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Four Things I Think I Know About Climate

Four Things I Think I Know About Climate. John R. Christy University 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

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Four Things I Think I Know About Climate

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  1. Four Things I Think I KnowAbout Climate John R. Christy University of Alabama in Huntsville Alabama State Climatologist

  2. 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

  3. Testing Hypothesis (assertions) about Climate UAHuntsville builds datasets from scratch Popular surface temperature datasets are poor metrics for checking on the greenhouse effect - and they are poorly measured as well Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced greenhouse warming 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

  4. Testing Hypotheses on Global Warming1. Testing Assertions based on Popular Surface Temperature DatasetsPopular surface datasets tend to: (a) overstate the warming, and (b) serve as a poor greenhouse metric

  5. CO2 up 38% at current rate of 0.6% per year

  6. Day vs. Night Surface Temp Greenhouse signal Warm air above inversion Cold air near surface 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

  7. Night Surface Temp Warm air above inversion Warm air Cold air near surface Buildings, heat releasing surfaces, aerosols, greenhouse gases, etc. can disrupt the delicate inversion, mixing warm air downward - affecting TMin. Nighttime - disconnected shallow layer/inversion. But this situation can be sensitive to small changes such as roughness or heat sources.

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

  9. 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

  10. 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

  11. 1. (c) Some surface data sources are simply poor

  12. Kilimanjaro

  13. Kilimanjaro

  14. Testing Hypothesis (assertions) about Climate UAHuntsville builds datasets from scratch Popular surface temperature datasets tend to be poor metrics for checking on the greenhouse effect - and they are often poorly measured as well Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced greenhouse warming 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

  15. Testing Hypotheses on Global Warming2. (a) Testing Assertions based on Climate Models for global trend magnitudeClimate models tend to overstate or misrepresent the warming

  16. Predictions

  17. Predictions Observations

  18. G. Schmidt NASA/GISS

  19. Individual Model Surface Trends 1979-2010

  20. Trends ending in 2008 with various start years IPCC AR4 Model Runs (22 models) vs. Obs. Start Year

  21. Trends ending in 2008 with various start years IPCC AR4 Model Runs (22 models) vs. Obs. Start Year

  22. Trends ending in 2010 (Jun) with various start years IPCC AR4 Model Runs (22 models) vs. Obs. Start Year

  23. Global Bulk Atmospheric Temperatures UAH Satellite Data Warming rate 50% of model projections Christy et al. 2007, 2009

  24. Testing Hypotheses on Global WarmingTesting Assertions based on Climate Models - Sierra Nevada loses 80% of snow by 2100Observations contradict this

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

  26. Trend +1.1 cm/decade Christy and Hnilo 2010 .

  27. Testing Hypotheses on Global Warming2. (b) Testing Assertions based on Climate Models concerning Tropical Upper Air Temperature trendsClimate models tend to misrepresent the observed relationship

  28. A Climate Model Simulation is a Hypothesis How does one define a falsifiable test for a model hypothesis?

  29. 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

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

  31. °C/decade Best Estimate of Models - given surface trend close to observed

  32. °C/decade Upper air trends of four observed datasets are significantly cooler in this apples to apples comparison

  33. °C/decade Upper air trends of four observed datasets are significantly cooler in this apples to apples comparison (Douglass et al. 2007).

  34. °C/decade 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.

  35. 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.)

  36. °C/decade 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.

  37. Ratio of Lower Tropospheric Trend to Surface Trend (Amplification Ratio) Model Median Christy et al. 2007, 2010; Christy and Norris 2006, 2009; Randall and Herman 2008; Klotzbach et al. 2009, 2010; McKitrick et al. 2010

  38. Observations (Surface much more than upper air) Land Surface Temperatures overstate warming Model Expectation (Surface less than upper air)

  39. Klotzbach 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. Christy 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. 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.]

  40. Testing Hypothesis (assertions) about Climate UAHuntsville builds datasets from scratch Popular surface temperature datasets tend to be poor metrics for checking on the greenhouse effect - and they are often poorly measured as well Warming is occurring but at a rate and in a manner that is inconsistent with model projections of enhanced greenhouse warming 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

  41. Testing Hypotheses on Global Warming3. Testing Assertions on the sensitivity of the climate to increases in greenhouse gas forcingClimate models tend to overstate the sensitivity due to missing negative cloud feedbacks

  42. Response of Clouds and Water Vapor (shortwave and longwave) to Increasing CO2 Negative Feedback? (mitigates CO2 impact) Positive Feedback? (enhances CO2 impact - models)

  43. A Climate Model Simulation is a Hypothesis How does one define a falsifiable test for a model hypothesis?

  44. 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

  45. Spencer and Braswell

  46. Global Warming in Models isGreatly Magnified by Positive Feedbacks Warming in models amplified by clouds & vapor (~3 deg. C by 2100) Warming from CO2 only Satellite data suggests clouds reduce warming (~0.5°C by 2100) Spencer and Braswell .

  47. Testing Hypothesis (assertions) about Climate UAHuntsville 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 actions are minuscule and will have no discernable impact on whatever the climate is going to do

  48. Testing Hypotheses on Global Warming4. Testing Assertions the impact of regulations on climateRegulations will have a minuscule impact on whatever the climate is going to do

  49. 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

  50. 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

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