1. Facts and Myths about Global Warming John R. Christy NWS Climate Services University of Alabama in Huntsville 20 June 2007

2. Consensus is not Science Michael Crichton

3. Consensus is not Science William Thompson (Lord Kelvin) All Science is numbers Michael Crichton

4. Some people will do anything to save the Earth... except take a science course.

5. Greenhouse “Affect”, Rolling Stone P.J. O’Rourke

6. Two Main observing systems for detecting Greenhouse Gas effects Surface thermometers –Daily High Temperature –Daily Low Temperature –Daily Mean Temperature (popular) Upper Air Temperatures –Balloon –Microwave emissions

7. Constructed from Mean Temperatures

8. Vertical Temperature Change due to Greenhouse Forcing in Models Model Simulations of Tropical Troposphere Warming: About 2X surface Lee et al. 2007

9. Is Mean Surface Temperature an Appropriate Index for the Greenhouse Effect? TMean = (TMax + TMin)/2

10. Day vs. Night Surface Temp Nighttime - disconnected shallow layer/inversion. Temperature affected by land-use changes, buildings, farming, etc. Daytime - deep layer mixing, connected with levels impacted by enhanced greenhouse effect

11. Night Surface Temp Nighttime - disconnected shallow 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

12. The nighttime minimum is related to the delicate formation of the nocturnal boundary layer which can be easily disrupted, mixing warm air downward and sending temperatures up dramatically Walters et al. (in press)

13. No. Alabama Summer TMax Temperatures Christy 2002

14. Mean Temperature Southeast USA 1899-2003 Models Observation

15. Christy et al. 2006, J. Climate

16. MODIS 21 Jul 2002 Jacques Descloitres MODIS Land Rapid Response Team NASA GSFC

17. + Valley Stations ° Mountain Stns Christy et al. 2006, J. Climate

18. Manually digitized thousands of records

19. Christy et al. 2006 Valley affected by irrigation and urbanization

20. Christy et al. 2006 Consistent with irrigation Consistent with irrigation and urbanization

21. Snyder et al. 2002 Sierras warm faster than Valley in model simulations

22. East Africa (Kenya/Tanzania)

23. East Africa: 5°S-Eq, 35-40°E (Nairobi, Mt. Kilimanjaro, Mt. Kenya) Daytime warming rate 20% of Mainline Datasets in E. Africa Christy et al. (submitted) uses 10 times the amount of surface data Upper Air

24. Model vs. Observations TMin minus TMax Preliminary study

25. Is Mean Surface Temperature an Appropriate Index for the Greenhouse Effect? Evidence indicates TMax is the better metric to serve as a proxy for monitoring deep atmospheric change Pielke et al. 2007, Walters et al. 2007, Christy et al. (submitted)

26. Upper Air Temperatures

27. Recent claims suggest the upper air temperature record is in agreement with the surface and with climate models, so global warming theory must be right IPCC more or less supports this view UAH satellite data reportedly “flawed”

28. Vertical Temperature Change due to Greenhouse Forcing in Models Model Simulations of Tropical Troposphere Warming: About 2X surface Lee et al. 2007

29. Christy and Spencer 2005 Christy and Norris 2006 Christy et al. 2007

30. Christy and Norris 2006 Christy et al. 2007

31. Global Bulk Atmospheric Temperatures UAH Satellite Data Warming rate 60% of model projections

32. Greenhouse Effect

33. Total Greenhouse Effect Water vapor and Clouds Dominate Total Greenhouse Effect is variable Climate models show strong water-vapor/cloud positive feedback with increased CO2

34. Greenhouse Effect

35. ?

36. Tropical Temp. and Cloud Forcing (major part of total greenhouse effect) based on latest satellite sensors Negative feedback on monthly time scales Spencer et al. (submitted)

37. What about Cold Places?

39. North Polar Regions HadCRUT3 Period of most polar ice observations

40. Greenland Summer Temperatures 1780-2005 Period of most polar ice observations

41. Greenland Borehole Temperature Dahl-Jensen et al. 1998

43. Alaska Hadley CRU 3 (°C) Shift in 1977, but high natural variability

44. When Hemingway writes “Snows of Kilimanjaro”—half of the “snows” are already gone X Mass Gain in 2006 Molg and Kaser 2007

45. Regional Snowpack, Central Andes, 1951-2005 Masiokas et al. 2006

47. Schneider et al. 2006 Antarctica Thermometers Ice Cores Doran et al. 2002

48. Antarctica snow accumulation trends cm/yr 1992-2003 Davis et al. 2005 See also: Monoghan et al 2006 Van de Berg et a. 2006

49. Evidence Thus Far Global surface temperature is rising, but in a way inconsistent with model projections of GHG forcing Overall decline in ice mass, with sea level rise of about 1” per decade Severe weather not becoming more frequent

50. Main Point: I don’t see a disaster developing But, suppose you do ….

51. Energy Technology 1900: World supported 56 billion human-life years

52. Energy Technology 1900: World supported 56 billion human-life years 2005: World supports 429 billion human-life years

53. Kenya, East Africa

54. Energy Transmission Energy System Energy Use Energy Source

55. All Science is Numbers The Human population currently uses energy at a rate of 14 terawatts to its considerable benefit.

56. All Science is Numbers The Human population currently uses energy at a rate of 14 terawatts to its considerable benefit. Most energy production relies on burning carbon (i.e. CO2 is released)

57. All Science is Numbers The Human population currently uses energy at a rate of 14 terawatts to its considerable benefit. Most energy production relies on burning carbon (I.e. CO2 is released) To replace 10% of this (i.e. 1.4 terawatts) requires 1000 nuclear power plants (1.4 gigawatt each)

58. IPCC “Best Estimate” Temp

59. California AB 1493 26% CO2 reduction LDV 2016

60. Net Effect of 10% CO2 emission reduction to A1B Scenario (~1000 Nuclear Plants by 2020)

61. OR A MORE RATIONAL APPROACH? In 50 years will we learn that the most cost-effective path was to adapt to changes we actually observed and measured, rather than try to outguess Mother Nature’s course? In 50 years will we be surprised not by climate change but by the inventive minds of our scientists and engineers as they discover profitable and affordable ways to generate energy without carbon emissions?