four things i think i know about climate john r. christy university of alabama in huntsville alabama...
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Four Things I Think I Know About Climate
John R. ChristyUniversity of Alabama in Huntsville
Alabama State Climatologist
We should always begin our scientific assessments with the following statement:
“At our present level of ignorance, we think we know …”
Paraphrase of Richard Mallory Hoover High School
Fresno CA Physics Teacher 1968
Testing Hypothesis (assertions) about ClimateUAHuntsville builds datasets from scratch
1. Popular surface temperature datasets are poor metrics for checking on the greenhouse effect - and they are poorly measured as well
2. Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced greenhouse warming
3. Sensitivity research suggests the climate system is less sensitive to CO2 increases as depicted in models due to unaccounted-for negative cloud feedbacks
4. Impacts on global emissions of current legislative actions are minuscule and will have no discernable impact on whatever the climate is going to do
Testing Hypotheses on Global Warming
1. Testing Assertions based on Popular Surface Temperature
Datasets
Popular surface datasets tend to:
(a) overstate the warming, and (b) serve as a poor greenhouse
metric
"Global" Surface TemperatureTmean is Average of Day and Night
HadCRUT3 (2010 Jan-Jun only)
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
1850 1870 1890 1910 1930 1950 1970 1990 2010
CO2 up 38% at current rate of 0.6% per year
Day vs. Night Surface Temp
Nighttime - disconnectedshallow layer/inversion. Temperature affected by land-use changes, buildings, farming, etc.
Daytime - deep layer mixing, connected with levels impacted by enhanced greenhouse effect
Warm air above inversion
Cold air near surface
Greenhouse signal
Night Surface Temp
Nighttime - disconnectedshallow layer/inversion. But this situation can be sensitive to small changes such as roughness or heat sources.
Buildings, heat releasing surfaces, aerosols, greenhouse gases, etc. can disrupt the delicate inversion, mixing warm air downward - affecting TMin.
Warm air above inversion
Cold air near surface
Warm air
MODIS21 Jul 2002
Jacques DescloitresMODIS Land Rapid Response Team NASA GSFC
CA Valley and Sierra (Jun-Nov) 1910-2003
8
10
12
14
16
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
°C
Valley TMin
Sierra TMin
Nighttime temperatures rising but not because of greenhouse gas warming, but nighttime readings are included in popular datasets
Daytime temperatures tell more accurate story
Christy 2002, Christy et al. 2006, 2007, 2009, Pielke et al 2008, Walters et al. 2007
CA Valley and Sierra Annual Avg TMax 1910-2003 .
18
20
22
24
26
28
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
°C
Valley TMaxSierra TMax
CA Valley and Sierra (Jun-Nov) 1910-2003
8
10
12
14
16
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
°C
Valley TMin
Sierra TMin
Nighttime temperatures rising but not because of greenhouse gas warming, but nighttime readings are included in popular datasets
Daytime temperatures tell more accurate story
Christy 2002, Christy et al. 2006, 2007, 2009, Pielke et al 2008, Walters et al. 2007
1. (c) Some surface data sources are
simply poor
East Africa TMax (Christy et al. 2009).
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
1900 1920 1940 1960 1980 2000
Obs: (HadCRUT3) +0.14 °C/decade
Kilimanjaro
East Africa TMax (Christy et al. 2009).
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
1900 1920 1940 1960 1980 2000
Obs: (UAH) +0.02 °C/decade
Obs: (HadCRUT3) +0.14 °C/decade
Kilimanjaro
Testing Hypothesis (assertions) about ClimateUAHuntsville builds datasets from scratch
1.1. Popular surface temperature datasets tend to be poor Popular surface temperature datasets tend to be poor metrics for checking on the greenhouse effect - and metrics for checking on the greenhouse effect - and they are often poorly measured as wellthey are often poorly measured as well
2. Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced greenhouse warming
3. Sensitivity research indicates the climate system is less sensitive to CO2 increases as depicted in models due to unaccounted-for negative cloud feedbacks
4. Impacts on global emissions of current legislative actions are minuscule and will have no discernable impact on whatever the climate is going to do
Testing Hypotheses on Global Warming
2. (a) Testing Assertions based on Climate Models for
global trend magnitude
Climate models tend to overstate or misrepresent
the warming
History Lesson 1988
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
1960 1970 1980 1990 2000 2010 2020
GISS-A(88)
GISS-B(88)
GISS-C(88)Predictions
History Lesson 1988
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
1960 1970 1980 1990 2000 2010 2020
GISS-A(88)
GISS-B(88)
GISS-C(88)
UAH-LT (SfcAdj)
RSS-LT (SfcAdj)
2010 to July Only .Observations
Predictions
G. Schmidt NASA/GISS
12
13
14
15
16
17
1979 1983 1987 1991 1995 1999 2003 2007
BCCR
CCMaT47_avg
CCMaT63
GFDL_CM2.0
GFDL_CM2.1
HadGEM1
CSIROMk3.0
CSIROMk3.5
GISS EH (3)
GISS ER (4)
ECHAM5
MRI232a (5)
CCSM3.0 (7)
PCM1 (2)
MIROC3.2HiRes (1)
CNRM CM3 (1)
INGV ECHAM4 (1)
INMCM3.0 (1)
IPSL CM4 (1)
MIROC3.2 MidRes (3)
ECHO G (3)
ESSENCE
UKMO HadCM3 (1)
QUMP HadCM3 (17)
Median
Individual Model Surface Trends1979-2010
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
1979 1985 1990 1995 2000
HadCRUT3v
UAHLTsfc
RSSltsfc
BCCR
CCMaT47_avg
CCMaT63
GFDL_CM2.0
GFDL_CM2.1
HadGEM1
CSIROMk3.0
CSIROMk3.5
GISS EH (3)
GISS ER (4)
ECHAM5
MRI232a (5)
CCSM3.0 (7)
PCM1 (2)
MIROC3.2HiRes (1)
CNRM CM3 (1)
INGV ECHAM4 (1)
INMCM3.0 (1)
IPSL CM4 (1)
MIROC3.2 MidRes (3)
ECHO G (3)
ESSENCE
UKMO HadCM3 (1)
QUMP HadCM3 (17)
Median
mean w/oMRI,MIROC HiRes
Trends ending in 2008 with various start yearsIPCC AR4 Model Runs (22 models) vs. Obs.
Start Year
0.00
0.05
0.10
0.15
0.20
0.25
0.30
1979 1984 1989 1994 1999
Mean of Model trends(w/o Max,Min)Median of ModelTrendsHadCRUT3v
UAHLTsfc
RSSLTsfc
Trends ending in 2008 with various start yearsIPCC AR4 Model Runs (22 models) vs. Obs.
Start Year
0.00
0.05
0.10
0.15
0.20
0.25
0.30
1979 1985 1990 1995 2000
Mean of Model trends(w/o Max,Min)Median of ModelTrendsHadCRUT3v
UAHLTsfc
RSSLTsfc
Trends ending in 2010 (Jun) with various start yearsIPCC AR4 Model Runs (22 models) vs. Obs.
Start Year
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1978 1982 1986 1990 1994 1998 2002 2006 2010
Global Bulk Atmospheric TemperaturesUAH Satellite Data
Warming rate 50% of model projectionsChristy et al. 2007, 2009
Testing Hypotheses on Global Warming
Testing Assertions based on Climate Models - Sierra
Nevada loses 80% of snow by 2100
Observations contradict this
Snyder et al. 2002
Sierras warm faster than Valley in model simulations
Southern Sierra Nevada Snowfall1915-16 to 2009-10
0
200
400
600
800
1000
1200
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
CM
So. Sierra Snowfall
Christy and Hnilo 2010 .
Trend +1.1 cm/decade
Testing Hypotheses on Global Warming
2. (b) Testing Assertions based on Climate Models concerning
Tropical Upper Air Temperature trends
Climate models tend to misrepresent the observed
relationship
A Climate Model Simulation is a Hypothesis
How does one define a falsifiable test for a model hypothesis?
Douglass, Christy, Pearson and Singer 2007
Select a prominent metric dependent on the main perturbation in forcing - a large signal - test against observations
One such signal is the vertical structure of the tropical tropospheric temperature trend - i.e. how surface and upper air trends compare
Vertical Temperature Change due to Greenhouse Forcing in
Models
Model Simulations of Tropical Troposphere Warming:About 2X surfaceLee et al. 2007
100
200
300
400
500
600
700
800
900
1000
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
Models: Mean and Standard Error
Model -2SE
Model +2SE
Model Best Guess
Best Estimate of Models - given surface trend close to observed
°C/decade
Observations: Four "corrected" Datasets
100
200
300
400
500
600
700
800
900
1000
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
HadATIGRARATPACRICH
Upper air trends of four observed datasets are significantly cooler in this apples to apples comparison
°C/decade
100
200
300
400
500
600
700
800
900
1000
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
Models vs. Obs
Model -2SEModel +2SEModel Best GuessHadATIGRARATPACRICH
Upper air trends of four observed datasets are significantly cooler in this apples to apples comparison (Douglass et al. 2007).
°C/decade
Model Sfc-to-Upper Air Trends Normalized to Observed Sfc
100
200
300
400
500
600
700
800
900
1000
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
Model Best GuessHadATIGRARATPACRICH
Cool ExtWarm Ext
Putting the hot and cold extremes (thick red) of model trends tied to actual surface trend, models are still too hot which in this case all models have been tied to the actual observed surface trend.
°C/decade
A different test asks whether the models and observational upper air trends agree if NO restriction is placed on the model surface trends (i.e. apples to oranges.)
Extremely weak hypothesis to test and does NOT address the sfc-to-upper air relationship (a key signature of greenhouse warming in models.)
Model Sfc-to-Upper Air Trends Normalized to Observed Sfc
100
200
300
400
500
600
700
800
900
1000
-0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6
Model Best GuessHadATIGRARATPACRICHS08-2SES08+2SE
Putting the hot and cold extremes (thick red) of model trends tied to actual surface trend, models are still too hot which in this case all models have been tied to the actual observed surface trend.
°C/decade
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
Model ARObs AR
Christy et al. 2007, 2010; Christy and Norris 2006, 2009; Randall and Herman 2008; Klotzbach et al. 2009, 2010; McKitrick et al. 2010
Ratio of Lower Tropospheric Trend to Surface Trend(Amplification Ratio)
ModelMedian
Land Surface Temperatures overstate warming
Model Expectation (Surface less than upper air)
Observations (Surface much more than upper air)
McKitrick et al. 2010
Over the interval 1979-2009, model-projected temperature trends are two to four times larger than observed trends in both the lower and mid-troposphere and the differences are statistically significant at the 99% level. [Note: recalculated Santer et al. 2008 method, and even with surface trend variation found Santer et al.’s result is not verified.]
Klotzbach et al. 2010
[Our] result is inconsistent with model projections which show that significant amplification of the modeled surface trends occurs in the modeled tropospheric trends.
Christy et al. 2010
Table 2 displays the new per decade linear trend calculations [of difference between global surface and troposphere using model amplification factor] … over land and ocean. All trends are significant at the 95% level.
Testing Hypothesis (assertions) about ClimateUAHuntsville builds datasets from scratch
1. Popular surface temperature datasets tend to be poor metrics for checking on the greenhouse effect - and they are often poorly measured as well
2.2. Warming is occurring but at a rate and in a manner that Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced is inconsistent with model projections of enhanced greenhouse warminggreenhouse warming
1. Sensitivity research suggests the climate system is less sensitive to CO2 increases (as depicted in models) due to unaccounted-for negative cloud feedbacks
4. Impacts on global emissions of current legislative actions are minuscule and will have no discernable impact on whatever the climate is going to do
Testing Hypotheses on Global Warming
3. Testing Assertions on the sensitivity of the climate to increases in greenhouse gas
forcing
Climate models tend to overstate the sensitivity due to
missing negative cloud feedbacks
Response of Clouds and Water Vapor (shortwave and longwave) to Increasing CO2
0
20
40
60
80
100
Relative Temperature Effect
Water Vapor and Clouds
CO2
Other
Negative Feedback?(mitigates CO2 impact)
Positive Feedback?(enhances CO2 impact - models)
A Climate Model Simulation is a Hypothesis
How does one define a falsifiable test for a model hypothesis?
Select a prominent metric dependent on the main perturbation in forcing - a large signal - test against observations
One such test is to calculate the climate feedback parameter during monthly and annual scale variations
Spencer and Braswell
Global Warming in Models isGreatly Magnified by Positive Feedbacks
Warming from CO2 only
Warming in modelsamplified by clouds
& vapor(~3 deg. C by 2100)
Satellite data suggests cloudsreduce warming(~0.5°C by 2100)
Spencer and Braswell .
Testing Hypothesis (assertions) about ClimateUAHuntsville builds datasets from scratch
1. Popular surface temperature datasets tend to be poor metrics for checking on the greenhouse effect - and they are often poorly measured as well
2. Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced greenhouse warming
3.3. Sensitivity research suggests the climate is less Sensitivity research suggests the climate is less sensitive to CO2 increases than depicted in models due sensitive to CO2 increases than depicted in models due to unaccounted-for negative cloud feedbacksto unaccounted-for negative cloud feedbacks
4. Impacts on global emissions of current legislative actions are minuscule and will have no discernable impact on whatever the climate is going to do
Testing Hypotheses on Global Warming
4. Testing Assertions the impact of regulations on
climate
Regulations will have a minuscule impact on whatever
the climate is going to do
What did California do?
• Force a limit on emissions of Light Duty Vehicles
• California AB 1493 seeks to reduce tail-pipe emissions of CO2 by 26% by 2016
• 11 NE States adopted AB 1493• Trial in Federal Court (Burlington
VT) to address the engineering, legal and climate issues of AB 1493, April-May 2007
What did California do?
• Force a limit on emissions of Light Duty Vehicles
• California AB 1493 seeks to reduce tail-pipe emissions of CO2 by 26% by 2016
• 11 NE States adopted AB 1493• Trial in Federal Court (Burlington
VT) to address the engineering, legal and climate issues of AB 1493, April-May 2007
What did California do?
• Force a limit on emissions of Light Duty Vehicles
• California AB 1493 seeks to reduce tail-pipe emissions of CO2 by 26% by 2016
• 11 NE States adopted AB 1493• Trial in Federal Court (Burlington
VT) to address the engineering, legal and climate issues of AB 1493, April-May 2007
What did California do?
• Force a limit on emissions of Light Duty Vehicles
• California AB 1493 seeks to reduce tail-pipe emissions of CO2 by 26% by 2016
• 11 NE States adopted AB 1493• Trial in Federal Court (Burlington
VT) to address the engineering, legal and climate issues of AB 1493, April-May 2007
IPCC “Best Estimate”
0.0
0.5
1.0
1.5
2.0
2.5
3.0
A1B
California AB 149326% CO2 reduction LDV 2016
0.0
0.5
1.0
1.5
2.0
2.5
3.0
A1BCANo. EastUSA
Net Impact if all US 0.01°C 2100
The temperature impact on global temperatures if the entire world adopted AB 1493 is an undetectable 0.03°C.
Latest sensitivity results suggest the impact is even smaller.
Pg 46
“Plaintiffs’ expert Dr. Christy estimated that implementing the regulations across the entire United States would reduce global temperature by about 1/100th (.01) of a degree by 2100. Hansen did not contradict that testimony.”
Judge William Sessions III Ruling 12 Sept 2007
AB 1493 is legal
Questions
• What could make a “dent” in forecasted global temperatures?
• What would be the impact of building 1000 nuclear power plants and putting them on-line by 2020?– (average 1.4 gigawatt output
each)
Questions
• What could make a “dent” in forecasted global temperatures?
• What would be the impact of building 1000 nuclear power plants and putting them on-line by 2020?– (average 1.4 gigawatt output
each)
IPCC “Best Estimate”
0.0
0.5
1.0
1.5
2.0
2.5
3.0
A1B
Net Effect of 10% CO2 emission reduction to A1B Scenario
(~1000 Nuclear Plants by 2020)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
A1B Emissions
10% Reduction A1B
Net Impact 0.07°C 2050
Testing Hypothesis (assertions) about ClimateUAHuntsville builds datasets from scratch
1. Popular surface temperature datasets tend to be poor metrics for checking on the greenhouse effect - and they are often poorly measured as well
2. Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced greenhouse warming
3. Sensitivity research suggests the climate is less sensitive to CO2 increases than depicted in models due to unaccounted-for negative cloud feedbacks
4. Impacts on global emissions of current legislative Impacts on global emissions of current legislative actions are minuscule and will have no discernable actions are minuscule and will have no discernable impact on whatever the climate is going to doimpact on whatever the climate is going to do
Kenya, East Africa
Energy Transmission
Energy System
Energy Use
Energy Source
Consensus is not Science
Michael Crichton
Consensus is not Science
William Thomson (Lord Kelvin)
All Science is numbers
Michael Crichton