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Paul Miller

Senior lecturer

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A method for climate and vegetation reconstruction through the inversion of a dynamic vegetation model

Author

  • Vincent Garreta
  • Paul Miller
  • Joel Guiot
  • Christelle Hely
  • Simon Brewer
  • Martin Sykes
  • Thomas Litt

Summary, in English

Climate reconstructions from data sensitive to past climates provide estimates of what these climates were like. Comparing these reconstructions with simulations from climate models allows to validate the models used for future climate prediction. It has been shown that for fossil pollen data, gaining estimates by inverting a vegetation model allows inclusion of past changes in carbon dioxide values. As a new generation of dynamic vegetation model is available we have developed an inversion method for one model, LPJ-GUESS. When this novel method is used with high-resolution sediment it allows us to bypass the classic assumptions of (1) climate and pollen independence between samples and (2) equilibrium between the vegetation, represented as pollen, and climate. Our dynamic inversion method is based on a statistical model to describe the links among climate, simulated vegetation and pollen samples. The inversion is realised thanks to a particle filter algorithm. We perform a validation on 30 modern European sites and then apply the method to the sediment core of Meerfelder Maar (Germany), which covers the Holocene at a temporal resolution of approximately one sample per 30 years. We demonstrate that reconstructed temperatures are constrained. The reconstructed precipitation is less well constrained, due to the dimension considered (one precipitation by season), and the low sensitivity of LPJ-GUESS to precipitation changes.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • MERGE: ModElling the Regional and Global Earth system
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publishing year

2010

Language

English

Pages

371-389

Publication/Series

Climate Dynamics

Volume

35

Issue

2-3

Document type

Journal article

Publisher

Springer

Topic

  • Physical Geography

Keywords

  • LPJ-GUESS
  • Pollen sample
  • vegetation model
  • Dynamic
  • Particle filter
  • Palaeoclimate reconstruction
  • Model inversion

Status

Published

ISBN/ISSN/Other

  • ISSN: 1432-0894