Economic effects of climate change in the agricultural sector towards a closed-loop assessment

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Lisa Burke
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1 Economic effects of climate change in the agricultural sector towards a closed-loop assessment Franziska Piontek Miodrag Stevanovic, Nico Bauer, Hermann Lotze-Campen, Alexander Popp, Jan Philipp Dietrich, Christoph Müller

Reduced form damage functions No interaction with preceding levels How

2 Motivation & aim Biophysical models Direct connection to GCMs Detailed representation of biophysical processes High resolution impacts IAMs Reduced form damage functions No interaction with preceding levels How can we synthesize detailed and vast results from impact models for policy makers? 2

3 Loop GHG emissions Temperature change Simplified climate model Integrated assessment model CO 2 Climate change e.g. demand, prices Impacts Impact model 3

Attempt @ PIK focus agricultural damages GCMs IAM ReMIND-R Biomass demand, GHG price LUC emissions, biomass price CC damages CO 2

4 PIK focus agricultural damages GCMs IAM ReMIND-R Biomass demand, GHG price LUC emissions, biomass price CC damages CO 2 Agro-economic model MAgPIE Climate change Land use pattern CO 2 Climate change Biophysical crop model LPJmL Constraints on yields, water, land 4

5 Where are we now? work in progress, multiple work streams LPJmL level: ISI-MIP results 5 GCMs 4 RCPs Runs with/without CO2 fertilization and irrigation 12 crops in analysis phase Why ISI-MIP? - CMIP5 data - Cross-sectorally consistent - Impact model uncertainty MAgPIE/ReMIND-R level: data from GLUES project UKMO GCM, SRES A2 Testing sensitivites and concept All results preliminary! Goal: use SSP framework 5

6 Step 1: Climate change impacts in LPJmL 6

Relative change in calorie availability 2069-2099 vs. 1980-2010 HadGEM2-ES RCP 8.

7 Relative change in calorie availability vs HadGEM2-ES RCP 8.5 No CO 2 fertilization 12 crops: wheat, rice, maize, soy, cassava, millet, groundnuts, rapeseed, sugar beet, sugar cane, sunflower, field peas Preliminary Preliminary 7

8 Step 2: Agricultural damages in MAgPIE 8

9 Concept of damages in MAgPIE regional level Total costs = production costs for livestock and crop production + costs of technological change to increase yields + land conversion costs + intraregional transport costs Change in supply Change in consumer & producer surplus Sum = change in total welfare 9

10 Agro-economic effects of climate change in MAgPIE UKMO, no CO 2 fertilization, SRES A2 Global climate change impact in % of GDP Preliminary Results from Stevanovic et al. (in preparation) 10

11 Regional effects % of agricultural GDP in 2085: Preliminary NAM: +35.1% FSU: +1.9% EUR: +4% PAO: -9.4% LAM: -6.8% PAS: -4.7% CPA: -5% AFR: -9.5% SAS: -15.7% MEA: -64.7% 11

12 Step 3: Input of agricultural damages in ReMIND-R 12

13 Method & problems GDP(t,r) export(t,r) + import(t,r) = consumption (t,r) + investment(t,r) + ESM costs(t,r) * Damages(t,r) = losses as % of GDP from MAgPIE results Currently only informing ReMIND-R! Problem: different regions 13

14 GDP difference [%] First results Preliminary 2010 Time

15 Conceptual challenges Mix of positive and negative impacts on biophysical level within regions Importance of impact differs when taking into account importance of agricultural sector regions with large agricultural GDP are those with smallest overall GDP Distribution issues: Consumer vs. producer side Variety of incomes in/between regions 15

16 Intermediate step: aggregation and equity 16

17 Intermediate step: equity Goal 2: apply equity weighting schemes from Frankhauser et al (for a utilitarian welfare function) Damage GDP > < world more average than doubles GDP, positive for e=1.5 CC impact Welfare change in 2085 [tr $] 17

18 Weighting with per capita GDP 0.5 unweighted damage e=0.5 e=1.0 e= AFR CPA EUR FSU LAM MEA NAM PAO PAS SAS Larger range, largest factors for SAS, AFR, CPA, MEA 18

19 Conclusions & next steps We have: 1st steps towards improving studies of CC damages by directly coupling biophysical and economic models Consistently trace effects from LPJmL via MAgPIE to ReMIND- R Clear need to look deeper into aggregation and weighting of damages this gives opportunity to do so! 19

20 Conclusions & next steps We need: Grid-based damages from MAgPIE Better integration of this in ReMIND-R Feedback via simplified climate model or impact functions? 20

21 Possible derivation of impact functions? Δyields [%] Relative change in wheat yields for 4 GCMs, all RCPs ( vs ) AFR MEA CPA PAO EUR SAS With (green) and without (blue) CO2 fertilization LAM FSU PAS Preliminary NAM global ΔGMT [ C] 21

22 Conclusions & next steps We need: Grid-based damages from MAgPIE Better integration of this in ReMIND-R Feedback via simplified climate model or impact functions? Extension to other sectors Links to : ISI-MIP cross-sectorally consistent impact and uncertainty assessment, impact functions SSP framework adaptation, aggregation 22

23 Thank you! 23

What can we say about global agriculture and what does it take: The global landuse model MAgPIE. 11. October 2011 Anne Biewald

What can we say about global agriculture and what does it take: The global landuse model MAgPIE 11. October 2011 Anne Biewald Outline A description of MAgPIE Policy relevant questions Technical details