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Global Climate Impacts in Agriculture and Coasts Juan-Carlos Ciscar, Miles Perry, Jon Pycroft, Jan Abrell 7 th Annual Meeting IAMC, University of Maryland November 18, 2014
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Global Climate Impacts in Agriculture and Coasts€¦ · A1B$ RAHM HIGH (0.47m) (1.12m) (1.75m) China 0.08 0.18 0.27 Japan& 0.49 1.21 1.73 Korea 0.42 1.08 1.42 Indonesia 0.12 0.47

Oct 12, 2020

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Page 1: Global Climate Impacts in Agriculture and Coasts€¦ · A1B$ RAHM HIGH (0.47m) (1.12m) (1.75m) China 0.08 0.18 0.27 Japan& 0.49 1.21 1.73 Korea 0.42 1.08 1.42 Indonesia 0.12 0.47

Global Climate Impacts

in Agriculture and Coasts

Juan-Carlos Ciscar, Miles Perry, Jon Pycroft, Jan Abrell 7th Annual Meeting IAMC, University of Maryland

November 18, 2014

Page 2: Global Climate Impacts in Agriculture and Coasts€¦ · A1B$ RAHM HIGH (0.47m) (1.12m) (1.75m) China 0.08 0.18 0.27 Japan& 0.49 1.21 1.73 Korea 0.42 1.08 1.42 Indonesia 0.12 0.47

2013 European Commission Adaptation Communication, Action 4: Bridge the knowledge gap

§ “In particular, the Commission will promote EU-wide vulnerability assessments, notably by supporting the Joint Research Centre in its work on estimating the economic implications of climate change, and will undertake a comprehensive review of what global climate change will mean for the EU”

Research Question

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Approach

EU and RoW perspective: economic transmission channels (general equilibrium model) •  Trade effects (EU main trade partners)

•  Terms-of-trade (effects on relative prices, e.g. ag prices)

•  Factor mobility (across sectors and regions; migration) Review of global climate impacts •  Agriculture, coasts (from FP7 ClimateCost project)

•  Possible additional impact areas (2015)

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RoW climate impacts

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Outline

1.  The CGE model: CAGE

2.  Agriculture impacts

3.  Coast impacts

4.  On-going and planned work

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2.  1. The CGE model: CAGE

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CGE Economic modelling (CAGE)

•  Multi-sector (19), multi-country (25) Computable General Equilibrium (CGE) model, based on GTAP data •  Idealised setup without market imperfections or rigidities •  Market equilibria in long term •  Ignores short-term adjustment costs

•  CGE as an accounting framework: direct and indirect effects; includes cross-sectoral and cross-country effects

•  Comparative static framework: impact of future climate change (2080s) on today’s economy

•  Possibility of using maximum entropy to simulate impact on future economy

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2.  2. Agriculture impacts

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Agriculture model

DSSAT Yield changes for A1B (baseline) and E1 (2C) average runs Farm-level adaptation (e.g. change in crops) Assuming there is not constraint on water irrigation or fertilizers use Shocks interpreted in the CGE model as productivity changes in the agriculture sector

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Yield % change

A1B     E1    China   11   1  Japan   -­‐13   -­‐5  Korea   -­‐10   -­‐2  Indonesia   -­‐14   -­‐6  Russia   7   3  India   -­‐18   -­‐6  USA   -­‐9   -­‐3  Brazil   1   -­‐4  UK  &  Ireland   6   11  Northern  Europe   24   15  Central  Europe  (North)   -­‐2   0  Southern  Europe   -­‐20   -­‐4  Rest  of  South  Asia   -­‐21   -­‐4  Rest  of  South-­‐east  Asia   -­‐21   -­‐8  Rest  of  South  America   0   0  WORLD   -­‐5   -­‐2  

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Agriculture results, % GDP

A1B     E1    China   0.99   0.08  Japan   -­‐0.28   -­‐0.10  Korea   -­‐0.33   -­‐0.05  Indonesia   -­‐1.50   -­‐0.67  Russia   0.42   0.19  India   -­‐2.63   -­‐0.88  USA   -­‐0.07   -­‐0.02  Brazil   -­‐0.01   -­‐0.18  UK  &  Ireland   -­‐0.01   0.06  Northern  Europe   0.26   0.19  Central  Europe  (North)   -­‐0.11   -­‐0.03  Southern  Europe   -­‐0.59   -­‐0.11  Rest  of  South  Asia   -­‐2.64   -­‐0.48  Rest  of  South-­‐east  Asia   -­‐1.65   -­‐0.53  Rest  of  South  America   0.02   0.01  WORLD   -­‐0.23   -­‐0.08  

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4.  3. Coast impacts

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DIVA model

Global estimates of sea and river flood damages, land loss, salinization damages and forced migration costs Three SLR scenarios by 2080s (including very rapid SLR): 0.47m, 1.12m, 1.75m Public adaptation is not considered Shocks interpreted in the CGE model (all damage components; not just land loss) as either capital loss or additional obliged consumption

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SLR shock (total 2080s direct damage, bn$)

Floods+Salinstn+LandLoss   Migra@on  A1B   RAHM   HIGH     A1B   RAHM   HIGH    

(0.47m)   (1.12m)   (1.75m)   (0.47m)   (1.12m)   (1.75m)  China   64.2   95.8   118.4   5.7   4.5   4.5  Japan   4.8   11.3   15.2   0   6.9   4.6  Korea   11.5   20.4   23.6   0   3.8   1  Indonesia   3.2   6.8   9.8   0.1   0.6   0.5  Russia   1.6   2.3   2.8   0.4   0.3   0.2  India   24.2   30.5   36   0.7   0.5   0.6  USA   10.3   18.4   25.2   0.4   17.2   17.2  Brazil   0.9   2.3   3.8   0   0.6   0.6  UK  &  Ireland   4   7   9.1   0.3   9.1   8.2  Northern  Europe   1.6   4.3   6.4   0   3.5   3.5  Central  Europe  (North)   14.8   23.4   31.4   0.1   7.2   10.9  Southern  Europe   1.5   3   4.5   0.3   3.3   3  Rest  of  South  Asia   16.3   23.2   30.8   0.4   0.8   1.2  Rest  of  South-­‐east  Asia   41.8   82   101.5   1.2   6.6   2.4  Rest  of  South  America   20.3   24.2   28.2   0.1   0.4   0.3  WORLD   242   385   486   11   75   64  

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SLR shock (% of capital loss)

A1B   RAHM   HIGH    (0.47m)   (1.12m)   (1.75m)  

China   0.08   0.18   0.27  Japan   0.49   1.21   1.73  Korea   0.42   1.08   1.42  Indonesia   0.12   0.47   0.82  Russia   0.04   0.06   0.09  India   0.05   0.12   0.18  USA   0.28   0.57   0.9  Brazil   0.03   0.13   0.25  UK  &  Ireland   0.31   0.62   0.95  Northern  Europe   0.34   1.09   1.86  Central  Europe  (North)   1.26   2.12   3.41  Southern  Europe   0.18   0.36   0.6  Rest  of  South  Asia   0.13   0.39   0.71  Rest  of  South-­‐east  Asia   0.56   1.69   2.43  Rest  of  South  America   0.18   0.48   0.84  

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Coast results, % GDP

A1B   RAHM   HIGH    (0.47m)   (1.12m)   (1.75m)  

China   -­‐0.1   -­‐0.21   -­‐0.3  Japan   -­‐0.21   -­‐0.53   -­‐0.75  Korea   -­‐0.22   -­‐0.57   -­‐0.74  Indonesia   -­‐0.08   -­‐0.32   -­‐0.55  Russia   -­‐0.03   -­‐0.04   -­‐0.06  India   -­‐0.04   -­‐0.09   -­‐0.13  USA   -­‐0.08   -­‐0.17   -­‐0.27  Brazil   -­‐0.02   -­‐0.07   -­‐0.13  UK  &  Ireland   -­‐0.15   -­‐0.35   -­‐0.49  Northern  Europe   -­‐0.18   -­‐0.61   -­‐1  Central  Europe  (North)   -­‐0.61   -­‐1.07   -­‐1.72  Southern  Europe   -­‐0.1   -­‐0.21   -­‐0.34  Rest  of  South  Asia   -­‐0.09   -­‐0.28   -­‐0.52  Rest  of  South-­‐east  Asia   -­‐0.37   -­‐1.12   -­‐1.57  Rest  of  South  America   -­‐0.1   -­‐0.28   -­‐0.48  WORLD   -­‐0.15   -­‐0.33   -­‐0.5  

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Coast results, % Welfare

A1B   RAHM   HIGH    (0.47m)   (1.12m)   (1.75m)  

China   -­‐2.18   -­‐4.14   -­‐5.63  Japan   -­‐0.56   -­‐1.7   -­‐2.16  Korea   -­‐1.28   -­‐3.96   -­‐4.22  Indonesia   -­‐0.54   -­‐2.2   -­‐3.44  Russia   -­‐0.17   -­‐0.21   -­‐0.23  India   -­‐0.77   -­‐1.52   -­‐2.22  USA   -­‐0.18   -­‐0.58   -­‐0.79  Brazil   -­‐0.08   -­‐0.4   -­‐0.66  UK  &  Ireland   -­‐0.37   -­‐1.29   -­‐1.58  Northern  Europe   -­‐0.57   -­‐2.56   -­‐3.68  Central  Europe  (North)   -­‐1.38   -­‐2.71   -­‐4.24  Southern  Europe   -­‐0.23   -­‐0.61   -­‐0.88  Rest  of  South  Asia   -­‐0.98   -­‐3   -­‐5.2  Rest  of  South-­‐east  Asia   -­‐3.3   -­‐10.42   -­‐12.91  Rest  of  South  America   -­‐0.46   -­‐1.31   -­‐2.14  WORLD   -­‐0.54   -­‐1.4   -­‐1.91  

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1.75m SLR, % Welfare

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4.  4. On-going and planned work

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Possible extensions

Energy River floods Human health Exploratory work on human migration

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Rigidities in CGE model (ECONADAPT project)

Elasticities of substitution Adjustment costs in good and factor markets Factors mobility Other structural features

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FP7 HELIX Project

High-End cLimate Impacts and eXtremes (HELIX), 4 years, 16 partners, coordinated by MetOffice, UK

•  What do 4ºC and 6ºC worlds look like compared to 2ºC? •  What are the consequences of different adaptation

choices?

Impacts and adaptation at 2ºC, 4ºC, 6ºC •  Global •  Europe, Sub-Saharan Africa and the South Asia Impacts covered: River floods, Water availability, Agriculture,

Ecosystems, Coastal flooding, Energy, Transport, Human health (additionally: Food security and Migration)

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