Future projection of water, food, bio‐energy, ecosystem and land

investigated with anIntegrated Earth System Model

(MIROC‐INTEG)Tokuta YOKOHATA (NIES), Tsuguki Kinoshita (Ibaraki University),

Gen Sakurai (National Agriculture and Food Research Organization), Yadu Pokhrel (Michigan State University), Akihiko

Ito (NIES), Yusuke Satoh (NIES), Etsushi Kato (The Institute of Applied Energy), Shinichiro Fujimori (Kyoto University and NIES), Kaoru Tachiiri (Japan Agency for Marine‐Science and

Technology), Tomohiro Hajima (Japan Agency for Marine‐Science and Technology), Kiyoshi Takahashi (NIES),

Naota Hanasaki (NIES), Seita Emori (NIES)

Interaction of natural‐human system

Visualizing the interconnection of climate risks, Yokohata et al. 2019, Earth’s Future

Impact of climate change on land(IPCC 2019, Climate Change and Land)

• Larger temperature increase• Decrease/increase in water

– drought, water stress / flooding• Desertification / land degradation• Decline in crop production• Expansion of cropland area• Mitigation / adaptation responses

– Forest management– Bioenergy cropland / carbon sequestration

Impact of land use change on climate(IPCC 2019, Climate Change and Land)

• Biophysical effects– soil moisture decrease ‐> evaporation decrease

‐> increase in surface air temperature– soil albedo increase ‐> solar absorption

decrease ‐> decrease in surface air temperature• Biogeochemical effects

– decrease in forest ‐> decrease in carbon sink ‐> increase in air temperature

IPCC 2019, Climate Change and Land, Chapter 2

BiophysicalBiogeochemical

Impact ofLand use change

BiophysicalBiogeochemical

Impact ofDeforestation 〇Afforestation *

IPCC 2019, Climate Change and Land, Chapter 2

BiophysicalBiogeochemical

BiophysicalBiogeochemical

Impact ofLand use change

Impact ofDeforestation 〇Afforestation *

Two‐way interaction between climate and land: Global warming ‐> function/state of the land

Land/Land use ‐> climate changeUnderstanding of two‐way interaction can help

improve adaptation/mitigation strategies, as well as manage landscape

This study• Coupling of state‐of‐the‐art global models:

Climate (MIROC, Watanabe et al. 2010), Land ecosystem (VISIT, Ito and Inatomi 2012), Water resource (HiGW‐MAT, Pokhrel et al. 2015),Crop growth (PRYSBI2, Sakurai et al. 2014),Land use (TeLMO, Yokohata et al. 2019)

– Sub‐models: contributed to CMIP / ISIMIP / AgMIP• Historical simulations

– Validation of model• Future simulations

– Socio‐economic & climate scenario– Interaction of water, food, bio‐energy, and land use

MIROC‐INTEG (Yokohata et al. 2019)(MIROC INTEGrated terrestrial model)

Eco‐systemThe exchange of C and Nbetween atmosphere‐vegetation‐soil is calculated. Changes in GHG are estimated.

Greenhouse gasbudget

CO2 emissions from forest fire

CO2 emissionsfrom land use

Water use（Agriculture, etc.）

Water resourcesWater use by human activity (agriculture, industry) is estimated. Irrigation from river is considered.

Crop growthCrop yield is estimated . The production of bio‐energy crop for mitigation option is considered.

Crop productivity

Afforestation/deforestation

Land useLand‐use change (cropland‐forest) is calculated based on future socio‐economic scenarios. Economic (e.g., trade) +natural (e.g. inclination) factors are considered.

Climate (Land surface)Soil water, temperature are

calculated based on the water and energy budget.

Atmospheric processes (precipitation etc) is option.

Global, 0.5‐1 degree

Climate (Land)

Water resource

Crop growth

Irrigation

Water withdrawal

Reservoir operation

Soil water/temperature

Crop yieldCroplandarea

Land useIrrigationarea

Land ecosystem

Cropland areaLand use transition

Demand (food/bioenergy etc)GDPPopulation

Demand (water)

Socio‐economic scenario

GDP (technical factor)

Climate scenario

Atmosphere

Socio‐economic scenario

Climate scenario

Atmosphere

MIROCWatanabe et al. 2010

Output of integrated assessment model, AIM

TeLMOYokota et al. 2019

HiGWMATPokhrel et al. 2014

PRYSBI2Sakurai et al.

2014

VISITIto and Inatomi

2012

ISIMIP“Forcing”

Output of AIM

Land use model: TeLMO(Yokohata, Kinoshita et al. in prep)

1. Definition of Agricultural Suitability Index (ASI)ASI = 1./(1.+exp(‐(‐1.228‐0.237*slope

+0.206*(priceagr/GDPpc*yield))))slope: slope at 30sec grid, priceagr: agricultural price (ratio to 2005), GDPpc:

GDP per capita, yield: crop yield

2. Calculation of threshold of ASI = ASIthASI > ASIth, then the land is used for cropland

ASIth is determined from the cropland area @ 2005

3. Calculation of priceagr by a general equilibrium modelAgricultural Demand = Production + Import (for 17 regions)

Demand data is calculated in AIM, Supply data is calculated based on (yield * cropland area)

3. Calculation of cropland area where ASI > ASIth

Food cropland area INTEG vs AIM vs FAO‐Stat (2005‐2015)

MIROC‐INTEG (TeLMO), AIM/CGE (IAM, used as input), FAO‐Stat

USA

Russia

China

Brazil Global

Australia

Future simulations• Climate scenario (ISIMIP1)

– Atmospheric output from climate model• 5GCMs (GFDL, MIROC, HadGEM, IPSL, NorESM)

– Representative Concentration Pathways (RCP)• RCP8.5, RCP4.5, RCP2.6

• Socio‐economic scenario– Shared Socio‐economic Pathways (SSP)

• SSP1, SSP2, SSP3 • Output of Integrated Assessment Model, AIM/CGE

SSP2 (middle of the road)

RCP2.6, 4.5, 6.0, 8.5

1. Changes in climate systemSSP2: RCP8.5 RCP6.0 RCP4.5 RCP2.6

RCP8.5RCP6.0RCP4.5RCP2.6

Temperature change [K] Soil moisture change [mm]0‐300mmThin = 5GCMs forcing

Thick = Ave. of 5GCMs

Soil moisture decreasesIn RCP8.5

2. Changes in crop yieldSSP2: RCP8.5 RCP6.0 RCP4.5 RCP2.6

RCP8.5RCP6.0RCP4.5RCP2.6

Thin = 5GCMs forcingThick = Ave. of 5GCMs

Crop yield increases due to fertilization effect

Crop yield decreases due to climate change

3. Changes in food cropland areaSSP2: RCP85 RCP60 RCP45 RCP26

Food cropland area [ratio](Global land area =1.0)

After 2060, in RCP85, yield decrease→ cropland area increase

Crop yield change [t/ha](Grid maximum)

Before 2050, crop yield increasesdue to fertilization effect

After 2060, crop yielddecreases due to

climate change

3. Changes in food / bioenergy cropland areaΔ Food cropland area, RCP2.6 Δ Food cropland area, RCP8.5

Δ Bioenergy cropland area, RCP2.6 Δ Bioenergy cropland area, RCP8.5

Anomaly 2100 ‐ 2005

4. Changes in biomass / soil carbon by LUCΔ Biomass, LUC‐noLUC, RCP2.6 Δ Biomass, LUC‐noLUC, RCP8.5

Δ Soil carbon, LUC‐noLUC, RCP2.6 Δ Soil carbon, LUC‐noLUC, RCP8.5

5. Biogeochemical effect by cropland changeSSP2: RCP85 RCP60 RCP45 RCP26

Biogeochemical effect:cumm. CO2 emission [GtCO2]

Food+BioE cropland area [ratio](Global land area = 1.0)

CO2 cumulative emission Increases due to

expansion of cropland area

SSP1 (sustainability)SSP2 (middle of the road)

SSP3 (Regional rivalry)

Food cropland area [Mha] vs IAMs Baseline RCP45 RCP26

SSP1SSP2SSP3

Popp et al. 2017

↑2005

↑2005

CO2 cumm. emission [GtCO2] vs IAMs Baseline RCP45 RCP26

SSP1SSP2SSP3

Popp et al. 2017

↑2005

↑2005 CO2 cumulative emission due to land use change is

underestimated compared to IAMs(Forestation is not considered in land use model TeLMO)

Irrigation demands [kg/yr]Baseline RCP45 RCP26

SSP1SSP2SSP3

Irrigation for food cropland area is calculated in the modelCropland expansion in SSP3 ‐> large water stress

Climate (Land)

Water resource

Crop growth

Irrigation

Water withdrawal

Reservoir operation

Soil water/temperature

Crop yieldCropland

area

Land useIrrigationarea

Land ecosystem

Cropland areaLand use transition

Soil moisture decrease Yield decrease

Cropland areaincrease

Increase in water demands

Nexus of climate, crop, water, land, ecosystem

Impacts on ecosystem

Carbon sinkdecrease

Summary and discussions• Integrated terrestrial model is developed

– Climate change ‐> crop yield ‐> land use ‐> land ecosystem ‐> water resource ‐> climate change

– Yokohata et al. 2019, Geosci. Model. Dev. Discussions• Next step

– Improvement of the Earth‐human system models• Feedback from Atmosphere‐ocean system• Coupling of Integrated Assessment Model, AIM/CGE

– Evaluation of mitigation/adaptation responses• management of water, forest, agriculture

– Response of earth system to human activity• Overshoot scenario• Tipping elements / planetary boundary / hothouse earth

End

Bioenergy cropland area [Mha] vs IAMs

SSP1SSP2SSP3

Popp et al. 2017

Baseline RCP45 RCP26

Food cropland area INTEG vs AIM vs FAO‐Stat (2005‐2015)

India USA Russia

China Brazil Canada

NigeriaIndonesiaAustralia

Argentina GlobalMIROC‐INTEG (TeLMO)AIM (IAM, used as input)FAO‐Stat

MIROC‐INTEG1 Yokohata etal(2019)

TeLMO (Land)HiGW‐MAT

(Water)

MIROC (climate)PRYSBI2 (crop)

VISIT (ecosystem)

Land cover, water demand

Crop yield, temperature,

moisture

Calvin and Bond‐Berry 2018, ERL

Coupling of natural‐human process models(e.g., Robinson et al. 2018, Muller‐Hansen et al. 2018)

• Integrated Assessment Models (IAM)– Energy supply/demand on whole economic transactions– Natural processes are simplified

• Earth‐system models (ESM) + human component– iESM (integrated ESM, Collins et al. 2015)

• Earth system + Integrated assessment model (CESM+GCAM)• Impact model (crop growth etc) is simplified

– LPJ‐GUESS, IMOGEN, PLUMv2 (Robinson et al. 2018)• Vegetation + climate emulator + land use model• Climate processes are simplified