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ABBOT THEORY BACKED BY MATHEMATICIANS

Observatory Men Support Idea That Sun-Radiation Affects Weather on Earth

NO WRITER ATTRIBUTED

Observatory mathematicians today brought support to the statistics by which Charles G. Abbot of the Smithsonian Institution, Washington, D. C., believes he has shown that there are important periodic changes in the sun's radiation, predictably affecting the earth's weather.

It is believed that the University statistical analysis eliminates one of the principal grounds of dispute over Dr. Abbot's findings, based on years of regular observations of solar radiation at stations scattered in different parts of the world.

Findings Called Errors

Critics have charged that the Smithsonian findings of solar periods were the results of either statistical errors in analyzing the figure tables, or of systematic errors of observation. Theodore E. Sterne, lecturer on Astrophysics, today cleared the Smithsonian charts of charges of statistical error.

Dr. Abbot found in his tables periods of 7, 8, 9, 3-4, 11, 21, 25, 34, 39 1-2, 46, and 68 months, in changes of solar radiation. Sterne finds that three of these periods may be attributable to statistical error,--those of 7 months, 8 months, and 34 months. But the remaining seven periods found by Dr. Abbot are not attributable to statistical error according to Sterne. The Harvard mathematician found that the odds against these seven periods being purely statistical error are 30,000 to 1, or higher.

Statistics Mainly

The research was confined to the statistics, and did not deal at all with questions of observational technique.

The tables in question cover the fifteen years 1920-34, giving three values each month for the intensity of solar radiation as observed in many parts of the world, and averaged. The observations are of the amount of radiation received in calories per minute per square centimeter at right angles to the sun. The overall average for the 15 year period was 1,9410 calories per square centimeter per minute or about 2 horse-power per square meter.

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