<p>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.</p>

<p>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.</p>

<p>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.</p>

<p>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.</p>

<p>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.).</p>

<p>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.</p>

<p>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.</p>

<p>All that without needing a random sample of Earths nor a control Earth.</p>

CC BY-SA 3.0
2017-06-03T21:45:08.947Z
2017-06-04T19:18:31.333Z
2017-06-04T19:18:31.333Z
Pere
<p>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 <em>did</em> act.</p>

<p>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.</p>

<p>When you build a climate model, you make sure that the things that <em>did</em> 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.</p>

<p>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. </p>

CC BY-SA 3.0
2017-06-02T17:38:33.257Z
@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.
bon
CC BY-SA 3.0
2017-06-02T19:00:58.373Z
@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.
kingledion
CC BY-SA 3.0
2017-06-02T16:52:47.440Z
2017-06-02T16:52:47.440Z
kingledion
<p>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')?  </p>

CC BY-SA 3.0
2017-06-02T08:18:42.367Z
What exactly is the question? Climate models are not designed to be a control.
bon
CC BY-SA 3.0
2017-06-02T12:08:15.960Z
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.
bon
CC BY-SA 3.0
2017-06-02T16:17:13.470Z
We have physics. We are not psychologists. You definetly need a control experiment if your only science question can be a "Yes/No" question with alpha and beta errors. With physics we can move beyond that to quantify things and ask "how much will it warm with humans, given the assumptions...". But in the models you can anytime just cut human influence to zero and have your control experiment. Which is a valid approach as long as you are comparing simulations with simulations.
AtmosphericPrisonEscape
CC BY-SA 3.0
2017-06-02T17:01:37.827Z
@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.
kingledion
<climate><climate-change><human-influence>
Why is it good scientific practice to 'build' a 'control Earth' from models, and where else do we 'build' controls?
Special Spirit
# Why is it good scientific practice to 'build' a 'control Earth' from models, and where else do we 'build' controls?

(Asked by: username_0 on 2017-06-02)

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')?

**Tags:** climate, climate-change, human-influence

> **Comments:**
> **username_1**: What exactly is the question? Climate models are not designed to be a control.  
> **username_1**: 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.  
> **username_2**: We have physics. We are not psychologists. You definetly need a control experiment if your only science question can be a "Yes/No" question with alpha and beta errors. With physics we can move beyond that to quantify things and ask "how much will it warm with humans, given the assumptions...". But in the models you can anytime just cut human influence to zero and have your control experiment. Which is a valid approach as long as you are comparing simulations with simulations.  
> **username_3**: @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.  

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## 2 answers

### Answer by username_4 on 2017-06-03. Score: 6

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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### Answer by username_3 on 2017-06-02. Score: 4

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.

> **Comments:**
> **username_1**: @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.  
> **username_3**: @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.  

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