دورية أكاديمية
Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering
| العنوان: | Combining a pollen and macrofossil synthesis with climate simulations for spatial reconstructions of European climate using Bayesian filtering |
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| المؤلفون: | N. Weitzel, A. Hense, C. Ohlwein |
| المصدر: | Climate of the Past, Vol 15, Pp 1275-1301 (2019) |
| بيانات النشر: | Copernicus Publications, 2019. |
| سنة النشر: | 2019 |
| المجموعة: | LCC:Environmental pollution LCC:Environmental protection LCC:Environmental sciences |
| مصطلحات موضوعية: | Environmental pollution, TD172-193.5, Environmental protection, TD169-171.8, Environmental sciences, GE1-350 |
| الوصف: | 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1814-9324 1814-9332 |
| Relation: | https://www.clim-past.net/15/1275/2019/cp-15-1275-2019.pdf; https://doaj.org/toc/1814-9324; https://doaj.org/toc/1814-9332 |
| DOI: | 10.5194/cp-15-1275-2019 |
| URL الوصول: | https://doaj.org/article/a2f0126acd37493bb278d4781c15091b |
| رقم الأكسشن: | edsdoj.2f0126acd37493bb278d4781c15091b |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 18149324 18149332 |
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| DOI: | 10.5194/cp-15-1275-2019 |