Pseudo-proxy tests of the analogue method to reconstruct spatially resolved global temperature during the Common Era
- 1Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
- 2Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
- 3Department of Physics, University of Murcia, Murcia, Spain
- 4Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany
- 5Institute of Geography, University of Bern, Bern, Switzerland
Abstract. This study addresses the possibility of carrying out spatially resolved global reconstructions of annual mean temperature using a worldwide network of proxy records and a method based on the search of analogues. Several variants of the method are evaluated, and their performance is analysed. As a test bed for the reconstruction, the PAGES 2k proxy database (version 1.9.0) is employed as a predictor, the HadCRUT4 dataset is the set of observations used as the predictand and target, and a set of simulations from the PMIP3 simulations are used as a pool to draw analogues and carry out pseudo-proxy experiments (PPEs). The performance of the variants of the analogue method (AM) is evaluated through a series of PPEs in growing complexity, from a perfect-proxy scenario to a realistic one where the pseudo-proxy records are contaminated with noise (white and red) and missing values, mimicking the limitations of actual proxies. Additionally, the method is tested by reconstructing the real observed HadCRUT4 temperature based on the calibration of real proxies. The reconstructed fields reproduce the observed decadal temperature variability. From all the tests, we can conclude that the analogue pool provided by the PMIP3 ensemble is large enough to reconstruct global annual temperatures during the Common Era. Furthermore, the search of analogues based on a metric that minimises the RMSE in real space outperforms other evaluated metrics, including the search of analogues in the range-reduced space expanded by the leading empirical orthogonal functions (EOFs). These results show how the AM is able to spatially extrapolate the information of a network of local proxy records to produce a homogeneous gap-free climate field reconstruction with valuable information in areas barely covered by proxies and make the AM a suitable tool to produce valuable climate field reconstructions for the Common Era.