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Here comes the


ediocre chemist though I am, one of my earliest heart-stopping scientifi c epiphanies came with introduction to an equation

summarising photosynthesis of water and carbon dioxide into sugars. It was so beautiful in its economical depiction of life’s dependence on our neighbourhood star. The sun is, both literally and fi guratively, the centre of almost everything we are and do: there is little, if anything, in our world or our view beyond, which is not affected by it in some way. Though small on many astronomical scales (Cristiano Sabiu, in relation to work NGS hosted work on galactic distribution, comments[1]

that he

treats ‘billions of stars... as a point source mass’), from a terrestrial viewpoint it dwarfs and dominates everything else in its immediate eight cubic parsec vicinity. Little wonder, then, that science has

always studied its idiosyncrasies and mood swings, its large gestures and its microscopic effects, its long-term behaviour and short-term tantrums. With the arrival of scientifi c computing, that study has become ever more comprehensive and precise but it will, at least for the foreseeable future, be a statistically-driven enterprise.



The application of statistical software is aiding of understanding of solar phenomena, as Felix Grant discovers

Although the software used for solar

physics modelling tends to be purpose written, a great deal of experimental and observational data analysis is done in off-the-shelf high-end desktop statistics packages. R, Systat and Statistica, for instance, crop up regularly in methodology sections of the literature. At the centre of data analytic solar study,

the centre of mass about which all else orbits, is the Standard Solar Model (see box, below). Observed data, theoretical

The Standard Solar Model

The Standard Solar Model (SSM) is a specifi c instance of the more general spherically symmetric quasi-static stellar mathematical model. The stellar model, derived from basic principles, is given a mass and elemental composition equivalent to that of the sun, then aged from year zero to the present (or other required stage).

The results are compared to actual

observations, and discrepancies ironed out by iterative refi nement. As understanding grows, the model becomes progressively closer to reality. Comparison of theoretical insights with the model serves as a way to test and develop both.

hypotheses and the model form a triangular comparison system by which all three can be tested and refi ned, and like everything else this has a fundamentally statistical nature. The distribution of elements presenting the protista from which our sun developed, for example, is estimated from that observed in primordial meteorites; the clean precise models do not precisely match physical processes; there are numerous assumptions involved. A high-profi le focus of solar study

over recent decades has been the concern over climate change, with investigation of causes requiring information on the extent to which changes in the sun itself may be contributing to the warming process. Reliable retrospective study requires indirect generation of data which was not gathered at the time (such as solar luminosity: see Up, up and away) from that in other sources. If this sort of enterprise is to be useful, sophisticated statistical analysis based monitoring and cross-checking are essential. Shifting perspective from parochial

to cosmological, the sun (as the only star available for close, detailed, high-resolution study) is used by analogy as the basis for study of other stars, particularly cool stars that it resembles it although ‘it is not yet well

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