What has caused recent climate What has caused recent climate change? change?

How statistical analysis has How statistical analysis has helped to provide the answerhelped to provide the answer

What has caused recent climate What has caused recent climate change? change?

How statistical analysis has How statistical analysis has helped to provide the answerhelped to provide the answer

Global warming alarmism

Intergovernmental Panel on Climate Change (IPCC)

• Joint body of UN Environment Program and World Meteorological Organization, established in 1988

• Every 5-6 years, carries out a comprehensive assessment of climate change science, impacts, and approaches for mitigation and adaptation to climate change

• Includes representatives from all countries• Fourth Assessment Report prepared by more than 500

scientists over the last three years• Summaries for Policy Makers approved by consensus

(including representatives of the Australian govt) at meetings in Paris (Feb 07), Brussels (Apr 07) and Bangkok (May 07)

• Received the 2007 Nobel Peace Prize jointly with Al Gore• Available from www.ipcc.ch

Causes of recent climate changeRadiative forcing components

WGI Fig SPM.2IPCC WGI Fig SPM.2

‘Most of the observed increase in global average temperatures since the mid-20th century is very likely (more than 90% certain) due to the observed increase in anthropogenic greenhouse gas concentrations.’ IPCC(2007)

Figure TS.23

IPCC WGI Fig TS.23

What is the most likely cause?

Detection of significant observed climate change and attribution of this observed change to one or more causes is a signal-in-noise problem: identifying possible signals in the noise of natural internal climate variations in the chaotic climate system.

Detection is the process of demonstrating that an observed change is significantly different (in a statistical sense) than can be explained by natural internal climate variability.

What is detection and attribution?

Attribution of climate change to specific causes involves statistical analysis and the careful assessment of multiple lines of evidence to demonstrate that the observed changes are:

• unlikely to be due entirely to internal climate variability;• consistent with the estimated responses to a given

combination of anthropogenic and natural forcing; and• not consistent with alternative, physically plausible

explanations of recent climate change

What is detection and attribution?

• Variable with high signal-to-noise ratio• Long observational record• Long control model simulations and ensembles of

forced climate model simulations• Consistent response to specified forcings between

different models – consistent signals• Separable signals between different forcings• Statistical analysis methods that enhance signal

relative to noise and for identifying signals in observed changes

Requirements of detection and attribution?

Detection and attribution methods• Greater confidence when

– We are able to separate the contributions to observed change from individual sources

• Decompose the observed global surface temperature change into contributions from GHG forcing, aerosol forcing, natural forcing, internal variability

– Account for multiple known sources of uncertainty– Models and observations agree on the amplitude of

the contributions– Able to demonstrate that competing explanations

are not viable– Models simulate similar levels of internal variability

as observed

Evaluateamplitudeestimates

Observations1946-56

Model

1986-96

XY Total least squares regression in reduced dimension space

XYFiltering and projection onto reduceddimension space

Evaluate goodness of

fit̂ ̂

Weaver and Zwiers, 2000

• Observations represented in a dimension-reduced space– Typically filtered

• Spatially (to retain large scales)

• Temporally (to retain decadal variability - 5-10 decades)

• Projected onto low-order space-time EOFs

εξ)β(XY

• Signals estimated from – Multi-model ensembles of 20th

century simulations• With different combinations of

external forcings– Anthropogenic (GHG,

aerosols, etc)– Natural (Volcanic, solar)

• Multiple models, ensemble sizes from 1-9 runs

• Assume linearity of response

IPCC WG1 AR4 Fig. TS-23

Figure 9.1

Examples of signals

Solar Volcanic

GHGs Ozone

Direct SO4 aerosol All

20th century

response to forcing simulated by PCM

IPCC WG1 AR4 Fig. 9.1

• Signal error term represents effects of– Internal variability (ensemble sizes are finite)– Structural error

• Know that multi-model mean often a better presentation of current climate• Do not know how model space has been sampled

εξ)β(XY

• Ultimate small sample inference problem: Ultimate small sample inference problem: Observations provide very little information Observations provide very little information about the error variance-covariance structureabout the error variance-covariance structure

• Scaling factor– Alters amplitude of simulated response pattern

• Error term– Sampling error in observations (likely small)– Internal variability (substantial, particular at smaller scales)– Misfit between model-simulated signal and real signal (hopefully

small … a scaling factor near unity would support this)

We think models adequately represent internal surface temperature variability on global scales …

Variability of observed and simulated annual global mean surface temperature(1901-2005)

ALL forcings58 simulations

14 models IPCC WG1 AR4 Fig. 9.7

Figure 9.8

… and also on continental scales

IPCC WG1 AR4 Fig. 9.8

Evaluateamplitudeestimates

Observations1946-56

Model

1986-96

XY Total least squares regression in reduced dimension space

XYFiltering and projection onto reduceddimension space

Evaluate goodness of

fit̂ ̂

Weaver and Zwiers, 2000

Estimated contribution from greenhouse gas (red), other anthropogenic (green) and natural (blue) components to observed global mean surface temperature changes, based on ‘optimal’ detection analyses

1900-99

1950-99

‘Most of the observed increase in global average temperatures since the mid-20th century is very likely

due to the observed increase in anthropogenic

greenhouse gas concentrations.’

• There have been significant advances in the methods used for attribution of the causes of observed climate change over the past two decades

• A clear anthropogenic signal can be identified in observed climate changes over the last 50 years in many variables and in temperature in almost all regions

• Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.

IPCC AR4 WGI chapt 9 (www.ipcc.ch)

Summary