The value of multiproxy reconstruction of past climate

Although long-term, widely distributed temperature observations are not available, there are other forms of data, known as climate proxies, that can have a statistical relationship with temperatures and have been used to infer temperatures in the past before direct measurements. We propose a Bayesian hierarchical model to reconstruct past temperatures that integrates information from different sources, such as proxies with different temporal resolution and forcings acting as the external drivers of large scale temperature evolution.

Additionally, this method allows us to quantify the uncertainty of the reconstruction in a rigorous manner. The reconstruction method is assessed, using a global climate model as the true climate system and with synthetic proxy data derived from the simulation. The target is to reconstruct Northern Hemisphere temperature from proxies that mimic the sampling and errors from tree ring measurements, pollen indices, and borehole temperatures.