A brief history of time the detection and attribution of climate change

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A brief history of timethe detection and
attribution of climate change

• David Karoly
• School of Meteorology
• University of Oklahoma

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What is detection and attribution?

• 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.

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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

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Why do detection and attribution?

• To identify the causes of recent observed climate
  variations
• To evaluate the performance of climate models in
  simulating the observed climate variations over
  the last century
• To constrain the projections of future climate
  change

Senator James Inhofe (R, Oklahoma), Chair, Senate
Env. and Public Works Comm., in a speech to the
US Senate on Jan 4, 2005 I called the threat of
catastrophic global warming the greatest hoax
ever perpetrated on the American people
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History
Madden and Ramanathan (1980) surface warming due
to increasing carbon dioxide should be
detectable (by) the year 2000
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History
IPCC First Assessment Report in 1990 had no
attribution chapter general statement on
consistency of observed warming with model
projections
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History
IPCC SAR (1995) had detection and attribution
chapter the balance of evidence suggests a
discernable human influence on climate
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History
IPCC TAR (2001) Most of the observed warming
over the last fifty years is likely to have been
due to the increase in greenhouse
gas concentrations
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History
IPCC Fourth Assessment Report (2007) ??
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Initial studies to SAR (1995)

• Univariate analysis of global mean temperature
  comparing change with internal variability
• Difficult to separate different causes that
  affect global radiation balance increasing
  greenhouse gases, increasing solar irradiance
• Use the spatial pattern of the temperature
  response to differentiate between different
  causes fingerprint analysis
• Initially consider contrast between troposphere
  and stratosphere using pattern correlation
  Karoly et al (1994), Santer et al (1995)

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Changes in zonal mean atmospheric temperature
(C), 1960-1995 Modelled and observed
From Tett et al (1996), following Santer et al
(1995)
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Further studies to TAR (2001)

• Use optimal fingerprint analysis to reduce noise
  by rotating detection vector away from noise
  direction
• Use linear regression to estimate amplitude of
  forced signal from model pattern and
  observational data
• Applied to spatial pattern of surface temperature
  change
• Use more models, including models without flux
  correction between the atmosphere and ocean

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Global mean surface temperature (C)
All factors
HadCM3 model (black) Observations (red)
Anthropogenic only
Natural only
Stott et al. (2000)
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Apply optimal fingerprint analysis to large-scale
variations of surface temperature at decadal
timescales
Bars show 5-95 uncertainty limits
Allen et al. (2000)
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Optimised predictions of temperature change (C),
from 1990 to 2040 under IS92a emissions (diamonds)
Allen et al, 2000
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Studies since the TAR

• Use other variables anthropogenic signal found
  in ocean heat content, mean sea level pressure,
  and temperature extremes
• Evaluate anthropogenic signal in temperature
  changes at smaller scales
• Key uncertainties include relating regional
  trends to anthropogenic climate change IPCC TAR

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Continental-scale studies

• Stott (2003) showed that most of the observed
  warming over the last 50 years in six separate
  continents, including North America, Eurasia and
  Australia, was likely to have been due to the
  increase in greenhouse gases

Karoly et al (2003)
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Detection of regional warming

• Calculate observed linear trend in each grid-box
  and test for 95 significance (marked with )
  using model control simulations to provide
  estimate of natural variability of trends (Karoly
  and Wu, 2005)

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Simple indices of climate variability change

• Select a small number of indices of surface
  temperature variations that represent different
  aspects of natural climate variability but
  represent key features of patterns of
  anthropogenic climate change (following Braganza
  et al., 2003, 2004)
• Want indices that show a common signal due to
  greenhouse climate change but are nearly
  independent for natural climate variations
• Global mean surface temperature (GM)
• Mean land ocean temp difference (LO)
• Mean magnitude of the annual cycle over land (AC)
• Mean meridional temperature gradient in the NH
  (MTG)

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Describing climate variability
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Assessing climate change
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Detection of regional warming California

• Compare observed area-mean temperature change
  with model simulations for 20th century from NCAR
  CCSM3 and GFDL CM2

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Attribution of regional warming California

• Probability distributions of 90-year trends in
  California temperature from control model
  simulations (solid line) and 20th century
  simulations with increasing greenhouse gases and
  aerosols (dash-dot line, 20C3M).

The observed trend agrees well with the 20C3M
simulations and cant be explained by natural
climate variations
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Attribution of regional warming Central England
temperature

• Probability distributions of 50-year trends in
  CET from control model simulations (solid line)
  and 20th century simulations with anthropogenic
  (ANT) and natural (NAT) external forcing

The observed trend agrees well with the ANT
simulations and cant be explained by NAT
simulations
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Continental-scale temperature projections
Uncertainty plumes for changes relative to 1990s
using scalings based on continental-scale
attribution. Probabilities are represented by the
depth of shading. From Stott et al. (2006)
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Conclusions

• There have been significant advances in the
  methods used for attribution of the causes of
  observed climate change over the past two decades
• The predictions of Madden and Ramanathan (1980)
  proved to be uncannily correct
• 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