1 scientific adventures with tom: detecting human-induced climate change, and the great msu debate...

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Scientific Adventures with Tom: Detecting Human-Induced Climate Change, and the Great MSU Debate

Scientific Adventures with Tom: Detecting Human-Induced Climate Change, and the Great MSU Debate

Ben Santer

Program for Climate Model Diagnosis and IntercomparisonLawrence Livermore National Laboratory, Livermore, CA 94550

Email: [email protected]

Wigley Symposium

National Center for Atmospheric Research, Boulder Colorado

June 19th, 2009

Ben Santer

Program for Climate Model Diagnosis and IntercomparisonLawrence Livermore National Laboratory, Livermore, CA 94550

Email: [email protected]

Wigley Symposium

National Center for Atmospheric Research, Boulder Colorado

June 19th, 2009

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Structure of talkStructure of talk

What is climate change detection and attribution?

A brief history of fingerprint research

Fingerprinting examples

Inconvenient observations

Does fingerprinting have a future?

Conclusions






Conclusions

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Detection of climate change

The process of showing that an observed change is highly unusual in a statistical sense

Attribution of climate change

The process of establishing cause and effect relationships

Detection and attribution definedDetection and attribution defined

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Detection and attribution research has made important contributions to the conclusions of IPCC assessments Detection and attribution research has made important contributions to the conclusions of IPCC assessments

“The balance of evidence suggests a discernible human influence on global climate”

“The balance of evidence suggests a discernible human influence on global climate”

“There is new and stronger evidence that most of the warming observed over the last 50 years is attributable to human activities”

“There is new and stronger evidence that most of the warming observed over the last 50 years is attributable to human activities”

“Most of the observed increase in globally averaged temperatures since the mid-20th century is very likely* due to the observed increase in anthropogenic greenhouse gas concentrations”

“Most of the observed increase in globally averaged temperatures since the mid-20th century is very likely* due to the observed increase in anthropogenic greenhouse gas concentrations”

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Conclusions






Conclusions

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Strategy: Search for a computer model-predicted pattern of climate change (the “fingerprint”) in observed climate records

Assumption: Each factor that influences climate has a unique signature in climate records

Method: Standard signal processing techniques

Advantage: Fingerprinting allows researchers to make rigorous tests of competing hypotheses regarding the causes of recent

climate change

Strategy: Search for a computer model-predicted pattern of climate change (the “fingerprint”) in observed climate records

Assumption: Each factor that influences climate has a unique signature in climate records

Method: Standard signal processing techniques

Advantage: Fingerprinting allows researchers to make rigorous tests of competing hypotheses regarding the causes of recent

climate change

What is “climate fingerprinting”?What is “climate fingerprinting”?

Key scientific questions addressed in detection and attribution (“D&A”) studiesKey scientific questions addressed in detection and attribution (“D&A”) studies

EARLY WORK (1979 to mid-1990s)

Can we use climate model data to identify promising “fingerprints” of human effects on climate?

What are the relative merits of different “fingerprint” detection methods?

LATER WORK (mid-1990s to present)

Can we apply D&A methods in the real world, and successfully identify a human-caused “fingerprint” in observed climate records?

Can we move beyond “temperature only” D&A studies?

Is the climate system telling us a physically- and internally-consistent story?

EARLY WORK (1979 to mid-1990s)

Can we use climate model data to identify promising “fingerprints” of human effects on climate?

What are the relative merits of different “fingerprint” detection methods?

LATER WORK (mid-1990s to present)

Can we apply D&A methods in the real world, and successfully identify a human-caused “fingerprint” in observed climate records?

Can we move beyond “temperature only” D&A studies?

Is the climate system telling us a physically- and internally-consistent story?

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A brief history of D&A research: Some important milestonesA brief history of D&A research: Some important milestones

1979 1980 1981 1982 1983 1984 1985 1986

1987 1988 1989 1990 1991 1992 1993 1994

1995 1996 1997 1998 1999 2000 2001 2002

Publication of IPCC SAR; Fingerprinting with atmospheric temperature and SAT

Publication of first paper on the theory of optimal detection

Publication of IPCC First Assessment Report

Publication of IPCC TAR; Fingerprinting with ocean heat content

2003 2004 2005 2006 2007 2008

Publication of IPCC FAR; Fingerprinting with zonal-mean rainfall, water vapor, and surface specific humidity

Fingerprinting with tropopause height, sea-level pressure, MSU T4 and T2 temperatures

Fingerprinting with continental runoff; CCSP Report 1.1 resolves MSU problem

First use of Bayesian methods in D&A studies

Application of pattern correlations and multi-variable methods to D&A problem

Introduction of space-frequency D&A approach; Detection of GS fingerprint in SAT

First work on S/N ratios for a greenhouse-gas signal

First application of optimal detection method to problem of detecting human influences on climate

Recognition that “Optimal detection is regression”; First use of space-time D&A methods

First assessment of “fractional attributable risk” for an extreme event

Introduction of “multi-pattern” fingerprinting

All sins of omission or commission are unambiguously attributable to Ben Santer


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A brief history of D&A research: Some important milestonesA brief history of D&A research: Some important milestones

1979 1980 1981 1982 1983 1984 1985 1986

1987 1988 1989 1990 1991 1992 1993 1994

1995 1996 1997 1998 1999 2000 2001 2002

Publication of IPCC SAR; Fingerprinting with atmospheric temperature and SAT

Publication of first paper on the theory of optimal detection

Publication of IPCC First Assessment Report

Publication of IPCC TAR; Fingerprinting with ocean heat content

2003 2004 2005 2006 2007 2008

Publication of IPCC FAR; Fingerprinting with zonal-mean rainfall, water vapor, and surface specific humidity

Fingerprinting with tropopause height, sea-level pressure, MSU T4 and T2 temperatures

Fingerprinting with continental runoff; CCSP Report 1.1 resolves MSU problem

First use of Bayesian methods in D&A studies

Application of pattern correlations and multi-variable methods to D&A problem

Introduction of space-frequency D&A approach; Detection of GS fingerprint in SAT

First application of optimal detection method to problem of detecting human influences on climate

Recognition that “Optimal detection is regression”; First use of space-time D&A methods

First assessment of “fractional attributable risk” for an extreme event

Introduction of “multi-pattern” fingerprinting



First work on S/N ratios for a greenhouse-gas signal

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D&A in the early 1980s: Defining and bounding the problem (Wigley and Jones, Nature, 1981)D&A in the early 1980s: Defining and bounding the problem (Wigley and Jones, Nature, 1981)

The best climate parameters to monitor are those with the highest signal-to-noise ratio (not necessarily those with highest signal!)

Information in the spatial and seasonal patterns of climate change may help to distinguish between a GHG signal and natural variability

Important to study other climate variables (not just surface temperature)

Noise reduction is helpful in D&A work (e.g., by spatial averaging, time averaging, and removal of noise associated with ENSO variability)

“The effects of CO2 may not be detectable until around the turn of the century. By this time, atmospheric CO2 concentration will probably have become sufficiently high… that a climatic change significantly larger than any which has occurred in the past century could be unavoidable.”

The best climate parameters to monitor are those with the highest signal-to-noise ratio (not necessarily those with highest signal!)

Information in the spatial and seasonal patterns of climate change may help to distinguish between a GHG signal and natural variability

Important to study other climate variables (not just surface temperature)

Noise reduction is helpful in D&A work (e.g., by spatial averaging, time averaging, and removal of noise associated with ENSO variability)

“The effects of CO2 may not be detectable until around the turn of the century. By this time, atmospheric CO2 concentration will probably have become sufficiently high… that a climatic change significantly larger than any which has occurred in the past century could be unavoidable.”

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D&A in 1990: The view from the first IPCC Scientific Assessment ReportD&A in 1990: The view from the first IPCC Scientific Assessment Report

“The fact that we have not yet detected the enhanced greenhouse effect leads to the question: When is this likely to occur? …Detection is not a simple yes/no issue. Rather, it involves the gradual accumulation of evidence in support of model predictions, which, in parallel with improvements in the models themselves, will increase our confidence in them and progressively narrow the uncertainties…”

“…the time frame for detection is likely to be of order a decade or more. In order to detect the enhanced greenhouse effect within this time frame, it is essential to continue the development of models, and to ensure that existing observing systems for both climate variables and potential climate forcing factors be maintained or improved.”

“The fact that we have not yet detected the enhanced greenhouse effect leads to the question: When is this likely to occur? …Detection is not a simple yes/no issue. Rather, it involves the gradual accumulation of evidence in support of model predictions, which, in parallel with improvements in the models themselves, will increase our confidence in them and progressively narrow the uncertainties…”

“…the time frame for detection is likely to be of order a decade or more. In order to detect the enhanced greenhouse effect within this time frame, it is essential to continue the development of models, and to ensure that existing observing systems for both climate variables and potential climate forcing factors be maintained or improved.”

Wigley and Barnett, “Detection of the greenhouse effect in the observations”, Chapter 8 of IPCC First Assessment Report (1990)Wigley and Barnett, “Detection of the greenhouse effect in the observations”, Chapter 8 of IPCC First Assessment Report (1990)

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Conclusions






Conclusions

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Different factors that influence climate have different “fingerprints”Different factors that influence climate have different “fingerprints”

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1. Solar1. Solar

3. Well-mixed greenhouse gases

3. Well-mixed greenhouse gases

5. Sulfate aerosol particles

5. Sulfate aerosol particles

2. Volcanoes2. Volcanoes

4. Ozone4. Ozone

Hei

ght

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eigh

t (k

m)

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ght

(km

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ssur

e (h

Pa)

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°C/centurySanter et al., CCSP Report (2006)Santer et al., CCSP Report (2006)

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Eq 30S 60S 90S90N 60N 30N

Eq 30S 60S 90S90N 60N 30N90N 60N 30N Eq 30S 60S 90S

90N 60N 30N Eq 30S 60S 90S

-1.2 -0.8 -0.4 0 0.4 0.8 1.2

-1 -0.6 -0.2 0.2 0.6 1

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“Fingerprinting” with temperature changes in Earth’s atmosphere“Fingerprinting” with temperature changes in Earth’s atmosphere

Model Changes: CO2 + Sulfate Aerosols + Stratospheric Ozone

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Observed Changes

Temperature changes in oCTemperature changes in oC

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Santer et al., Nature (1996)Santer et al., Nature (1996)

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The climate system is telling us a physically-consistent story. We have identified human fingerprints in…The climate system is telling us a physically-consistent story. We have identified human fingerprints in…

TEMPERATURE FIELDS

1. Global-scale surface temperatures

2. Regional-scale surface temperatures

3. Vertical profiles of atmospheric temperature

4. Global ocean heat content

5. MSU stratospheric and tropospheric temperatures

6. The height of the tropopause

7. Vertical structure of upper-ocean temperatures

8. SSTs in hurricane formation regions

9. Arctic and Antarctic temperatures

TEMPERATURE FIELDS

1. Global-scale surface temperatures

2. Regional-scale surface temperatures

3. Vertical profiles of atmospheric temperature

4. Global ocean heat content

5. MSU stratospheric and tropospheric temperatures

6. The height of the tropopause

7. Vertical structure of upper-ocean temperatures

8. SSTs in hurricane formation regions

9. Arctic and Antarctic temperatures

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We’ve moved beyond “temperature only” fingerprint detection studies…We’ve moved beyond “temperature only” fingerprint detection studies…

ATMOSPHERIC CIRCULATION, SEA-ICE, AND THE HYDROLOGICAL CYCLE

1. Sea-level pressure

2. Continental-scale runoff

3. Atmospheric water vapor over oceans

4. Surface specific humidity

5. Zonal-mean precipitation

6. Hydrologically-relevant climate variables in the western U.S.

7. Arctic sea-ice extent

ATMOSPHERIC CIRCULATION, SEA-ICE, AND THE HYDROLOGICAL CYCLE

1. Sea-level pressure

2. Continental-scale runoff

3. Atmospheric water vapor over oceans

4. Surface specific humidity

5. Zonal-mean precipitation

6. Hydrologically-relevant climate variables in the western U.S.

7. Arctic sea-ice extent

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Conclusions






Conclusions

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No history of detection and attribution work would be complete without discussion of the “great MSU debate” No history of detection and attribution work would be complete without discussion of the “great MSU debate”

James Schlesinger (former U.S. Secretary of Energy, Secretary of Defense, and Director of the CIA), “Cold Facts on Global Warming,” L.A. Times, January 22, 2004

James Schlesinger (former U.S. Secretary of Energy, Secretary of Defense, and Director of the CIA), “Cold Facts on Global Warming,” L.A. Times, January 22, 2004

“…satellite measurements over 35 years show no significant warming in the lower atmosphere, which is an essential part of the global-warming theory.”“…satellite measurements over 35 years show no significant warming in the lower atmosphere, which is an essential part of the global-warming theory.”

“Inconvenient observations” – the apparent lack of tropospheric warming in satellite data“Inconvenient observations” – the apparent lack of tropospheric warming in satellite data

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Using microwave sounders to measure atmospheric temperature from spaceUsing microwave sounders to measure atmospheric temperature from space

Higher temperatures = more microwave emissions from oxygen molecules

By choosing different microwave frequencies, different layers in the atmosphere can be measured

Much of the scientific focus has been on measurements of the temperature of the lowest 7–8 km of the atmosphere

Higher temperatures = more microwave emissions from oxygen molecules

By choosing different microwave frequencies, different layers in the atmosphere can be measured

Much of the scientific focus has been on measurements of the temperature of the lowest 7–8 km of the atmosphere

Figure and text courtesy of Carl Mears, RSSFigure and text courtesy of Carl Mears, RSS

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Which groups have been involved in constructing “Climate Data Records” from MSU information?Which groups have been involved in constructing “Climate Data Records” from MSU information?

University of Alabama at Huntsville (UAH)

John Christy and Roy Spencer

Remote Sensing Systems (RSS)

Frank Wentz and Carl Mears

University of Maryland (UMd)

Konstantin Vinnikov, Norm Grody

NOAA National Environmental Satellite, Data, and Information Service

Cheng-Zhi Zou, Mitch Goldberg, et al.

University of Alabama at Huntsville (UAH)

John Christy and Roy Spencer

Remote Sensing Systems (RSS)

Frank Wentz and Carl Mears

University of Maryland (UMd)

Konstantin Vinnikov, Norm Grody

NOAA National Environmental Satellite, Data, and Information Service

Cheng-Zhi Zou, Mitch Goldberg, et al.

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The UAH satellite dataset implied that the troposphere cooled as the tropical surface warmedThe UAH satellite dataset implied that the troposphere cooled as the tropical surface warmed

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The RSS satellite data showed that the troposphere warmed by more than the surfaceThe RSS satellite data showed that the troposphere warmed by more than the surface

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What factors contribute to these differences?What factors contribute to these differences?

1980 1985

As

ce

nd

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CT

(H

rs.)

1990 1995 2000

NOAA-6 NOAA-8 NOAA-10 NOAA-12

NOAA-6

TIROS-N NOAA-7 NOAA-9 NOAA-11NOAA-14

Year

Local measurement time for each satellite drifts due to orbital drift

This leads to drifts in the sampling of the Earth’s daily temperature cycle

These drifts need to be removed, or they can affect long-term trends

Local measurement time for each satellite drifts due to orbital drift

This leads to drifts in the sampling of the Earth’s daily temperature cycle

These drifts need to be removed, or they can affect long-term trends

Figure and text courtesy of Carl Mears, RSSFigure and text courtesy of Carl Mears, RSS

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An early satellite-based analysis of the temperature of the tropical troposphere has a spurious cooling trend An early satellite-based analysis of the temperature of the tropical troposphere has a spurious cooling trend

Weather balloon estimates of the temperature of the tropical troposphere also contain a spurious cooling trend

Weather balloon estimates of the temperature of the tropical troposphere also contain a spurious cooling trend

When errors in the satellite and weather balloon data are accounted for, both models and observations show warming of the tropical troposphere relative to the surface

When errors in the satellite and weather balloon data are accounted for, both models and observations show warming of the tropical troposphere relative to the surface

Three papers in Science partially resolved the “great MSU debate”Three papers in Science partially resolved the “great MSU debate”

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ResolutionResolution

(Executive Summary of U.S. Climate Change Science Program Report, May 2006)(Executive Summary of U.S. Climate Change Science Program Report, May 2006)

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ResolutionResolution

(Executive Summary of U.S. Climate Change Science Program Report, May 2006)(Executive Summary of U.S. Climate Change Science Program Report, May 2006)

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A brief history of MSU research: Some important milestonesA brief history of MSU research: Some important milestones

1947 1956 1961 1963 1978

1979 1990 1991 1992 1993 1994

1995 1996 1997 1998 1999 2000 2001 2002

Theory of microwave absorption by oxygen by J.H. van Vleck


Publication of first MSU paper by Spencer and Christy in Science


2003 2004 2005 2006 2007 2008

Santer et al. perform “fingerprinting” with MSU T4 and T2; Vinnikov and Grody produce T2 record


U.S. Climate Change Science Program Report 1.1 partially resolves MSU problem


Wentz and Schabel identify “falling satellite” effect missed by UAH group


Christy et al. discover two errors which compensate for the “falling satellite” effect


Fu et al. quantify contribution of cooling stratosphere to MSU T2




Douglass et al. claim existence of significant model- versus-OBS discrepancy

Douglass et al. claim existence of significant model- versus-OBS discrepancy

Rebuttal of Douglass et al. paper by Santer et al.

Rebuttal of Douglass et al. paper by Santer et al.

Christy and Spencer outline a method for retrieving lower tropospheric temperature


First complete year of MSU-based temperature measurements


J.I.F. King proposes using satellites to derive atmospheric temperature by measurement of atmospheric thermal emissions


M.L. Meeks suggests use of microwave emissions from oxygen for monitoring atmospheric temperature


Meeks and Lilley develop basic concept for use of microwave emissions from oxygen for monitoring atmospheric temperature


Hurrell and Trenberth identify multiple problems with UAH MSU records


Mears and Wentz, Sherwood et al., and Santer et al. papers published in Science


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A brief history of MSU research: Some important milestonesA brief history of MSU research: Some important milestones

1947 1956 1961 1963 1978

1979 1990 1991 1992 1993 1994

1995 1996 1997 1998 1999 2000 2001 2002





2003 2004 2005 2006 2007 2008













IPCC FAR published; Douglass et al. claim significant model/ OBS discrepancy

IPCC FAR published; Douglass et al. claim significant model/ OBS discrepancy

Rebuttal of Douglass et al. paper

Rebuttal of Douglass et al. paper















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Conclusions






Conclusions

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Looking towards the futureLooking towards the future

In a post AR4 world, is the science “done and dusted”?

What will the role of detection and attribution research be in AR5?

In a post AR4 world, is the science “done and dusted”?

What will the role of detection and attribution research be in AR5?

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Key scientific issues for future detection and attribution (“D&A”) studiesKey scientific issues for future detection and attribution (“D&A”) studies

1. Most fingerprint work has focused on global-scale changes in individual, “primary” climate variables

Can we identify anthropogenic effects on climate at continental to regional scales?

Can we identify anthropogenic fingerprints in variables of direct relevance to climate-change impacts? (e.g., timing of stream flow, snowpack depth)

Can we attribute shifts in the distributions of plant and animal species to human influences? (the “double attribution” problem)

Can a “multi-variable” fingerprint help us to identify human effects on climate?

1. Most fingerprint work has focused on global-scale changes in individual, “primary” climate variables

Can we identify anthropogenic effects on climate at continental to regional scales?

Can we identify anthropogenic fingerprints in variables of direct relevance to climate-change impacts? (e.g., timing of stream flow, snowpack depth)

Can we attribute shifts in the distributions of plant and animal species to human influences? (the “double attribution” problem)

Can a “multi-variable” fingerprint help us to identify human effects on climate?

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2. We now live in a multi-model world, yet most D&A studies to date have been performed with individual models

Can we show that D&A results are robust to current uncertainties in model estimates of the searched-for fingerprint and the noise of natural variability?

2. We now live in a multi-model world, yet most D&A studies to date have been performed with individual models

Can we show that D&A results are robust to current uncertainties in model estimates of the searched-for fingerprint and the noise of natural variability?

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3. We cannot confidently attribute any specific extreme event to human-induced climate change

But can we make informed scientific statements about the influence of human activities on the likelihood of extreme events? (the “operational attribution” issue)

3. We cannot confidently attribute any specific extreme event to human-induced climate change

But can we make informed scientific statements about the influence of human activities on the likelihood of extreme events? (the “operational attribution” issue)

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Conclusions






Conclusions

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ConclusionsConclusions

MSU-based estimates of tropospheric temperature change are not

“inconvenient observations”

We have identified human “fingerprints” in a number of different aspects

of the climate system

We have moved beyond “temperature only” D&A

Criticisms leveled at IPCC Second Assessment Report (“you are only

looking at surface temperature changes”) are no longer valid

The climate system is telling us a physically- and internally-consistent story:

Natural causes alone cannot explain the observed climate changes

Tom Wigley has played a major role in telling both the MSU and

fingerprint stories

MSU-based estimates of tropospheric temperature change are not

“inconvenient observations”

We have identified human “fingerprints” in a number of different aspects

of the climate system

We have moved beyond “temperature only” D&A

Criticisms leveled at IPCC Second Assessment Report (“you are only

looking at surface temperature changes”) are no longer valid

The climate system is telling us a physically- and internally-consistent story:

Natural causes alone cannot explain the observed climate changes

Tom Wigley has played a major role in telling both the MSU and

fingerprint stories

1 scientific adventures with tom: detecting human-induced climate change, and the great msu debate...

Documents

climate fingerprinting

detection of climate

attribution of climate

climate change detection

global climate

observed climate records

climate model diagnosis

humaninduced climate