Is coverage a factor in non-Gaussianity of IMF parameters?

Details Is coverage a factor in non-Gaussianity of IMF parameters? Is coverage a factor in non-Gaussianity of IMF parameters?

Jun 1995

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995sowi.confr..89a&link_type=abstract

New Mexico Univ., International Solar Wind 8 Conference, p. 89

Statistics

Interplanetary Magnetic Fields, Astronomical Observatories, Magnetic Field Reconnection, Distribution Moments, Variance (Statistics), Correlation Coefficients, Kurtosis, Mean, Normal Density Functions, Skewness

Scientific paper

Recently, Feynman and Ruzmaikin (1994) showed that IMF parameters for the 1973 to 1990 period are not log-normally distributed as previously suggested by Burlaga and King (1979) for the data obtained over a shorter time period (1963-75). They studied the first four moments, namely: mean, variance, skewness, and kurtosis. For a Gaussian distribution, moments higher than the variance should vanish. In particular, Feynman and Ruzmaikin obtained very high values of kurtosis during some periods of their analysis. We note that the coverage for IMF parameters is very uneven for the period analyzed by them, ranging from less than 40% to greater than 80%. So a question arises as to whether the amount of coverage is a factor in their analysis. We decided to test this for the Bz component of IMF, since it is an effective geoactive parameter for short term disturbances. Like them, we used 1-hour averaged data available on the Omnitape. We studied the scatter plots of the annual mean values of Bz(nT) and its kurtosis versus the percent coverage for the year. We obtain a correlation coefficient of 0.48 and 0.42 respectively for the 1973-90 period. The probability for a chance occurrence of these correlation coefficients for 18 pair of points is less than 8%. As a rough measure of skewness, we determined the percent asymmetry between the areas of the histograms representing the distributions of the positive and the negative values of Bz and studied its correlation with the coverage for the year. This analysis yields a correlation coefficient of 0.41 When we extended the analysis for the whole period for which IMF data are available (1963-93) the corresponding correlation coefficients are 0.59, 0.14, and 0.42. Our findings will be presented and discussed

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