Climate and weather are very different things
Policy makers and the public need recognize the difference between weather and climate, the latter is the average state.
Grist.org:
Objection: Scientists can’t even predict the weather next week, so why should we believe what some climate model tells us about 100 years from now?
Answer: Climate and weather are very different things, and the level of predictability is comparably different.
Climate is defined as weather averaged over a period of time — generally around 30 years. This averaging smooths out the random and unpredictable behaviour of weather. Think of it as the difference between trying to predict the height of the fifth wave from now versus predicting the height of tomorrow’s high tide. The former is a challenge — to which your salty, wet sneakers will bear witness — but the latter is routine and reliable.
This is not to say it’s easy to predict climate changes. But seizing on meteorologists’ failures to cast doubt on a climate model’s 100-year projection is an argument of ignorance.
By The Way
Be aware that a cold winter does not mean Global Warming has been canceled. The climate may cool for a decade due to internal resonance of the climate, including factors such as the Atlantic Meridional Overturning circulation. After making that point, that article goes on to:
‘No distraction’
The projection does not come as a surprise to climate scientists, though it may to a public that has perhaps become used to the idea that the rapid temperature rises seen through the 1990s are a permanent phenomenon.
“We’ve always known that the climate varies naturally from year to year and decade to decade,” said Richard Wood from the UK’s Hadley Centre, who reviewed the new research for Nature.
“We expect man-made global warming to be superimposed on those natural variations; and this kind of research is important to make sure we don’t get distracted from the longer term changes that will happen in the climate (as a result of greenhouse gas emissions).”
Note that the warming trend exists whether or not the ocean forcing is included:
If you consider yourself a skeptic worth your salt, actually read the scientific publications, don’t just search for and select aspects to remove from context to attempt your debunking.
Yours sincerely,
Jason Box, Climatologist
April 2nd, 2009 at 4:48 pm
Dr Box, are you trying to make this easy for me? Just look at the chart that you used to justify your position. Unless my eyes are lying to me, it clearly shows temperatures continually increasing from 1970, and that this year is the warmest of all. That is absurd, just look outside. I know of no credible source that claims that today’s temperatures are above the level on 1998. Even the fudged data from NASA and NOAA don’t show current temperatures above the level of 1998. The most accurate form of temperature measurement out there, satellite, shows no net warming over the last 30 years, and rapid cooling since 1998. Your chart does however highlight just how absurd this science it, they claim to have a consensus, and yet there isn’t even a consensus on the dependent variable’s data. The conclusions are all reached upon picking and choosing your preferred chart. The other important point your bogus chart demonstrates is just how absurd these computer models are. It clearly shows that if you plug garbage in you will get garbage out. By plugging in that bogus temperature data you got a bogus predicted temperature. Facts are the computer doesn’t think, it doesn’t know you are using garbage data, and it doesn’t know it is giving garbage results. It is up to the scientists to know that Garbage In results in Garbage Out. Your chart does nothing more that highlight just how worthless computer models are, and the very fact that this was PEER REVIEWED “Research” simply stands as evidence of just how incompetent the peer review process if for this “science.” As I have said Dr Box, you will really need to up your game if you are going to play in this sand box. BTW, why don’t you install a poll on your blog so people can see who is winning the debate? My bet is that you have lost on every point you have made so far. That is the problem of having a field of nothing but yes men, you never gain a true understanding of the science.
April 3rd, 2009 at 8:42 am
“Objection: Scientists can’t even predict the weather next week, so why should we believe what some climate model tells us about 100 years from now?
Answer: Climate and weather are very different things, and the level of predictability is comparably different. ”
Weather and climate may in fact be different but the computers and statistical modeling techniques aren’t. Facts are all forecast models have huge errors in them. No computer model can tell the future. If any Climate Scientist could accurately model the climate, an infinitely complex animal, they wouldn’t be spending their time sitting on glaciers in Greenland making a professor’s salary, they would be on Wall Street making billions of dollars a DAY. All the computer power and Ivy League Grads on Wall Street can’t even tell you what the Dow Jones Industrials, an infinitely less complex animal than climate, will do next quarter. The modeling capabilities just simply don’t exist to support the claims of these climate scientists. Even if they did, they don’t have reliable and accurate data sets to model, so it is still GIGO. Bernie Madoff had a great computer model, and his model look honest to the claims made by the IPCC. The IPCC makes Bernie Madoff look honest.
The other problems with these models is that they have them reversed. They have CO2 as the independent variable and Temp as the dependent variable, when in fact, it is just the reverse. CO2 is a function of temperature, not vise versa. Temperature drives CO2, CO2 does not drive temperature. This observation is proven by Al Gore’s chart and any chemistry book that covers Henry’s Law. You can test it yourself, warm up a Coke and watch what happens, CO2 will bubble out at a rapid rate. Think of the oceans as the globes Coke. They have their model reversed. Instead of Y=mX+b they have X=mY+b. That is simply junk science. This is like claiming that lung cancer causes smoking.
Every model must also include all significant variables. If I was going to do a study on weight loss, I would need to include exercise and caloric intake in my model. The climate models don’t include water vapor and the sun in any accurate manner, and they exaggerate the influence of CO2. Once again, this is simply junk science.
April 3rd, 2009 at 9:53 am
Here is a video to make my point:
http://www.youtube.com/watch?v=ckQKCmiBZv8
April 5th, 2009 at 12:42 pm
Robert Warner’s Ten Basic Errors
Warner: “Just look at the chart that you used to justify your position. Unless my eyes are lying to me, it clearly shows temperatures continually increasing from 1970, and that this year is the warmest of all. That is absurd, just look outside. I know of no credible source that claims that today’s temperatures are above the level on 1998.”
Fact 1: Warner is confused. This chart is from an article in Nature — (“Advancing decadal-scale climate prediction in the North Atlantic sector” N. S. Keenlyside, M. Latif, J. Jungclaus, L. Kornblueh & E. Roeckner) (http://www.nature.com/nature/journal/v453/n7191/abs/nature06921.html).
The chart reflects global 10-year average temperatures. Because temperatures vary daily, weekly, monthly and yearly, it is helpful to use averages to focus on the significant data rather than on the “noise” the variations that distract us from seeing the significant trend.
Warner focuses on the fluctuation –the noise. This is probably–although I hope not– a deliberate attempt to get us to ignore the underlying trend–the significant portion of the data. It is simply dishonest — maybe he himself is simply a victim of someone else’s dishonesty. Unfortunately this is the way denialists have chosen to spin the temperature record. In general, they are able to dupe a significant portion who know who are easily misled especially those who have an conservative ideological bias against science.
Warner: “The most accurate form of temperature measurement out there, satellite, shows no net warming over the last 30 years, and rapid cooling since 1998.”
Fact 2: This is simply false. The temperature of lower troposphere has been rising at a rate of 0.155 K per decade since 1979.
Source: http://www.ssmi.com/msu/msu_data_description.html#channels
Temperatures have been increasing from 1970. This fact is supported by both the surface and satellite data.
Warner: “…Rapid cooling since 1998.”
Warning: Warner is trying to mislead the gullible. The trend is more important than the variations.
Warner then descends into Coo-Coo La-la Land.
Warner: “Your chart does however highlight just how absurd this science it [sic], they [sic] claim to have a consensus, and yet there isn’t even a consensus on the dependent variable’s data.”
Fact 3: First, the chart does not characterize a dependency relationship between two variables. It tracks only one variable over a time line. There is no suggestion that time is causing a fluctuation in temperature.
Fact 4: the authors of this paper did not refer to a consensus. Warner is probably referring to the consensus among scientists, in general, and among climate scientists, in particular, that (a) global warming is occurring and (b) that it is caused by man’s increased production of CO2 released into the atmosphere.
Warner: “The conclusions are all reached upon picking and choosing your preferred chart.”
Fact 5: Warner doesn’t tell us what “conclusions” he is referring to. I will assume the conclusions he refers to are the claims (a) that global warming is happening, and (b) that it is caused by human/industrial sourced atmospheric CO2.
These conclusions are not based on charts.
Glaciers are melting. The arctic ice is declining. Data indicate a global trend of rising temperature.
There must be a cause for this. What is the cause?–two things account for it. Part of the cause is a small increase in solar activity but the largest single factor is an increase in atmospheric CO2.
If you can come up with a better explanation — write it out and publish it–or suggest it to someone qualified to do it. You will be the next super-hero scientist.
Warner: “The other important point your bogus chart demonstrates is just how absurd these computer models are. It clearly shows that if you plug garbage in you will get garbage out.”
Fact 5: This chart does not demonstrate the absurdity of computer models. At the end of a coherent insightful analysis you might conclude that the chart is based on faulty science. But the demonstration of absurdity would be in that analysis and not in the chart itself.
Warner: “Climate and weather are very different things, and the level of predictability is comparably different.
“Weather and climate may in fact be different but the computers and statistical modeling techniques aren’t. Facts are all forecast models have huge errors in them. No computer model can tell the future.”
Fact 6: I have no idea what he means by his claim that the computers are different. Warner demonstrates a fundamental mistake in his reference to “statistical modeling techniques”. Climate models are not statistical models employing statistical modeling techniques. Climate models are physical models:
“The physics in climate models can be divided into three categories. The first includes fundamental principles such as the conservation of energy, momentum, and mass, and processes, such as those of orbital mechanics, that can be calculated from fundamental principles. The second includes physics that is well known in theory, but that in practice must be approximated due to discretization of continuous equations. Examples include the transfer of radiation through the atmosphere and the Navier-Stokes equations of fluid motion. The third category contains empirically known physics such as formulas for evaporation as a function of wind speed and humidity.”
(Source: http://www.giss.nasa.gov/research/briefs/schmidt_04/)
The failure to comprehend this distinction between physics based models and statistical models is the reason for his comment about garbage in garbage out–this meme fails to have any meaning.. Physics-based models on the other hand, try to capture the real physical cause of any relationship. Statistical models capture existing information, and if things don’t change much, they can provide reasonable predictions of future events
But things are likely to change in the future.
A physical model is intended to handle this — put garbage in (i.e., data that doesn’t fit the conditions of the past)– but the output is still an accurate prediction, The classic example is Newton’s Law of motion, F=ma. It can be used in multiple contexts to give highly accurate results completely independent of the data Newton himself had on hand.
Weather models use as much data as there is available to start off close to the current weather situation. Then, using the physics of the atmosphere, make short-term predictions. This has good skill for a few days and some skill for a little longer. Because they are run for short periods of time only, they tend to have much higher resolution and more detailed physics than climate models. Weather models leave out the influences of solar variability, greenhouse effects, and feedbacks in general. Warner: “No computer model can tell the future”.
Fact 7: Every model will have an error factor. But some models are amazingly accurate at predicting the future. Newtonian physics is one such model.
Climate models can be fairly accurate as well. I can accurately predict that the temperatures in December, in Ohio, will consistently be, on average, colder than the temperatures in August in Ohio. I cannot predict whether the temperature on any randomly chosen day will be colder than the temperature on any other randomly chosen day. This is the difference between climate and weather. Climate is, in some cases, easier to predict then weather.
Warner: “If any Climate Scientist could accurately model the climate, an infinitely complex animal, they wouldn’t be spending their time sitting on glaciers in Greenland making a professor’s salary, they would be on Wall Street making billions of dollars a DAY.”
Fact 8: This comment reflects Warner’s ignorance of the difference between intellectual domains. People who are amazingly good at landing space craft on a specific location on the surface of Mars aren’t, in general, any better than anyone else at understanding the underlying science of the stock market. The stock market and human behavior, in general, is infinitely more complex.
If a stockbroker jumps out the window from the top floor of a tall building — I can predict the rate of his fall and the result of the impact to his body. Individual and collective human behavior is much more complex than anything physics can tackle. That’s why physicists don’t try to do it.
Warner: “The modeling capabilities just simply don’t exist to support the claims of these climate scientists. Even if they did, they don’t have reliable and accurate data sets to model, so it is still GIGO [garbage in - garbage out]”
Again, climate models are not statistical models. The comment is irrelevant.
Warner: “The other problems with these models is [sic] that they have them reversed. They have CO2 as the independent variable and Temp as the dependent variable, when in fact, it is just the reverse. CO2 is a function of temperature, not vise versa. Temperature drives CO2, CO2 does not drive temperature.”
Fact 9: This is bogus. A variable can be dependent in one context and independent in another. Chickens lay eggs but they hatch from eggs as well. Temperature rise can result in added atmospheric CO2 but more atmospheric CO2 results in higher temperatures. More chickens – more eggs — more chickens. It isn’t that complicated conceptually.
Warner: The climate models don’t include water vapor and the sun in any accurate manner, and they exaggerate the influence of CO2. Once again, this is simply junk science.
Fact 10: This is patently false.
“The 1991 eruption of Mount Pinatubo provided a good laboratory for model testing (see the figure). Not only was the subsequent global cooling of about 0.5 °C accurately forecast soon after the eruption, but the radiative, water-vapor, and dynamical feedbacks included in the models were quantitatively verified.”
Source: http://www.giss.nasa.gov/research/briefs/schmidt_04/
Source: http://www.giss.nasa.gov/research/briefs/schmidt_04/
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