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

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Presentation on theme: "Four Things I Think I Know About Climate John R. Christy University of Alabama in Huntsville Alabama State Climatologist."— Presentation transcript:

1 Four Things I Think I Know About 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 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

4 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

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

6 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 Warm air above inversion Cold air near surface Greenhouse signal

7 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

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

14 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 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 Warming 2. (a) Testing Assertions based on Climate Models for global trend magnitude Climate models tend to overstate or misrepresent the warming

16 Predictions

17 Observations Predictions

18 G. Schmidt NASA/GISS

19 Individual Model Surface Trends

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 Warming Testing Assertions based on Climate Models - Sierra Nevada loses 80% of snow by 2100 Observations contradict this

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

26 Christy and Hnilo Trend +1.1 cm/decade

27 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

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

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

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

34 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

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 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

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

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

39 McKitrick et al Over the interval , 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 method, and even with surface trend variation found Santer et al.s result is not verified.] Klotzbach et al [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 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.

40 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 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

41 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

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 is Greatly Magnified by Positive Feedbacks Warming from CO 2 only Warming in models amplified by clouds & vapor (~3 deg. C by 2100) 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 Warming 4. Testing Assertions the impact of regulations on climate Regulations 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 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 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

51 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 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

52 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 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

53 IPCC Best Estimate

54 California AB % CO2 reduction LDV 2016

55 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.

56 Pg 46 Plaintiffs expert Dr. Christy estimated that implementing the regulations across the entire United States would reduce global temperature by about 1/100 th (.01) of a degree by Hansen did not contradict that testimony. Judge William Sessions III Ruling 12 Sept 2007 AB 1493 is legal

57 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)

58 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)

59 IPCC Best Estimate

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

61 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 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.Impacts on global emissions of current legislative actions are minuscule and will have no discernable impact on whatever the climate is going to do

62 Kenya, East Africa

63 Energy Transmission Energy System Energy Use Energy Source

64 Consensus is not Science Michael Crichton

65 Consensus is not Science William Thomson (Lord Kelvin) All Science is numbers Michael Crichton

66


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