NAO: a code for reconstructing North Atlantic Oscillation from XRF data
Más información: https://github.com/andrewcparnell/NAO Contacto: Andrew Parnell, andrew.parnell@mu.ie R code for a Bayesian model for reconstructing North Atlantic Oscillation from X-Ray Fluorescence (XRF) data. This code follows a Bayesian modelling approach to produce a reconstruction of the NAO’s...
Main Authors: | , , , , |
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Other Authors: | , , , , , |
Format: | Software |
Language: | English |
Published: |
2018
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Subjects: | |
Online Access: | http://hdl.handle.net/10261/239385 https://doi.org/10.20350/digitalCSIC/13848 https://doi.org/10.13039/501100003381 https://doi.org/10.13039/501100001602 https://doi.org/10.13039/501100003339 https://doi.org/10.13039/501100000780 https://doi.org/10.13039/501100002809 https://doi.org/10.13039/501100003329 |
Summary: | Más información: https://github.com/andrewcparnell/NAO Contacto: Andrew Parnell, andrew.parnell@mu.ie R code for a Bayesian model for reconstructing North Atlantic Oscillation from X-Ray Fluorescence (XRF) data. This code follows a Bayesian modelling approach to produce a reconstruction of the NAO’s impact on the central Iberian Peninsula. The relationship between proxy and climate is derived from a training data set for the instrumental/proxy calibration period and is expressed through a likelihood function. This function is combined with a prior probability density function containing parameter information in order to obtain a posterior probability distribution of the reconstructed NAO values using Bayes’ theorem. Whilst Parnell et al. (2015) based their framework on reconstructing multivariate temperature and moisture measurements from raw pollen data, this method is easily adaptable to other proxies and climate variables. Indeed, Cahill et al. (2016) used a similar approach to reconstruct sea level from foraminifera. In all cases the measurements/counts of the proxy are required for a set of sediment layers (depths) in a core. Spanish Ministry of Economy and Competitiveness, CGL2010-15767/BTE PaleoNAO; Spanish Ministry of Economy and Competitiveness, CGL2013-40608-R; RapidNAO; Spanish Ministry of Economy and Competitiveness ,CGL2016-75281-C2-1-R PaleoModes; PhD JAE grant BOE 03/02/2011; Generalitat de Catalunya y European Union Horizon 2020 2016 BP 00023 Beatriu de Pinós – Marie Curie Cofund programme fellowship; Portuguese FCT project PTDC/CTA-GEO/29029/2017 HOLMODRIVE—North Atlantic Atmospheric Patterns Influence on Western Iberia Climate: From the Late Glacial to the Present; Science Foundation Ireland Career Development Award 17/CDA/4695; Science Foundation Ireland 12/RC/2289_P2 Peer reviewed |
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