Development and evaluation of a system of proxy data assimilation for paleoclimate reconstruction
Atsushi Okazaki1 and Kei Yoshimura21RIKEN Advanced Institute for Computational Science, Japan 2Atmosphere and Ocean Research Institute, University of Tokyo, Japan
Received: 21 Nov 2016 – Accepted: 21 Nov 2016 – Published: 22 Nov 2016
Abstract. Data assimilation (DA) has been successfully applied in the field of paleoclimatology to reconstruct past climate. However, data reconstructed from proxies have been assimilated, as opposed to the actual proxy values. This banned to fully utilize the information recorded in the proxies.
This study examined the feasibility of proxy DA for paleoclimate reconstruction. Isotopic proxies (δ18O in ice cores, corals, and tree-ring cellulose) were assimilated into models: an isotope enabled general circulation model (GCM) and forward proxy models, using offline data assimilation.
First, we examined the feasibility using an observation system simulation experiment (OSSE). The analysis showed a significant improvement compared with the first guess in the reproducibility of isotope ratios in the proxies, as well as the temperature and precipitation fields, when only the isotopic information was assimilated. The accuracy for temperature and precipitation was especially high at low latitudes. This is due to the fact that isotopic proxies are strongly influenced by temperature and/or precipitation at low latitudes, which, in turn, are modulated by the El Niño-Southern Oscillation (ENSO) on interannual timescales. The proxy temperature DA had comparable or higher accuracy than the reconstructed temperature DA.
The proxy DA was compared with real proxy data. The reconstruction accuracy was decreased compared to the OSSE. In particular, the decrease was significant over the Indian Ocean, eastern Pacific, and the Atlantic Ocean where the reproducibility of the proxy model was lower. By changing the experimental design in a stepwise manner, the decrease in accuracy was found to be attributable to the misrepresentation of the models. In addition, the accuracy was also dependent on the number and/or distribution of the proxies to be assimilated. Thus, to improve climate DA, it is necessary to enhance the performance of models, as well as to increase the number of proxies.
Okazaki, A. and Yoshimura, K.: Development and evaluation of a system of proxy data assimilation for paleoclimate reconstruction, Clim. Past Discuss., doi:10.5194/cp-2016-121, in review, 2016.