This short discussion should help students understand the basic concept behind climate models. Notes on answers:

• (1) Smaller grid elements mean better resolution and therefore should make better models.
• (2) Shorter time steps similarly should give better results because they have better time resolution.
• (3) The number of calculations – and hence the computer speed — required for a model is larger if the grid size is smaller or the time elements shorter. It simply isn’t possible to make the sizes and times as small as you want, because the calculations would take too long even on the most powerful computers. Scientists must come up with acceptable tradeoffs that can realistically run on today’s computers.
• (4) This question is answered under the next subheading, so it is here to see if students can come up with some ideas for themselves.
• (5) The referenced TED talk is very good but fairly sophisticated, so you many need to help students understand it. We recommend it because it is very clear and has great visuals associated with it.

This activity, developed by the Center for Science Education at the University Corporation for Atmospheric Research (UCAR), introduces students to a “very, very simple” computer model. In this model, the only variable is the emission rate for carbon dioxide, and it can be set only at a fixed annual rate (that is, you can’t have emissions going up or down with time). Still, it should provide students with some insight into what climate models can do.

• If you would like to provide a structured activity, you can make use of this lesson plan developed by UCAR: https://scied.ucar.edu/activity/very-very-simple-climate-model-activity. Click the “Instructions” link for the lesson plan, and the “background and extensions” link to learn more about the model itself.

This activity builds on the above discussion to help students see how model reliability can be evaluated.

• (1) This can be a challenging question, because there clearly are differences between the model predictions and reality. You should help students focus on the “big picture,” which is that overall, the model does an excellent job. The general trend is correct most everywhere, and even the size of the trend is very close. This general agreement should give confidence in the reliability of the model, even if we know it won’t be perfect in its details.
• (2) The comparison may be a bit tricky in terms of trying to watch the correct time period in both videos together, but again, students should notice that the general trend of the predictions is pretty accurate.
• (3) Be sure that, as noted in the question, students pay attention to the different meaning of the darkest color. They will then see that the model is predicting substantial increases in global temperatures by 2100.
• (4) Students should be able to read the increase for your region in Celsius from the map, and convert to Fahrenheit by multiplying by 1.8. You may then wish to have students give the increase some context by, for example, considering how much hotter it would make typical winter days and summer days, assuming the average held true year-round.
• (5) The fact that the model used an underestimate of emissions to date would suggest that it probably also underestimated what the future temperature increases would be.
• (6) Be sure students recognize that a model is only as good as its assumptions, which means we are NOT “doomed” to what the model shows. However, if we want to have less increase than the model predicts, we likely need to lower our greenhouse gas emissions compared to what was assumed.

• (1) To answer this question, students should recognize that the 20th century average was almost 1°C lower than the 1986–2015 average. This does not affect the shapes of the curves at all, nor does it change what the models predict for the future. However, it does change the values we’d read from the graph as the “increase,” making each of them almost 1°C higher. For example, the most likely temperature increase for the high pathway would be almost 5°C when compared to the 20th century average, instead of about 4°C when compared to the average for 1986-2015.
  Note: This concept is important because, as the two graphs show (both taken directly from their original sources), scientists don’t always choose the same zero line.
• (2) If you read directly from the graph in Figure 7.2.2-4, both the intermediate (blue) and the low (green) curves would keep us below 2°C of future warming. However, if you use the 20th century average as a baseline, then as found in question 1 above, the increases would all be almost 1°C higher than you read from the graph. In that case, only the low (green) pathway keeps us below 2°C of warming.
  For your background, the reference point in the IPCC reports (and most other scientific reports) is usually the “pre-industrial” global average temperature, which is a little lower than the 20th century average. However, for our purposes here, we will ignore this difference.
• (3) Only the low (green) pathway appears likely to keep the total warming below 2°C for the longer term, because it is the only pathway for which the model predicts a temperature that is no longer rising in the year 2100. The intermediate (blue) pathway is still rising at that time and looks likely to surpass 2°C not long after 2100 (and even before if we compare to the 20th century average).
• (4) First, students should recognize that by asking about the 100th birthday of someone their age, we are looking beyond the year 2100. In general, students should support this claim by noting that the low (green) pathway is the only one that keeps the warming below this level, and this pathway assumes that we immediately begin reducing emissions and bring them to zero not long after 2050.
  However, there is a bit of wiggle room in this answer, since the graph only shows 3 possible pathways. For example, we might be able to wait a few years on beginning the reductions of emissions if we then bring them to zero at a faster rate than the low model assumes, or if we find a way to draw carbon dioxide out of the atmosphere. There may also be some pathways in between the low and intermediate models that would work. Still, students should recognize the key point: Sooner is better for reducing emissions if we hope to limit the future warming.

This CER activity addresses another common skeptic claim, this one about the reliability of models. There is some room for legitimate debate about models, but in general, concern about model predictions is overstated. A few key notes:

• Question 1: There isn’t an unambiguous answer to this question, but Figure 7.1.4-1 shows that:
• Over the past 800,000 years, the largest upward swings in the natural carbon dioxide concentration have been from about 180 to 280 parts per million, which is an increase of about 60%.
• These 60% increases in carbon dioxide concentration have been accompanied by temperature increases of about 8°C to 10°C (14°F to 18°F).
• Putting these two facts together, the past data seem to suggest that a 60 increase in the carbon dioxide concentration can cause warming of 8°C or more. This is substantially greater warming than even the high (red) models suggest for the rest of this century, even though these models assume a doubling (100 increase) of the carbon dioxide concentration well before the century ends. In other words, the projection you would make from actual past data would seem to be worse than what the models predict.
• Caveat: The fact that we were already in an interglacial warm period (near the high temperature of the past 800,000 years) before human-caused global warming gives skeptics some wiggle room. In particular, the common skeptic argument is that given this starting point, the climate is less sensitive to increases in the carbon dioxide concentration than it would be if we had been in an ice age, and therefore we should expect a much lower amount of warming. In other words, the models depend on how they account for the “climate sensitivity,” and the skeptics argue that the models are missing factors (for example, detailed effects of clouds) that cause them to overestimate the climate sensitivity. We cannot completely rule out this possibility, but there are at least two strong counterarguments that most scientists think make the skeptic claim highly unlikely: (1) If the models were missing any factors that would have significant effects on climate sensitivity, then we would not expect the models to match existing climate data as well as they do; that is, the success of the models at simulating the past climate makes it highly unlikely (though not impossible) that the models could be missing something that would have a major impact on future predictions. (2) Although we are near the high temperature for the past 800,000 years, Earth has been much warmer in the more distant past, which suggests that we are nowhere near the limit of what could happen with a rising carbon dioxide concentration.
• Question 2: This is another common claim made by climate skeptics, but it should be refuted as follows:
• First, regardless of what anyone believes about the first part of the statement (“the climate is too complex for scientists to predict”), the second part (“without these models, there is no evidence”) is clearly false: As discussed in question 1 above, the ice core data provide evidence that is independent of the models and that suggests that a doubling of the carbon dioxide concentration would cause a rise much larger than 2°C.
• While there may be some opinion-based component to the first part (“the climate is too complex for scientists to predict”), students should be able to cite what they’ve already learned about how scientists evaluate the reliability of models. This offers plenty of evidence that models are indeed useful, even if they are not perfect.