The theory that failed
It takes only one experiment to disprove a theory. The climate models are predicting a global disaster, but the empirical evidence disagrees. The theory of catastrophic man-made global warming has been tested from many independent angles.
The heat is missing from oceans; it’s missing from the upper troposphere. The clouds are not behaving as predicted. The models can’t predict the short term, the regional, or the long term. They don’t predict the past. How could they predict the future?
The models didn’t correctly predict changes in outgoing radiation, or the humidity and temperature trends of the upper troposphere. The single most important fact, dominating everything else, is that the ocean heat content has barely increased since 2003 (and quite possibly decreased) counter to the simulations. In a best case scenario, any increase reported is not enough. Models can’t predict local and regional patterns or seasonal effects, yet modelers add up all the erroneous micro-estimates and claim to produce an accurate macro global forecast. Most of the warming happened in a stepchange in 1977, yet CO2 has been rising annually.
Observations from every angle point to a similar conclusion
Studies involving 28 million weather balloons, thousands of satellite recordings, 3,000 ocean buoys, temperature recordings from 50 sites in the US and a 1,000 years of temperature proxies suggest that the Global Climate Models overestimate positive feedback and are based on poor assumptions. Observations suggest lower values for climate sensitivity whether we study long-term humidity, upper tropospheric temperature trends, outgoing long wave radiation, cloud cover changes, or the changes in the heat content of the vast oceans.
Continued faith in flawed models breaks central tenets of science
The two things which make science different from religion are that nothing in science is sacred, and everything in science must ultimately fit with observations of the real world. While a theory may never be 100% proven, it can be disproven. The pieces of the climate jigsaw are coming together. The observations suggest that the warming effect of man-made emissions of CO2has been exaggerated by a factor of 3 – 7 in computer simulations.
Observations show major flaws
- The missing heat is not in the ocean 8 – 14
- Satellites show a warmer Earth is releasing extra energy to space 15 -17
- The models get core assumptions wrong – the hot spot is missing 22 – 26, 28 – 31
- Clouds cool the planet as it warms 38 – 56
- The models are wrong on a local, regional, or continental scale. 63- 64
- Eight different methods suggest a climate sensitivity of 0.4°C 66
- Has CO2 warmed the planet at all in the last 50 years? It’s harder to tell than you think. 70
- Even if we assume it’s warmed since 1979, and assume that it was all CO2, if so, feedbacks are zero — disaster averted. 71
- It was as warm or warmer 1000 years ago. Models can’t explain that. It wasn’t CO2. (See also failures of hockey sticks) The models can’t predict past episodes of warming, so why would they predict future ones?
The direct effect of CO2 is only 1.2C
The IPCC estimates that carbon dioxide’s direct effect is 1.2 °C1 of warming (that is, before feedbacks are taken into account) for each doubling of the carbon dioxide level. Models amplify that warming with assumptions about positive feedback (see the blue region of model estimates in the graph below). But observations show that net feedback is probably negative, which would instead reduce the direct effect of the extra carbon dioxide.
While independent scientists point to the empirical evidence, government funded scientists argue that a majority of scientists, a consensus, support the theory that a man-made catastrophe is coming.2 This is plainly unscientific and a logical fallacy. The test of scientific knowledge is through experiment and observation. The only evidence the government scientists provide on the key points of attribution (the cause of the warming) come from simulations of the climate done with computers. Those models are unverified, and when tested, have “no skill” at predicting the climate. Scientists may claim otherwise, but no single model is proficient, rather a selection of models has “success” with a few parameters.
A multitude of observations are in rough agreement that any increase in global average temperature caused by a doubling of CO2 is more likely to be about half a degree than the 3.3 degrees determined by the IPCC3.
The major problem for models: Feedbacks
Our climate changes because of outside effects, called forcings: the sun grows brighter, or its magnetic field changes, ocean currents shift, vegetation changes, or continents move. The Earth is a ball of magma, is a 12,000 km thick, with a thin crust about 12 km of rock on top, who knows what effects come from within? The IPCC recognizes only two types of forcings: greenhouse gases and solar luminosity.
Forcings are difficult to unravel. Harder still are feedbacks, as systems all over the planet simultaneously adjust to changing conditions. In a warmer world, for instance, less ice and more plant-life means less sunlight is reflected to space, which creates more warming. The oceans release carbon dioxide, more water evaporates, humidity changes, sea-levels rise, and all of those consequent changes further affect temperatures.
The feedbacks are not just icing on the cake, but in the IPCC’s view, collectively more powerful than any forcing due directly to CO2. Indeed while CO2 may cause one degree of warming, the feedbacks amplify this – theoretically anyway – by up to three degrees. The major agent of feedback, according to the IPCC, is water vapor (ie. humidity).4 The IPCC could be right about one hundred factors, but if they are using the wrong assumptions about the way clouds and humidity behave, the forecast of an alarming three degrees could be reduced to a forecast of a mere half-a-degree. Some details matter more than others.
Not only is it hard to put a value on all the feedbacks, it’s difficult to know if some changes are a feedback or a forcing5 or even both at once — for example, clouds. Clouds’ impact on climate would obviously change as the world warms (a feedback) but, if solar-magnetic effects change clouds, as now seems likely, clouds could also drive climate change (a forcing).6, 7
The references here independently show that core model assumptions are wrong. Models assume that relative humidity will stay the same over the tropics as the world warms, that clouds are a positive feedback and not a negative one, and that cloud changes are a feedback and not a forcing in their own right. These are three critical and demonstrable errors.
Every which way we measure it, the models predictions don’t match the observations.
The warming we’ve had in the last thirty years implies that at best, we could expect 1°C from a doubling of CO2, but observations from eight natural experiments around the globe, and even on Mars and Venus suggest that 0.4°C is the upper bound of climate sensitivity to any cause. In addition, if Miscolscki is right, and an increase in carbon dioxide leads to a decrease in water vapor, then the sensitivity due to CO2 could be close to zero.
The global warming predictions are contradicted by the data. The vast funding which is now being directed to ‘solving’ global warming should be redirected to researching hypotheses which are consistent with empirical data and confirmed by observable evidence.
The exception proves that the rule is wrong. That is the principle of science. If there is an exception to any rule, and if it can be proved by observation, that rule is wrong.
Richard Feynman, according to The Meaning of it All, 1999