Analysis of regression methods for solar activity forecastingThe paper deals with the potential use of the most recent solar data to project trends in the next few years. Assuming that a mode of solar influence on weather can be identified, advantageous use of that knowledge presumably depends on estimating future solar activity. A frequently used technique for solar cycle predictions is a linear regression procedure along the lines formulated by McNish and Lincoln (1949). The paper presents a sensitivity analysis of the behavior of such regression methods relative to the following aspects: cycle minimum, time into cycle, composition of historical data base, and unnormalized vs. normalized solar cycle data. Comparative solar cycle forecasts for several past cycles are presented as to these aspects of the input data. Implications for the current cycle, No. 21, are also given.
Document ID
19800031947
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Lundquist, C. A. (NASA Marshall Space Flight Center Huntsville, AL, United States)
Vaughan, W. W. (NASA Marshall Space Flight Center Space Sciences Laboratory, Huntsville, Ala., United States)
Date Acquired
August 10, 2013
Publication Date
January 1, 1979
Subject Category
Solar Physics
Meeting Information
Meeting: Solar-terrestrial influences on weather and climate