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A Bayesian multinomial regression model for palaeoclimate reconstruction with time uncertainty
Author(s) -
Ilvonen Liisa,
Holmström Lasse,
Seppä Heikki,
Veski Siim
Publication year - 2016
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.2393
Subject(s) - bayesian probability , multinomial distribution , bayesian inference , regression , econometrics , multinomial logistic regression , statistics , climate change , climatology , computer science , geology , mathematics , oceanography
Estimating chronological uncertainty is a critical but often neglected prerequisite in palaeoclimatological reconstructions and core comparisons. We describe a hierarchical Bayesian multinomial regression model for temperature reconstruction that allows uncertainty in the sediment core sample dates. Climate model output is used as pseudodata to provide prior information about the overall variability of past temperatures. Including time uncertainty in the model can make usual summaries such as the posterior mean temperature less useful. We therefore recommend considering also fixed chronology reconstructions and exploration of individual temperature history realizations. This can be particularly relevant for tracking short‐lived events. We demonstrate the proposed model by reconstructing the past temperature from fossil pollen data obtained from three cores in Estonia and southern Sweden. Copyright © 2016 John Wiley & Sons, Ltd.