Paleoclimate reconstruction and observation error estimation in climate proxies using data assimilation and innovation statistics

Abstract

Data assimilation (DA) has been successfully applied to paleoclimate reconstruction. As DA fuses model simulations and observations based on their error, it is essential to estimate them properly. However, observation errors have been treated in a crude way. This study estimates the observation errors using innovation statistics and shows the impact of estimated errors on reconstruction skills.