Presentation by Keith Weibe, Senior Research Fellow at the International Food Policy Research Institute (IFPRI), on April 11, 2016 in Washington, DC

1. Climate change impacts on
agriculture and food security from a
global economic perspective
Keith Wiebe
Senior Research Fellow, IFPRI
Co-leader, AgMIP Global Economics Team
IFPRI Policy Seminar
Washington DC, 11 April 2016

2. Partners in global modeling
• The AgMIP Global Economics
team
• IFPRI, PIK, GTAP, Wageningen,
EC/JRC, USDA/ERS, IIASA, FAO,
OECD, UFL, NIES, …
• Global Futures & Strategic
Foresight – 15 CGIAR centers
• AfricaRice, Bioversity, CIAT, CIFOR,
CIMMYT, CIP, ICARDA, ICRAF,
ICRISAT, IFPRI, IITA, ILRI, IRRI, IWMI,
WorldFish

3. Modeling climate impacts on agriculture:
biophysical and economic effects
General
circulation
models
(GCMs)
Global
gridded crop
models
(GGCMs)
Global
economic
models
Δ Temp
Δ Precip
…
Δ Yield
(biophys)
Δ Area
Δ Yield
Δ Cons.
Δ Trade
Climate Biophysical Economic
Adapted from Nelson et al., Proceedings of the National Academy of Sciences (2014)
RCPs SSPs Food security, etc

4. Maximum temperature (°C) Annual precipitation (mm)
Climate change impacts in 2050
The case of maize yields using HadGEM (RCP8.5), DSSAT, and IMPACT (SSP2)
Change in rainfed maize yields before economic adjustments
Change in rainfed maize yields
after economic adjustments
Source: IFPRI, IMPACT version 3.2, November 2015

5. Climate change impacts in 2050
Average of 5 global economic models for coarse grains, rice, wheat, oilseeds & sugar
-10
-5
0
5
10
15
20
Yields Area Production Prices Trade
Percentchangein2050
SSP1-RCP4.5 SSP2-RCP6.0 SSP3-RCP8.5
Source: Wiebe et al., Environmental Research Letters (2015)

6. Population at risk of hunger (SSP2, RCP8.5)
Source: IFPRI, IMPACT version 3.2, November 2015
EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa

7. Climate-related deaths in 2050 (SSP2, RCP8.5)
Source: Springmann et al., The Lancet (2016)

8. Links to regional modeling
• Regional results as inputs to global modeling
• E.g. complementing pixel-level crop model results as
part of scenario definition
• Global results as inputs to regional modeling
• E.g. world prices under different socioeconomic and
climate scenarios
• Goal is not a single mega-model, but a set of
complementary tools for different scales

9. Thank you
k.wiebe@cgiar.org