The great failure of the climate models

[zachroidott]

Again. Using data from a computer model to support a conclusion reached by another computer model has no credibility.

Do you not understand computation? Everything is a computer model based on another computer model, including your life.

[Chris]

If How do climate models work? is correct, a model can be described as follows:

...A global climate model typically contains enough computer code to fill 18,000 pages of printed text; it will have taken hundreds of scientists many years to build and improve; and it can require a supercomputer the size of a tennis court to run.

...For example, scientists want climate models to abide by fundamental physical principles, such as the first law of thermodynamics (also known as the law of conservation of energy), which states that in a closed system, energy cannot be lost or created, only changed from one form to another.

...However, this set of partial differential equations is so complex that there is no known exact solution to them (except in a few simple cases).

...The code in global climate models is typically written in the programming language Fortran. Developed by IBM in the 1950s...

...Because of the complexity of the climate system and limitation of computing power, a model cannot possibly calculate all of these processes for every cubic metre of the climate system. Instead, a climate model divides up the Earth into a series of boxes or “grid cells”. A global model can have dozens of layers across the height and depth of the atmosphere and oceans.

...For processes that happen on scales that are smaller than the grid cell, such as convection, the model uses “parameterisations” to fill in these gaps. These are essentially approximations that simplify each process and allow them to be included in the model.

...A similar compromise has to be made for the “time step” of how often a model calculates the state of the climate system. In the real world, time is continuous, yet a model needs to chop time up into bite-sized chunks to make the calculations manageable.

There's much more in the article, of course, but I just wanted to highlight some of the reasons climate models are inexact. Anyone who's ever written code knows how buggy any system is. Anyone who understands how science must abstract and assume and exclude, knows how far from the real world you can get.

[Admiral Ackbar]

If How do climate models work? is correct, a model can be described as follows:



There's much more in the article, of course, but I just wanted to highlight some of the reasons climate models are inexact. Anyone who's ever written code knows how buggy any system is. Anyone who understands how science must abstract and assume and exclude, knows how far from the real world you can get.

These climate models are wrong because people with biases write the code. Take for example the Hurricane Models. Guess what as of a day ago they were all going to hit Florida direct. A few hours later they all say it will turn up the coast.

Bottom line they don't know


It is also like a "decision based" video game. The results of your decision depends on how the person that created the game thinks.. not you...

[Chris]

These climate models are wrong because people with biases write the code. Take for example the Hurricane Models. Guess what as of a day ago they were all going to hit Florida direct. A few hours later they all say it will turn up the coast.

Bottom line they don't know


It is also like a "decision based" video game. The results of your decision depends on how the person that created the game thinks.. not you...

Huurricanes, heck, they can't even model clounds and clouds are important in climate change: NASA: We Can’t Model Clouds, So Climate Models Are 100 Times Less Accurate Than Needed For Projections.

[mamooth]

Since the models have been so accurate, all of these political conspiracy theories about models have been conclusively shot down by reality.

That would stop any non-cultists from repeating such nonsense, but it obviously doesn't stop deniers. Results don't matter to them; ideology is all that matters to them.

[Hoosier8]

Since the models have been so accurate, all of these political conspiracy theories about models have been conclusively shot down by reality.

That would stop any non-cultists from repeating such nonsense, but it obviously doesn't stop deniers. Results don't matter to them; ideology is all that matters to them.

Accurate as in running too hot?

[skepticalmike]

Huurricanes, heck, they can't even model clounds and clouds are important in climate change: NASA: We Can’t Model Clouds, So Climate Models Are 100 Times Less Accurate Than Needed For Projections.

Correction: The NASA GISS site states that climate models must be improved by a factor of 10 not 100. I interpret these comments to mean that the climate models must be able to determine the
radiation balance at the surface to within an accuracy of +/- 0.5%. I assume the confidence level to be 95%. This is one person's opinion at NASA.
www.giss.nasa.gov/research/briefs/rossow_01/coml
"Unfortunately, that margin of error is too large for making a reliable forecast about global warming. A doubling in atmospheric carbon dioxide (CO2), predicted to take place in the next 50 to 100 years, is expected to change the radiation balance at the surface by only about 2 percent. Yet according to current climate models, even such a small change could raise global temperatures between 2-5°C (4-9°F), with potentially dramatic consequences. If a 2 percent change makes that much difference, a climate model must be accurate to within at least half a percent to be useful. Thus today's models must be improved more than tenfold in accuracy, requiring much more and much better data for developing a better understanding of clouds."

Even though there is considerable uncertainty in the modelling of clouds, the IPPC AR5 report concludes that it is likely that the feedback is positive. A positive feedback for clouds means that the climate sensitivity is likely
high rather than low. The fact that models aren't highly accurate is no reason to not worry about climate change.

(from IPCC AR5)

Several cloud feedback mechanisms now appear consistently in GCMs,summarized in Figure 7.11, most supported by other lines of evidence.Nearly all act in a positive direction. First, high clouds are expectedto rise in altitude and thereby exert a stronger greenhouse effect inwarmer climates. This altitude feedback mechanism is well understood,has theoretical and observational support, occurs consistently in GCMsand CRMs and explains about half of the mean positive cloud feedbackin GCMs. Second, middle and high-level cloud cover tends to decreasein warmer climates even within the ITCZ, although the feedback effectof this is ambiguous and it cannot yet be tested observationally. Third,observations and most models suggest storm tracks shift poleward ina warmer climate, drying the subtropics and moistening the high latitudes, which causes further positive feedback via a net shift of cloudcover to latitudes that receive less sunshine. Finally, most GCMs also
predict that low cloud amount decreases, especially in the subtropics,another source of positive feedback though one that differs significantly among models and lacks a well-accepted theoretical basis. Overmiddle and high latitudes, GCMs suggest warming-induced transitionsfrom ice to water clouds may cause clouds to become more opaque,but this appears to have a small systematic net radiative effect inmodels, possibly because it is offset by cloud altitude changes."

Based on the preceding synthesis of cloud behaviour, the net radiative feedback due to all cloud types is judged likely to be positive. Thisis reasoned probabilistically as follows. First, because evidence fromobservations and process models is mixed as to whether GCM cloudfeedback is too strong or too weak overall, and because the positivefeedback found in GCMs comes mostly from mechanisms now supported by other lines of evidence, the central (most likely) estimate ofthe total cloud feedback is taken as the mean from GCMs (+0.6 W m–2°C–1). Second, because there is no accepted basis to discredit individualGCMs a priori, the probability distribution of the true feedback cannotbe any narrower than the distribution of GCM results. Third, since feedback mechanisms are probably missing from GCMs and some CRMssuggest the feedback must be broader than its spread in GCMs. We estimatea probability distribution for this feedback by doubling the spreadabout the mean of all model values in Figure 7.10 (in effect assumingan additional uncertainty about 1.7 times as large as that encapsulated in the GCM range, added to it in quadrature). This yields a 90%(very likely) range of −0.2 to +2.0 W m–2 °C–1, with a 17% probabilityof a negative feedback.

[Peter1469]

Since the models have been so accurate, all of these political conspiracy theories about models have been conclusively shot down by reality.

That would stop any non-cultists from repeating such nonsense, but it obviously doesn't stop deniers. Results don't matter to them; ideology is all that matters to them.

You cannot just make stuff up and expect to be believed. Dooms day has be predicted often yet it has never arrived.

[Peter1469]

Why do the warmists refuse to answer the political and economic question?

That is why their ideas are not enacted in law.

[Chris]

Correction: The NASA GISS site states that climate models must be improved by a factor of 10 not 100. I interpret these comments to mean that the climate models must be able to determine the
radiation balance at the surface to within an accuracy of +/- 0.5%. I assume the confidence level to be 95%. This is one person's opinion at NASA.
www.giss.nasa.gov/research/briefs/rossow_01/coml
"Unfortunately, that margin of error is too large for making a reliable forecast about global warming. A doubling in atmospheric carbon dioxide (CO2), predicted to take place in the next 50 to 100 years, is expected to change the radiation balance at the surface by only about 2 percent. Yet according to current climate models, even such a small change could raise global temperatures between 2-5°C (4-9°F), with potentially dramatic consequences. If a 2 percent change makes that much difference, a climate model must be accurate to within at least half a percent to be useful. Thus today's models must be improved more than tenfold in accuracy, requiring much more and much better data for developing a better understanding of clouds."

Even though there is considerable uncertainty in the modelling of clouds, the IPPC AR5 report concludes that it is likely that the feedback is positive. A positive feedback for clouds means that the climate sensitivity is likely
high rather than low. The fact that models aren't highly accurate is no reason to not worry about climate change.

(from IPCC AR5)

Several cloud feedback mechanisms now appear consistently in GCMs,summarized in Figure 7.11, most supported by other lines of evidence.Nearly all act in a positive direction. First, high clouds are expectedto rise in altitude and thereby exert a stronger greenhouse effect inwarmer climates. This altitude feedback mechanism is well understood,has theoretical and observational support, occurs consistently in GCMsand CRMs and explains about half of the mean positive cloud feedbackin GCMs. Second, middle and high-level cloud cover tends to decreasein warmer climates even within the ITCZ, although the feedback effectof this is ambiguous and it cannot yet be tested observationally. Third,observations and most models suggest storm tracks shift poleward ina warmer climate, drying the subtropics and moistening the high latitudes, which causes further positive feedback via a net shift of cloudcover to latitudes that receive less sunshine. Finally, most GCMs also
predict that low cloud amount decreases, especially in the subtropics,another source of positive feedback though one that differs significantly among models and lacks a well-accepted theoretical basis. Overmiddle and high latitudes, GCMs suggest warming-induced transitionsfrom ice to water clouds may cause clouds to become more opaque,but this appears to have a small systematic net radiative effect inmodels, possibly because it is offset by cloud altitude changes."

Based on the preceding synthesis of cloud behaviour, the net radiative feedback due to all cloud types is judged likely to be positive. Thisis reasoned probabilistically as follows. First, because evidence fromobservations and process models is mixed as to whether GCM cloudfeedback is too strong or too weak overall, and because the positivefeedback found in GCMs comes mostly from mechanisms now supported by other lines of evidence, the central (most likely) estimate ofthe total cloud feedback is taken as the mean from GCMs (+0.6 W m–2°C–1). Second, because there is no accepted basis to discredit individualGCMs a priori, the probability distribution of the true feedback cannotbe any narrower than the distribution of GCM results. Third, since feedback mechanisms are probably missing from GCMs and some CRMssuggest the feedback must be broader than its spread in GCMs. We estimatea probability distribution for this feedback by doubling the spreadabout the mean of all model values in Figure 7.10 (in effect assumingan additional uncertainty about 1.7 times as large as that encapsulated in the GCM range, added to it in quadrature). This yields a 90%(very likely) range of −0.2 to +2.0 W m–2 °C–1, with a 17% probabilityof a negative feedback.

Be it 10 or 100 times inaccurate, "NASA has conceded that climate models lack the precision required to make climate projections due to the inability to accurately model clouds."