• search hit 2 of 11
Back to Result List

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

  • 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 errorPaleoclimate 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 themodel. This result might help the dendrochronology community to optimize their sampling efforts.show moreshow less

Download full text files

  • pmnr627.pdfeng
    (7646KB)

    SHA-1: 93c268fe537e23e6516a198292fbcd5e7c762524

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Metadaten
Author:Walter Acevedo, Bijan Fallah, Sebastian ReichORCiDGND, Ulrich Cubasch
URN:urn:nbn:de:kobv:517-opus4-418743
DOI:https://doi.org/10.25932/publishup-41874
ISSN:1866-8372
Parent Title (English):Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe
Series (Serial Number):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (627)
Document Type:Postprint
Language:English
Date of first Publication:2019/02/19
Year of Completion:2017
Publishing Institution:Universität Potsdam
Release Date:2019/02/19
Tag:Kalman filter; climate reconstructions; co-limitation; ensemble; framework; high resolution paleoclimatology; limiting factors; reanalysis; sparse proxy data; variability
Issue:627
Pagenumber:13
First Page:545
Last Page:557
Source:Climate of the Past 13 (2017) 5, pp. 545–557 DOI 10.5194/cp-13-545-2017
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Publication Way:Open Access
Licence (English):License LogoCreative Commons - Attribution 3.0 unported