The test: if your political candidate supports the climate change dogma, then vote against them. There are no exceptions. They will harm you.
Everyday, there are more and longer lists of scientists skeptical of human-caused global warming. On the other hand, the UN and many politicians and media are trying to scare you. But nothing, no expert, no consensus, changes the simple facts that falsify the hypothesis put forth by the proponents of human-caused global warming. Despite years of trying and spending billions of dollars on research, there is no evidence that a statistically significant trend of increasing CO2 concentration causes a statistically significant trend of warming.
However, there is substantial evidence from multiple sources that falsifies their hypothesis. For example, while CO2 concentration trend was steadily increasing, temperature trends declined for years, then increased for years (see Hadley Temp vs CO2 graphic) and now more recently has been trendless or only slightly increasing for more than 20 years. If CO2 causes warming, as they claim, then there cannot be extended periods of cooling or no temperature trend at the same time CO2 is rising. But, in fact, there are such periods.
As we all know, correlation by itself does not prove cause. However, for there to be a cause, there must be a correlation. An increasing trend of human-produced CO2 was hypothesized to be the cause (trigger, forcing) of significant global warming. Therefore, for that hypothesis to be valid, there must be a strong positive correlation with an increasing temperature trend. But there is only a very weak correlation or none. In other words, in a 2 line graph of CO2 change versus temperature change, the two lines must be parallel or converging if the hypothesis is true. But, the lines are diverging; there is no strong positive correlation. Worse for the AGW hypothesis, there are other trends that more strongly correlate with temperature, for example, total solar irradiance (TSI) and ocean warming (PDO and AMO.)
Then there is the ongoing problem with the year after year progressively lower high temperature readings (or the number of days per year over say 90 degrees or 95 degrees), a measurement process which avoids the problem of data closure caused by averaging averages.
Then there is the problem that ice core drillings smoothed over statistically appropriate long periods show that warming trends always occur BEFORE trends of increasing CO2. Obviously, the hypothetical effect cannot occur before its hypothetical cause. In multiple studies the CO2 change LAGS the atmospheric temperature change, both warming and cooling.
“Petit et al (1999) (ref 1 below) reconstructed histories of surface air temperature and atmospheric CO2 concentration from data obtained from a Vostok ice core that covered the prior 420,000 years, determining that during glacial inception “the CO2 decrease lags the temperature decrease by several thousand years” and that “the same sequence of climate forcing operated during each termination.” Likewise, working with sections of ice core records from around the times of the last three glacial terminations, Fischer et al (1999) (ref 2) found that “the time lag of the rise in CO2 concentrations with respect to temperature change is on the order of 400 to 1000 years during all three glacial-interglacial transitions.”
“On the basis of atmospheric CO2 data obtained from the Antarctic Taylor Dome ice core and temperature data obtained from the Vostok ice core, Indermuhle et al (2000) (ref 3) studied the relationship between these two parameters over the period 60,000-20,000 years BP (Before Present). One statistical test performed on the data suggested that shifts in the air’s CO2 content lagged shifts in air temperature by approximately 900 years, while a second statistical test yielded a mean lag-time of 1200 years. Similarly, in a study of air temperature and CO2 data obtained from Dome Concordia, Antarctica for the period 22,000-9,000 BP — which time interval includes the most recent glacial-to-interglacial transition — Monnin et al. (2001) (ref 4) found that the start of the CO2 increase lagged the start of the temperature increase by 800 years. Then, in another study of the 420,000-year Vostok ice-core record, Mudelsee (2001) (ref 5) concluded that variations in atmospheric CO2 concentration lagged variations in air temperature by 1,300 to 5,000 years.”
Then there is the atmospheric physical chemistry problem that increasing CO2 concentration results in progressively (log rate) diminishing amounts of warming because the quantum bands in CO2 molecules available for IR adsorption and re-emission are already occupied by energy radiated from other molecules. Thus, we see over the last 15 years, AGW proponents have been progressively reducing in their peer-reviewed publications their estimates for climate sensitivity attributable to CO2.
Then there is the statistical problem that the net amount of warming (or forcing: W/m^2) which can be attributed to human-produced CO2 is less than the standard error in the measurement of the net warming (or forcing) that can be attributed to water vapor/clouds. Water vapor and clouds are of course the dominant “greenhouse” gases according to all scientists. Forcing due to CO2 at today’s 0.04% concentration (or 400 ppmv) is about 1.5 Watts per square meter (W/m^2), whereas forcing due to water vapor and clouds are each about 10 W/m^2 and both are highly variable because humidity in air is highly variable and far outside human control. We have a 10 times larger variable that is 10 times more variable than CO2. Water vapor/clouds are responsible for about 94.99% of the total “greenhouse effect,” whereas total CO2 is responsible for only about 3.5% and human-produced CO2 is responsible for only about 0.12%. In other words, the warming effect (or forcing) due to CO2 is so small that it cannot be distinguished from noise, i.e. human CO2 is statistically insignificant. How can feedback or feedforward be modelled if one variable is too small to measure? The amount of warming due to human-caused CO2 is a computer calculation which is so small that it cannot be measured or validated in nature with the precision required by measurement sciences. Since the effect of CO2 is so small, the models cannot be validated by observations.
According to the rules of science and statistics, AGW is a failed hypothesis.
(1) Petit, J.R., Jouzel, J., Raynaud, D., Barkov, N.I., Barnola, J.-M.,Basile, I., Bender, M., Chappellaz, J., Davis, M., Delaygue, G., Delmotte, M., Kotlyakov, V.M., Legrand, M., Lipenkov, V.Y., Lorius, C., Pepin, L., Ritz, C., Saltzman, E., and Stievenard, M. 1999. Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica. Nature 399: 429-436.
(2) Fischer, H., Wahlen, M., Smith, J., Mastroianni, D. and Deck B. 1999. Ice core records of atmospheric CO2 around the last three glacial terminations. Science 283: 1712-1714.
(3) Indermuhle, A., Monnin, E., Stauffer, B. and Stocker, T.F. 2000. Atmospheric CO2 concentration from 60 to 20 kyr BP from the Taylor Dome ice core, Antarctica. Geophysical Research Letters 27: 735-738.
(4) Monnin, E., Indermühle, A., Dällenbach , A., Flückiger, J, Stauffer, B., Stocker, T.F., Raynaud, D. and Barnola, J.-M. 2001. Atmospheric CO2 concentrations over the last glacial termination. Science 291: 112-114.