ADDRESSING SOLAR MODULATION AND LONG-TERM UNCERTAINTIES IN SCALING SECONDARY COSMIC RAYS FOR IN SITU COSMOGENIC NUCLIDE APPLICATIONS - Lifton N.A.; Bieber J.W.; Clem J.M.; Evenson P.; Pyle R.; Duldig M.L.; Humble J.E. (My University, 2005)
Solar modulation affects the secondary cosmic rays responsible for in situ cosmogenic nuclide (CN) production the most at the high geomagnetic latitudes to which CN production rates are traditionally referenced. While this has long been recognized (e.g., D. Lal, B. Peters, Cosmic ray produced radioactivity on the Earth, in: K. Sitte (Ed.), Handbuch Der Physik XLVI/2, Springer-Verlag, Berlin, 1967, pp. 551–612 and D. Lal, Theoretically expected variations in the terrestrial cosmic ray production rates of isotopes, in: G.C. Castagnoli (Ed.), Proceedings of the Enrico Fermi International School of Physics 95, Italian Physical Society, Varenna 1988, pp. 216–233), these variations can lead to potentially significant scaling model uncertainties that have not been addressed in detail. These uncertainties include the long-term (millennial-scale) average solar modulation level to which secondary cosmic rays should be referenced, and short-term fluctuations in cosmic ray intensity measurements used to derive published secondary cosmic ray scaling models. We have developed new scaling models for spallogenic nucleons, slow-muon capture and fast-muon interactions that specifically address these uncertainties. Our spallogenic nucleon scaling model, which includes data from portions of 5 solar cycles, explicitly incorporates a measure of solar modulation (S), and our fast- and slow-muon scaling models (based on more limited data) account for solar modulation effects through increased uncertainties. These models improve on previously published models by better sampling the observed variability in measured cosmic ray intensities as a function of geomagnetic latitude, altitude, and solar activity. Furthermore, placing the spallogenic nucleon data in a consistent time-space framework allows for a more realistic assessment of uncertainties in our model than in earlier ones.