introduction to climate change scenario development

The Canadian Climate Impacts Scenarios (CCIS) Project is funded by the

Climate Change Action Fund and provides climate change scenarios and related information to the VIA community in Canada

Introduction to Climate Change Scenario

Development

Dr. Elaine Barrow

CCIS Principal Investigator (Science)



What is a climate change scenario?

Definitions:

“…a coherent, internally consistent and plausible description of a possible future state of the world…”

[Parry & Carter, 1998]

“…a plausible future climate that has been constructed for explicit use in investigating the potential consequences of anthropogenic climate change…”

[IPCC TAR, 2001]



A climate scenario is not a prediction of future

climate!



Why do we need climate change

scenarios?• To provide data for VIA assessment studies• To act as an awareness-raising device• To aid strategic planning and/or policy

formation• To scope the range of plausible futures• To structure our knowledge (or ignorance) of

the future• To explore the implications of decisions



Key component of a framework for conducting integrated assessment of climate change for policy applications



What are the challenges of developing climate

scenarios?• simple to obtain, interpret and apply

• provide sufficient information for VIA assessments

• physically plausible and spatially compatible

• consistent with the broad range of global warming projections

• reflect the potential range of future regional climate change, i.e., be representative of the range of uncertainty in projections



What you want …

… typically is daily weather for a particular place for some future year



Three ways ...

• Incremental (arbitrary, synthetic) scenarios

• Analogue scenarios

• Scenarios from global climate models (GCMs)

COMPLEXITY



Incremental Scenariosfor sensitivity studies

4

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Year

Me

an

an

nu

al t

em

pe

ratu

re (

°C)

T=2°C

Can provide valuable information about:• sensitivity• thresholds or discontinuities of response• tolerable climate change



ADVANTAGES: simple to construct and apply, allow relative sensitivity of impacts sectors/models to be explored

DISADVANTAGES: arbitrary (and unrealistic) changes, may be inconsistent with uncertainty range

Yield change (t/ha) of Valencia orange in response to changing temperature and CO2 concentration [Source: Rosenzweig et al. (1996)]



Identification of recorded climate regimes which may resemble the future climate in a given region

Assumption: climate will respond in the same way to a unit change in forcing despite its source and even if boundary conditions differ

Analogue Scenarios



Identify regions which today have a climate analogous to that anticipated in the study region in the future

Spatial Analogues

[Source: Parry & Carter, 1988]

• Approach restricted by frequent lack of correspondence between other non-climatic features of the two regions

• Causes of the analogue climate likely different from the causes of future climate change



Use climate information from a past time period as an analogue of possible future climate

• Palaeoclimatic

• Instrumental

Temporal Analogues



Palaeoclimatic Analogues

Use information from the geological record - fossils, sedimentary deposits - to reconstruct past climates

• mid-Holocene, 5-6k BP, 1°C warmer

• last (Eemian) interglacial, 125k BP, approx. 2°C warmer

• Pliocene, 3-4m BP, 3-4°C warmer

IPCC, 1990



Palaeoclimatic Analogues

• changes in the past unlikely to have been caused by increased GHG concentrations

• data and resolution generally insufficient, i.e., extremely unlikely to get daily resolution and individual site information

• uncertainty about the quality of palaeoclimatic reconstructions

• higher resolution (and most recent) data generally lie at the low end of the range of anticipated future climatic warming



Past periods of observed global- or hemispheric- scale warmth used as an analogue for the future

Instrumental Analogues

Difference =0.4°C

Lough et al., 1983

Northern Hemisphere temperature record



Instrumental AnaloguesThe 1930s in the North American Great Plains have frequently

been used as an analogue for the future.

Mean temperature (°C)

Precipitation (mm)

Differences between 1931-1940 average and 1951-1980 average in the MINK states (Easterling et al., 1992)

State Winter (DJF) Spring (MAM) Summer (JJA) Autumn (SON) AnnualMissouri 1951-1980 51 100 97 82 989

1930s +16 -23 -21 -1 -28Iowa 1951-1980 26 79 106 61 815

1930s +6 -53 -28 +16 -60Nebraska 1951-1980 14 60 79 35 566

1930s +4 -23 -54 -21 -93Kansas 1951-1980 19 67 88 54 684

1930s 0 -19 -59 -24 -102

State Winter (DJF) Spring (MAM) Summer (JJA) Autumn (SON) AnnualMissouri 1951-1980 0.3 12.7 29.4 13.9 12.8

1930s +1.0 0.0 +1.1 +0.6 +0.7Iowa 1951-1980 -5.7 8.9 22.3 10.6 9.0

1930s +1.1 +0.3 +1.2 +0.6 +0.8Nebraska 1951-1980 -3.6 8.9 22.6 10.5 9.6

1930s +0.6 +0.7 +1.6 +1.0 +1.0Kansas 1951-1980 0.1 12.1 25.2 13.6 12.8

1930s +0.9 +0.6 +1.3 +1.0 +0.9



Palmer Drought Severity Index (PSDI) for the US Corn Belt, 1930-1980.

[Source: Rosenberg et al., 1993]




Rice-growing areas in Japan


Base, 1951-1980 Warm decade, 1921-1930

0.4°C warmer than base




ADVANTAGES• data available on a daily and local scale• scenario changes in climate actually observed and

so are internally consistent and physically plausible

DISADVANTAGES• climate anomalies during the past century have been

fairly minor cf. anticipated future changes• anomalies probably associated with naturally-

occurring changes in atmospheric circulation rather than changes in GHG concentrations



GCMs are the“…only credible tools currently available for

simulating the physical processes

that determine global climate...”

[IPCC]

[Source: David Viner, UK Climate Impacts LINK Project]

Scenarios from GCMs



What do GCMs do?

Growth in population, energy demand, changes in technology and land-use/cover

Greenhouse gas emissions

Atmospheric GHG concentrations

Future climate projections

Energy-economy models

Carbon cycle and other chemical models

Climate models

Simulate the response of the global climate system to changes in atmospheric composition



GCM evolution

EQUILIBRIUM EXPERIMENTS

TRANSIENT EXPERIMENTS

COLD START

WARM START

1980s

late 1980s

early 1990s



Warm start GCMs



-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

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0.6

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Glo

bal

-mea

n t

emp

erat

ure

ch

ang

e (°

C)

wrt

196

1-19

90

CGCM1



• Vintage

• Resolution

• Validity

• Representativeness of results

[Source: Smith and Hulme, 1998]

Which GCM should I use?



BUT ...• Climate models are not accurate• Different GCMs give different results• The future is uncertain - it is expensive

to run many climate change experiments using different emissions scenarios

• Climate model results are not at a fine enough spatial scale



Climate models are not accurate ...



t2

t1

Climate change integration

Time

Glo

bal m

ean

tem

pera

ture

(°C

)

t1 is typically 1961-1990t2 is a future time period, e.g., 2040-2069, representing the 2050s

T=t2-t1

Some models exhibit large inter-decadal variability, so average over 30 years to capture longer-term trend.

so we cannot use their output directly ...



IPCC-TGCIA recommend 1961-1990 as the climatological

baseline

Role in climate scenario construction:• serves as a reference period from which

estimated future change in climate is calculated

• used to define the observed present-day climate with which climate change scenario information is usually combined



Specifying the BaselineImportant for:• characterising the prevailing conditions under

which an exposure unit functions and to which it must adapt

• describing average conditions, spatial and temporal variability and anomalous events, some of which can cause significant impacts

• calibrating and testing impact models across the current range of variability

• identifying possible ongoing trends or cycles• specifying the reference situation with which to

compare future changes



[Source: Hadley Centre for Climate Prediction and Research, UK Met. Office]

Sources of Uncertainty

Cascade of uncertainty



The future is uncertain ...

IPCC Special Report on Emissions Scenarios (2000)




1.4-5.8°C




0.09-0.88m



SRES climate change



Different GCMs give different results …



2050s: JJA

-20

-10

0

10

20

30

40

-2 -1 0 1 2 3 4 5 6 7 8

Mean temperature change (°C)

Pre

cip

itat

ion

ch

ang

e (%

)Which scenarios?

Cooler, wetter

Cooler, drier Warmer, drier

Warmer, wetter



Risk assessment approach

ADVANTAGES• makes (some)

uncertainties explicit• good for risk assessment• can be applied at different

scales

DISADVANTAGES• not yet a well developed

methodology• requires a lot of model

data to develop• expert assumptions still

needed



Effect of scenario resolution on impact outcome

Spatial Scale of Scenarios

[Source: IPCC, WGI, Chapter 13]



1. What climate variables are essential for your study?

2. How many scenarios do you want? Which uncertainties are you going to explore?

3. Do you need local data for case studies/sites, or national/regional coverage?

4. What spatial resolution do you really need - 300km, 100km, 50km, 10km, 1km? Can you justify this choice?

5. Do you need changes in average climate, or in variability?

6. Do you need changes in daily weather, or just monthly totals?

Scenario Needs



Further Reading

• IPCC TAR - Chapter 13 (www.ipcc.ch)• Smith & Hulme - Chapter 3: Handbook on

Methods of Climate Change Impacts Assessment and Adaptation Strategies (http://130.37.129.100/english/o_o/instituten/IVM/research/climatechange/Handbook.htm)

• Parry & Carter - Climate Impact and Adaptation Assessment. Earthscan, 166pp.

• IPCC TGCIA Guidelines on Climate Scenarios (currently under revision)

introduction to climate change scenario development

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