Net Global Warming Could be Caused by Something Besides
Greenhouse Gas; Soot?
Dr. Tom May29 November 2018
Dr. Tom May Resume• Education
PhD: Physics, Mathematics- University of Minnesota, 1968MS: Physics, Mathematics- University of Minnesota, 1961Bachelor of Physics (with distinction): University of Minnesota, 1959
• Aerospace Industry2011-2017 Millennium Space (Consultant)1992-2011 Spectrum Astro/General Dynamics/Orbital Sciences (Chief Scientist)1981-1992 TRW Electromagnetics Application Center (Chief Engineer)
• USAF1977-1981 Space Division (Lt Col) – IR surveillance1971-1977 Air Force Weapons laboratory (Major) – Plasma Physics1967-1971 Air Force Technical Applications Center (Captain) – Satellite Data Analysis1964-1967 University of Minnesota (Capt) – Graduate Student, Gamma Ray Astronomy1961-1964 Air Force Technical Applications Center (lieutenant) – Radiochemistry
• University of Minnesota1959-1961 Research Associate (Cosmic Ray Research)1955-1959 Research Assistant (laboratory technician)
MOTIVATION
RADIATION TRANSPORT ANALYIS
FUTURE PLANS (Update and extend earlier work)
WHY CHINESE SOOT HYPOTHESE
SUMMARY
The Miskolczi-principle
• The greenhouse effect is not a free variable.
• Earth type planetary atmospheres, having partial cloud cover and sufficient water vapor reservoirs, maintain an energetically maximized (constant, ‘saturated’) greenhouse effect that cannot be increased by emissions.
• The following presentation serves the proof of the above statements.
2
• https://friendsofscience.org/assets/documents/The-Saturated-Greenhouse-Effect of Ference Miskolczi
• 85 viewgraph pages summarizing Miskolczi’s publications• High Resolution Atmospheric Radiative Transfer LBL Code
(Miskolczi et al., 1989)http://miskolczi.webs.com/hartcode_v01.pdf
• Quarterly Journal of the Hungarian Meteorological Society 2001,2004 and 2007
The Saturated Greenhouse effect principle of Dr. Ference MiskolcziPresented by Miklos Zagoni
2/(1 + τA + exp(-τA)) =3/5+2exp(-τA)/5 , which
gives for τAas general solution:
Observation
(HARTCODE computation on
TIGR, 2004): τA=1.868 .
Theoretical derivation (Eqs 8-28, 2007): τA=1.86756 .
Interpretation (cont.):
• If the system energetically could increase its surface temperature, it need not wait for our anthropogenic CO2 emissions, since another GHG, water vapor, is available in a practically infinite reservoir, in the surface of the oceans.
• Energetic constraints can compensate the increasing CO2-amount in the air for example by removing water vapor, rearranging its spatial distribution, or by modifying the amount (~62%) and/or the average height (~2 km) of the partial cloud cover.
NOAA Reanalysis Project
MOTIVATION
RADIATION TRANSPORT ANALYIS
FUTURE PLANS (Update and extend earlier work)
WHY CHINESE SOOT HYPOTHESE
SUMMARY
Radiation Transport Analysis Used Available Models that are Based on Measured Data• Used MODTRAN® 1radiation transport code• Used default models of temperature and pressure profiles for northern hemisphere
• Tropical• Mid latitude summer• Mid latitude winter• Sub artic summer• Sub artic winter
• Varied selected green house gases from 1988-2015 (28 Years)» Water va
• Water vapor• Carbon dioxide• Ozone• Nitrous oxide• Methane
• All other input data left constant at defaultWater va
• Aerosols (Navy Maritime) • CFCs• Carbon monoxide
1. Owned by USAF, Developed and Maintained by Spectral Sciences Inc.
. Berk, P. Conforti, R. Kennett, T. Perkins, F. Hawes, and J. van den Bosch, "MODTRAN6: a major upgrade of the MODTRAN radiative transfer code," Proc. SPIE 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral
Imagery XX, 90880H (June 13, 2014); doi:10.1117/12.2050433.
Input Data
• SWOOSH and Reanalysis Project data separated by up to 20 standard deviations at 316 and 300 mb respectively
• SWOOSH user instructions recommended caution outside of 1-100mb range• Interpolated using default profile corrected by linear pressure dependentfunction defined by 100 mb SWOOSH data and 300 mb Reanalysis project data.
1.Kalnay E.and coauthors 1996The NCEP/NCAR Reanalysis 40 year project Bull.Amer. Meteor. Soc. 77 437471Data at https://www.ersl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl2. Davis, S. M., Rosenlof, K. H., Hassler, B., Hurst, D. F., Read, W. G., Vömel, H., Selkirk, H., Fujiwara, M., and Damadeo, R.: The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database: A long-term database for climate studies, Earth Syst. Sci. Data, doi:10.5194/essd-8-461-2016, 2016.Data at https://www.esrl.noaa.gov/csd/groups/csd8/swoosh/
Species Timehistory Altitudeprofile Latitude1000mb>H2O<300mb
30mb>H2O>100mbCO2 NOAAMonaloayearlyAve codeprofile notvaried
O3 Dobsonspectrophotometer1 codeprofile Barrow,Hanford,MuanaLoaN2O NOAAMonaloayearlyAve codeprofile notvariedCH4 NOAAMonaloayearlyAve codeprofile notvaried
NCEP/NCARReanalysisProject1
NOAA/SWOOSHdataset2
SUMMARY RESULTS FOR NORTHERN HEMISPHERE
Tropical MidLat SubArticWeightedAverage
H2ODataLatitudeRange1 0-20N 20N-55N55N-90N1988AverageIRFlux(W/m2) 264.905 236.643 219.2222GasHeating(W/m2)2 0.80193 0.4997 0.614981
GasandH2OHeating(W/m2) -0.2441 0.06332 0.727838RelativeArea 0.342 0.477 0.181WeightedGasHeatng(W/m2) 0.27426 0.23836 0.111312 0.6239WeightedGas&H2OHeating(W/m2) -0.0835 0.0302 0.131739 0.078
ApproximateIncreaseinTroposphericH20(%) 2.06 2.67 4.22PossibleTroposphericIncreasedHeating(W/m2)(speculative) -0.3296 -0.4272 -0.67521AverageddataforJan,Feb,June,July,Aug,Dec
2O3dataforMuanaLoaandHanfordAveragedforDecJanFebJuneJulyAug,BarrowforMarchJuneJulyAug.Othergasesyearly.
MODTRAN Detailed Results
tropical w&s midlat winter midlatitudsummer subartic winter subartic summer88gases88h20
15gases88h20
15gases15h20
gaswarming
gas&h2owarming
zoneave
88gases88h20
15gases88h20
15gases15h20
gaswarming
gas&h2owarming
88gases88h20
15gases88h20
15gases15h20
gaswarming
gas&h2owarming
zoneave
88gases88h20
15gases88h20
15gases15h20
gaswarming
gas&h2owarming
88gases88h20
15gases88h20
15gases15h20
gaswarming
gas&h2owarming
zoneave
noclouds 275.087 274.251 275.055 0.836 0.032 0.032 221.994 221.474 222.258 0.52 -0.264 268.237 267.686 267.582 0.551 0.655 0.196 194.688 194.359 194.105 0.329 0.583 258.94 258.216 257.715 0.724 1.225 0.904cumulus 248.854 247.74 249.541 202.745 202.362 203.179 242.856 242.443 242.774 182.393 182.14 181.968 229.904 229.468 229.359altostratus 247.025 246.414 247.74 201.28 200.908 201.727 241.24 240.837 241.184 180.964 180.72 180.561 228.359 227.939 227.842stratus 264.688 263.937 265.107 214.574 214.099 214.897 259.472 258.965 259.119 193.771 193.448 193.189 246.613 246.013 245.757stratocumulus 257.315 256.621 257.888 209.739 209.299 210.109 252.575 252.106 252.349 188.958 188.666 188.448 238.932 238.407 238.229nimbostratus 268.611 267.828 268.905 217.107 216.616 217.409 262.635 262.113 262.205 195.988 195.651 195.375 250.686 250.046 249.732cirrus 259.138 258.419 259.136 209.517 209.075 209.744 253.224 252.758 252.671 185.003 184.723 184.501 243.956 243.358 242.921cirrus-thin 273.595 272.771 273.57 220.799 220.288 221.064 266.823 266.282 266.18 193.739 193.417 193.614 257.496 256.786 256.291cloudave 259.889 259.104 260.27 210.823 210.378 211.1613 254.1179 253.643 253.783 188.688 188.395 188.237 242.278 241.717 241.447rain-drizzle 264.686rain-light 268.608rain-moderate 268.604rain-heavy 248.84rain-extreme 248.817rainave 259.911netclouds&noclouds 264.905 264.103 265.149 0.801926 -0.24414 -0.244 214.5094 214.04 214.8232 0.46965 -0.313771 258.7772 258.277 258.337 0.4997 0.440409 0.063 190.668 190.36312 190.173 0.30488 0.494847 247.776 247.161 246.816 0.614981 0.960829 0.728area 0.342 0.342 0.477 0.477 0.181 0.181weightedave 0.274259 -0.083 0.23836 0.03 0.111312 0.132sumgas+h20 0.07845sumgas 0.62393
CO2 Absorption Spectra
• Radiance at main CO2 absorption dip reverses and starts increasing at tropopause even though absorption cross section continues to increase because the effective radiation zone and temperature begin to increase with altitude
• This effect partially mitigates CO2 warming as seen in difference spectrum.
• The integral of the difference spectrum in this region is 0.29 W/m2 out of 0.55 W/m2 for the entire spectral difference.
Example H2O Data Input
0.1
1
10
100
1000
10000
100000
0.00001 0.0001 0.001 0.01 0.1 1 10 100 1000
H20(ppm
v)
AtmosphericPressure(mb)
1988MidLatitudeNorthSummerH2OProfile
ReanalysisProjectData InterpolatedInputValues SWOOSHNormalizedCode SW00SHData
Example of Ratio of 2015/1988 H2O Input Data
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
0 100 200 300 400 500 600 700 800 900 1000
H 2ORatio
AtmosphericPressure(mb)
Ratioof2015/1988H2OValuesMidLatitudeNorthSummer
SWOOSHData ReanalysisData RatioofInputH20values
MODTRAN Main Screen
MOTIVATION
RADIATION TRANSPORT ANALYIS
FUTURE PLANS (Update and extend earlier work)
WHY CHINESE SOOT HYPOTHESE
SUMMARY
Four Decade Temperature Anomaly
• Greenhouse gases are unable to produce measured warming.• For small changes:!"
"= −!%
&%where F is IR flux; solar flux and cloud cover constant
• For northern hemisphere 𝑑𝑇 = .007℃/decade versus 0.14℃/decade• For sub-artic 𝑑𝑇 = .07℃/decade versus something larger
Northern and Southern Hemisphere Average Temperature Anomalies
Southern Hemisphere (Jan 1979-Dec 2007)
y = 0.000859x - 0.106334
-1
-0.5
0
0.5
1
1.5
0 100 200 300 400
Months
Tem
pera
ture
Ano
mal
y (C
)
Northern Hemisphere (Jan 1979-Dec 2007)
y = 0.001772x - 0.208572
-1
-0.5
0
0.5
1
1.5
0 100 200 300 400
Months
Tem
pera
ture
Ano
mol
y (C
)
• Data from: - NOAA satellite MSU & AMSU Instruments- Presented on internet by Remote Sensing
Systems 2008- Northern hemisphere 0 to 82.5 N latitude- Southern hemisphere 0 to 70 S latitude
• Results are:- Northern hemisphere warming 0.21C/decade- Southern hemisphere warming 0.076C/decade- Northern hemisphere warming 2.76 times
southern hemisphere warming• Similar data presented by University of Alabama
Huntsville show similar trends Northern hemisphere warming 0.19C/decade
- Southern hemisphere warming 0.07C/decade- Northern Hemisphere warming 2.7 times
southern hemisphere warming
Northern and Southern Hemisphere Carbon Dioxide Content
Mauna Loa CO2 Measurements 2001-2005
y = 0.1636x + 370.5
355360365370375380385390
0 10 20 30 40 50 60
Months
PPM
V
Mauna Loa
Linear (MaunaLoa)
Barrow CO2 Measurements 2001-2005
y = 0.1439x + 372.36
355360365370375380385390
0 10 20 30 40 50 60
Months
PPM
V Barrow
Linear(Barrow)
South Pole CO2 Measurements 2001-2005
y = 0.1716x + 367.6
355360365370375380385390
0 10 20 30 40 50 60
MonthsPP
MV
South Pole
Linear (SouthPole)
American Samoa CO2 Measurements 2001-2005
y = 0.1684x + 368.88
355360365370375380385390
0 10 20 30 40 50 60
Months
PPM
V AmericanSamoa
Linear(AmericanSamoa)
• Data from ORNL’s Carbon Dioxide Information Analysis Center
• Average CO2 difference between northern and southern hemispheres about 2½ PPMV (0.6%)
• How can 0.6% difference in driving function produce >200 % difference in warming between northern and southern hemispheres?
Temperature Anomaly Data AnalysisSouthern Hemisphere Measured (11 year running average & Fit Temperature Variations with Sun Spot Number, Carbon
Use & Mt Pinotubo Model Components
-0.3-0.2-0.1
00.10.20.30.4
1980 1990 2000 2010
Year
Tem
pera
ture
Var
iatio
n
MeasuredTemperature Variation
Fit TemperatureVariation
Sun Spot NumberTemperature Variation
Carbon UseTemperature Variation
Mt Pinatubo AerosolModel TemperatureVariation
Northern Hemisphere Measured (11 year running average) & Fit Temperature Variations with Sun Spot Number,
Carbon Use & Mt Pinotubo Model Components
-0.3-0.2-0.1
00.10.20.30.4
1980 1990 2000 2010
Year
Tem
pera
ture
Var
iatio
nMeasuredTemperature Variation
Fit TemperatureVariation
Sun Spot NumberTemperature Variation
Carbon UseTemperature Variation
Mt Pinatubo AerosolModel TemperatureVariation
DRIVING FUNCTION VALUENorthern Hemisphere Southern Hemisphere
Sun Spot Number 0.0039 ± 24% 0.0033 ± 24%Carbon Use 0.00017 ± 9% 0.00015 ± 59%Volcano Aerosols -0.035 ± 46% -0.10 ± 13%
• Performed 11 year running average on all input data and least square analyzed temperature data against 3 driving function data sets;
- Sunspot number accelerated 16 years forfor best fit (minimum R2 values of 0.99 fornorthern hemisphere and 0.94 for southern)-- Data from NASA Marshal Space Fight Center
- Carbon usage data accelerated 16 years--Data from ORNLs CO2 Information Center
- Mount Pinatubo model accelerated 1 yearfor minimum R2 value
• Results shown in graphs and table below- Components of Fit temperature in graphs obtained by multiplying input driving function data by their respective least squaresanalyzed constants below
- Solar effect small but equal in both hemispheres-- Same input data and same constants
- Carbon usage effect 10x higher in north--Same constant but input data slope 10x higher
- Mt Pinatubo reduced temperatures more in south than north
MOTIVATION
RADIATION TRANSPORT ANALYIS
FUTURE PLANS (Update and extend earlier work)
WHY CHINESE SOOT HYPOTHESE
SUMMARY
• China has been using as much coal as the rest of the world combined and is at a high latitude1.
• Chinese Coal is almost entirely lignite and other bituminous coals with far more than normal Al2O3 fiber that makes design and use of electrostatic precipitators difficult2,3.
• About ½ of Chinese coal use is for electricity production and ½ for other uses including industry(16%) and heating (14%). (2007 data)2.
• Picture shows Greenland Ice cap in spring (year unknown between 2009 and 2014).4
• Ice tests have shown Greenland icepack melted in 1889 and 2012 due to large forest fires and warmer weather5,6.
Coal and Forest Fire Soot Contributors
1.www.iea.org/newsroom/energysnapshots/world-total-coal-production-1971-2016.html
2.en.wikipedia.org/wiki/Coal_in_China
3. Lillieblad, Lena st al, Electrostatic Precipitator Performance with Chinese Coals, ICESPX Australial 2006, paper 3a2
4, news.nationalgeographic.com/news/2014/06/140610-connecting-dots-dust-soot-snow-ice-climate-change-dim
5.phys.org/news/2014-05-climate-forest-drove-widespread-surface.html6.www.pnas.org/content/22/7964
The Good News
• China is making concerted effort to reduce its incredible local pollution and its CO2 footprint1.
• 90% of China’s coal fueled electrical power plants use electrostatic precipitators, (2003 statement)2.
• China has started using advanced technologies such as coal gasification and supercritical burn to improve efficiency and reduce local pollution1.
• Chinas initial anti-smog campaign caused a natural gas crisis and a switch from “dispersed coal” to “clean coal”3.
• Example: After natural gas shortage disaster, a Beijing modern power plant was taken out of mothballs and restarted, enabling use of limited natural gas to replace non pollution controlled coal burners.
• China has a very very long way to go and is not motivated to reduce snow field soot.
1.www.vox.com/energy-and-environment/2017/5/15/15634538/china-coal-cleaner
2.Lillieblad, Lena et al, Electrostatic Precipitator Performance with Chinese Coals, ICESPX Australia 2006, paper 3a23. Xizhou Zhou, How China’s anti-smog campaign triggered a natural gas crisis and a switch to “clean coal”, Wall Street Journal, March 7, 2018
MOTIVATION
RADIATION TRANSPORT ANALYIS
FUTURE PLANS (Update and extend earlier work)
WHY CHINESE SOOT HYPOTHESE
SUMMARY
• Two Independent data sets show little or no anthropogenic net greenhouse gas effects• Satellite measurements and analysis of Tropospheric temperature anomaly• Radiation transport analysis with realistic changes in greenhouse gases including H20• These results support Miskolczi’s Saturation Effect Principle.
• Radiation transport model shows latitude effect• Zagoni’s web presentation on Miscolczi’s work does not show nor rule out a latitude effect• Effects of increased tropospheric water vapor may reduce latitude effect.• Regret: O3 data need seasonal effect and higher fidelity; northern O3 hole could reduce heating.
• Greenhouse gases are unable to produce measured warming.• No valid evidence proves existence of anthropogenic greenhouse gas effect.
• The greenhouse gas idea comes from multiple groups running large General Circulation Model computer codes which all show a warming trend.
• These are not valid proof of greenhouse gas effect because:• They appear to have inadequate altitude zones for the problem
• The CO2 emission zone is in the top of about 20 zones.• Assumption of constant relative humidity at altitude produces doubling of anthropogenic gas
warming where data model humidity cancels out at least most anthropogenic gas warming.• All Solar cycle effects are not included, including Cosmic ray effect that varies cloud cover
over solar cycle.• The codes over-predict reality.
• Trying to solve the wrong problem (greenhouse gas emission) may be making the warming plus ice cap and glacier melting problems worse by not adequately addressing soot,
• The good news; China, the major coal user, is beginning address its heating and power plants for local pollution reduction and reduced CO2 footprint (but not for albedo change)
Summary and Conclusions
BACKUPS
MODTRAN RT Options
MODTRAN Surfaces Screen
MODTRAN Spectral Options Screen
MODTRAN Custom Atmosphere Sub-Screen
MODTRAN Clouds and Aerosols Screen