August 17, 2009

Global Warming Misconceptions

There are several questions dealing with global warming that come up frequently...and it happened again this week when I gave a lecture at Google in Kirkland.

"How can you meteorologists possibly predict global warming fifty years from now when you have problems forecasting the weather three days ahead?"

(Some questioners use more earthy language to describe the current state of meteorological prediction skill, while others suggest that weather forecasters use dice for all the skill they have).

Well, we CAN predict what is going to happen fifty years from now and the forecasts are worth listening to. How can that be?

First, let me say that weather forecasts have gotten much more accurate during the past decade or so. And that is due to several reasons: far better computer forecast models (better understanding of physical processes, better resolution due to more powerful computers) and FAR better and much more observations that allow us to start our computer models with a better starting description of the current state of the atmosphere. We rarely get big storm forecasts wrong today and the day 4 forecasts has the skill of the day 2 forecast 25 years ago. Major progress. And these are basically the same computer models used to predict climate.

But forecast skill of even our new models degrades with time and by 1-2 weeks ago there is little forecast skill left. So knowing that, how can we forecast 50 years from now what will be happening with increasing greenhouse gases?

First, a fifty year climate forecast is completely different than a 2 day weather prediction. In a weather prediction we attempt to forecast the exact configuration of the atmosphere at specific times. Exactly what the temp will be at Olympia at noon, the strengths of all the highs and lows and their exact positions at 7PM Thursday, the wind conditions everywhere at exact times. Pretty challenging. And we know based on theoretical studies that our ability to do this degrades rapidly in time. But for climate predictions we don't do this. We forecast the average temp over 10 years or average precipitation for all the Marches for a decade. This is MUCH easier to do.

Second, the nature of a climate forecast is very different. For weather forecasts our predictions are dependent on the details of the initial state and small errors or differences grow during the forecast. For climate predictions averaged over decades, there is far less sensitivity to the initial state and far more dependence on the overall forcing by the sun's radiation and how the composition of the atmosphere changes its ability to absorb and transfer infrared radiation. For example, if the earth's atmosphere acts to hold in more radiation, than the planet will tend to warm. Technically, one is an initial value problem and other a boundary condition problem. We have run our climate models over the past hundred years and have been able to duplicate the climate variations over decadal time scales...providing confidence in climate forecasts.

The bottom line of all this is that useful climate predictions ARE possible even when weather prediction skill is lost in a few weeks. These climate prediction aren't and won't be perfect. But they provide great insights into what will happen over the next 50-100 years.

My next blog will deal with the other major argument used by those questioning the potential for human-induced global warming..the lack of warming over the past decade. And then I will talk about the hyping of global warming by some scientists and the media.


  1. Yea, Google Kirkland, my old stomping ground!

    When I first moved out here 20 years ago, forecasts were horrendous. They basically stuck with "a mix of sun and rain" but couldn't predict much of anything.
    I've been struck by how well they've (you've?) predicting things like the heat wave a week in advance and winter snows.
    Good job!
    Now how much snow can we expect this winter? It's ski pass presale time!

  2. Will this lecture be on-line? I know that Google does that with some of the lectures given at its offices.

  3. Cliff,

    Thanks for this post. I look forward to your next two topics.

    Paul Middents

  4. Cliff, this may not be the forum, but I'm curious to learn what progress has been made or insights gained regarding solar cycles and their influence in earth's climate cycles. If I remember correctly "Little Ice Age" weather corresponded with an absence of sunspots and corresponding statistically significant decline in solar energy output. But I also remember that that argument isn't conclusive and remains debated. If you have time, and inclination, could you address that subject in discussing climate change, please? Not being a scientist, nor commanding the data, I've no bias for or against solar cycle influence, and no bias to any conclusion regarding solar cycle offset of carbon dioxide caused warming. I'm just innately curious and a compulsive science reader who is interested in the state of knowledge on these subjects. Thanks.

  5. I've stopped using the term "Global Warming", "Global Climate Change." It seems like more people can get their heads around things not remaining the same vs everything warms.

  6. I'd like to know the role CO2 plays vs water vapor in the greenhouse effect.

    My understanding is that the total human CO2 contribution is just one part in 10,000, and that water vapor has a far more powerful effect than CO2.

  7. lapetus999, not to take anything away from Cliff, but forecast models (and some forecasters) were predicting the heat wave over a week and a half in advance, and even then, predicting that its magnitude could rival the all-time hottest on record in the Northwest. Honestly, it wasn't a difficult thing to do, because the models were really consistent about it and its magnitude nearly two weeks in advance. If you know how to read the models, then you could have forecasted it too. Heck, if the public knew how to read forecast models, which isn't difficult, they could do just as good a job, if not better, at forecasting the weather than meteorologists. They are the forecast models that have really improved and are what really make the forecasts.

  8. Weather is my Life,

    Not sure what your point is. Meteorologists like Cliff built the models that you find so useful. Climate guys work similar models and refine them to project various emission scenarios into the future.

  9. Mark,
    You can evaluate the greenhouse effects of a gas solely by its concentration. Some gases (like CO2) are extraordinarily effective at very, very small concentrations. Water vapor is also an important greenhouse fact, the most important. And unfortunately they work together in a positive feedback..more co2 caused more warming, which causes more evaporation, which causes more warming...etc. So C02 is very important...cliff mass

    PS: lecture at google should be online eventually. And Mcskudler...I will talk about the solar business later (coming is a small effect)

  10. Cliff - So if more CO2 causes more water vapor, then wouldn't that make more clouds? Doesn't water vapor equal clouds? If so, wouldn't that reduce solar heating and we'd have an inherently stable system?

    In this current post you explain why weather forecasts are conceptually different from climate predictions. In response to an earlier post I made, you said that despite the fact that CO2 has increased in the past 10 years while temps have decreased, that that is consistent with the models because there's so much noise in the data and models. So here's the question: Why do we believe the 50 year models are accurate while the 10 year ones are not and the weather forecast for next week is not applicable? At what point into the future are the climate models believed to be reliable, and what empirical evidence is available to support claims of model reliability?

  11. Great topic to cover here. Much appreciated!

  12. Mark,
    Cloud feedback is something that has and is being intensively researched...clouds act both to cool and warm, so the answer is not obvious (clouds reflect solar radiation, which cools, by is active in the infrared, which can warm). The computer models are considering cloud effects. You can't look at a ten year or shorter period..there is internal variability on those scales that obscures the global warming signal...especially when it is relatively weak like now (think of noise plus a long-term signal). There are no ten year or 50 year models as you suggest. But we are much more confident of warming on a 50-year time scale than a 10 year time scale...since greenhouse gases are rapidly increasing and we are looking at time scales greater than some of the short-term variations that obscure it. ..cliff

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  14. Lets just throw it all on black and hope for the predictions are going to be wrong..Las Vegas style thinking and logic...

  15. Thanks for the great post, Cliff.

    I like the analogy with population demographics: it's hard to predict accurately how many babies will be born next week, but we know with near certainty how many 30-year-olds there will be 20 years from now: just count the number of 10-year-olds today.

    Cliff I'd be interested in your take on the work of Scott Armstrong , at University of Pennsylvania, who studies long-term forecasting. (You can see his specific analysis of IPCC forecasts here).

  16. Cliff - I appreciate your thoughtful replies to my posts. I can be convinced, but only with bulletproof scientific data and rigorous statistical analysis.

    In your latest reply you said "we are much more confident of warming on a 50-year time scale than a 10 year time scale...".

    While you didn't drop the dreaded "F bomb"..."Faith", you did not provide any evidence of empirical data as I requested to support the claim that the models are valid.

    The science of statistics is all about separating signal from noise. Chi Squared is one of the tools available to cut through the noise to get to the signal at a given confidence level. I've spent countless hours trying to find CO2 and temp data, and to find Chi Squared analysis proving a causal effect. I can't find it. If you can provide such data and analysis, I'll trade in my carbon spewing SUV for a Prius tomorrow.

  17. Obviously, I'm a GW skeptic. I hope that doesn't make me a pariah here. I value the fact that we have the opportunity to have a polite intellectual conversation with Dr. Mass on a matter of critical importance.

    There are plenty of other places to discuss the political and economic implications of the outcome of the GW scientific debate. But please, let's not pollute this blog with all that. Let's keep this one focused on just the facts, data, rational analysis, and civil discourse.

  18. Mark,

    Have you taken a look at the 2007 report on climate change from the International Panel on Climate Change? You'll find thousands of pages of info on the science behind climate change, along with many of the facts and figures that you claim are missing from the debate.

  19. Heinlein perhaps said it best: "Climate is what we expect. Weather is what we get."

    That said, here's a metaphor for why a longer-term prediction (or less granular one) may be more accurate than a short-term one.

    It's probably a fairly good bet I'll be asleep tomorrow, in my bed at home, between 1am-4am. Given that, you can predict my location within a few feet without any problem.

    But what my exact position and posture may be within that bed, at a specific time -- 3:27a, say -- that's trickier.

    The amazing thing isn't that we can't get those final few feet accurately in our predictions (metaphorically). The amazing thing is how closely we can come given the 197 million square miles of the earth's surface.

    (I leave it as an exercise for the reader the validity of the flip side of that. I.e., when the argument is made that nothing can be changing in the 197 million square miles of earth, because one's local 400 square miles or so seems the same as it's always been.)


Please make sure your comments are civil. Name calling and personal attacks are not appropriate.

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