I once heard that you should be skeptical of any discipline with the word "science" included. The reasoning is that the addition of "science" is merely a device for enhancing the credibility of a particular discipline. While that comment was made in connection with "social science," it also applies to climate science.
I'm not discussing here whether man-made global warming is real, or is part of other, larger forces, or not happening at all. What I am saying is that the discpline called climate science does not meet my standards for what can be legitimately be considered science.
Here's why: I'm a strict constructionist when it comes to using the "s" word. Scientific theories are established by developing a hypothesis and a model, then verifying them by repeated experiments and control groups. In the case of climate science, researchers don't have that opportunity, for obvious reasons.
It is possible to formulate a model which explains what had been observed, but that's not the same as proving it to be scientifically valid. Just because you can explain something doesn't mean your explanation is correct. After all, astronomers were able to use the Earth-centric Ptolemaic model of the Universe to accurately predict the position and motion of Earth, moon and stars. But that theory was superseded by the better Sun-centric Copernican model on which we now rely.
Einstein provides many excellent examples. In 1905, he developed a unified explanation for the contradictory data of the photoelectric effect, but it was also verified by further tests. In the same year, he published a paper which provided an explanation for the observed data on the Brownian motion of particles using an energy-partitioning thermal perspective.
For verification, Einstein used well-known oil-drop data and came up with a value for Avogadro's number that agreed closely with its long established value. Since Einstein used a radically different approach to determine that fundamental number, his method represented fairly good verification, but it was still not 100-percent proof that he was correct.
The real proof was when Einstein's Theory of General Relativity predicted an occurrence that others hadn't anticipated or observed. In this case, one consequence of general relativity was that the mass of an object would bend passing light. Years later, astronomers were able to confirm this and the amount Einstein's theory predicted. They used data from a total eclipse where the sun deflected light from stars with apparent positions located close to the Sun's edge.
The real test of a theory is not only its ability to credibly explain what we see, and to resolve inconsistencies, but to predict things that no one has yet seen. Due to the constraints of having only one Earth and our inability to run controlled experiments on it, climate researchers can't do that. Yes, they can predict the localized weather for the next few days, and with increasing accuracy. This implies that such small-scale models and their cause-and-effect links are probably correct.
This capability is not available for long-term climate research. Therefore, it isn't science.
You may ask: What about astrophysics? Since we can't set up tests or control the actions of the universe and its bodies, is it really science?
I'd say yes. The astrophysics community proposes theories and then tests them by observing many different stars, which provides some level of confidence. More significantly, astrophysicists also make predictions such as, "If we see 'A' coming from that neutron star, then by our theory we should also see this quantity of 'B'." If they don't see "B" as predicted, something is wrong. I don't see such correlation possibilities in climate research.
So, is man-made climate change happening or not? I don't know, nor do I think anyone really knows. But I am skeptical when proponents of a theory look at the data and rationalize what they see to fit their hypothesis.
Climate researchers point to "up" data as confirming their theory, while dismissing "down" data as mere noise or localized fluctuations within the bigger picture. In other words, all data—whether up or down--maps to the desired conclusion.
If that's your approach to data analysis, don't call it "science." Actually, why even bother examing the data at all?