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Foster and Rahmstorf All
Five datasets of global surface temperature and lower troposphere temperature are shown in this animation before and after removing the short-term effects of the El Niño Southern Oscillation (ENSO), solar variability, and volcanic aerosols. A 12-month running average was applied to each dataset. Foster and Rahmstorf (2011) used multiple linear regression to determine and then statistically filter out these short-term effects to reveal the steady underlying trend of primarily human-caused global surface warming. This method effectively removes the short-term noise that can complicate the interpretation of temperature trends or permit "cherry picking" of graph endpoints or short time periods to find periods that erroneously suggest global warming has paused rather than continued unabated as these results show.
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