Publication Date:
2016-09-26
Description:
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.
Print ISSN:
1814-9340
Electronic ISSN:
1814-9359
Topics:
Geosciences