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.…
Verfasserangaben: | Walter Acevedo, Bijan Fallah, Sebastian ReichORCiDGND, Ulrich Cubasch |
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URN: | urn:nbn:de:kobv:517-opus4-418743 |
DOI: | https://doi.org/10.25932/publishup-41874 |
ISSN: | 1866-8372 |
Titel des übergeordneten Werks (Englisch): | Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe |
Schriftenreihe (Bandnummer): | Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (627) |
Publikationstyp: | Postprint |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 19.02.2019 |
Erscheinungsjahr: | 2017 |
Veröffentlichende Institution: | Universität Potsdam |
Datum der Freischaltung: | 19.02.2019 |
Freies Schlagwort / Tag: | Kalman filter; climate reconstructions; co-limitation; ensemble; framework; high resolution paleoclimatology; limiting factors; reanalysis; sparse proxy data; variability |
Ausgabe: | 627 |
Seitenanzahl: | 13 |
Erste Seite: | 545 |
Letzte Seite: | 557 |
Quelle: | Climate of the Past 13 (2017) 5, pp. 545–557 DOI 10.5194/cp-13-545-2017 |
Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät |
DDC-Klassifikation: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer Review: | Referiert |
Publikationsweg: | Open Access |
Lizenz (Englisch): | Creative Commons - Namensnennung 3.0 Unported |