Sometimes, I encounter arguments suggesting that since we cannot predict the weather beyond a couple of weeks, then it must be impossible to predict the climate in 100 years. Such statements tend to present themselves as a kind of revelation, often in social settings and parties after I have revealed for some of the guests that I’m a climatologist (if I say I work for the Meteorological Institute, I almost always get the question “so, what’s the weather going to be like tomorrow?”). Such occasions also tend to be times when I’m not too inclined to indulge in deep scientific or technical explanations. Or when talking to a journalist who wants an easy answer. In those cases I try to provide a short and simple, but convincing, explanation that is easy for most people to understand why climate can be predicted despite the chaotic nature of the weather (a more theoretical discussion is provided in the earlier post Chaos and Climate). One approach is to try to relate the topic to something with which they are familiar, such as to point to empirical observations which most accept (I suppose with hindsight it could be similar to the researchers in the early 20th century trying to convince that nuclear reactions were possible – just look at the Sun, and there is the proof! Or before that, the debate about whether atoms were real or not – just look at the blue sky, and you look at the proof…). I like to emphasised the words ‘weather‘ and ‘climate‘ above, because they mean different things.
It is true that we cannot predict the weather indefinetely (or even beyond a couple of weeks), because of the chaotic nature and infinitesimally small uncertainties in the state as we know to day, will affect how the weather evolves in a few weeks (the ‘chaos effect’). But, still I say that I know with certainty that there is a very high probability that the temperature in 6 months will be lower than now – when winter has arrived (it’s summer on the northern hemisphere at the present). In fact, the seasonal variation in temperature and rainfall (wet and dry seasons in the tropics) tends to be highly predictable: the winters at high latitudes are cold and summers mild (if anyone doubts, read on here); the southeast Asian Monsoon usually starts over India in the first days of June. I don’t usually bring with me maps and figures to social events, but it would be nice to show a picture such as the one in Fig. 1 to illustrate. If the person is not convinced, I may continue with other arguments for why the climate is predictable: take the latitude for instance – the poles are cold and tropics warm. Furthermore, maritime climates at higher latitudes with wet and mild (small day-to-day or season-to-season temperature variations) are distinct to continental climates far away from the sea (dry with great temperature variations). It is well-established that high-altitude places tend to have lower temperatures and greater temperature variations. Most hikers and mountaineers have experienced that. These are local climatic properties that we can predict if we know the geography, even if we cannot predict the weather on an exact day far in the future. To convince further, I may add that empirical evidence suggesting that (local) climate is not unpredictable, but rather systematically influenced by external factors (boundary conditions) is that Northern Europe enjoys a mild climate: Oslo is roughly on the same latitude as the southern tip of Greenland. There is a reason for that – Oslo has a considerably warmer climate because of the effects of oceanic heat transport/capacity and prevailing winds. I also remind that people really have known for centuries that there are systematic factors influencing the local climate, it’s just that this fact sometimes gets forgotten by those who claim that we cannot predict climate. Isn’t it silly? I may ask if there is any reason to think that the predictability stops at the seasonal and geographical variations.
I may continue with in a hand-wavy manner: In a similar fashion as seasonal and geographical effects, changes in Earth’s orbit around the Sun alters the planetary climate by modifying the amount of energy received from our star (but because of terrestrial response, the atmospheric composition is modified as well, enhancing the effect even further), and changes in the atmospheric composition affects the climate because grenhouse gases absorb heat that otherwise would escape into space – greenhouse gases are transparent to sunlight, but opaque to infrared light due to their molecular properties and their ability to absorb energy (if I say it’s quantum physics, people tend to understand it’s getting a bit technical). I stress that the greenhouse effect is also beyond doubt – without it, the energy balance between total energy Earth intercepts from the Sun and the energy lost through black body radiation implies that Earth’s surface on average would be about 30K cooler than we know it. Volcanoes also affect our climate, and we have theories explaining why. Furthermore, looking to other planets, the observation that Venus has higher surface temperature than Mercury, despite being further away from the Sun, can only be explained as a result of different absorbing properties of their respective atmospheres (a strong greenhouse effect at Venus).
So, my question is, do you think people get the message that I try to convey this way? Is it too simple or too complicated? Somebody who knows of every-day examples demonstrating the central principles? Any suggestions on how to explain for laypersons not connected to the Internet?
Re: #200,
Nice acronym, Pat! It’ll be tough to remember, though, or at least to keep the letters in the right order.
Say ARGGGH.
Anthropogenic Rapid Greenhouse Gas Global Heating.
I’m really not qualified to comment on the scientific debate above, but I do have a suggestion in answer to your original request, how to explain the predictability of climate when you can’t necessarily predict weather. The reason I have bothered to post is because the more I think about this idea, the more interesting it becomes. I hope it helps.
The Golf analogy.
Predicting the weather is like playing a stroke on a golf course. I know where the ball is, how far away the hole is, what obstacles may be in my way, how to stand, hold the club, address the ball and swing. But I don’t know where the ball is going to end up. This is because there are some things I cannot anticipate perfectly; the exact bounce of the ball, a slight ‘twitch’ in a muscle at the crucial moment, a sudden gust. But I can still get the ball closer to the hole. How can I do this? I take into account the known variables, apply the principles I have learned over many years’ practice, amd concentrate. Sometimes, on a good day, I’ll strike the ball perfectly and it will end up right by the hole. The next hole, I could play just as good a shot and end up 30 yards out. On a bad day, I’ll shank the ball and end up in the rough.
Predicting the climate, on the other hand, is like trying to win a Major tournament. A lot depends on it, including the well-being of my ‘family’. What I can predict is that I will complete the round, even though I don’t know where each shot is going to go. I also know that, if I am good enough, I should get round in in a number of strokes closely related to my handicap. When I start the round, I’ll look at the course, the conditions and my skill, and choose the clubs, clothing and, probably, the strategy I intend to adopt to maximise my potential to hit birdies, and minimise the risk of bogies. (If it’s a windy day on a links course, i might choose clubs with less loft, for example).
If someone asks me what score I’m going to make today, I can consider all of these things and give an answer, which I can expect to be close to my final score, because of what I know about golf. I can do this, even if I don’t know where my first drive on the first green is going to end up, or in fact, where any one shot will land, exactly.
Then, I realised, that this analogy can be extended to cover much of the debate between Realclimate and Climate Science. Realclimate: I’ve practised hard, I’m on the course, I have to do my best; people are depending on me. I know I can play a good round. Climate Science: You are not good enough; you are playing off the wrong tees; you don’t have the right equipment…
So, are climate models as good as Tiger Woods – would you bet on them? Or are they the gifted amateur with a dream, and a chance? Whichever the answer, we have to play the tournament – the future. But both sides of your debate have important points to make about the outcome of the event, and the ability to predict the outcome.
Like I said; it’s all comparable to golf. Trouble is, the stakes we are playing for are high, and even Tigers sometimes get beaten.
I hope this works for you. :)
RE# 196,
Steve I have gotten past Google first hit of Cpk [California Pizza Kitchen] and now cramming on Cpk – Process Capability Index. Doesn’t mean I will [do the real work]. Admittedly, that is beyond my pay grade.
But, I will read what I can undestand. And, I will consider variation in sea ice coverage inlcuding inputs of Asian north flowing rivers, shallow profile of the Arctic and influence of the Polar low. Then, I will see if I understand arctic meltback while using more data and return to this thread.
Someone may have suggested this above– I haven’t searched all the comments– but I often find a familiar analogy will carry more weight than an explanation that continues to focus on the topic at hand. For example, you could point out that predicting how an individual gambler in Vegas does on a particular day is difficult, but predicting how the average gambler does on that day is easy. Since climate really is average weather (in a sense that gets technical in many ways), we can predict it without needing to be able to predict the actual weather…
So are you saying that you could predict when the next ice age would come and when it would end, or if you lived before the last ice age you could have predicted when it would start and when it would end?
If you’re speaking to someone who likes to play Poker or other card games (and many people do, these days), here’s one way to explain it: If you deal out a billion hands, you can come up with extremely precise probabilities for how frequently certain cards, or certain combinations of cards, will come up. This is what makes card-counting in Blackjack possible. But no matter how accurate your probabilities are, it would be virtually impossible to predict with any accuracy exactly which cards would reveal themselves at any given moment in the game. So if you know the math and bet accordingly, you can ride the big waves to profit, but you’ll never be able to predict the small chop that you encounter in between those big waves.
My experience is that people on average understand extremely poorly probabilities. Would they, there would exist no games of chance in the world.
To my mind predicting future climate is analogous to predicting whether next day. While it is not possible to announce beforehand the exact minute rain will come next day, it is possible to be sure that in the evening next day it rains.
Re #206: Vagelford, I am but an amateur with regard to paleoclimate, but I believe the answer is yes. Well, yes provided you are willing to accept predictions with +- 2000 year error bars.
The paleoclimate records from ice cores, for example, clearly indicate the importance of what is called ‘orbital forcing’, that is, changes in the solar insolation in the far north due to slow, small changes in the Earth’s orbit around the sun. These changes can readily and accurately be computed far into both the past and the future.
If the change is enough, ice ages will start or end. For example, without AGW the next major coolings are predicted for 50,000, 100,000, 600,000 and 650,000 years from now. Any of these could have been enough to trigger an ice age. But with AGW?
If you meet someone at a party who asks you, with a snide smile, “How can you predict the climate in the future when you can’t even tell me what the weather will be like tomorrow?”, give them this to think about.
“You have been imprisoned in solitary confinement, for twelve years, for the new crime of Climate Change Denial. For twelve years you have lived in a small cell, with no window, and have been deprived of any contact with the outside world. You haven’t seen the sky for ten years, you live entirely indoors in a air-condition facility. At the end of your twelve years, on the day of your release, a guard comes in with some civilian clothes for you – a nice pair of Bermuda shorts, tropical shirt, straw hat and sandals.
The only problem is, that you are imprisoned in Chicago and it’s January 20th.
Now tell me that I can’t predict the climate”
Re #209: David thanks for your comments. They give me the chance to comment further on the subject.
So David, what you are saying is that you can’t make a prediction, since you can’t “model” AGW, but given the history of ice ages and the fact that they are related to orbital forcing they should, but also could not, happen at the intervals that you are giving?
What I’m trying to say is that there must be models that have a number of parameters, such as the earth orbital elements or the solar insolation or the volcanic activity, that model the climate in the range of thousands of years. Are you suggesting that given a small uncertainty in one or some of the above parameters you can guaranty that the result after a couple of runs of the model will be the same climate (ice age – not ice age) in the same periods of time within the reasonable errors?
In the article titled Chaos and Climate, the author claims that the Lorenz model will not show a change in climate if there is a perturbation in the r parameter (since climate is not chaotic) and uses the mean value of z to demonstrate that, which is a bit of cheating since the Lorenz model is 3-D and the x and y would show a dramatically different behaviour. First of all the Lorenz model has a natural climate variability that is evident in the full 3-D by the characteristic two wings (an information suppressed by the choice of z) and secondly a plot of y would show that a small change in r would give a completely different oscillation between the two climates than the plot with no change (characteristic of the chaotic nature of the Lorenz system).
http://www.geocities.com/vagelford/Science/Lorenz_comparison.gif
Are you saying that the case with climate is not analogues to the Lorenz system?
And since we are talking about the Lorenz model, it is a well known model with well known equilibrium points that the climate oscillates between them. My question is, how well do we know the terrestrial system and the equilibrium points of its climate?
[Response: The ‘climate’ of the Lorenz model includes the two lobes and the time spent on average in each (think of ENSO in the real world). A change in climate in that system would be a change in the location of the lobes or of their relative importance or something similar. The point being I would trace out essential the same butterfly wherever I started given enough time. Thus the ‘climate’ of the Lorenz system is stable. – gavin]
Re #211: Vagelford, my current amateur research project has led me to have great interest in the paleoclimate of the Alaskan Penninsula and the Gulf of Alaska coast during the period 50,000 to 40,000 years ago. This led me to read three books on paleoclimate. Also several papers. In this reading I noticed to strong effect of orbital forcing upon macro features of climate.
In my readings, four different papers offered the four different dates I mentioned as potential tipping points into the next ice age, assuming no AGW. If the authors of those papers offered probablities, I don’t recall them. What I do recall is that each in series seemed to me as more likely to led to an ice age than the previous one.
If you like mathematical models, I suggest thinking more along the lines of Markov chains, wherein the current system state does not lead definitely to just one fixed state, but rather assigns probabilties to the various transitions. To the limited extent that I know about climate modeling, it appears that this approach is not often used.
To get back to Rasmus’s original question, I think you may be able to make the same point with less technical detail (or at least withhold it until requested).
Here’s the analogy I used to distinguish between predicting climate and weather: you can predict with some confidence and a narrow margin of error the average height of the next 100 people who will walk past the sidewalk cafe where you are holding forth — but you can’t know the height of the next person to go by (except to say that if it’s an adult human, it’ll be between 120 and 240 cm). Any other example that built on the listener’s personal experience would likely work as well.
“Short and simple arguments for why climate can be predicted”
Does anyone think that any future IPCC assessment report will actually issue predictions for methane atmospheric concentrations, CO2 emissions and atmospheric concentrations, and resultant globally averaged surface temperature and lower tropospheric temperature?