Abstract
Abstract. We investigate the assimilation of Tree-Ring-Width (TRW) chronologies into an atmospheric global climate model using Ensemble Kalman Filter (EnKF) techniques and a process-based tree-growth forward model as observation operator. Our results, within a perfect-model experiment setting, indicate that the non-linear response of tree-growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged (EnKF) methodology. Moreover, this skill loss appeared significantly sensitive to the structure of growth rate function, used to represent the Principle of Limiting Factors (PLF)s within the forward model. On the other hand, it was observed that the error reduction achieved by assimilating a particular pseudo-TRW chronology is modulated by the strength of the yearly internal variability of the model at the chronology site. This result might help the dendrochronology community to optimize their sampling efforts. In our experiments, the ''online'' (with cycling) paleao Data Assimilation (DA) approach did not outperform the ''offline'' (no-cycling) one, despite its considerable additional implementation complexity.
Funder
Bundesministerium für Bildung und Forschung
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献