Kalugin, I., Daryin, A., Smolyaninova, L., Andreev, A., Diekmann, B. and Khlystov, O. 2007. 800-yr-long records of annual air temperature and precipitation over southern Siberia inferred from Teletskoye Lake sediments. Quaternary Research 67: 400-410.
What was done
The authors collected several sediment cores from the deepest area of Teletskoye Lake (51°39'N, 87°40'E) in the Altai Mountains of southern Siberia, for which they measured the spectra of numerous elements - including Ba, Cd, Ce, I, La, Mo, Nb, Rb, Sb, Sn, Sr, Th, U, Y, Zr - after which they report that "artificial neural networks (ANN) (Veelenturf, 1995) were used for reconstruction of annual temperature and precipitation by sediment properties (Smolyaninova et al., 2004)."
What was learned
In describing their findings, Kalugin et al. say that "a global cold period, the Little Ice Age with Maunder minimum, is clearly designated, as well as global warming during the 19-20th centuries," all of which also implies the existence of the Medieval Warm Period that preceded the Little Ice Age. In fact, from their plot of the pertinent data, it can be seen that the mean peak temperature of the latter part of the Medieval Warm Period was about 0.5°C higher than the mean peak temperature of the Current Warm Period, which occurred at the end of the record.
What it means
During the peak warmth of the Medieval Warm Period, when there was fully 100 ppm less CO2 in the air than there is currently, it may well have been half a degree C warmer in southern Siberia than it is now. Adding this finding to the many other such findings from around the world that we routinely collect and display on a continuing basis in our Medieval Warm Period Project casts great doubt upon the climate-alarmist crowd's unflinching contention that our actually not-so-unprecedented current warmth is driven by our much more historic atmospheric CO2 concentration. The true facts of the case simply don't support this conclusion.
Smolyaninova, L.G., Kalugin, I.A. and Daryin, A.V. 2004. Technique of receiving empiri-mathematical interdependence models between climatic parameters and litologi-geochemical character of bottom deposits. Computer Technology 9: Mathematic, Mechanic, Computing 3: 43-46.
Veelenturf, L.P.J. 1995. Analysis and applications of artificial neural networks. Computer Science 259.Reviewed 5 September 2007