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No Improvement of Climate Models

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Climate models are being run on ever faster supercomputers, but they don't seem to be getting any better.

Most people are interested in one output of climate models, which are predictions of average global temperatures. But models also have results for several other critical variables such as precipitation and regional or local temperatures. It is these latter things that require the spacial information that costs so much in computer time to determine.

Annual anomalies in global temperatures don't require this spacial information to compute. If all that one is interested in is the change in global temperatures from year to year, then the spacial information cancels out and need not be computed.

The temperature turns out to vary with an arithmetic combination of forcings from various factors such as greenhouse gasses, aerosols, albedo from snow and ice, and so on. A lag factor has to be included.

Ironically, it is global temperature that the models tend to agree on. They agree on nothing else.

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Wide variation.

The response patterns of clouds and precipitation to warming vary dramatically depending on the climate model, even in the simplest model configuration. Shown are changes in the radiative effects of clouds and in precipitation accompanying a uniform warming (4C) predicted by four models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) for a water planet with prescribed surface temperatures.
Variation in local climate or climate by latitude and longitude, precipitation, and so on, is all over the park. In short, the part of the model that requires the supercomputer time isn't working yet as none of the models are in agreement. Agreement of the models with real world data for specific locations is very bad.

The latest iteration of the IPCC's report includes the latest models, and they appear to be very little different from previous models in terms of output in spite of the increasing divergence from real world data of these models. (The models are no better and perhaps can't get any better, but we should still base policy decisions on them, say these investigators in an amusing bit of dicta.)

Other investigators are recommending that the whole general circulation model concept be dumped and climate science return to the drawing board to examine other alternatives. (See first link above.)
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  1. longview's Avatar
    It must be difficult to model something, when the interaction of the variables
    is unknown. The forcing described is so loosely defined that it cannot be tested.
    So far the models show a linear positive feedback to increased Co2,
    The observed data appears to show a looser correlation.


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