Statistics – Methodology
Scientific paper
Dec 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufmsh51e..03s&link_type=abstract
American Geophysical Union, Fall Meeting 2004, abstract #SH51E-03
Statistics
Methodology
1739 Solar/Planetary Relationships, 1600 Global Change (New Category), 1610 Atmosphere (0315, 0325), 1620 Climate Dynamics (3309), 1650 Solar Variability
Scientific paper
We study the solar signature on global temperature time series and use the corrected ACRIM satellite total solar irradiance composite data of Willson and Mordvinov. These data present a +0.04% per decade trend during solar cycles 21-23 (1980-2002). We use these data to estimate the climate sensitivity to solar activity at different time scales. After discussing certain limitations of multiple linear regression analysis in analyzing nonstationary time series, we introduce a stochastic linear wavelet transfer methodology that uses the influence of the Schwabe (11 years) and the Hale (22 years) solar cycles on the global surface temperature. The direct total solar irradiance forcing during the 21-23 solar cycles might have contributed from a minimum of 7-12% (by evaluating the upward trend of the ACRIM data with a step function) to a possible 10-20% (according to a linear increase) of surface warming during the same period. However, the Sun's variability on climate, the net solar forcing, might have minimally contributed ˜10-30% of the global temperature trend over 1980-2002. This finding suggests the presence of strong climate feedbacks to solar dynamics.
Scafetta Nicola
West Bruce J.
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