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Rebuttal to 'Scientist's Can't Even Predict The Weather Right'

Posted on 24 January 2011 by dansat

This claim is based more on an appeal to emotion than fact. The inference is that climate predictions, decades into the future, cannot be possibly right when the weather forecast for the next day has some uncertainty.

In spite of the claim in this myth, short term weather forecasts are highly accurate and have improved dramatically over the last three decades. However, slight errors in initial conditions make a forecast beyond two weeks nearly impossible.   

Atmospheric science students are taught "weather is what you get and climate is the weather you expect". This is why this common skeptical argument doesn't hold water. Climate models are not predicting day to day weather systems. Instead, they are predicting climate averages.

A record high is an example of weather. Increasing numbers of record highs is a symptom of a changing climate. From Meehl et. al

Figure 1: Record highs are an example of extreme weather, but an increase in record highs versus record lows is a symptom of a changing climate. From Meehl et al.* 

A change in temperature of 7º Celsius from one day to the next is barely worth noting when you are discussing weather. Seven degrees, however, make a dramatic difference when talking about climate. When the Earth's AVERAGE temperature was 7ºC cooler than the present, ice sheets a mile thick were on top of Manhattan! 

A good analogy of the difference between weather and climate is to consider a swimming pool. Imagine that the pool is being slowly filled. If someone dives in there will be waves. The waves are weather, and the average water level is the climate. A diver jumping into the pool the next day will create more waves, but the water level (aka the climate) will be higher as more water flows into the pool. 

In the atmosphere the water hose is increasing greenhouse gases. They will cause the climate to warm but we will still have changing weather (waves).  Climate scientists use models to forecast the average water level in the pool, not the waves. A good basic explanation of climate models is available in Climate Change- A Multidisciplinary Approach by William Burroughs. 

Source: AMS Policy Statement on Weather Analysis and Forecasting. Bull. Amer Met. Soc., 79, 2161-2163

*Image source: Meehl, G. A., C. Tebaldi, G. Walton, D. Easterling, and L. McDaniel (2009), Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S., Geophys. Res. Lett., 36, L23701, doi:10.1029/2009GL040736.

This blog post is the Basic Rebuttal of the skeptic argument 'Scientists can't even predict weather'. It was written by Dan Satterfield, Chief Meteorologist for WHNT TV (CBS) in Huntsville and writer of Dan's Wild, Wild Science Journal.

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Comments 51 to 59 out of 59:

  1. "I doubt the climate scientist can model the pattern of weather for the various regions of the earth for period of about 30 years, for example, from 2070 to 2100."

    No one would bother to try projecting annual variability over a thirty year period. In effect you'd be generating noise to disguise the long-term trend from yourself.
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  2. h pierce
    "they don't make predictions or projections and their climate models produce only senarios since phenomena such as clouds, aerosols and in particular black carbon are difficult to model and their effects on climate are not well undersood"

    No, they are called projections primarily because they are contingent on assumptions about forcings (e.g. anthropogenic carbon emissions), rather than becuase of the limitations of the models. That is why e.g. Hansen gave three emissions scenarios and a projection for each one of them. He didn't know how emissions would evolve, so he could only make projections for a set of scenarios rather than a prediction. Even if the model were perfect, he could still only have made projections.

    "I doubt the climate scientist can model the pattern of weather for the various regions of the earth for period of about 30 years, for example, from 2070 to 2100. "

    Of course climate modellers can *model* the pattern of weather for various regions for thirty years, the do so quite routinely. What they can't do is *predict* the pattern of weather for thirty years. But then again, they wouldn't claim that they can becuase climate projections are based on simulating weather not predicting it.
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  3. Harold Pierce (jr?)@48
    "After watching weather reports on the TV over 50 years, I have concluded that the earth's climate has not changed much at all."

    Well maybe 300 or 500 years ago, such an anecdote might be accepted as wise words.
    But in this day of science, someone watching TV and making a personal assessment doesn't really add to human knowledge or provide any evidence.
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  4. Mod at 48

    What I want to see a 30 year animation of weather maps for all regions of earth.

    All climate models are fatally flawed because the concentration of CO2 used for the calculations is only valid for purified dry air which does not occur in the earth's atmosphere. Go to Universal Industrial Gases Inc.'s website at:

    http://www.uigi.com/air.html

    and study the tables that show the effects of temperature, pressure and humidity on the properties of air. The data are for air samples that do not include clouds. Note that moist tropical air is much less dense than cold dry air. There is much less CO2 in the air than is indicated by air analysis.

    In particular the article mentions that composition of local air is site specific and this determines the type of equipment used for processing of real air.
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  5. H pierce,

    From your link: "On an annual basis, the concentration of carbon dioxide in air rises and falls in a seasonal pattern; with the span between the seasonal high and low values typically being about 6 ppmv; or about one-and-a-half percent of the average annual value."

    Hardly evidence that CO2 concentrations are much lower than anyone realizes Furthermore, we don't determine CO2 concentrations by modelling, we do it by direct measurement.
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  6. Trueofvoice
    "we do it by direct measurement."
    and the same site shows, guess what, the Mauna Loa data :)

    h pierce
    please do not presume that atmospheric scientists do not know that the air pressure varies and the amount of CO2 will vary accordingly. Didn't you notice that CO2 concentration is usually quoted in ppm rather than in Kg/m3?
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  7. h pierce The greenhouse effect is not determined by the absorption of IR radiation at the surface, but in the upper atmosphere (upper trophosphere/stratosphere), where the air is dry, pure and CO2 "well mixed". The composition of air my be site specific at the surface, but that doesn't mean it isn't homogeneous where it matters for the greenhouse effect (and therefore for the models).

    A 30 year animation of the weather around the world would be very pretty, but not very informative. Data is not the same thing as information and statistics is generally a good way of distilling information from data, which is why climatologists use statistics such as global averages or trends.
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  8. #54: "composition of local air is site specific"

    Within a given band of latitudes, CO2 concentrations are stunningly consistent as a function of longitude all the way around the globe. There's a worldwide network of atmospheric gas measurement stations; the primary variables are time of year and latitude. Even the timing and amplitude of seasonal cycles are consistent by latitude.

    The only way to see significant local variations is to measure CO2 around an urban center. You find that CO2 concentrations rise and fall with traffic volume, on both daily and weekly cycles. That's a good proof that CO2 is anthropogenic.
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    Moderator Response: A relevant post is "CO2 is not increasing."
  9. For non-technical types, I find that this explanation seems to work:

    I can predict that Alex Rodriquez will bat close to .325 next season. Now, say it's July 22nd, and the A's are coming to town. Try predicting the first pitch (type & location) A-Rod will face in today's game. Your prediction becomes more accurate as the actual situation (number of outs, men on base, etc) approaches. That's weather. The prediction for the season average is climate.

    Nine times out of ten I get the Aha! reaction.
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