Courtesy of Lane J:
A Relationship Between Cosmic Radiation and Tree Rings
Dengel et al., New Phytologist, 2009
Sigrid Dengel and company performed a tree ring analysis of Sitka Spruce cross sections taken from a single tree plantation in Scotland, UK. The collection's annual rings were measured and correlated with numerous climatic and atmospheric factors to determine relational significance. Of eight factors including temperature, precipitation and cloud base, cosmic ray flux was the factor found to have positive statistical correlation to tree ring growth.
Based on the findings, Dengel et al. suggest that galactic cosmic radiation (GCR) could be used to explain tree-ring growth patterns across the globe. The researchers propose that high galactic cosmic radiation increases aerosol particles in the atmosphere. These aerosols scatter incoming solar radiation creating diffuse solar energy that supposedly stimulates photosynthesis. A more direct approach where GCR directly affects tree growth is also given as a possibility. The class was skeptical.
The article has received negative reviews from portions of the scientific community for a number of reasons including: poor statistical methods, limited information presented on statistical methods, choice of study area, age of samples, and study extent. In contrast, climate change skeptics have used the study to cast doubt on the accuracy of dendroclimatological studies in the prediction of past climate. This is another challenge scientists will have to overcome in getting their climate change message across.
Time Scales of Climate Change
Bartlein et al., Encyclopedia of Quaternary Science, 2006
We took a break from focused research to get an overview by PJ Bartlein on the character of climate variations over time. Scott was kind enough to break down the terminology used within the paper, much of which can be reviewed in the survival guide posted November 9th.
Spurious periodicity (SP) was a hot topic, especially for Keith. Random data without any cycles or patterns can be interpreted to have meaning when certain statistical methods are applied. Any interpretations made from patterns discovered during dataset analysis should be linked with an obvious mechanism to account for SP. It was noted that humans love to assign meaning to random chance.
In general, Bartlein made it clear that climate oscillations are found across a wide range of time scales. Across these time scales, oscillations can be broken up into periodic and quasi-periodic patterns. External climate forces like the Milankovitch cycle or the earth's annual orbit can be predicted with accuracy and are considered cyclical. Quasi-periodic oscillations like ENSO have a distinct pattern but cannot be predicted with certainty. These patterns can be compared on a variance spectrum (see fig. 2) to show differences in frequency and magnitude. Climate variability occurs at all levels of time, but variability increases with scale.
Time series can be expressed by frequency. This was discussed by Bartlein but expanded upon by Scott. With spectral analysis, different colored series represent a specific level of variance and periodicity - red series being slow changes (orbital cycles), blue being fast (ENSO), and the white series as steady variation without a discernable frequency (precipitation).