Demonstration of process-based reconstruction of annual temperatures from tree ring oxygen isotope

Abstract

Forecasting the global warming of the post-industrial period requires knowledge of natural variations in climatic parameters, especially temperature in preceding times. Due to its stable time resolution and known physiochemical formation process, tree ring cellulose isotope datasets have immense potential to yield climatic variability information. The first standardized site-independent temperature reconstruction model from tree-ring cellulose oxygen isotope data is demonstrated here using data from a montane site in the western Himalayas. This model does not require any statistical calibration and can be directly compared with instrumental or modelled data. The resulting temperature amplitude is dependent on moisture availability and this input is needed to modulate the reconstruction. The present work tests the possibility of input of carbon isotope discrimination as a proxy of relative humidity. This input achieved amplitude control but additional frequency components were introduced to the reconstruction.