Saturday, 15 March 2008

I got pointed to World Climate Report from Denis Dutton's Climate Debate Daily, where three recent articles caught my eye:

1 comment:

  1. Sadly, Mr. Green and Mr. Armstrong found no evidence the IPCC was even aware of the vast literature on scientific forecasting methods, much less applied the principles.

    The IPCC and its defenders often argue that critics who are not climate scientists are unqualified to judge the validity of their work. However, climate predictions rely on methods, data and evidence from other fields of expertise, including statistical analysis and forecasting. Thus, the work of the IPCC is open to analysis and criticism from other disciplines.

    Amen to that.

    How many warmists (hey, even non-climate scientists who lurks around here), do understand that the term forecast means different things to different people? Even the majority of climate scientists themselves are not expertise in this field. They are expertise in data collecting (digging up ice cores, analysing tree rings & rocks, etc, etc,...), but at the end of any data-collection process, it has to use a numerical model (algorithms) to confirm its hypothesis.

    This is the heart of the debate. Do you follow the algorithm blindly? It is irrelevant whether someone is a climate scientist or not. You can follow techniques of how to collect data easily, even an accountant can do that. The crunch of the analysis and much of the debate, is when one applies an algorithm or technique to the data to confirm his hypothesis. In the vast number of literatures in the field of numerical analysis (mathematical modeling), there is no such thing as a final solution. There is always a modification or a new discovery that is more generalize than others, where the old models are just been discarded since they don't account for a lot of things.

    Dr. Jim Salinger can say, 'Oh, but Falafulu is not a climate scientist, where he can't say things like that because it is wrong'. That's correct, but at the end of any data collection process, be it economic, nuclear physics, chemical kinetics, population dynamics, atmospheric physics, blah, blah, blah,..., one must use numerical modeling to confirm the hypothesis, so specialist skills in being a climate scientists is irrelevant. All you need is a good understanding of numerical modeling to be able to understand any possible shortfall in the model.

    This is the point that I have highlighted in the quote that I made above from the article linked to by PC, is that most IPCC defenders put forward the argument that some critiques are not climate scientists therefore their opinions are invalid. But you have to ask the question, how many of those defenders do read the regular issues of INTERNATIONAL JOURNAL OF FORECASTING or Journal of Forecasting and many related journals in the field?

    I bet any reader on this blog, that even NIWA scientists (Jim Salinger, et al) don't read those literatures? Any one wants to make a bet? So, it means that even he (Jim) is knowledgeable in climate science, it doesn't mean that he is an expert on forecasting. These are completely 2 different things. This is where warmists got it wrong. They equate not being a climate scientist as an unqualified nutter, and this is where they get it wrong. All you need to have if you want to be well verse in climate science is a capability to understand numerical modeling, that's it. You don't need a prior knowledge of detail climate principles, because if you know modeling, then anything easier than that (such as descriptive climate process), can be acquired in a fairly short period of time.

    Based on following arguments and counter-arguments about AGW, IMO, I am not convinced (although I am not a climate scientist), since I agree with the authors of the article that PC linked to, that most climate scientists are not aware of recent publications in the literatures about new algorithms & techniques that have shown to be more robust than existing or old ones that are the favorites for analysis by climate scientists.

    We all know when one get stuck to old methods, is that he/she tends to believe in conclusions that have been entirely dismissed by new methods, which he/she was unaware of their existence.


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