CO2 Forcing: Fact or Fiction - PowerPoint PPT Presentation

science provides the unambiguous answer george white october 2008 revised july 2009 co2@palisad com n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
CO2 Forcing: Fact or Fiction PowerPoint Presentation
Download Presentation
CO2 Forcing: Fact or Fiction

play fullscreen
1 / 61
CO2 Forcing: Fact or Fiction
197 Views
Download Presentation
mandel
Download Presentation

CO2 Forcing: Fact or Fiction

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Science provides the unambiguous answer George White October 2008 Revised July 2009 co2@palisad.com CO2 Forcing: Fact or Fiction

  2. Many sources of information • Ice Core Data(ppt)‏ • Atmospheric Absorption(ppt)‏ • Satellite Observations(ppt)‏ • Ground Based Observations(ppt)‏ • Biology(ppt)‏ • Physics(ppt)‏

  3. The Ice Cores • > 400K year history from Vostok • > 800K year history from DomeC • 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?

  4. Vostok Ice Core Temperatures

  5. Effects of Sample Interval

  6. Ice Core Temp+CO2

  7. Temp+Co2+CH4

  8. Last 15K years Temp+CO2

  9. DomeC Ice Temp+CO2

  10. 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

  11. Temp+CO2 1500 year smoothing

  12. DomeC Temp+CO2 with smoothing

  13. Last 15K years with smoothing

  14. Last 15K years DomeC

  15. DomeC 15K years + smoothing

  16. Compare Vostok and DomeC

  17. 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

  18. 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

  19. Cross Correlate Temp and CO2

  20. Cross Correlate Temp and CH4

  21. Cross Correlate Temp, CO2 and CH4

  22. DomeC Cross Correlation • DomeC 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

  23. DomeC Correlate Temp and Co2

  24. DomeC Correlate with smoothing

  25. DomeC TEMP, CO2 and CH4

  26. Auto Correlation Analysis • Auto correlate temperature • Apparent short term periodic behavior • 200 year DomeC, 300 year Vostok • Seems to be aliasing of seasonal variability • Apply smoothing • Unambiguous 22K, 41K period (Vostok and DomeC)‏ • 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

  27. Short Term Auto Correlation

  28. Medium Term Auto Correlation

  29. Long Term Auto Correlation

  30. Longer Term Auto Correlation

  31. An Even Longer Term Effect

  32. 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

  33. 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

  34. 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 14μ • Weak ozone absorption in the middle • 7.5μ CH4 line on one side, 15μ CO2 line on the other, water vapor continuum absorption throughout

  35. Atmospheric Absorption Spectrum

  36. CO2 Absorption • 15u 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 2u and 4.3u • Narrower lines • Significant H2O overlap • Far less energy available to be absorbed

  37. GHG Forcing • The Energy Cycle • CO2 captures 15u 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

  38. 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

  39. Anomaly Analysis

  40. Anomaly Fix

  41. Anomaly Partial Fix

  42. Observed Variability • Global mean temperature varies significantly • +/- 2.1˚ C seasonal variability • +2.1˚ in June, -2.1˚ 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

  43. Global Average Temperature

  44. Hemispheric Differences • Southern Hemisphere • 8˚K Degrees peak to peak variability • 276˚K mean • Northern Hemisphere • 24˚K Degrees peak to peak variability • 280˚K Mean • Equatorial • Small 6 month periodic variability • Clearly illustrates 2001/2002 calibration error

  45. Hemispheric Temperatures

  46. Surface Reflectivity • Northern Hemisphere • Higher mean • More land, less water • More variability • Greater range in surface ice • More time spent during higher reflectivity • More persistent ice coverage • Consequences • Sun closer in Northern summer -> cooler climate • Sun closer in Southern summer -> warmer climate

  47. Reflectivity Asymmetries

  48. Temperature and Reflectivity

  49. 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%

  50. Temperature and Energy