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CO2 Forcing: Fact or Fiction
Science provides the unambiguous answer
George WhiteOctober 2008
Revised July 2009
The Ice Cores
> 400K year history from Vostok
> 800K year history from Dome C
The climate is far from constant
CO2, CH4 and Temperature are all correlated
The data tells us far more than this
What kind of changes are expected?
Which came first, the gas or the heat?
What are the periodic influences?
Many sources of information
Ice Core Data
Atmospheric Absorption Data
Satellite Observations
Ground Based Observations
Biology
Physics
Vostok Ice Core Temperatures
Ice Core Temp + CO2
Temp + CO2 + CH4
Last 15K years Temp + CO2
Dome C Ice Temp + CO2
Data Smoothing
Data samples are intrinsically biased
Recent samples represent short term averages
Ancient samples represent long term averages
Different variables have different sample periods
Integrate samples over N years
Matches short term data to long term data
Matches temperature to CO2 and CH4
Isolate long and short term periodicity
Isolate long and short term dependency
Temp + CO2 1500 year smoothing
Dome C Temp + CO2 with smoothing
Last 15K years with smoothing
Last 15K years Dome C
Compare Vostok and Dome C
Dome C 15K years + smoothing
Correlation Analysis
Simple correlation metric for time Δt from t
Plus 1 when t+Δt changes in the same direction as t
Minus 1 when t+Δt changes in the opposite direction
Cross correlation identifies cause and effect
Auto correlation identifies periodic components
Use smoothing to select long or short term
Variable window to match Δt to sample period
Cross Correlation Analysis
Can identify which of 2 variables changes first
Temperature and CO2
Temperature and CH4
CO2 and CH4
Smoothing is required to normalize variability
Smoothing does not mask cause and effect
Smoothing makes short term dependence apparent
Cross Correlate Temp and CO2
Cross Correlate Temp and CH4
Cross Correlate Temp, CO2 and CH4
Dome C Cross Correlation
Dome C has finer resolution CO2 measurements
Shows apparent correlation of CO2 to future Temp
Frequently misinterpreted as a causal dependency
Also shows earlier correlation to opposite change
This is an aliasing effect which really indicates
CO2 increase -> Temp Decrease -> Temp Increase
Indicates correlation across a period of unrelated change
Indicates interference from a periodic effect
When smoothing is applied
Same results as Vostok data
Dome C Correlate Temp and Co2
Dome C Correlate with smoothing
Dome C Temp, CO2 and CH4
Auto Correlation Analysis
Auto correlate temperature
Apparent short term periodic behavior
180 year Dome C, 120 Year (25yr bucket), 270 year Vostok
Seems to be aliasing of seasonal variability
Apply smoothing
Unambiguous 22K, 41K period (Vostok and Dome C)
Modulated peaks are evidence for other periodicity
Related to variability in Earth's orbit and axis
Related to sums and harmonics of this variability
Common to temperature, CO2 and CH4
Short Term Auto Correlation
Medium Term Auto Correlation
Long Term Auto Correlation
Longer Term Auto Correlation
An Even Longer Term Effect
Combined Effects
The change between 96K and 41K ice ages
Considered by some to be a mystery
When the 41K, 96K and 500K forcing are combined
One can cancel or enhance the other
96K is weaker, 500K is weakest, 41K is dominant
The pattern is clearly an interference pattern
We are entering a new age of 41K ice ages
Evidenced by current weaker, but longer interglacial
Currently approaching 500K peak
41K and 96K peaks are separated by about 30K years
Stretching out the current interglacial
Is This Enough Forcing?
Some say that these effects are not strong enough
The periodicity clearly aligns
Magnitudes seem unexpected
96K is weak, but appears dominant recently
Several 41K peaks have aligned with 96K minimums
This mitigates the magnitude of the 41K effects
There is a feedback effect at work
Hemispheric asymmetry and ice amplification
Atmospheric Absorption
An objective review of atmospheric absorption is all that's required to disprove CO2 forcing
The atmospheric absorption spectrum is known
It has been measured and correlated to theory
Water vapor contributes about 2/3, CO2 is 1/3
Relatively transparent window from 8μ to 14μWeak ozone absorption in the middle
7.5μ CH4 line on one side, 15μ CO2 line on the other, water vapor continuum absorption throughout
Atmospheric Absorption Spectrum
CO2 Absorption
15μ CO2 line absorption
Highly saturated
Energy limited, not concentration limited
Double CO2
Insignificant increase in width
Primarily decreases mean distance before absorption
Other bands are between 2μ and 4.3μNarrower lines
Significant H2O overlap
Far less energy available to be absorbed
GHG Forcing
The Energy Cycle
CO2 captures 15μ surface energy
Collisions transfer energy to other gas molecules
Some energy gets back to the surface
The cycle repeats
Delays the release of surface energy
GHG flux is a circulating flux
Solar flux is an incident flux
Satellite Observations
25 year history of detailed weather measurements
10 km surface resolution
3 hour time resolution
100% surface coverage
Measurements include
Surface temperature
Cloud temperature
Cloud coverage
Reflectivities
Anomaly Analysis
Anomaly Fix
Anomaly Partial Fix
Observed Variability
Global mean temperature varies significantly
+/- 2.1˚C seasonal variability
+2.1˚C in June, -2.1˚C in December
Sun is closest in early January, farthest in July
Global mean temperature changes oppositely
Indicates dramatic hemispheric asymmetry
Unambiguously supports Milankovitch forcing
Data calibration error around 2001-2002
This has been misinterpreted as 'evidence' of warming
Global Average Temperature
Hemispheric Differences
Southern Hemisphere
8˚C peak to peak variability
276˚K absolute mean temperature (=3˚C)
Northern Hemisphere
24˚C peak to peak variability
280˚K absolute mean temperature (=7˚C)
Equatorial
Small 6 month periodic variability
Clearly illustrates 2001/2002 calibration error
Hemispheric Differences
Surface Reflectivity
Northern Hemisphere
Higher mean
More land, less water
More variability
Greater range in albedo – whiteness of snow and ice
More time spent during higher reflectivity
More persistent snow and ice coverage
Consequences
Sun closer in Northern summer -> cooler climate
Sun closer in Southern summer -> warmer climate
Reflectivity Asymmetries
Temperature and Reflectivity
Where is the Sun Now?
Sun is closest in early January
3.4% more incident energy than average
Sun is farthest away in early July
3.4% less incident solar energy than average
Nearly 7% total solar variability over a year
Corresponds to a 4˚C difference in temperature
Peak aphelion/perihelion differences are > 20%
Temperature and Energy
Implications of Sun-Earth distance?
When Sun is closest during North winter (now)
Warmer seasons, ice shrinks
Ice shrinks, -> less reflected energy -> even warmer
Positive feedback stops once minimum ice is reached
When Sun is farther away during Northern winter
Colder seasons, ice grows
Ice grows -> more reflected energy -> even colder
Southern hemisphere climate is more stable
Equatorial climate is even more stable
Ice Amplification
A popular hypothesis is that CO2 forcing amplifies periodic influences of orbit and axis
As evidenced by hemispheric differences, small changes in reflectivity have big consequences
This is confirmed by energy balance modeling
Surface ice and snow reflects a lot of energy
Positive feedback reinforces this effect
Models show that the ebb and flow of northern hemisphere surface snow and ice provides all of the required amplification
Ground Based Observations
Thermometers, tree rings, etc.
Must be very careful here
It's invalid to compare short term changes to changes in long term averages
The most common mistake in climate alarmists arguments The 'Hockey Stick' Claims that temperatures are rising faster than ever
Mauna Loa CO2 measurements
Yes, CO2 is increasing, but ...
Mauna Loa CO2
Overlay Mauna Loa CO2 with global temperature
Temperature decreases as CO2 increases
Actually CO2 decreases as temperature increases
Clear biological response
More warmth, more plants, more CO2 is consumed
As it cools, plants die, decomposing into CO2 and CH4
Very fast acting
Responds to temperature changes immediately
Removing trend bias, the response is relatively linear
Short term response
Mauna Loa CO2 and Temperature
Biology
The CO2 and CH4 record reflects biology
Short term
More warmth -> more plants -> less CO2
Less warmth -> more decomposition -> more CO2
Long Term
Plants require Sun energy + CO2
Build up of CO2 required to support more biomass
More biomass -> more decomposition -> more CO2/CH4
More CO2 and Energy -> more biomass
Animals slowly catch up, increasing CH4/CO2 ratio
Physics
Conservation of Energy
Precludes runaway greenhouse effects
Atmospheric absorption has no effect on the energy budget, i.e. Energy in == Energy out
Clouds and greenhouse gases, warm surface
Clouds trap far more energy than greenhouse gases
Greenhouse gases redistribute atmospheric energy
Greenhouse gas effects are primarily diurnal
Is CO2 Forcing Plausible?
Ice cores The recent rate of temperature change is exceeded in the data Past temperatures were warmer with far lower CO2 levels Temperature changes are correlated to orbit and axis variability There is no correlation of temperature to prior CO2 or CH4 levels Biology offers a complete explanation for CO2 and CH4
Atmospheric absorption CO2 absorption is energy limited and not concentration limited Water vapor is a far larger contributor
Mauna Loa Increasing temperature is associated with decreasing CO2
Satellite Ebb and flow of ice provides all necessary positive feedback Hemispheric asymmetry amplifies seasonal differences
Politics
Unfortunately, politics has subverted the science
Many want global warming to man made
There are convenient scapegoats
It's a self righteous feel good kind of politics to promote man made causes of global warming
The issue fits too well as a left/right conflict
Guilt/greed
Environment/business
There's money to be made
Conclusion
Natural CO2 and CH4 are indicators of biology
No forward feedback to temperature is in the record
To Solve Global Warming
All we need to do is wait
In geologic terms, another ice age is eminent
It's too bad that anthropomorphic CO2 can't stop it
Spending money on CO2 mitigation
Absolute worst thing to do
No climate change reversal will result
Better spent on adapting to the inevitable
References
Data Hyperlinks
Satellite Data
Ice Core Data
Irradiance Data
Atmospheric Absorption Data
Science Hyperlinks
Milankovitch
Weather Satellite Data
Black Body Radiation And Stefan-Boltzmann Law