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Usually, when data is collected in an experiment, scientists have a control. Experiments are seen as flawed without controls. I am just curious as to where else scientists have 'built' controls using models. Obviously, we cannot find a real 'control Earth', so we must make climate models, but then why can we even proceed with the experiment (how are we so sure the models act within a small error of the 'control Earth')?

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    $\begingroup$ What exactly is the question? Climate models are not designed to be a control. $\endgroup$ – bon Jun 2 '17 at 8:18
  • $\begingroup$ @bon The question is that, being that taking years of climate data on the Earth is an experiment, and experiments need controls where is the control Earth? My professor said we use models to build a "control Earth'. I further question why this is good scientific practice and where we have built controls elsewhere. He did not have an answer. I am just curious if someone can explain this absence of basic experimental fundamentals. If we don't use climate models to build a control then what is the control? Do we not need one? Is this not regarded as an experiment? I am genuinely curious. $\endgroup$ – Joey Marlowe Jun 2 '17 at 12:04
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    $\begingroup$ It's obviously not a controlled experiment but that doesn't make it any less valid to collect data on the climate. All sorts of science is done this way. Look at something like gravitational wave detection for example. You obviously can't build a control there. $\endgroup$ – bon Jun 2 '17 at 12:08
  • $\begingroup$ @bon I agree that both are not a controlled experiment. I'm just wondering how scientists can make conclusions about uncontrolled experiments like in climate change caused by humans if we have no way of knowing what Earth would have been like without us. In LIGO they are just taking data and making conclusions about the existence of gravitational waves. Why in this case can we make conclusions not just on the existence of rising global temperatures but also on human effect on them if we have no way of knowing the error of the current data to data taken if humans never existed? $\endgroup$ – Joey Marlowe Jun 2 '17 at 12:33
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    $\begingroup$ @EpsilonSigma There is some faith involved in believing climate models; I don't build them and input test data myself. However, most people with a good understanding of the science agree that the models are generally correct. Also, if you look at the first IPCC reports from 1990, the results are generally valid. I graphed the predictions of IPCC 1990 vs actual data (5 year rolling average) to 2015 myself. The IPCC best guess predicted 0.40 C of warming, and the actual data indicates 0.35 C of warming. So I think my faith is justified. $\endgroup$ – kingledion Jun 2 '17 at 17:01
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It's true that, usually, when data is collected in an experiment scientists have a control, and very often not having a control results in a flawed experiment - that is, an experiment from which less conclusions can be drawn.

Experiments are a very efficient way to gather high quality data, but in some fields they might even be impossible. However, experiments aren't the only way to get knowledge and they aren't mandatory to make science.

In some fields experiments are quite easy and therefore most research is based in experiments. For example, it's usually easy for chemist to test the way substances react by making experiments.

In other fields some questions can't be resolved by direct experiments due to practical or ethical reasons. In a known textbook example, sociologists are interested in what circumstances cause suicide rates to rise or drop, but ethics prevents them from performing an experiment by submitting a sample of people to circumstances supposed to induce suicide and compare suicide rate of this sample with suicide rate in a control sample. Therefore, sociologist need to draw conclusions from observational data - that is, observing real population under natural circumstances they can't adjust - or from experiments of related phenomena that can be performed without ethical concerns.

We in Earth sciences face a similar problem: some experiments can't be done because of scale or just because we just have an only Earth. For example, how do we know that rivers cause deltas? Ideally, we'd like to do an experiment by selecting several coast tracts, putting rivers in a randomly chosen sample of them, waiting a few millions of years and comparing evolution of the coast tracts with and without rivers. We can't do this experiment, but it doesn't prevent geologists to have learned a lot about deltas, because we have a lot of data from observation of naturally occurring deltas, from small scale experiments, and from study of auxiliary sciences (physics, hydraulics, etc.).

Climate is similar to deltas. Just as we can experiment with setting and removing rivers, we can't change CO2 levels of the whole atmosphere to measure what happens, but we can observe what actually happens, search for geological register of what happened in the past, do a lot of small scale experiments, and use our knowledge of basic sciences and draw conclusions about climate evolution from them.

Clearly, interpretation of that data is not as straightforward as data from a big experiment would be, but it is still possible and useful. In fact, it's the way most of current knowledge in many fields has been built.

All that without needing a random sample of Earths nor a control Earth.

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What do you mean by a control Earth? There is a control Earth: all of history until now. We don't know everything that happened on this control Earth, but we have some reasonable estimates of how temperature, carbon dioxide levels, and other factors changed in the past, and so we us those as best we can to develop how the Earth did act.

However, we have another data point to use, other than our limited information about the past Earth. We have physics to describe heat transfer, radiation emission and absorption and more. We could use this knowledge to create a model wholly independent of any knowledge of past Earth conditions. Since the various physics we use is all experimentally confirmed, we can be much more confident in it than we can in past Earth conditions.

When you build a climate model, you make sure that the things that did happen can be modeled correctly by that model. The climate models that I am familiar with meet that criteria, for some subsection of the past that was used to create the model. Admittedly, the model is only as good as the past data we are using to calibrate it; but in the physics of the model we can be certain.

So we have created models that can correctly predict the temperature changes in some subset of the past, and we are using those to extrapolate into the future.

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  • $\begingroup$ Hello. By control Earth I mean an Earth without humans. I am saying that as @bon pointed out taking climate data from Earth (currently with humans) is an uncontrolled experiment. The idea of a yes/no answer to human-influenced climate change requires a 'control Earth'. "Why in this case can we make conclusions not just on the existence of rising global temperatures but also on human effect on them if we have no way of knowing the [difference] of the current data (Earth with humans) to data taken if humans never existed?" $\endgroup$ – Joey Marlowe Jun 2 '17 at 17:10
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    $\begingroup$ @EpsilonSigma Did you read the answer? We have confidence in the models because they are based in experimentally verified physics and they are calibrated against known past climatic conditions, before humans were around. $\endgroup$ – bon Jun 2 '17 at 17:38
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    $\begingroup$ @EpsilonSigma Prior to about 10,000 years ago, this Earth was an Earth without humans, for all intents and purposes. Furthermore, from a climate analysis perspective, really only the last 200 years have humans had the numbers and technology to make a significant impact on climate and albedo and things. $\endgroup$ – kingledion Jun 2 '17 at 19:00
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    $\begingroup$ @bon That still does not explain how modeling temperature data from "past climatic conditions" (conditions without humans, for all intents and purposes) is actually deterministic of current climate conditions without humans. From a chaos theoretical/differential equations standpoint, that seems like an interesting point of view. Are you saying a mathematical model can reproduce climate conditions (today, as if humans weren't here) on a system as sensitive to initial conditions as the Earth without producing a large error, based on old temperature data? This seems like a big logical leap. $\endgroup$ – Joey Marlowe Jun 2 '17 at 19:50
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    $\begingroup$ @bon In other words, what makes you so sure that it is actually deterministic, if you cannot possibly know what a humanless Earth would be like? Especially given chaos. $\endgroup$ – Joey Marlowe Jun 2 '17 at 19:52

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