Articles | Volume 13, issue 5
Clim. Past, 13, 545–557, 2017
Clim. Past, 13, 545–557, 2017

Research article 31 May 2017

Research article | 31 May 2017

Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

Walter Acevedo1,2, Bijan Fallah1, Sebastian Reich2, and Ulrich Cubasch1 Walter Acevedo et al.
  • 1Institut für Meteorologie, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
  • 2Institut für Mathematik, Universität Potsdam, Karl-Liebknecht-Strasse 24–25, 14476 Potsdam, Germany

Abstract. Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, 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 an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

Short summary
The purpose of this study is to contribute to the present knowledge of paleo data assimilation techniques by addressing the following two questions: (i) Does the off-line regime naturally appear for the assimilation of tree-ring-width records into an AGCM? (ii) Is the fuzzy logic (FL)-based extension of a forward model still useful to improve the performance of a time-averaged ensemble Kalman filter technique when a climate model is used?