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Why Do Meteorologists Dismiss Climate Change Science?


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When I asked that question, somebody here told me that they like snow too much.

I personally think that's too pat an answer. Hell I like snow too.

My theory is that weather forecasting COMPELS you to look at the "trees" (the daily details of weather) so much that it becomes difficult to put that stuff away when thinking about larger/longer scale events. Most of the stuff we discuss on this board simply doesn't matter in a climatological context. This must be tough to take if you've been trained to think entirely in terms of daily/weekly weather patterns.

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A little bit of knowledge can be a dangerous thing. Mets know that phenomena like PDO and ENSO affect climate on yearly to decadal time periods. They know the Sun is the source of all energy driving the weather machine and that it is somewhat variable. They are generally aware of the Earth's past history of climate change as a natural occurrence. The idea that climate changes is nothing new. They have first hand knowledge in the fallibility of weather forecast models

Now to convince them that all they have learned of climate change is insufficient to hold a valid scientific opinion on AGW.

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Hi all,

I'll throw my 2 cents in. Being an operational meteorologist for the last 28 years, I have seen a lot of changes in computer models. From the most crudest to the most sophisticated, they still go off the wall at times due to chaos. This small scale chaos, combined with at times, bad initialization leads to big bust with these models, hence the skepticism of anything generated by computer models. I find it hard to believe that chaos ends in the small scale. There has to be large scale chaos that climate models have no clue on how to handle, especially the farther into the future they go. Just look at the the leveling of the past 10 years in global temperatures. I do not recall any publicly promoted climate forecasts from 20 or even 10 years ago that showed this. If there were, they were kept out of the public eye. I feel that there are many surprises down the road for climate forecasts due to large scale chaos. Just my 2 cents.

Bob

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I think most meteorologists are skeptical of the sensitivity of the climate projections...not the actual science behind doubling of CO2 which by itself increases temps around 1C (plus or minus a few tenth, but correct me if I'm wrong)....most are skeptical of the sensitivity issue that says all this extreme weather will keep happening and the temps will keep accelerating. The input into climate models is that CO2 has a much higher effect than stuff like solar...which might be true...but the number might be wrong. The models are only as good as what we input into it. I don't think it helps that the IPCC's (AR4) higher range of sensitivity is getting discarded recently in peer reviewed literature which lends to the question of how much more will they slice the sensitivity in the future.

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I think most meteorologists are skeptical of the sensitivity of the climate projections...not the actual science behind doubling of CO2 which by itself increases temps around 1C (plus or minus a few tenth, but correct me if I'm wrong)....most are skeptical of the sensitivity issue that says all this extreme weather will keep happening and the temps will keep accelerating. The input into climate models is that CO2 has a much higher effect than stuff like solar...which might be true...but the number might be wrong. The models are only as good as what we input into it. I don't think it helps that the IPCC's (AR4) higher range of sensitivity is getting discarded recently in peer reviewed literature which lends to the question of how much more will they slice the sensitivity in the future.

The higher range in sensitivity has not been discarded. I believe you are referring to a recent study which placed climate sensitivity at 2.3C. The many individual such studies have clustered in the 2C to 4.5C range. This is just another of those studies. The generally accepted single value used today is 2.7C, it could end up being higher or lower...who can say for sure?

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Hi all,

I'll throw my 2 cents in. Being an operational meteorologist for the last 28 years, I have seen a lot of changes in computer models. From the most crudest to the most sophisticated, they still go off the wall at times due to chaos. This small scale chaos, combined with at times, bad initialization leads to big bust with these models, hence the skepticism of anything generated by computer models. I find it hard to believe that chaos ends in the small scale. There has to be large scale chaos that climate models have no clue on how to handle, especially the farther into the future they go. Just look at the the leveling of the past 10 years in global temperatures. I do not recall any publicly promoted climate forecasts from 20 or even 10 years ago that showed this. If there were, they were kept out of the public eye. I feel that there are many surprises down the road for climate forecasts due to large scale chaos. Just my 2 cents.

Bob

Climate models are not starting condition reliant like weather forecast models are. Climate modeling is a boundary condition problem, where if you change a given parameter the whole system shifts to a new condition by a to be determined amount. This is not an iterative process where a mistake of input compounds and blows up the outcome.

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I have always accepted Climate Change and even accepted an anthropogenic component which years ago I commented that the temperature curve seemed to be getting out of synch with the Solar activity based upon studies then I've even posted here about how volcanic CO2 is not capable at current levels of release of having any real effect. But what troubles me is how every extreme event is leaped upon as proof one way or another. I also recall NASA in the 1990's blaming ALL of the Ozone depletion upon CFCs neglecting the minor issue of 17 million tons of SO2 blown into the upper atmosphere by Pinatubo-they later admitted that Pinatubo did have an effect on the Ozone. I also find some of the more outlandish predictions disturbing especially since they detract from the real science.

Steve

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I have always accepted Climate Change and even accepted an anthropogenic component which years ago I commented that the temperature curve seemed to be getting out of synch with the Solar activity based upon studies then I've even posted here about how volcanic CO2 is not capable at current levels of release of having any real effect. But what troubles me is how every extreme event is leaped upon as proof one way or another. I also recall NASA in the 1990's blaming ALL of the Ozone depletion upon CFCs neglecting the minor issue of 17 million tons of SO2 blown into the upper atmosphere by Pinatubo-they later admitted that Pinatubo did have an effect on the Ozone. I also find some of the more outlandish predictions disturbing especially since they detract from the real science.

Steve

I agree. The glaciers ARE melting, but why or at what rate change? We have so little data and people want to act as if data taken before the automobile was invented is accurate. Its only accurate if it suits there desired result.

It is the new shiek thing to tie every weather event to climate change. Wunderground.com head guy Dr. Masters is the biggest offender of this one. When a tree falls in the woods and nobody hears it... It still fell. Just because we now have more eyes on the ground worldwide seeing these trees fall doesnt mean the rate of trees falling is increasing.

Somebody on here tried telling me about all the global flooding taking place. Truthfully we know floods have ALWAYS happened, its just we now have people building human structures and domesticating these flood plains.

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  • 2 weeks later...

The biggest reason is that some meteorologists see weather and climate as two sides of the same coin. They think of climate as the statistics of weather. Therefore, anything that seems unreasonable in the weather-forecasting world automagically becomes unreasonable in the climate-forecasting world.

They fail to see climate and climate change as a balance of forcings, and as the transition to that balance, respectively. A quick analogy would be forecasting the mean tempearture in a closed room with a heater and window vs. forecasting the temperature fluctuations over time at a specific point somewhere between the heater and the window. The former is really only based on the balance between the total energy going out the window and the total energy being added by the heater. The latter depends on convective currents within the room, and is heavily driven by chaotic processes that can't be forecast well in the long term. But just because you can't forecast the temperature at that point 24 hours down the line doesn't mean you can't forecast the mean temperature of the closed room to a high degree of accuracy.

Obviously this is a simplification, as the climate of Earth is dependent on much more than just two forcing mechanisms... but the idea is nonetheless the same. Meteorologists have grown to become skeptical of modeled weather forecasts 7 days in advance, and some project that skepticism onto climate forecasts decades or centuries in advance. They don't realize that the factors that make weather chaotic aren't really pertinent when discussing a climate forecast.

In other words: what WeatherRusty said. :P

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The biggest reason is that some meteorologists see weather and climate as two sides of the same coin. They think of climate as the statistics of weather. Therefore, anything that seems unreasonable in the weather-forecasting world automagically becomes unreasonable in the climate-forecasting world.

They fail to see climate and climate change as a balance of forcings, and as the transition to that balance, respectively. A quick analogy would be forecasting the mean tempearture in a closed room with a heater and window vs. forecasting the temperature fluctuations over time at a specific point somewhere between the heater and the window. The former is really only based on the balance between the total energy going out the window and the total energy being added by the heater. The latter depends on convective currents within the room, and is heavily driven by chaotic processes that can't be forecast well in the long term. But just because you can't forecast the temperature at that point 24 hours down the line doesn't mean you can't forecast the mean temperature of the closed room to a high degree of accuracy.

Obviously this is a simplification, as the climate of Earth is dependent on much more than just two forcing mechanisms... but the idea is nonetheless the same. Meteorologists have grown to become skeptical of modeled weather forecasts 7 days in advance, and some project that skepticism onto climate forecasts decades or centuries in advance. They don't realize that the factors that make weather chaotic aren't really pertinent when discussing a climate forecast.

In other words: what WeatherRusty said. :P

I think that statement is completely wrong. The climate system is quite nonlinear and chaotic, there are different reasons for the chaos though which might be what you meant.

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I think that statement is completely wrong. The climate system is quite nonlinear and chaotic, there are different reasons for the chaos though which might be what you meant.

I would agree with a "nonlinear" climate system, in that feedbacks can be quite complicated. But, if you know the forcings, I don't think I agree with "chaotic". Chaos in weather means, to me, that tiny differences in initial conditions cause the system to diverge substantially in the future, all else being equal. The same cannot be said about climate. If all else is equal in the climate world and you slightly alter the initial conditions, the equilibrium down the line is still going to be pretty much the same either way. This is mainly because one looks at climate in the context of timescales much longer than those of baroclinic waves and smaller-scale eddies, which are the main sources of "chaos" in the atmosphere. So these chaotic features are smoothed out over the longer timescales.

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I would agree with a "nonlinear" climate system, in that feedbacks can be quite complicated. But, if you know the forcings, I don't think I agree with "chaotic". Chaos in weather means, to me, that tiny differences in initial conditions cause the system to diverge substantially in the future, all else being equal. The same cannot be said about climate. If all else is equal in the climate world and you slightly alter the initial conditions, the equilibrium down the line is still going to be pretty much the same either way. This is mainly because one looks at climate in the context of timescales much longer than those of baroclinic waves and smaller-scale eddies, which are the main sources of "chaos" in the atmosphere. So these chaotic features are smoothed out over the longer timescales.

This isn't true, though I wish it was. Clouds, biological life, the thermohaline circulation, ice and snow cover, man, and climate scale weather phenomena like ENSO interact in nonlinear ways. If you change one of those things (such as carbon dioxide emissions), the result will be a nonlinear interaction between all of those things.

Alot of AMS papers talk about such climate nonlinearity.

http://journals.amet...AT%3E2.0.CO%3B2

http://journals.amet...TS%3E2.0.CO%3B2

http://journals.amet...AW%3E2.0.CO%3B2

http://journals.amet...SC%3E2.0.CO%3B2

There's alot more to be found with the AMS search http://journals.amet...action/doSearch

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You are right in saying that the things that drive weather chaos, inherent in the advective term of the navier-stokes equations and some other things, don't apply in the same way to the climate scale. Some meteorologists who don't believe in climate change are wrong since they try to apply that chaos. Not being able to make a forecast past 7 days has little to do with climate change forecasting, like you're saying.

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This isn't true, though I wish it was. Clouds, biological life, the thermohaline circulation, ice and snow cover, man, and climate scale weather phenomena like ENSO interact in nonlinear ways. If you change one of those things (such as carbon dioxide emissions), the result will be a nonlinear interaction between all of those things.

Alot of AMS papers talk about such climate nonlinearity.

http://journals.amet...AT%3E2.0.CO%3B2

http://journals.amet...TS%3E2.0.CO%3B2

http://journals.amet...AW%3E2.0.CO%3B2

http://journals.amet...SC%3E2.0.CO%3B2

There's alot more to be found with the AMS search http://journals.amet...action/doSearch

Ya, like I said, nonlinearity exists. But I wouldn't consider completely adding/removing the effects of carbon dioxide, for example, as "slightly altering the initial conditions". :P

If you change the initial forcing of CO2 by 0.05 W/m^2, that would be slightly altering the initial conditions, IMO. That would have basically no impact on the climate down the line. However, if you change the 500mb height by 0.5 m over an area the size of New England, that's also "slightly altering the initial conditions", however, a forecast on a weather model with that difference would diverge significantly over time.

You are right in saying that the things that drive weather chaos, inherent in the advective term of the navier-stokes equations and some other things, don't apply in the same way to the climate scale. Some meteorologists who don't believe in climate change are wrong since they try to apply that chaos. Not being able to make a forecast past 7 days has little to do with climate change forecasting, like you're saying.

Ya, this is what I was saying. :)

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Ya, like I said, nonlinearity exists. But I wouldn't consider completely adding/removing the effects of carbon dioxide, for example, as "slightly altering the initial conditions". :P

If you change the initial forcing of CO2 by 0.05 W/m^2, that would be slightly altering the initial conditions, IMO. That would have basically no impact on the climate down the line. However, if you change the 500mb height by 0.5 m over an area the size of New England, that's also "slightly altering the initial conditions", however, a forecast on a weather model with that difference would diverge significantly over time.

Ya, this is what I was saying. :)

Chaos doesn't just apply to slight perturbations though, it can also apply to a situation where you change one thing in the system significantly and the results are unpredictable to an extent due to all the feedbacks.

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Chaos doesn't just apply to slight perturbations though, it can also apply to a situation where you change one thing in the system significantly and the results are unpredictable to an extent due to all the feedbacks.

Well I guess it kinda depends on your definition of "chaos", then. But you pretty much hit what I was getting at, anyway, so it's pretty much just semantics. For sure there are some things in the climate system that make it quite complex and difficult to predict with a high degree of accuracy. But it's not an inherent principle of the science, like it is for forecasting weather, that there is a fundamental limit to the predictability.

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Well I guess it kinda depends on your definition of "chaos", then. But you pretty much hit what I was getting at, anyway, so it's pretty much just semantics. For sure there are some things in the climate system that make it quite complex and difficult to predict with a high degree of accuracy. But it's not an inherent principle of the science, like it is for forecasting weather, that there is a fundamental limit to the predictability.

Might I add that a "slight perturbation" is an arbitrary quantification.....some would say that the human contribution of CO2 is "slight" or tiny compared to the total composition, while others would claim that a doubling is not slight.....

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Might I add that a "slight perturbation" is an arbitrary quantification.....some would say that the human contribution of CO2 is "slight" or tiny compared to the total composition, while others would claim that a doubling is not slight.....

No doubt. It's a semantics game, but I think my point was clear nonetheless. :P

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If the Sun were to increase it's radiative output at all wavelengths so that 1% more energy were received at Earth, this would be the equivalent of doubling CO2. In both cases a forcing of about 3.7W/m^2 would warm the Earth's surface. I don't thing anyone would doubt that if the Sun were to brighten like that, that the temperature on Earth would rise by at least 1.2C. Somehow it won't happen if CO2 produces the same forcing?

It's the chaos of feedbacks you say? Well, study of climate sensitivity, past and present, indicates a range between 2C and 4.5C in the positive direction. There's the uncertainty due to chaos. No?

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The "chaos of feedbacks" reminds me of George Gamow's line about the chances that all of the air molecules might gather in the far corner of the room you are in, thereby asphyxiating you.

There IS a finite chance of that, just as there is a chance of AGW being a crock.

We don't NEED to predict each of the molecular paths of each air molecule to know that the first of these propositions is HIGHLY unlikely - to the point that it can be ignored. The second one is not quite as unlikely, but it is getting there. It should be ignored, especially when planning policy.

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If the Sun were to increase it's radiative output at all wavelengths so that 1% more energy were received at Earth, this would be the equivalent of doubling CO2. In both cases a forcing of about 3.7W/m^2 would warm the Earth's surface. I don't thing anyone would doubt that if the Sun were to brighten like that, that the temperature on Earth would rise by at least 1.2C. Somehow it won't happen if CO2 produces the same forcing?

It's the chaos of feedbacks you say? Well, study of climate sensitivity, past and present, indicates a range between 2C and 4.5C in the positive direction. There's the uncertainty due to chaos. No?

That's pretty much unrelated to chaos feedbacks. It's not easily quantifiable.

The "chaos of feedbacks" reminds me of George Gamow's line about the chances that all of the air molecules might gather in the far corner of the room you are in, thereby asphyxiating you.

There IS a finite chance of that, just as there is a chance of AGW being a crock.

We don't NEED to predict each of the molecular paths of each air molecule to know that the first of these propositions is HIGHLY unlikely - to the point that it can be ignored. The second one is not quite as unlikely, but it is getting there. It should be ignored, especially when planning policy.

That's not chaos.

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That's pretty much unrelated to chaos feedbacks. It's not easily quantifiable.

That's not chaos.

This is interesting. How is what I said about climate sensitivity unrelated to chaos feedbacks?

If not in the feedbacks, then where does chaos enter the picture?

BTW, the climate sensitivity I speak of IS unrelated to chaos, but you are the one claiming chaos renders climate change fundamentally unpredictable due to chaos. Climate sensitivity is given as an equilibrium value, that is after all the churning of chaotic behavior settles down to a new stable state.

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This is interesting. How is what I said about climate sensitivity unrelated to chaos feedbacks?

If not in the feedbacks, then where does chaos enter the picture?

BTW, the climate sensitivity I speak of IS unrelated to chaos, but you are the one claiming chaos renders climate change fundamentally unpredictable due to chaos. Climate sensitivity is given as an equilibrium value, that is after all the churning of chaotic behavior settles down to a new stable state.

A simple way to think of chaos is many nonlinear terms feeding back on each other, so if you change one thing the result is something you can't predict to an extent.

Climate sensitivity is merely approximating the result of changing one thing in the system, and is derived directly out of an already incorrect climate model. Climate models have no nonlinear terms, period. Nonlinear terms are intractable for numerical models. So it's a very weak first approximation of climate chaos, and I'm sure no one who makes such estimates claims that climate sensitivity values bound true chaos in any way.

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A simple way to think of chaos is many nonlinear terms feeding back on each other, so if you change one thing the result is something you can't predict to an extent.

Climate sensitivity is merely approximating the result of changing one thing in the system, and is derived directly out of an already incorrect climate model. Climate models have no nonlinear terms, period. Nonlinear terms are intractable for numerical models. So it's a very weak first approximation of climate chaos, and I'm sure no one who makes such estimates claims that climate sensitivity values bound true chaos in any way.

Are you certain of that?

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Having done a fair amount of fortran programming in my time, I find that to verge on the silly.

Are you trying to say that a polynomial equation would not be used in a climate simulation model?

Have you ever done any scientific programming?

Polynomial approximations are still approximations. Also, imagine numerical modeling of the climate, it takes incredible amounts of time to run a real climate model due to the time of integration and the spatial resolution. Climate scientists and meteorologists can only afford to make simple approximations, approximating a term more than a few times isn't feasible.

And yes, I've done scientific programming and am studying it. My job is working with numerical simulations of hurricanes.

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Polynomial approximations are still approximations. Also, imagine numerical modeling of the climate, it takes incredible amounts of time to run a real climate model due to the time of integration and the spatial resolution. Climate scientists and meteorologists can only afford to make simple approximations, approximating a term more than a few times isn't feasible.

And yes, I've done scientific programming and am studying it. My job is working with numerical simulations of hurricanes.

Who does numerical simulations of hurricanes using student programmers?

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