JLM asked me to ask you to explain what this says in layman's terms for him. Can you?
The temperature record over hundreds of millennia holds fundamental information about the dynamics inherent in climate variability. Analysis of paleoclimate temperature records from the Vostok, GISP2, and EPICA Dome C ice cores show single power scaling exponents ranging from 1.5 to 1.7 over time ranges of hundreds to thousands of years. Previous studies have reported multiple scaling exponents ranging from 0.5 to 2.0. Compaction of the ice cores and intervals of erosion introduce gaps into the paleoclimate temperature records. Previous studies have not considered the impact of these gaps on the scaling exponent output by the analysis methods. The Lomb periodogram method of analysis is found to either under or over estimate the scaling exponent of gapped time series depending on the number, size, and pattern of the gaps. The correct scaling exponent of a paleoclimate time series with gaps can be determined by measuring the effect of the gaps on the scaling exponent of a synthetic time series of known scaling exponent, with data points removed corresponding to gaps in the paleoclimate record. Gap-corrected scaling exponents for the Vostok, GISP2, and EPICA ice core temperature records are 1.7, 1.5, and 1.5, respectively. The method was further validated on a natural data set. By introducing gaps to the evenly sampled Dome Fuji core temperature record, analyzing the data, and correcting for the gaps, we obtain a scaling exponent equal to that of the original ungapped dataset. The power scaling exhibited by all of the ice core records analyzed demonstrates that climatic temperature variation is a nonlinear dynamical process. Climate models that correctly model the dynamics should exhibit similar power scaling properties.
