气候变化领域集成服务门户(CCPortal): Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering

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DOI	10.5194/cp-15-1275-2019
	Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering
	Weitzel N.; Hense A.; Ohlwein C.
发表日期	2019
ISSN	18149324
起始页码	1275
结束页码	1301
卷号	15 期号:4
英文摘要	Probabilistic spatial reconstructions of past climate states are valuable to quantitatively study the climate system under different forcing conditions because they combine the information contained in a proxy synthesis into a comprehensible product. Unfortunately, they are subject to a complex uncertainty structure due to complicated proxy-climate relations and sparse data, which makes interpolation between samples difficult. Bayesian hierarchical models feature promising properties to handle these issues, like the possibility to include multiple sources of information and to quantify uncertainties in a statistically rigorous way. We present a Bayesian framework that combines a network of pollen and macrofossil samples with a spatial prior distribution estimated from a multi-model ensemble of climate simulations. The use of climate simulation output aims at a physically reasonable spatial interpolation of proxy data on a regional scale. To transfer the pollen data into (local) climate information, we invert a forward version of the probabilistic indicator taxa model. The Bayesian inference is performed using Markov chain Monte Carlo methods following a Metropolis-within-Gibbs strategy. Different ways to incorporate the climate simulations into the Bayesian framework are compared using identical twin and cross-validation experiments. Then, we reconstruct the mean temperature of the warmest and mean temperature of the coldest month during the mid-Holocene in Europe using a published pollen and macrofossil synthesis in combination with the Paleoclimate Modelling Intercomparison Project Phase III mid-Holocene ensemble. The output of our Bayesian model is a spatially distributed probability distribution that facilitates quantitative analyses that account for uncertainties. © 2019 Author(s). This work is distributed under the Creative Commons Attribution 4.0 License.
语种	英语
scopus关键词	Bayesian analysis; climate variation; fossil record; Holocene; Markov chain; paleoclimate; palynology; proxy climate record; quantitative analysis; reconstruction; spatial analysis; Europe
来源期刊	Climate of the Past
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/146800
作者单位	Institut für Umweltphysik, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 229, Heidelberg, 69120, Germany; Institut für Geowissenschaften und Meteorologie, Rheinische Friedrich-Wilhelms-Universität Bonn, Auf dem Hügel 20, Bonn, 53121, Germany
推荐引用方式 GB/T 7714	Weitzel N.,Hense A.,Ohlwein C.. Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering[J],2019,15(4).
APA	Weitzel N.,Hense A.,&Ohlwein C..(2019).Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering.Climate of the Past,15(4).
MLA	Weitzel N.,et al."Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering".Climate of the Past 15.4(2019).