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Dataset supporting the PhD thesis "Statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation" by Benoit Espinola. Output of the Montecarlo simulation

Dataset supporting the PhD thesis "Statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation" by Benoit Espinola. Output of the Montecarlo simulation
Dataset supporting the PhD thesis "Statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation" by Benoit Espinola. Output of the Montecarlo simulation
This Dataset supporting the PhD thesis "Statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation" by Benoit Espinola. This is the output data from the Montecarlo particle backtracking for COMICS I, deployment 6. The method for obtaining the data is described in the methods section of my thesis.
University of Southampton
Espinola, Benoit Henri Guillaume
b6c5a42f-9068-4ed6-a1a6-8e83628787fb
Espinola, Benoit Henri Guillaume
b6c5a42f-9068-4ed6-a1a6-8e83628787fb

Espinola, Benoit Henri Guillaume (2022) Dataset supporting the PhD thesis "Statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation" by Benoit Espinola. Output of the Montecarlo simulation. University of Southampton doi:10.5258/SOTON/D2379 [Dataset]

Record type: Dataset

Abstract

This Dataset supporting the PhD thesis "Statistical funnel-based approach to assess spatial contributions to uncertainty in organic carbon flux attenuation" by Benoit Espinola. This is the output data from the Montecarlo particle backtracking for COMICS I, deployment 6. The method for obtaining the data is described in the methods section of my thesis.

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ReadMe_file_of_the_Montecarlo_simulation.txt - Dataset
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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output.csv - Dataset
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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Published date: 22 September 2022
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Identifiers

Local EPrints ID: 469675
URI: http://eprints.soton.ac.uk/id/eprint/469675
DOI: doi:10.5258/SOTON/D2379
PURE UUID: 3e32e12a-ad40-4bf8-b2e2-541df9d2f72d
ORCID for Benoit Henri Guillaume Espinola: ORCID iD orcid.org/0000-0003-2412-9645

Catalogue record

Date deposited: 22 Sep 2022 16:31
Last modified: 05 May 2023 20:05

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Contributors

Creator: Benoit Henri Guillaume Espinola ORCID iD

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