from the Danish Meteorological Institute works actively on the development of statistical methods for climate reconstructions, a field of intense debate in the past few years. Hopefully we will enter a phase in which scientific debates remain .. well, in the scientific realm. Enjoy his post.
Anthropogenic emissions of greenhouse gases - in particular CO2 and methane - change the radiative properties of the atmosphere and thereby impose a tendency of heating at the surface of the Earth. In the past the Earths temperature has varied both due to external forcings such as the volcanic eruptions, changes in the sun, and due to internal variability in the climate system. Much effort has in recent years been made to understand and project man-made climate change. In this context the past climate is an important resource for climate science as it provides us with valuable information about how the climate responds to forcings. It also provides a validation target for climate models, although paleoclimate modelling
is still in its infancy. It should be obvious that we need to understand the past climate variability before we can confidently predict the future.
Fig 1. Pseudo-proxy experiments with seven different reconstruction methods. The black curve is the NH mean temperature, the target which we hope the reconstructions will catch. But this is not the case: All reconstructions underestimate the pre-industrial temperature level as well as the amplitude of the low-frequency variability. Note that the reconstructions are very good in the last 100 years which have been used for calibration. The three panels differ in the strength of the variability of the target. From Christiansen et al. 2009.
Unfortunately, we do not have systematic instrumental measurements of the surface temperature much further back than the mid-19th century. Further back in time we must rely of proxy data. The climate proxies include tree rings, corals, lake and marine sediment cores, terrestrial bore-hole temperatures, and documentary archives. Common to all these sources is that they include a climate signal but that this signal is polluted by noise (basically all non-climatic influences such as fires, diseases etc.).