Presentation at Yale University

lecture by Ben Santer, UoMichigan, March 27, 2008, AOSS 480

How Do We Know That Human Activities Have Influenced Global Climate? Ben Santer Program for Climate Model Diagnosis and Intercomparison Lawrence Livermore National Laboratory, Livermore, CA 94550 Email: [email protected]

Climate Change: The Move to Action Lecture to Prof. Richard B. Rood’s Class (AOSS 480 // NRE 501) University of Michigan, Ann Arbor, March 27, 2008

1


Key result of previous IPCC reports: There is growing evidence for a human “fingerprint” 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”

“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” 2


Structure of talk

z Climate Change 101 z How do we study the causes of climate change? z A few common myths about climate change z Conclusions and some personal thoughts

3

Section 1: Climate Change 101


Natural mechanisms influence climate

Natural mechanisms z

Changes in the Sun

z

Changes in the amount of volcanic dust in the atmosphere

z

Internal variability of the coupled atmosphere-ocean system

4



Human factors also influence climate Non-natural mechanisms z

Changes in atmospheric concentrations of greenhouse gases

z

Changes in aerosol particles from burning fossil fuels and biomass

z

Changes in the reflectivity (albedo) of the Earth’s surface

5 Smoke from fires in Guatemala and Mexico (May 14, 1998)



Recent changes in carbon dioxide are largely humaninduced

Carbon dioxide is the most important greenhouse gas produced by human activities Atmospheric CO2 has increased from a pre-industrial value of about 280 parts per million (ppm) to 379 ppm in 2005 The atmospheric concentration of CO2 in 2005 exceeds by far the natural range (180 to 300 ppm) over the last 650,000 years Fossil fuel use is the primary source of the increased concentration of CO2 since the pre-industrial period

Source: IPCC AR4 (2007)



Average surface temperature change (°C)

Models can perform the “control experiment” that we can’t do in the real world

Meehl et al., J. Climate (2004)

7



We routinely test how well current climate models simulate: z Response to external “forcings” on a range of time scales ¨ Today’s annual mean climate ¨ The diurnal cycle ¨ The seasonal cycle ¨ The response to massive volcanic eruptions ¨ Ocean uptake of products of atmospheric tests of nuclear weapons ¨ The climate changes of the past 30 to 150 years ¨ Climates of the “deep past” (e.g., the last Ice Age)

z “Unforced” behavior ¨ Weather ¨ Modes of natural climate varibility (El Niño, North Atlantic Oscillation, etc.) 8



One test: Evaluating the relative skill of coupled models in simulating the seasonal cycle “Worst”

Latent heat flux at surface Sensible heat flux at surface Surface temperature Reflected SW radiation (clear sky) Reflected SW radiation Outgoing LW radiation (clear sky) Outgoing LW radiation Total cloud cover Precipitation Total column water vapor Sea-level pressure Meridional wind stress Zonal wind stress Meridional wind at surface Zonal wind at surface Specific humidity at 400 mb Specific humidity at 850 mb Meridional wind at 200 mb Zonal wind at 200 mb Temperature at 200 mb Geopotential height at 500 mb Meridional wind at 850 mb Zonal wind at 850 mb

“Best” V

T

U

S

R

P

Q

N

O

L

M

K

I

J

H

F

G

E

D

C

A

B

Mean

Median

Temperature at 850 mb

CMIP3 (IPCC) model

IPCC AR4 Model

Gleckler, Taylor, and Doutriaux, Journal of Geophysical Research (2008)

9



Another test: Do coupled models capture the atmospheric temperature changes after major volcanic eruptions?

10



Testing how well models simulate climate variability Average model water vapor variability is slightly larger than in observations

Santer et al., Proceedings of the National Academy of Sciences (2007)

11



Can we evaluate model performance in simulating future climate change?

Figure TS.26

12

Section 2: Studying the Causes of Climate Change


Structure of talk


13



Multiple lines of evidence on which “discernible human influence” conclusions are based 1. “Basic physics” evidence ¨ Physical understanding of the climate system and the heat-trapping properties of greenhouse gases 2. Circumstantial evidence ¨ Qualitative agreement between observed climate changes and model predictions of human-caused climate changes (warming of oceans, land surface, and troposphere, stratospheric cooling, water vapor increases, etc.) 3. Paleoclimate evidence ¨ Temperature reconstructions enable us to place the warming of the 20th century in a longer-term context 4. Fingerprint evidence ¨ Rigorous statistical comparisons between modeled and observed patterns of climate change 14



What is “climate fingerprinting”?

z Strategy:

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

z Assumption:

Each factor that influences climate has a different characteristic signature in climate records

z Method:

Standard signal processing techniques

z Advantage:

Fingerprinting allows researchers to make rigorous tests of competing hypotheses regarding the causes of recent climate change

15



Different factors that influence climate have different “fingerprints” 10

10

24

50

20

50

20

100

16

100

16

200

12

200

12

300

8

500 700 1000 90N 10

4 60N

30N

Eq

30S

60S

90S

300

Pressure (hPa)

3. Well-mixed greenhouse gases

24

60N

30N

Eq

30S

60S

28 25

24 20

100

16

100

16

200

12

200

12

8

500 700 1000 90N 10

4 60N

30N

Eq

30S

60S

90S

300

8

500 700 1000 90N

4 60N

30N

Eq

30S

60S

90S

10 28

25

Pressure (hPa)

5. Sulfate aerosol particles

28

24

25

50

20

50

20

100

16

100

16

200

12

200

12

8

300

300 500 700 1000 90N

4 60N -1

Santer et al., CCSP, 2007

6. 1st five factors combined

90S

20

300

4. Ozone

4

50

50

2. Volcanoes

8

500 700 1000 90N 10

28 25

Height (km)

24

28 25

Height (km)

25

Height (km)

1. Solar

Pressure (hPa)

28

-1.2

30N -0.6

-0.8

Eq -0.2

-0.4

30S 0.2

0

60S

0.6 0.4

90S

24

8

500 700 1000 90N

4 60N

1 0.8

-1 1.2

-1.2

30N -0.6

-0.8

Eq -0.2

-0.4

30S 0.2

0

60S

0.6 0.4

90S

1 0.8

1.2

°C/century

16



“Fingerprinting” with temperature changes in Earth’s atmosphere Model Changes: CO2 + Sulfate Aerosols + Stratospheric Ozone 50

14 200 10

300

Height (km)

Pressure (hPa)

18 100

6

500

2

850 60N

45N

30N

15N

0

15S

30S

45S

60S

Observed Changes 50

100 14 200 10

300

6

500

2

850 60N

45N

30N

-1.5 -1.8

Santer et al., Nature (1996)

Height (km)

Pressure (hPa)

18

15N

-0.9 -1.2

0 -0.3

-0.6

15S 0.3

0

30S 0.9

0.6

45S

60S

1.5 1.2

1.8

Temperature changes in oC

17



Searching for fingerprints of human activities in the world’s oceans

z

Initial work by Syd Levitus and colleagues showed an increase in the heat content of the oceans over the second half of the 20th century (Levitus et al., 2001, Science)

z

Subsequent research by Tim Barnett and colleagues identified a human fingerprint in the observed ocean heat content changes (Barnett et al., 2001, Science)

18



“Fingerprinting” in the ocean: Warming of the North Atlantic over 1955-99

Barnett et al., Science (2005)

19



“Fingerprinting” in the ocean: Warming of the world’s oceans over 1955-99

Barnett et al., Science (2005)

20



Fingerprint detection explained pictorially…. Time-varying observed patterns

t=1 t=2 t=3 t=4 t=n

Time-varying control run patterns

t=1 t=2 t=3 t=4 t=n

Model fingerprint

Projection onto model fingerprint

Signal and noise time series

Projection onto model fingerprint

Signal-to-noise ratios

21



Human-caused fingerprints have been identified in many different aspects of the climate system Surface specific humidity

Water vapor over oceans

Tropospheric temperatures

Stratospheric temperatures

Tropopause height

Ocean temperatures

Sea-level pressure

Atmospheric temperature 50 18 100 14 200

Zonal-mean rainfall

Near-surface temperature

10

300

6

500

2

850 60N

45N

30N

15N

0

15S

30S

45S

60S

Continental runoff

22



Key results of IPCC AR4: We are now able to identify human influences on climate at continental scales

Continental warming likely shows a significant anthropogenic contribution over the past 50 years

23

Section 3: A Few Common Myths About Climate Change


Structure of talk


24



Myth 1: Climate models can’t simulate the “observed” variability of ocean temperatures

z A persistent criticism: ¨ “Variability is not adequately simulated in the current generation of coupled climate models used to study the impact of anthropogenic influences on climate” (Lyman et al., Geophysical Research Letters, 2006) z If true, this would cast doubt on the credibility of studies that have

claimed identification of a human “fingerprint” in ocean temperatures

25



The ocean observing network has changed dramatically over time Number of Observations at the 100m Level 1955 1965

1975

1985

26 Source: AchutaRao et al., JGR (2006)



Time-variability of “sub-sampled” ocean temperature data (°C)

Do models systematically underestimate “observed” variability of ocean temperature?

Models with volcanoes

Models without volcanoes

Time-variability of “complete” ocean temperature data (°C) Source: AchutaRao et al., PNAS (2007)

27



Time-variability of “sub-sampled” ocean temperature data (°C)

Sampling climate model data at the locations of ocean observations improves model-data agreement

Models with volcanoes

Models without volcanoes

Time-variability of “complete” ocean temperature data (°C) Source: AchutaRao et al., PNAS (2007)

28



Myth 2: The global ocean cooled over 2003 to 2005 (Lyman et al., Geophysical Research Letters, 2006)

29



Fractional coverage of measurements

The coverage of different temperature measurement systems changed markedly over the early 21st century

0.8 0.6 0.4 0.2 0.0

AchutaRao et al., Proceedings of the National Academy of Sciences (2007)

30



ARGO profiling floats have transformed our ability to monitor the temperature of the global ocean

“…climate models cannot capture this variablity…”

31



Explanation of global cooling

z Gouretski

and Koltermann (Geophysical Research Letters, 2007) identified biases between different types of instrument used for measuring temperature

z The global ocean “cooling” over 2003 to 2005 reported on by Lyman et

al. is an artifact of time-varying coverage of instruments with different biases

32



Temperature anomaly (˚C; 0-700m)

The “global ocean cooling” between 2003 and 2005 is an artifact!

AchutaRao et al., Proceedings of the National Academy of Sciences (2007)

33


Uncertainty in key observations affects out ability to evaluate climate models!

From Church et al. (Nature, submitted)

34



Myth 3: Models cannot simulate “observed” changes in tropospheric temperature ● Douglass, Christy, Pearson, and Singer: “A comparison of tropical temperature trends with model predictions”. International Journal of Climatology, 2007 ● Based on application of a “robust statistical test”, Douglass et al. conclude that “Models and observations disagree to a statistically significant extent”

● This conclusion is “based on essentially the same data” used in previous work

● Douglass et al. findings are “an inconvenient truth”, and prove that “Nature rules the climate: Human-produced greenhouse gases are not responsible for global warming”* *Press release from press conference held at U.S. National Press Club, January 2008 35



Real-world data (RSS)

Real-world trend plus random noise

Tropospheric temp. anomaly (°C)

Tropospheric temp. anomaly (°C)

A brief primer on fitting trends to noisy data

36



What happens when you compare modeled and observed trends, AND include trend error bars?

37



What happens when you DON’T include trend error bars, and used a flawed test?

38



Comparisons between modeled and observed trends: The view from Douglass et al. (2007)

39



Comparisons between modeled and observed trends: The view from Santer et al. (2008)

40

Section 4: Conclusions


Structure of talk


41



Conclusions: What we know z Human activities have changed the chemical composition of the

atmosphere z Atmospheric CO2 increased by roughly 30% since the 1850s, and is

now at higher levels than at any time in at least the last 650,000 years z The earth’s surface warmed by about 0.74°C ±0.18°C over the last 100

years z The 20th century was probably the warmest of the past two millennia z We have identified human “fingerprints” in a number of different aspects

of the climate system z The climate system is telling us an internally-consistent story 42



Conclusions: What we don’t know very well z How much warmer will the Earth be in 2100? z How will the carbon cycle respond to (and influence) climate change? z How rapidly will the ocean’s conveyor belt circulation respond to climate

change? z At

what level of temperature change do we risk “dangerous anthropogenic interference” with the climate system?

z How will hurricane intensity and frequency change in a warming world? z Can we make useful predictions of the regional-scale features of

climate change? z Will we be smart enough to “do the right thing” for future generations? 43



Personal thoughts (I) z A human-induced warming signal has emerged from the background

“noise” of natural climate variability z A similar “signal” has emerged in media coverage of climate change: ¨ Are humans affecting global climate? ¨ Yes, humans really are affecting climate, and we can see it happening now ¨ How do we mitigate and/or adapt to human-caused climate change?

44



Personal thoughts (II) z

Several months ago, Seth Borenstein asked me: “Why aren’t you profoundly depressed by your work? How can you have any optimism about the future?”

z

My answer: ¨ I’m optimistic because of the “media signal” – thanks to the work of many scientists and journalists, most Americans now understand that our actions have influenced global climate ¨ I’m optimistic because I believe most inhabitants of this planet truly care about the kind of world we will leave behind for our children and grandchildren ¨ I’m optimistic because I believe that we are capable of making smart choices on “what to do” about climate change, if: z

The public has some basic grasp of climate science;

z

The public understands the possible risks of inaction;

z

The public recognizes that they are not helpless, and can take individual and collective action to address human-caused climate change 45



The “Wheel of Climate Fortune”

5°C

(3.8%; 1 in 26 odds)

Source: MIT Joint Program on the Science and Policy of Climate Change

46



The atmosphere does not respect national boundaries

47

Presentation at Yale University

Presentation at Yale University

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