The value of multiproxy reconstruction of past climate

Bo Li, Douglas W. Nychka, Caspar M. Ammann

Research output: Contribution to journalArticle

Abstract

Understanding the dynamics of climate change in its full richness requires the knowledge of long temperature time series. Although longterm, widely distributed temperature observations are not available, there are other forms of data, known as climate proxies, that can have a statistical relationship with temperatures and have been used to infer temperatures in the past before direct measurements. We propose a Bayesian hierarchical model to reconstruct past temperatures that integrates information from different sources, such as proxies with different temporal resolution and forcings acting as the external drivers of large scale temperature evolution. Additionally, this method allows us to quantify the uncertainty of the reconstruction in a rigorous manner. The reconstruction method is assessed, using a global climate model as the true climate system and with synthetic proxy data derived from the simulation. The target is to reconstruct Northern Hemisphere temperature from proxies that mimic the sampling and errors from tree ring measurements, pollen indices, and borehole temperatures. The forcing series used as covariates are solar irradiance, volcanic aerosols, and greenhouse gas concentrations. The Bayesian model was successful in integrating these different sources of information in creating a coherent reconstruction. Within the context of this numerical testbed, a statistical process model that includes the external forcings can improve the quality of a hemispheric reconstruction when long time scale proxy information is not available. This article has supplementary material online.

Original languageEnglish (US)
Pages (from-to)883-911
Number of pages29
JournalJournal of the American Statistical Association
Volume105
Issue number491
DOIs
StatePublished - Sep 1 2010
Externally publishedYes

Fingerprint

Climate
Forcing
Bayesian Hierarchical Model
Climate Models
Pollen
Greenhouse Gases
Temperature
Hemisphere
Irradiance
Climate Change
Bayesian Model
Aerosol
Testbed
Process Model
Statistical Model
Driver
Covariates
Time Scales
Quantify
Time series

Keywords

  • Bayesian hierarchical model
  • Forcings
  • Global climate model
  • Past temperature reconstruction
  • Proxies

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

The value of multiproxy reconstruction of past climate. / Li, Bo; Nychka, Douglas W.; Ammann, Caspar M.

In: Journal of the American Statistical Association, Vol. 105, No. 491, 01.09.2010, p. 883-911.

Research output: Contribution to journalArticle

Li, Bo ; Nychka, Douglas W. ; Ammann, Caspar M. / The value of multiproxy reconstruction of past climate. In: Journal of the American Statistical Association. 2010 ; Vol. 105, No. 491. pp. 883-911.
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