydrology  &  Earth  Sys.  Sc.  

Extreme  biomass  produc.on  scenario  

Limited  biomass  produc.on  scenario  

Figures  show  water  scarcity  associated  with  different  pathways  toward  roughly  4  W/m2  rela.ve  to  a  higher-­‐emissions  reference  scenario  leading  to  forcing  of  roughly  8.5  W/m2.  Scarcity  defined  as  annual  water  demand  over  annual  water  supply.  

Linked model experiments will be a key approach for integrated assessment

17

Linking GCAM-USA, a regional Earth system model, and a coupled hydrology-water management model,

Annual county scale water deficit as a fraction of demand

Hejazi,  Mohamad  I.,  et  al.  "21st  century  United  States  emissions  mi.ga.on  could  increase  water  stress  more  than  the  climate  change  it  is  mi.ga.ng."  Proceedings  of  the  Na.onal  Academy  of  Sciences  112.34  (2015):  10635-­‐10640.  

The emerging frontier – fully coupled water supplies and demands within an integrated framework

!  Adaptive decisions to water scarcity will alter agricultural and land use patterns

!  Non-renewable groundwater availability and extraction costs are key determinants of withdrawal projections.

Kim et al. (accepted). Climatic Change

Percent changes in wheat production in 2100

!   Question: What is the effect of climate change on agriculture and land use?

!   Key Results: The inclusion of changes in climate, without CO2 fertilization, results in an expansion of cropland globally.

Climate Change Could Alter the Extent of Cropland Area Required to Feed a Growing Population

Change in Cropland Area in Response to Climate Change

Source: Redrawn from Nelson et al. (2014) Results from the Agricultural Model Intercomparison Project

-2

0

2

4

6

8

10

12

14

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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

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0

20

40

60

80

100

120

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160

180

200

2005 2020 2035 2050 2065 2080 2095

EJ/y

r RCP8.5 RCP6.0 RCP4.5 RCP2.6 RCP8.5, with Impacts RCP6.0, with Impacts RCP4.5, with Impacts RCP2.6, with Impacts

Agriculture Impacts

Source: Kyle, P., C. Mueller, K. Calvin and A. M. Thomson (2014). "Meeting the Radiative Forcing Targets of the Representative Concentration Pathways in a World with Agricultural Climate Impacts." Earths Future 2(2): 83-98.

Global purpose grown bioenergy production

Many More Examples of IA Impacts Analysis

Hydropower  

Ocean  Acidifica,on  

Water  Temperature  and  Thermal  Cooling  

From:  Water  Body  Temperature  Model  for  Assessing  Climate  Change  Impacts  on  Thermal  Cooling,  Ken  Strzepek,  Charles  Fant,  Yohannes  Gebretsadik,  Megan  Lickley,  Brent  Boehlert,  Steven  Chapra,  Eric  Adams,  Andrzej  Strzepek  and  C.  Adam  Schlosser  

21

IGSM-CAM CS3-REF

IGSM-CAM CS3-POL3.7

MIROC CS3-REF

MIROC CS3-POL3.7

Figure 13. Changes in withdrawal allowed for HUCs with once-through cooling technology in 2050.

IGSM-CAM CS3-REF

IGSM-CAM CS3-POL3.7

MIROC CS3-REF

MIROC CS3-POL3.7

Figure 14. Changes in withdrawal allowed for HUCs with recirculating cooling technology in 2050.

Challenge: Climate Variability and Extreme Events

Electricity  investments  need  to  consider  the  confluence  of  demand  increasing  and  supply  decreasing  effects:  •  heat  waves  effec.ng  both  

supplies  and  demands  •  low  wind  •  droughts    Along  with  demand  management,  storage,  infrastructure  more  generally    

BoNom  line:  For  IA  research  to  explore  these  factors,  it  needs  to  address  events  taking  place  on  the  ,me  scale  of  days  to  weeks  to  years  and  at  local  to  regional  scales.  

Example:  Electricity  Impacts  

The Shared Socioeconomic Pathways

6000

7000

8000

9000

10000

11000

12000

13000

SSP1

SSP2

SSP3

SSP4

SSP5

Popula,on  SSP  3  

SSP  4  SSP  2  

SSP  5  SSP  1  

SSP1   Fast  

SSP2   Central  

SSP3   Slow  

SSP4   Fast/Central  

SSP5   Fast  

Urbaniza,on  

0

20

40

60

80

100

120

140

160

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

GDP  pe

r  cap

its  ($/cap

 -­‐PP

P)

GDP/cap  

     SSP  1:  Sustainability  

         SSP  3:  Fragmenta.on  

         SSP  4:  Inequality  

           SSP  5:  Conven.onal  Development  

         SSP  2:    Middle  of  the  Road  

SSP  3  

SSP  4  SSP  2  

SSP  5  

SSP  1  

China  

Eastern  Africa  

La.n  America  

Western  Europe  

Working  Group  III  contribu.on  to  the  IPCC  Fioh  Assessment  Report  

Emissions  and  concentra,ons  are  expected  to  con,nue  to  rise  despite  improvements  in  technology.  

! !

Global GHG Emissions Global GHG Concentrations

Global mean surface temperature increases in 2100 in baseline scenarios…range from 3.7°C to 4.8°C above the average for 1850–1900 for a median climate response. They range from 2.5°C to 7.8°C when including climate uncertainty (5th to 95th percentile range)

4.5°F to 14°F

The Challenges of Full-Coupling in Highly-Resolved IA Research

25  

Energy Water Land Socio-

Economics

Climate

Challenge  1.  Spa.ally-­‐  and  temporally-­‐resolved  climate  informa.on  that  effec.vely  represents  uncertainty  

Challenge  2.  Intermediate  Responses  (e.g.,  response  surfaces  for  agricultural  yields)  

Challenge  3.  “Hooks”  to  take  on  climate  or  intermediate  informa.on  in  IA  models,  incorpora.ng  higher-­‐resolu.on  phenomenon    

Questions