Upload
gerald-nelson
View
121
Download
2
Tags:
Embed Size (px)
Citation preview
Scenario-based assessment of climate
change impacts on agriculture
Gerald C. NelsonProfessor Emeritus, University of Illinois,
Urbana-Champaign
Presentation at the AAAS session “New Scenarios for Assessing Future Climate Change”, 26 February 2014
… or how we used the SSPs (and an RCP) in a model intercomparison
exercise
… or should we do any more integrated
assessments until we fix the Lamppost problem
Policy questions that need scenario answers
What is the future of agricultural prices?
How will agricultural production evolve?
How will climate change alter …PricesLand useTradeUndernourishment
Do we have the tools to answer these questions?
Alternate perspectives on future prices with no climate change, 2000-2050 in
2011
IMPACT – big price increases (e.g. 80% increase in coarse grains price)
Why do the results differ?Differing perspectives on
Today’s unknowns that we should know Future unknowns
Economic development Population growth Climate change Natural resource availability Technological advance
Differing economic modeling approaches CGE models more ‘flexible’ (?) Functional forms determine outcomes (e.g., Armington
assumption, demand parameters; ref Bennett’s Law)
We had no idea which is most important
Scenario harmonization:Common values for key drivers
Harmonized four key drivers Population from SSP2 and 3 GDP from SSP2 and 3 Exogenous component of agricultural yield growth Climate change effects on yield growth
No harmonization on other important drivers
Three ‘orthogonal’ comparisons in 2050 Socioeconomics – SSP2 versus SSP3 Bioenergy policies – not covered here Climate change – no climate change versus RCP 8.5 with
no CO2 fertilization
SSPs: What did we use and why?What?
SSP2 and SSP3, version 0.5GDP, OECD version Population
What not?StorylinesPopulation makeupUrbanization
Why?
SSP per capita incomePer capita incomes in 2010;
SSP2 and SSP3 in 2050
Wor
ld
Develop
ing E
ast A
sia
South
Asia
Euro
pe & C
entra
l Asia
WB d
efiniti
ons
Mid
dle E
ast &
Nor
th A
frica
Sub-Sah
aran
Afri
ca
Latin
Am
erica
& C
arib
bean
High In
com
e0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
2010 SSP2 SSP3
The modeling chain:From biophysical to
socioeconomic
Nelson, et al., PNAS 2013
Results: price changes between 2005 and 2050
are smaller, but…
Maximum price changes between 2005 and 2050 reduced. Large differences remain.
General equilibrium Partial equilibrium
2050 price effects from the socioeconomic
scenarios, with no climate change
Model differ dramatically in their responses to the negative future of
SSP3
Price declines
Price increases
Price not affected
Climate change and economic responses
Quantity
Price
Demand
Supply
Climate change shifts supply to the left
Initial shortage caused by climate
change
Initial shortage =
big price increase
Final quantity
Final
pri
ce
Model choices- Supply response?
- Area- Yield
- Demand response?- Where?- How much trade?
Results from the climate change scenarios
Comparisons are differences in 2050 outcomes
Mean -17% -11% +11% -2% - 1% -3% +20%
Climate change reduces 2050 yields. Producers, consumers, & trade
partially compensate
Nelson, et al., PNAS 2013
Finalyield
Biophysicaleffect
How do the model distribute their 2050 responses to climate change?
Mostly area
Mostly yield
Demand Area YieldDemand/Supply
Model Type
AIM 0.12 0.90 -0.02 0.14 CGE
ENVISAGE 0.17 0.32 0.51 0.2 CGE
FARM 0.04 0.67 0.29 0.04 CGE
GTEM 0.06 0.29 0.65 0.06 CGE
MAGNET 0.1 1.39 -0.49 0.11 CGE
GCAM 0.22 0.78 0 0.28 PE
GLOBIOM 0.49 0.12 0.38 0.98 PE
IMPACT 0.38 0.53 0.09 0.61 PE
MAgPIE -0.01 -0.08 1.09 -0.01 PE
AVERAGE 0.17 0.53 0.3 0.21
Large demand
Nelson, et al., Agricultural Economics 2014
How ‘plausible’ are the ensemble results? Two
viewsThey are too pessimistic
GHG concentration pathway with the greatest forcing (RCP 8.5)
Crop models assumed constant CO2 concentrations throughout the period
They are not too badActual GHG concentrations similar to RCP 8.5 so
farField results from FACE experiments suggest CO2
fertilization effect in the field is less than in the lab
And then there is the Lamppost Problem
What is missing in our climate change results?
The models don’t include effects of Increasing pest and disease pressure Increasing extreme events Increasing ozone Effects on nutrition
Models for most crops don’t exist
These could swamp the negative effects already quantified
What to do about the Lamppost Problem?
Merge the silos!
It’s not enough for each community to work together. We
need a community of communities, old and new.
• Standard data protocols, developed together• Commonly agreed aggregation methods• ‘Centrally’ managed data storage
Open the black boxes so they aren’t reinvented
• Share code within each community• Identify ‘best’ versions• ‘Centrally’ manage code storage and
dissemination• Identify data needs and develop new sources
Develop 21st century modeling environment
Approach depends on topic
Crop modeling Code hierarchy with modular construction
Plant-level functions (e.g. photosynthesis) Species-level functions Variety-level functions
Design with modularity in mind Identify critical parameters and data needs at each
level Talk to the computational biology folks Facilitates the needed bulk development of models for
fruits and vegetables
ConclusionsSubstance
RCP8.5 results in lower yieldsAdaptation reduces some of those effects across
the supply and demand sideEconomic models allocate response differently
between supply (area and yield) and demand
ProcessExisting models/methods are underestimating the
effects of climate change on food security. We urgently need to address the Lamppost Problem before we do more assessments.