CLIM 690: Scientific Basis of Climate Change Physical Science Basis of Climate Change: IPCC 2007 Jim Kinter28 Jan 2010 Chapter 1. Historical Overview of

CLIM 690: Scientific Basis of Climate Change

Physical Science Basis of Climate Change: IPCC 2007

Jim Kinter 28 Jan 2010

Chapter 1. Historical Overview of Climate Change Science


WHAT DETERMINES CLIMATE?

(1) Energy balance at the top of the atmospherea) Determines the global average, annual

average temperature at the top of the atmosphere

b) Affected by solar energy fluxc) Planetary albedo


Earth’s Energy Balance

Solar Radiation

S = 1380 Wm-2

(plane, parallel)

In equilibrium,

INCOMING ENERGY = OUTGOING ENERGY

(1 - ) S a2 = E (4 a2)

E = 1/4 (1 - ) S

Measured albedo () = 0.31Calculated planetary E = 235 Wm-2

Measured planetary E = 237 Wm-2

Implied TE = 255 K (Stefan-Boltzmann)

EPlanetary Emission






(2) Greenhouse effect a) surface temperature of any planetary body

with an absorbing/emitting atmosphere (e.g. Earth or Venus) is warmer than one without (e.g. Moon)

b) Surface temperature is therefore also affected by concentrations of absorber/emitter gases




Hence the term, “Greenhouse Effect”



Solar Radiation

S = 1380 Wm-2

(plane, parallel)

Assume radiative equilibrium, so that


(1 - ) S a2 = E (4 a2)

E = 1/4 (1 - ) S

Measured albedo () = 0.31Calculated planetary E = 235 Wm-2

Measured planetary E = 237 Wm-2

Implied TE = 255 K (Stefan-Boltzmann)

EPlanetary Emission

Measured surface Es = 390 Wm-2

Atmosphere absorbs 153 Wm-2

Measured Ts = 288 K


Global Radiative Balance

Heat and energy is transported from the equatorial areas to higher latitudes via atmospheric and oceanic circulations, including storm systems.

What Factors Determine Earth’s Climate?

BOM, Australia


This is necessary to achieve radiative balance. The zonal mean absorbed short wave and outgoing long wave radiation, as measured at the top of the atmosphere, are shown with their difference highlighted to show the excess in the tropics and the deficit at high latitudes. The lower part shows the required northward heat transport for balance (green), the estimated atmospheric transports (purple) and the ocean transports (blue) computed as a residual.

The pole-equator-pole radiation balance The poleward energy transport for the atmosphere and ocean

BOM, Australia




Due to the rotation of the Earth, the atmospheric circulation patterns tend to be more east-west than north-south.

Embedded in the mid-latitude westerly winds are large-scale weather systems that act to transport heat toward the poles.

These weather systems are the familiar migrating low- and high-pressure systemsand their associated cold and warm fronts.



Because of land-ocean temperature contrasts and obstacles such as mountain ranges and ice sheets, the circulation system’s planetary-scale atmospheric waves tend to be geographically anchored by continents and mountains although their amplitude can change with time.

Changes in various aspects of the climate system - the size of ice sheets, the type and distribution of vegetation or the temperature of the atmosphere or ocean - will influence the large-scale circulation features of the atmosphere and oceans.


Global mean surface temperature


The natural greenhouse effect (TS-TO) depicted as the difference between the radiative equilibrium surface temperature of the atmosphere of preindustrial times (centre panel) and that of a hypothetical atmosphere with no radiatively active gases but the same albedo as at present (left panel). The right panel of the diagram shows schematically the radiative equilibrium temperature profile in the atmosphere resulting from the greenhouse effect compared with the planetary temperature of 255K.

BOM, Australia


Electromagnetic Spectrum

255 K


The radiation absorption characteristics of water vapor and carbon dioxide as a function of wavelength. The upper portion of the chart shows the wavelength distribution of radiation emitted from black bodies radiating at 6000K (approximately the solar photosphere) and 255K (approximately the earth’s planetary temperature), with the solar irradiance measured at the mean distance of the earth from the sun. The percentage absorption of a vertical beam by representative atmospheric concentrations of water vapor (H2O) and carbon dioxide (CO2) are shown in the lower panels.


CH4

O2 & O3

CO2

H2O

N2O

methane

nitrousoxide

oxygenozone

carbondioxide

watervapor






(2) Greenhouse effect a) surface temperature of any planetary body

with an absorbing/emitting atmosphere (e.g. Earth or Venus) is warmer than one without (e.g. Moon)

b) Surface temperature is therefore also affected by concentrations of absorber/emitter gases

(3) Water vapor feedback changes in surface temperature produce (nonlinear) increases in water vapor thereby increasing the greenhouse effect

(4) Instability and other feedbacks


Tsurf

H20 vapor Absorb/emit IR

Clausius –

Clapyron

Greenhouse

Effect

Ftop = 4 Wm-2 Tsurf = + 1 K (without WVF )

Ftop = 4 Wm-2 Tsurf = + 2 K (with WVF )

Water Vapor Feedback


FAQ 1.1, Figure 130%

20%

10%

100% 70%

-19oC

14oC



Solar Radiation

S = 1380 Wm-2

(plane, parallel)

Assume radiative equilibrium, so that


(1 - ) S a2 = E (4 a2)

Planetary Emission

Planetary albedo

Solar energy flux

Terrestrial energy emission


Possible Origins of Climate Change


Solar Variability and the Total Solar Irradiance

Measurement of the absolute value of total solar irradiance (TSI)the changes in solar radiation could cause surface temperature

changes of the order of a few tenths of a degree celsius.

• After the invention of the telescope, the solar radiation variations can be inferred from cosmogenic isotopes (10Be, 14C) and from the sunspot number.

• Measurements of TSI from mountain sites (Langley, 1884; Abbot, 1902-1957)

• In 1978, the Nimbus-7 satellite was launched (Hickey et al., 1980)

The solar cycle variation in irradiance corresponds to an 10-11 year cycle in radiative forcing which varies by about 0.2 W m–2.

Progress inUnderstanding Climate Processes


Measured range of variability


2.5 W/m2

0.45 W/m2

0.45 W/m2 = 0.03%

2.5 W/m2 = 0.2%

SOLAR OUTPUT

VARIABILITY




Energy Received From Sun Varies On Geologic Time Scales

Earth orbit variability


Eccentricity(100 Kyrs) Obliquity

(40 Kyrs) Precession(20 Kyrs)

Total Insolation(solar radiation)

Solar Radiation Received and Earth Orbital Parameters

Time scale: 10s to 100s of millennia




Global Thermohaline Ocean Circulation aka “Conveyor Belt”

Time scale: Decades to centuries

Nature, 12/2/2005:Measurements indicate THC

is slowing down


El Niño and the Southern Oscillation:

the major mode of interannual variation in

the tropical climate

First simulated in a dynamical model by Philander and Seigel

(Princeton, 1985)


El Niño years

La Niña years

Time scale: 4-7 years




Radiative forcing (RF): the radiative imbalance (W m–2) in the climate system at the top of the atmosphere caused by the addition of a gas



Influence of volcanic plume on planetary albedo. (Source: Garrett, 1997)


Net solar radiation at Mauna Loa Observatory, relative to 1958

Climate Monitoring Division, NOAA


Reduction in global mean temperature following major volcanic eruptions

BOM, Australia


Change of global mean surface temperature

• Warming

- Greenhouse gases (GHG): Water vapor, carbon dioxide, methane- Human activities intensify the greenhouse effect through the

release of GHG. - For instance, the amount of carbon dioxide in the atmosphere has

increased by about 35% in the industrial era, and this increase is known to be due to human activities, primarily the combustion of fossil fuels and removal of forests.

- Clouds contribute locally to the greenhouse effect similar to that of GHG; however, clouds tend to have a net cooling effect on climate.




Human activities contribute



Changes in Greenhouse GasesFrom Ice Age to Modern Data



Amplify (‘positive feedback’) or diminish (‘negative feedback’) the effects of a change in climate forcing.

Example) Ice-Albedo feedback

GreenhouseGases

Increase

Snow and IceMelt

DarkerSurface

More Sun’s heatAbsorb

AlbedoDecrease

Warming


Science is inherently self-correcting; incorrect or incomplete scientific concepts ultimately do not survive repeated testing against observations of nature.

Each successful prediction adds to the weight of evidence supporting the theory, and any unsuccessful prediction demonstrates that the underlying theory is imperfect and requires improvement or abandonment.

The IPCC assesses the scientific literature to create a report based on the best available science. The IPCC also contributes to science by identifying the key uncertainties and by stimulating and coordinating targeted research to answer important climate change questions.

Nature of Earth Science


• Earth scientists are unable to perform controlled experiments on the planet as a whole and then observe the results.

• Sometimes a combination of observations and models can be used to test planetary-scale hypotheses.

Example 1) the global cooling and drying of the atmosphere observed after the eruption of Mt. Pinatubo provided key tests of particular aspects of global climate models (Hansen et al., 1992).

Example 2) Model projections was compared with observations (IPCC)



Hansen et al., 1992

- Test the Aerosol Climate Forcing

A: fast (exponential) growth rates for greenhouse gases and no volcanic aerosols after 1985.

B: linear growth of greenhouse gases and an El Chichon sized volcano in 1995.

El: Pinatubo aerosol properties are a 75• solution of sulfuric acid in water, with sizes based on the May and October distributions of Hofmann and Rosen (1983)

2*El: experiment r is twice as large as in the E1 experiment, in recognition of early reports that sulfur emissions from Pinatubo may have been twice as large as for E1Chichon.

P: the same time dependence of global optical depth as the E1 and 2*El experiments, but with r 1.7 times larger than in E1 and the aerosol geographical distribution Modified.


Figure 1.1


• Self-correcting nature of Earth science:

Prediction of global cooling in the mid-1970s

- Global cooling over Northern Hemisphere (e.g., Gwynne,1975).

- Increases in carbon dioxide (CO2) should be associated with a

decrease in global temperatures (Bryson and Dittberner, 1976)

- The cooling projected by their model was due to aerosols (small

particles in the atmosphere) produced by the same combustion that

caused the increase in CO2 (Bryson and Dittberner, 1977).

However, because aerosols remain in the atmosphere only a short

time compared to CO2, the results were not applicable for long-term

climate change projections.



Climate science in recent decades has been characterized by the increasing rate of advancement of research in the field and by the notable evolution of scientific methodology and tools, including the models and observations that support and enable the research.

• Between 1965 and 1995, the number of articles published per year in atmospheric science journals tripled (Geerts, 1999).

• Stanhill (2001) found that the climate change science literature grew approximately exponentially with a doubling time of 11 years for the period 1951 to 1997.

• 95% of all the climate change science literature since 1834 was published after 1951.

• The additional physics incorporated in climate models over the last several decades.



1990 1996

2001 2007

• The complexity of climate models has increased over the last few decades. The additional physics incorporated in the models are shown pictorially by the different features of the modelled world.

As a result of the cumulative nature of science, climate science today is an interdisciplinary synthesis of countless tested and proven physical processes and principles painstakingly compiled and verified over several centuries of detailed laboratory measurements, observational experiments and theoretical analyses; and is now far more wide-ranging and physically comprehensive than was the case only a few decades ago.


Global Surface Temperature: Development of in situ observations and satellite data

Obstacles to turning instrumental observations into accurate global info:

(1) access to the data in usable form

(2) quality control to remove or edit erroneous data points

(3) Homogeneity assessments and adjustments where necessary to ensure

the fidelity of the data

(4) area-averaging in the presence of substantial gaps.

Since 1982, satellite data, anchored to in situ observations, have contributed

to near-global coverage (Reynolds and Smith, 1994).

Despite the fact that many recent observations are automatic, the vast

majority of data that go into global surface temperature calculations

– over 400 million individual readings of thermometers at land stations and

over 140 million individual in situ SST observations – have depended on the

dedication of tens of thousands of individuals for well over a century.

Progress in Detecting and AttributingRecent Climate Change


Figure 1.3


Detection of cause of climate change: the process of demonstrating that climate has changed in some defined statistical sense, without providing a reason for that change.

Attribution of cause of climate change: the process of establishing the most likely causes for the detected change with some defined level of confidence.

Attribution of anthropogenic climate change must be pursued by(a) detecting that the climate has changed(b) demonstrating that the detected change is consistent with computer model simulations of the climate change ‘signal’ that is calculated to occur in response to anthropogenic forcing(c) demonstrating that the detected change is not consistent with alternative, physically plausible explanations of recent climate change that exclude important anthropogenic forcings.

rely on observational data and model output.



Detection and Attribution

‘fingerprint’: climate changes that are identical as a function of latitude, longitude,

height, season and history over the 20th century (not limited to just

temperature at the Earth’s surface).

Model-predicted fingerprints of anthropogenic climate change are

clearly statistically identifiable in observed data.

The common conclusion of a wide range of fingerprint studies

conducted over the past 15 years is that observed climate changes

cannot be explained by natural factors alone (Santer et al., 1995,

1996a,b,c; Hegerl et al., 1996, 1997, 2000; Hasselmann, 1997; Barnett et

al., 1999; Tett et al., 1999; Stott et al., 2000).



The Earth’s Greenhouse Effect

John Tyndall (1861) noted that changes in the amount of any of the

radiatively active constituents of the atmosphere such as water (H2O) or CO2

could have produced all the mutations of climate determined by geologists.

In 1895, Svante Arrhenius (1896) made a climate prediction based on

greenhouse gases, suggesting that a 40% increase or decrease in the

atmospheric abundance of the trace gas CO2 might trigger the glacial

advances and retreats.

G. S. Callendar (1938) found that a doubling of atmospheric CO2

concentration resulted in an increase in the mean global temperature of 2°C,

with considerably more warming at the poles, and linked increasing fossil

fuel combustion with a rise in CO2 and its greenhouse effect.



Carbon cycle science

In the 1950s, the greenhouse gases of concern remained CO2 and H2O, the

same two identified by Tyndall a century earlier.

In the 1970s, other greenhouse gases – CH4, N2O and CFCs – were widely

recognized as important anthropogenic greenhouse gases (Ramanathan,

1975; Wang et al., 1976)

By the 1970s, the importance of aerosol-cloud effects in reflecting sunlight

was known (Twomey, 1977), and atmospheric aerosols (suspended small

particles) were being proposed as climate-forcing constituents.



Past Climate Observations, Astronomical Theory

and Abrupt Climate Changes

• The Working Group I (WGI) WGI FAR noted that past climates could provide analogues.

• The pace of palaeoclimatic research has accelerated over recent decades.

deep-sea cores, ice cores

• By the end of the 1990s, palaeoclimate proxies for a range of climate

observations had expanded greatly

: The analysis of deep corals, precise measurements of the CH4 abundances

(a global quantity) in polar ice cores, etc.



USGSNationalIceCoreLab


Warm and Cold

Periods in Earth

History

AGE OF DINOSAURS

FORMATION OF “FOSSIL FUELS”

QUATERNARY - LAST ~2 MILLION YEARS: ICE AGES, MODERN AGE


Biogeochemistry and Radiative Forcing

In terms of greenhouse agents, the main conclusions from the WGI FAR

Policymakers Summary are still valid today:

(1) increasing the atmospheric concentrations of the greenhouse

gases: CO2, CH4, CFCs, N2O.

(2) some gases are potentially more effective (at greenhouse warming).

(3) feedbacks between the carbon cycle, ecosystems and atmospheric

greenhouse gases in a warmer world will affect CO2 abundances.

Radiative forcing (RF): the radiative imbalance (W m–2) in the climate system

at the top of the atmosphere caused by the addition of a greenhouse gas (or

other change)



Figure TS.5


Cryospheric Topics

• Cryosphere: includes the ice sheets of Greenland and Antarctica,

continental (including tropical) glaciers, snow, sea ice, river and lake ice,

permafrost and seasonally frozen ground

• high reflectivity (albedo) for solar radiation• low thermal conductivity• large thermal inertia• potential for affecting ocean circulation (through exchange of freshwater

and heat) and atmospheric circulation (through topographic changes)• large potential for affecting sea level (through growth and melt of land

ice), potential for affecting greenhouse gases (through changes in

permafrost)




WE

AT

HE

RC

LIM

AT

E

WHAT IS CLIMATE? What is the Relationship between Climate Change and Weather?


• Climate concerns the entire Earth system, including the atmosphere, land, oceans, snow, ice and living things that serve as the global background conditions that determine weather patterns.

• Example: El Niño affects the weather in coastal Peru. The El Niño sets limits on the probable evolution of weather patterns that random effects can produce. A La Niña would set different limits.

• While many factors continue to influence climate, scientists have determined that human activities have become a dominant factor, and are responsible for most of the warming observed over the past 50 years.

• As climate changes, the probabilities of certain types of weather events are affected.

• For example, as Earth’s average temperature has increased, some weather phenomena have become more frequent and intense (e.g., heat waves and heavy downpours), while others have become less frequent and intense (e.g., extreme cold events).

What is the Relationship between Climate Change and Weather?

BOM, Australia


Schematic view of the components of the climate system, their processes and interactions.


Climate is a statistical representation of the average conditions in the atmosphere, oceans and land surface.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

-10 -8 -6 -4 -2 0 2 4 6 8 10

expected value

CLIMATE IS WHAT YOU EXPECT …

std. dev.

extreme value

WEATHER IS WHAT YOU GET.


0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

-10 -8 -6 -4 -2 0 2 4 6 8 10

Probabilistic Climate Problem

Climate change may be a shift in the mean value of the distribution.

sample extreme value

Simple response


0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

-10 -8 -6 -4 -2 0 2 4 6 8 10

Climate change may be a change in the mean value and/or the variance of the distribution.

sample extreme value

Shift with more energy

input

Probabilistic Climate Problem


Model Evolution and Model Hierarchies

• The computational progress (capacity) has permitted a corresponding increase in model complexity by including more components and processes, in the length of the simulations, and in spatial resolution, etc.

• A parallel evolution toward increased complexity and resolution has occurred in the domain of numerical weather prediction, and has resulted in a large and verifiable improvement in operational weather forecast quality.

• “Simplicity” of model depends on number of Equation, Dimension, Scale, Process, etc.

• With the development of computer capabilities, simpler models have not disappeared; on the contrary, a stronger emphasis has been given to the concept of a ‘hierarchy of models’ as the only way to provide a linkage between theoretical understanding and the complexity of realistic models (Held, 2005).

Progress in Modelling the Climate


1990 1996

2001 2007

The complexity of global climate models has increased enormously over the last 20 years, as shown in this flow chart. Beneath each time period is a list of the components included in state-of-the-art models such as the NCAR-based Community Climate System Model (Warren Washington, NCAR)


• Geographic resolution characteristic of the generations of climate models used in the IPCC Assessment Reports: FAR (IPCC, 1990), SAR (IPCC, 1996), TAR (IPCC, 2001a), and AR4 (2007).

• The figures show how successive generations of these global models increasingly resolved northern Europe. These illustrations are representative of the most detailed horizontal resolution used for short-term climate simulations.

• The century-long simulations cited in IPCC Assessment Reports after the FAR were typically run with the previous generation’s resolution. Vertical resolution in both atmosphere and ocean models is not shown, but it has increased comparably with the horizontal resolution, beginning typically with a single-layer slab ocean and ten atmospheric layers in the FAR and progressing to about thirty levels in both atmosphere and ocean.


Duration and/or Ensemble size

Re

so

luti

on

ComputingResources

Complexity

Resources Tradeoffs


Complexity

Duration and/or Ensemble size

Re

so

luti

on Computing

Resources


Model Clouds and Climate Sensitivity

• Clouds, which cover about 60% of the Earth’s surface, are responsible for up to two thirds of the planetary albedo, which is about 30%.

• The sensitivity of the Earth’s climate to changing atmospheric greenhouse gas concentrations depends strongly on cloud feedbacks



History of Model Clouds


Early 1980’s Prescribed cloud amounts

Late 1980’s Explicit representation of clouds (Sundqvist, 1978)

TAR • More realistic representation of clouds in most climate models The amplitude and the sign of cloud feedbacks was noted in the TAR as highly uncertain.

1980’s-1990’s • Increase of operational ground-based measurements (e.g. ARM), operational meteorological satellites (e.g. ISCCP), shorter field campaigns dedicated to the observation (TOGA CORE). Observational data have clearly helped the development of models. However, existing data have not yet brought about any reduction in the existing range of simulated cloud feedbacks.

2000’s 1. Using single-column models (Randall et al., 1996; Somerville, 2000) and higher-resolution cloud-resolving models to evaluate GCM parametrizations.

2. To make use of the more global and continuous satellite data, on a statistical basis, through an investigation of the correlation between climate forcing and cloud parameters (Bony et al.,1997)


Coupled Models: Evolution, Use, Assessment

• The first attempts at coupling atmospheric and oceanic models were carried out during the late 1960s and early 1970s (Manabe and Bryan, 1969; Bryan et al., 1975; Manabe et al., 1975).

• Replacing ‘slab’ ocean models by fully coupled ocean-atmosphere models (Trenberth, 1993)

• ‘flux adjustments’ or ‘flux corrections’ (Manabe and Stouffer, 1988; Sausen et al.,1988)

These were essentially empirical corrections that could not be justified on physical principles, and that consisted of arbitrary additions of surface fluxes of heat and salinity in order to prevent the drift of the simulated climate away from a realistic state.

• By the time of the TAR, some models without flux adjustment were able to maintain stable climatologies of comparable quality to flux-adjusted models’ (McAvaney et al., 2001).



Uncertainties in Coupled Models: Assessment

• The first kind of predictionInitial-value problems: Because of the nonlinearity and instability of the governing equations, such systems are not predictable indefinitely into the future. Ensemble simulations show that the projections tend to form clusters around a number of attractors as a function of their initial state

• The second kind of predictionThe determination of the response of the climate system to changes in the external forcings (boundary conditions of SST, soil wetness, snow, sea ice, solar flux, volcanoes, greenhouse gases, land use changes, etc.) Estimates of future climate scenarios as a function of the concentration of atmospheric greenhouse gases are typical examples of predictions of the second kind.



Ensemble

Ensemble Mean

Observation

Nature of Atmosphere

Potentiality of Seasonal Prediction

A Realization = Signal + Noise

Signal : Memory of Boundary Condition (ensemble mean)

Noise : Nonlinear Process (deviation from ensemble mean)

Ensembles from Small Initial Perturbation


Uncertainties in Coupled Models: Assessment

• Comparing different models: Intercomparison of GCM results (AMIP, CMIP, etc. refer )

Setting standards of quality control, providing organisational continuity and ensuring that results are generally reproducible.

The most problematic areas of coupled model simulations involve cloud-radiation processes, the cryosphere, the deep ocean and ocean-atmosphere interactions.

• Using multiple simulations from a single model (the so-called Monte Carlo, or ensemble, approach) has proved a necessary and complementary approach to assess the stochastic nature of the climate system.

• Data available in http://www.ipcc-data.org/ http://www-pcmdi.llnl.gov/


http://www.ipcc-data.org/

http://www-pcmdi.llnl.gov/


• IPCC: Three Working Groups Working Group I: The Physical Science BasisWorking Group II: Impacts, Adaptation and VulnerabilityWorking Group III: Mitigation of Climate Change Working Group I (WGI) assesses the scientific aspects of the climate system and climate change while Working Groups II (WGII) and III (WGIII) assess the vulnerability and adaptation of socioeconomic and natural systems to climate change, and the mitigation options for limiting greenhouse gas emissions, respectively.

• IPCC Main Activity1. To provide on a regular basis an assessment of the state of knowledge on climate change2. Policy relevant but not policy prescriptive: IPCC prepares Special Reports and Technical Papers on topics for which independent scientific information and advice is deemed necessary, and it supports the United Nations Framework Convention on Climate Change (UNFCCC, policy mechanism of the UN) through its work on methodologies for National Greenhouse Gas Inventories.

Please refer http://www.ipcc.ch/

The IPCC Assessments of Climate Change and Uncertainties



The Issue of “predictions”

The SRES (The Emission Scenarios of the IPCC Special Report on Emission Scenarios)


Sarachick, Univ. of Washington


Different scenarios:

A1. The A1 storyline and scenario family describes a future world of very rapid economic growth, global population that peaks in mid-century and declines thereafter, and the rapid introduction of new and more efficient technologies. Major underlying themes are convergence among regions, capacity building and increased cultural and social interactions, with a substantial reduction in regional differences in per capita income. The A1 scenario family develops into three groups that describe alternative directions of technological change in the energy system. The three A1 groups are distinguished by their technological emphasis: fossil intensive (A1FI), non-fossil energy sources (A1T), or a balance across all sources (A1B) (where balanced is defined as not relying too heavily on one particular energy source, on the assumption that similar improvement rates apply to all energy supply and end use technologies).

A2. The A2 storyline and scenario family describes a very heterogeneous world. The underlying theme is self reliance and preservation of local identities. Fertility patterns across regions converge very slowly, which results in continuously increasing population. Economic development is primarily regionally oriented and per capita economic growth and technological change more fragmented and slower than other storylines.

B1. The B1 storyline and scenario family describes a convergent world with the same global population, that peaks in mid-century and declines thereafter, as in the A1 storyline, but with rapid change in economic structures toward a service and information economy, with reductions in material intensity and the introduction of clean and resource efficient technologies. The emphasis is on global solutions to economic, social and environmental sustainability, including improved equity, but without additional climate initiatives.

B2. The B2 storyline and scenario family describes a world in which the emphasis is on local solutions to economic, social and environmental sustainability. It is a world with continuously increasing global population, at a rate lower than A2, intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 storylines. While the scenario is also oriented towards environmental protection and social equity, it focuses on local and regional levels.




The Issue of “predictions”

An illustrative scenario was chosen for each of the six scenario groups A1B, A1FI, A1T, A2, B1 and B2. All should be considered equally sound.

The SRES scenarios do not include additional climate initiatives, which means that no scenarios are included that explicitly assume implementation of the United Nations Framework Convention on Climate Change or the emissions targets of the Kyoto Protocol.


Sarachick, Univ. of Washington


The Treatment of Uncertainty

• Confidence Uncertainty

High Confidence: 8 of 10 changes of being right

• Likelihood of Results

Very Likely: >90% Probability

Likely: >66% Probability


Documents

CLIM 690: Scientific Basis of Climate Change Physical Science Basis of Climate Change: IPCC 2007 Jim Kinter28 Jan 2010 Chapter 1. Historical Overview of