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: santer1@llnl.gov 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-20 th century is very likely* due to the observed increase in anthropogenic greenhouse gas concentrations 2
Structure of talk Climate Change 101 How do we study the causes of climate change? A few common myths about climate change Conclusions and some personal thoughts 3
Section 1: Climate Change 101 Natural mechanisms influence climate Natural mechanisms Changes in the Sun Changes in the amount of volcanic dust in the atmosphere Internal variability of the coupled atmosphere-ocean system 4
Section 1: Climate Change 101 Human factors also influence climate Non-natural mechanisms Changes in atmospheric concentrations of greenhouse gases Changes in aerosol particles from burning fossil fuels and biomass Changes in the reflectivity (albedo) of the Earth s surface Smoke from fires in Guatemala and Mexico (May 14, 1998) 5
Section 1: Climate Change 101 Recent changes in carbon dioxide are largely humaninduced Carbon dioxide is the most important greenhouse gas produced by human activities Atmospheric CO 2 has increased from a pre-industrial value of about 280 parts per million (ppm) to 379 ppm in 2005 The atmospheric concentration of CO 2 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 CO 2 since the pre-industrial period Source: IPCC AR4 (2007)
Models can perform the control experiment that we can t do in the real world Section 1: Climate Change 101 Average surface temperature change ( C) Meehl et al., J. Climate (2004) 7
We routinely test how well current climate models simulate: Section 1: Climate Change 101 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) Unforced behavior Weather Modes of natural climate varibility (El Niño, North Atlantic Oscillation, etc.) 8
Section 1: Climate Change 101 One test: Evaluating the relative skill of coupled models in simulating the seasonal cycle 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 Temperature at 850 mb Mean Median A B C D E F G H I J K L M N O P Q R S T U V CMIP3 (IPCC) model IPCC AR4 Model Worst Best Gleckler, Taylor, and Doutriaux, Journal of Geophysical Research (2008) 9
Section 1: Climate Change 101 Another test: Do coupled models capture the atmospheric temperature changes after major volcanic eruptions? 10
Section 1: Climate Change 101 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? Section 1: Climate Change 101 Figure TS.26 12
Section 2: Studying the Causes of Climate Change Structure of talk Climate Change 101 How do we study the causes of climate change? A few common myths about climate change Conclusions and some personal thoughts 13
Section 2: Studying the Causes of Climate Change 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
Section 2: Studying the Causes of Climate Change What is climate fingerprinting? 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 different characteristic 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 15
Different factors that influence climate have different fingerprints Section 2: Studying the Causes of Climate Change 1. Solar 3. Well-mixed greenhouse gases 5. Sulfate aerosol particles Pressure (hpa) Pressure (hpa) Pressure (hpa) Santer et al., CCSP, 2007 10 25 50 20 100 200 300 500 700 1000 90N 60N 30N 10 25 100 200 300 500 700 1000 90N 60N 30N 10 E q 30S 60S 90S 50 20 25 100 200 300 500 700 1000 90N 60N 30N -1.2-1 -0.8-0.6-0.4-0.2 E q 30S 60S 90S 50 20 Eq 30S 60S 90S 0 0.2 0.4 0.6 0.8 1 1.2 28 24 16 12 8 4 28 24 16 12 8 4 28 24 16 12 8 4 10 25 50 100 200 300 500 700 1000 90N 60N 30N 10 25 100 200 300 500 700 1000 90N 60N 30N 10 25 50 20 100 200 300 500 700 1000 90N 60N 30N -1-0.6-1.2-0.8-0.4 E q 30S 60S 90S 50 20 E q 30S 60S 90S Eq 30S 60S 90S -0.2 0.2 0.6 1 0 0.4 0.8 1.2 28 24 20 16 12 8 4 28 24 16 12 8 4 28 24 16 12 8 4 Height (km) Height (km) Height (km) C/century 2. Volcanoes 4. Ozone 6. 1 st five factors combined 16
Section 2: Studying the Causes of Climate Change Fingerprinting with temperature changes in Earth s atmosphere Model Changes: CO 2 + Sulfate Aerosols + Stratospheric Ozone 50 18 Pressure (hpa) 100 200 300 500 14 10 6 Height (km) 850 60N 45N 30N 15N 0 15S 30S 45S 60S 2 50 Observed Changes 18 Pressure (hpa) 100 200 300 500 14 10 6 Height (km) 850 60N 45N 30N 15N 0 15S 30S 45S 60S 2 Santer et al., Nature (1996) -1.8-1.5-1.2-0.9-0.6-0.3 0 0.3 0.6 0.9 1.2 1.5 1.8 Temperature changes in o C 17
Section 2: Studying the Causes of Climate Change Searching for fingerprints of human activities in the world s oceans Initial work by Syd Levitus and colleagues showed an increase in the heat content of the oceans over the second half of the 20 th century (Levitus et al., 2001, Science) 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 Section 2: Studying the Causes of Climate Change Barnett et al., Science (2005) 19
Fingerprinting in the ocean: Warming of the world s oceans over 1955-99 Section 2: Studying the Causes of Climate Change Barnett et al., Science (2005) 20
Section 2: Studying the Causes of Climate Change Fingerprint detection explained pictorially. Time-varying observed patterns Time-varying control run patterns t=1 t=2 t=3 t=4 t=n t=1 t=2 t=3 t=4 t=n Model fingerprint Projection onto model fingerprint Projection onto model fingerprint Signal and noise time series Signal-to-noise ratios 21
Human-caused fingerprints have been identified in many different aspects of the climate system Section 2: Studying the Causes of Climate Change Surface specific humidity Water vapor over oceans Tropospheric temperatures Stratospheric temperatures Ocean temperatures Tropopause height Sea-level pressure 50 Atmospheric temperature 100 18 14 Zonal-mean rainfall Near-surface temperature 200 300 10 500 6 850 60N 45N 30N 15N 0 15S 30S 45S 60S 2 Continental runoff 22
Section 2: Studying the Causes of Climate Change 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 Climate Change 101 How do we study the causes of climate change? A few common myths about climate change Conclusions and some personal thoughts 24
Section 3: A Few Common Myths About Climate Change Myth 1: Climate models can t simulate the observed variability of ocean temperatures 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) If true, this would cast doubt on the credibility of studies that have claimed identification of a human fingerprint in ocean temperatures 25
Section 3: A Few Common Myths About Climate Change The ocean observing network has changed dramatically over time Number of Observations at the 100m Level 1955 1965 1975 1985 Source: AchutaRao et al., JGR (2006) 26
Do models systematically underestimate observed variability of ocean temperature? Section 3: A Few Common Myths About Climate Change Time-variability of sub-sampled ocean temperature data ( C) Source: AchutaRao et al., PNAS (2007) Time-variability of complete ocean temperature data ( C) Models with volcanoes Models without volcanoes 27
Sampling climate model data at the locations of ocean observations improves model-data agreement Section 3: A Few Common Myths About Climate Change Time-variability of sub-sampled ocean temperature data ( C) Source: AchutaRao et al., PNAS (2007) Time-variability of complete ocean temperature data ( C) Models with volcanoes Models without volcanoes 28
Section 3: A Few Common Myths About Climate Change Myth 2: The global ocean cooled over 2003 to 2005 (Lyman et al., Geophysical Research Letters, 2006) 29
Section 3: A Few Common Myths About Climate Change The coverage of different temperature measurement systems changed markedly over the early 21 st century Fractional coverage of measurements 0.8 0.6 0.4 0.2 0.0 AchutaRao et al., Proceedings of the National Academy of Sciences (2007) 30
Section 3: A Few Common Myths About Climate Change ARGO profiling floats have transformed our ability to monitor the temperature of the global ocean climate models cannot capture this variablity 31
Section 3: A Few Common Myths About Climate Change Explanation of global cooling Gouretski and Koltermann (Geophysical Research Letters, 2007) identified biases between different types of instrument used for measuring temperature 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
Section 3: A Few Common Myths About Climate Change The global ocean cooling between 2003 and 2005 is an artifact! Temperature anomaly ( C; 0-700m) 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
Section 3: A Few Common Myths About Climate Change 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
Section 3: A Few Common Myths About Climate Change A brief primer on fitting trends to noisy data Tropospheric temp. anomaly ( C) Real-world data (RSS) Real-world trend plus random noise Tropospheric temp. anomaly ( C) 36
Section 3: A Few Common Myths About Climate Change What happens when you compare modeled and observed trends, AND include trend error bars? 37
Section 3: A Few Common Myths About Climate Change What happens when you DON T include trend error bars, and used a flawed test? 38
Section 3: A Few Common Myths About Climate Change Comparisons between modeled and observed trends: The view from Douglass et al. (2007) 39
Section 3: A Few Common Myths About Climate Change Comparisons between modeled and observed trends: The view from Santer et al. (2008) 40
Section 4: Conclusions Structure of talk Climate Change 101 How do we study the causes of climate change? A few common myths about climate change Conclusions and some personal thoughts 41
Section 4: Conclusions Conclusions: What we know Human activities have changed the chemical composition of the atmosphere Atmospheric CO 2 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 The earth s surface warmed by about 0.74 C ±0.18 C over the last 100 years The 20 th century was probably the warmest of the past two millennia We have identified human fingerprints in a number of different aspects of the climate system The climate system is telling us an internally-consistent story 42
Section 4: Conclusions Conclusions: What we don t know very well How much warmer will the Earth be in 2100? How will the carbon cycle respond to (and influence) climate change? How rapidly will the ocean s conveyor belt circulation respond to climate change? At what level of temperature change do we risk dangerous anthropogenic interference with the climate system? How will hurricane intensity and frequency change in a warming world? Can we make useful predictions of the regional-scale features of climate change? Will we be smart enough to do the right thing for future generations? 43
Section 4: Conclusions Personal thoughts (I) A human-induced warming signal has emerged from the background noise of natural climate variability 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
Section 4: Conclusions Personal thoughts (II) 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? 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: The public has some basic grasp of climate science; The public understands the possible risks of inaction; The public recognizes that they are not helpless, and can take individual and collective action to address human-caused climate change 45
Section 4: Conclusions The Wheel of Climate Fortune <1 C (4.1%; 1 in 24 odds) 1 to 1.5 C (11.4%; 1 in 9 odds) 1.5 to 2 C (20.6%; 1 in 5 odds) 2 to 2.5 C (22.5%; 1 in 4 odds) 2.5 to 3 C (16.8%; 1 in 6 odds) 3 to 4 C (16.2%; 1 in 6 odds) 4 to 5 C (4.6%; 1 in 22 odds) >5 C (3.8%; 1 in 26 odds) Source: MIT Joint Program on the Science and Policy of Climate Change 46
Section 4: Conclusions The atmosphere does not respect national boundaries 47