Djf Warsaw Sept05

Predicting and Attributing Climate Change

Dave Frame Department of Physics, University of Oxford Oxford University Centre for the Environment [email protected]

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Defining Climate „

Climate is the statistics of the weather – – – – –

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Global mean, annual mean surface temperature East Pacific summer sea-surface temperatures Mean annual Indian Rainfall Average July humidity in Toruń Return period of Florida hurricanes

Wide range of spatial and time scales involved “Climate is what we expect; weather is what we get” – Ed Lorenz

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Climate responds due to: „

Factors internal to the climate system: – Variability in the atmosphere – Variability in the oceans – Variability in the biosphere

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Factors external to the climate system: – Rising levels of greenhouse gases – Volcanoes – Fluctuations in solar output

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Climate as a predictable system Climate is to weather as the bank is to the roulette wheel: „ The statistics of the system are simpler than the system itself „ Easier to be right in the long run than in the short

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Factors governing predictability

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Initial conditions – are the state and trajectory of the climate system at the beginning of the forecast

Necessary for predicting weather „ Boundary conditions – are the external factors that control the weather we should expect on average

Crucial in predicting climate

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Predictive skill over time „

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Skill diminishes as natural anomalies in climate “wash out” of the system (as the roulette wheel relaxes back to its statistical norm) Skill increases over time as the boundary conditions start to drive the statistical norms (as the roulette wheel gums up)

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Sources of predictability

Boundary Condition Predictability

Predictive Skill

Initial Condition predictability

Time (yrs) Oxford University

Boundary conditions and global climate

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Climate is determined by the boundary conditions of the atmosphere-ocean system: – solar irradiance (power output of the sun) – atmospheric composition (greenhouse gases, volcanic activity, etc.) – positions of continents, ice-sheets etc.

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If these change, climate is likely to change

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Factors in the climate system

Kiehl and Trenberth, 1996 Oxford University

..most escapes to outer space and cools the earth... SUN …but some IR is trapped by some gases in the air, thus reducing the cooling…. Sunlight passes through the atmosphere..

..and warms the earth.

Infra-red radiation is given off by the earth... Source: Ellie Highwood Oxford University

Energy in the climate system

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Climate varies on geological timescales

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Global Temperature last 1000 yr

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“In the light of new evidence and taking into account the remaining uncertainties, most of the observed warming over the last 50 years is likely to have been due to the increase in greenhouse gas concentrations” Source: IPCC Third Assessment Report, 2001

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Model hierarchy „

Physics constraints operate at all scales: – – – – –

energy balance energy transport geostrophic balance Moisture availiability Cloud condensation principles

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Model hierarchy „

And we can usefully model the climate system at a similarly wide range of scales 1. 2. 3. 4.

zero-dimensional energy balance models (EBMs); one dimensional radiative-convective models (RCMs); two-dimensional statistical-dynamical models (SDMs); three-dimensional general circulation models (GCMs).

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Energy Balance Models „

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Treat the climate system as an energy balance problem: what goes in must come out Can write an equation that looks at temperature response to “forcing” (changes in incoming or outgoing radiation)

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d∆T = F − λ ∆T dt

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Energy Balance Models „

Treat the climate system as an energy balance problem: what goes in must come out Heat uptake of the system

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Climate forcing

Temperature response

d∆T = F − λ ∆T dt

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Energy Balance Models „

Treat the climate system as an energy balance problem: what goes in must come out

Ocean heat uptake

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Atmospheric feedbacks

d∆T = F − λ ∆T dt (For a given climate forcing) Oxford University

Energy Balance Models - Ensembles „

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Ideally, we’d take an unbiased sample of all viable climate models, but we can’t do that Best we can do is take this scatter-gun approach Repeat with other models

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d∆T = F − λ ∆T dt

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General Circulation Model of the Atmosphere:

3 Equations of Motion Equation of State Energy Equation Mass Conservation The Model also includes:

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3D wind field Temperature Pressure Density

• Convection scheme • Cloud scheme • Radiation scheme • Sulphur cycle • Precipitation • Land surface and vegetation • Gravity wave drag scheme

Each of these equations is evaluated at each point in the model [96 longitudes by 73 latitudes by 19 vertical levels] every half hour timestep

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Climate modelling (1990) „

General Circulation Models (GCMs) – Atmospheric GCMs – Ocean GCMs

Atmosphere only Model

Ocean only Model

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Climate modelling (2000) „

Coupled Ocean-Atmosphere GCMs

Atmosphere Model

Ocean Model

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Climate modelling (2005?) „

Coupled GCMs with biogeochemical cycles

Atmospheric Model Chemistry Model Cryosphere Model

Coupler Biosphere Model Ocean Model

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GCM Performance „

Modern Coupled GCMs 5 Perform well at continental scales 5 Perform well at interannual -> climatological scales 4 Perform less well at short time scales 4 Perform less well at regional scales

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Model simulation of recent climate

Natural forcings only (solar, volcanic etc. variability)

Anthropogenic forcings only (human-induced changes)

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Model simulation of recent climate Natural forcings

Natural + Anthropogenic forcings Anthropogenic forcings Oxford University

Solar forcing in models Combined forcing, doubling solar response

Stott et al, 2001 Oxford University

Increasing greenhouse gases: „ „ „ „

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Increases the infrared opacity of the atmosphere. Raises the mean altitude of air radiating to space. Higher air is colder (by ~6K/km) and so emits less. Net radiation to space is reduced, by ~4W/m2 for a doubling of CO2. Climate system adjusts to restore balance.

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Forcing Uncertainties

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Warming rates in different models (“Model Spread”)

Different models yield different warmings under the same scenarios

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Net ranges under various scenarios

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Developed Country Per capita Emissions far Exceed Developing Country Per Capita Emissions

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Uncertainty in global warming under two scenarios of future emissions

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Risk of global warming first exceeding 1.5K by a given date

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Global model predictions

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Zonal mean precipitation changes at time of CO2 doubling in CMIP-2 models

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How uncertain are these model predictions? „

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Models depend on “parameterisations” of processes too small to resolve. Parameterisations represent the feedbacks between smaller and larger scales. Many prescribed “parameters” (e.g. “ice fall speed in clouds”) are poorly constrained.

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GCM resolution ~ 2.5° in lat,lon Explicit representation of larger scale features; Sub-grid scale processes need to be parameterized “Arbitrarily small scales affect arbitrarily large scales in finite time” (Lorenz 1969) The Met Office Oxford University

Uncertainty in climate forecasts

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2080 temperature change (K)

2080 precipitation change (%)

We can produce very detailed predictions of climate change which span a range of possibilities because of uncertainties in: •Future forcing •System uncertainty •Chaos

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Regional responses: temperature and precipitation

Standard model version

Low sensitivity model

High sensitivity model

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Uncertainty in climate forecasts

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Combining physical uncertainty with economic uncertainty: the Integrated Assessment problem 0.5

Probability Density

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Median: 2.3

0.3

0.2

Lower 95%: 0.9 0.1

Upper 95%: 5.3 0.0 0

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Temperature Change (Degrees C) 2000-2100

Source: Webster et al, 2001 Oxford University

Elements of Sustainable Development

Courtesy of The World Bank

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World Bank Strategy Carbon Trading JI More Renewables

More GEF

Clean Technology Economic Instruments Sector Reform

Internalizing Global Externalities (supporting the postKyoto process)

Environmental Standards Energy Efficiency

Local/Regional Pollution Abatement (to be Regional Agreements strengthened)

Clean Fuel

Rural Energy

Win-Win (in place)

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Regional Behaviour – European Precipitation Mediterranean Basin

Northern Europe

Winter Winter

Summer Summer

Annual

Annual

Unpublished analysis from climateprediction.net: Source: David Stainforth

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Record hot events are more likely in a generally warmer world

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Summer 2003 temperatures relative to 2000-2004

From NASA’s MODIS - Moderate Resolution Imaging Spectrometer, courtesy of Reto Stöckli, ETHZ

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Excess mortality rates in early August 2003 indicate 22,000 - 35,000 heat-related deaths

Daily mortality in Baden-Württemberg Oxford University

Was the hot summer of 2003 due to climate change?

Anthropogenic emissions of greenhouse gases have doubled the risk of a summer like 2003

By 2050, it could be that hot every other summer Oxford University

Hotspots: 1.4% of Land Surface but 40-50% of biodiversity

Consideration of climate change challenges the concept of “corridors” as a mechanism to protect some ecosystems

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Standard Visualisation Package

http://www.climateprediction.net

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Since September 2003, 100,000 participants in 142 countries have completed 100,000 45 -year GCM runs computed 3 million model years donated 8,000 years of computing time Oxford University