Climate change: models and their limitations

• First, assumptions are made about unresolved processes by using tuned parameters.
   
• Second, errors may be exaggerated by:

using the computational outputs as new “data” by reintroducing that “data” as inputs into a new model, upon which new projections are predicted;

and it assumes not only that a close spread within an essemble raises the confidence of the prediction but also that a broad spread, rather than disproving the accuracy or otherwise of the models, indicates a range of possibilities, though with a lower (assumed) confidence.

• Third, multi-model SRES outputs are based on so many assumptions that its use is inherently unscientific because many of the model elements are not falsifible. It is, nonetheless, a good tool for advocacy though, especially when presented in the guise of science.

This SRES approach has no place in the scientific processes as its outputs can not be verified with real world data: projections are not records and models are not data generators. As yet there is no scientific principle that says that one can derive valid estimates from model outputs until the model output resembles the observed non-modelled data. The uncertainty of an essemble of climate change projections will always depend on the accuracy of the raw data input irrespective of the spread of projections.

This is not to say that there is no place for models in climate science: even though they are a tool and not data generators there are there are many examples of statistical climate forecasting models providing good projection examples over short time frames. It is important that models, in this context, remain a tool of climate science and not a tool of advocacy.

Many mainstream media science, economic and environmental journalists are not sufficiently trained to be aware of models’ limitations when they present climate-modelled output computated projections not only as data but also advocate this output as supposed proof of the threat posed by anthropogenic global warming, particularly with regard to runaway or catastrophic climate change.

This disjunct between scientific and the media presentation, when contained within the paradigm of advocacy, represents a threat to the integrity and falsifibility of science.

Science seeks the truth in knowledge; (some) media advocacy seeks to propagandise this knowledge. The impact is reinforced if a climate scientist/modeller is directly quoted as an expert, further blurring the line between science and advocacy. This has societal repercussions as the science of AGW and the perceived impact of runaway or catastrophic climate change is so model-dependent that the citizenry is not always able to differentiate between the science and advocacy - the implications of which, as regards policy development in term of climate change mitigation, are likely to have a profound affect on society.

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