Impact of Proxies and Prior Estimates on Data Assimilation Using Isotope Ratios for the Climate Reconstruction of the Last Millennium

Abstract

Climate reconstructions by data assimilation need to accommodate for sensitivities to proxies and prior estimates because models are uncertain and proxies are spatiotemporally limited. This study examines these sensitivities using multiple climate model simulations and different combinations of proxies (i.e., corals, ice cores, and tree-ring cellulose). Experiments were conducted using an offline data assimilation approach; the results showed annual variations in the global distribution of surface air temperature and precipitation amount from 850 to 2000. Standard deviations of surface air temperature and precipitation amount during the entire period differed by up to 36% due to prior estimates. Experiments with different types of proxies showed that the El Niño-like distribution of positive anomalies in the central to eastern tropical Pacific may only be adequately reproduced in experiments with corals, and not experiments without corals. The correlation coefficient of the NINO.3 index from 1971 to 2000 between experiments with corals and the Japanese 55-year Reanalysis (JRA-55) was 0.81 at maximum. By contrast, the correlation coefficient between experiments without corals and JRA-55 was a maximum of 0.19.