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Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation

We present a model written in python to evaluate data from comprehensive (85)Kr collection schemes comprising 11 datasets from different monitoring stations around the globe. The model is designed to (1) calculate atmospheric input functions for the application of (85)Kr as a dating tracer and (2) t...

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Detalles Bibliográficos
Autores principales: Kersting, Arne, Brander, Sofia, Suckow, Axel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374161/
https://www.ncbi.nlm.nih.gov/pubmed/34434768
http://dx.doi.org/10.1016/j.mex.2021.101245
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author Kersting, Arne
Brander, Sofia
Suckow, Axel
author_facet Kersting, Arne
Brander, Sofia
Suckow, Axel
author_sort Kersting, Arne
collection PubMed
description We present a model written in python to evaluate data from comprehensive (85)Kr collection schemes comprising 11 datasets from different monitoring stations around the globe. The model is designed to (1) calculate atmospheric input functions for the application of (85)Kr as a dating tracer and (2) to investigate atmospheric circulation based on a two-box model of the atmosphere. Different functions were implemented, to (1) filter the data, (2) fit polynomials and running means, (3) extrapolate fits from the northern to the southern hemisphere, (4) calculate interhemispheric exchange times and (85)Kr emission rates and (5) export data to a csv file. Although the model is designed to evaluate atmospheric (85)Kr datasets, some functionality and basic concepts can be applied to other dating tracers, like tritium and SF(6). • Standardized method to systematically analyse atmospheric (85)Kr activity concentration time series for dating water and ice and to investigate atmospheric circulation. • Easily modifiable python script to adapt functions for similar data analysis procedures.
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spelling pubmed-83741612021-08-24 Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation Kersting, Arne Brander, Sofia Suckow, Axel MethodsX Method Article We present a model written in python to evaluate data from comprehensive (85)Kr collection schemes comprising 11 datasets from different monitoring stations around the globe. The model is designed to (1) calculate atmospheric input functions for the application of (85)Kr as a dating tracer and (2) to investigate atmospheric circulation based on a two-box model of the atmosphere. Different functions were implemented, to (1) filter the data, (2) fit polynomials and running means, (3) extrapolate fits from the northern to the southern hemisphere, (4) calculate interhemispheric exchange times and (85)Kr emission rates and (5) export data to a csv file. Although the model is designed to evaluate atmospheric (85)Kr datasets, some functionality and basic concepts can be applied to other dating tracers, like tritium and SF(6). • Standardized method to systematically analyse atmospheric (85)Kr activity concentration time series for dating water and ice and to investigate atmospheric circulation. • Easily modifiable python script to adapt functions for similar data analysis procedures. Elsevier 2021-01-23 /pmc/articles/PMC8374161/ /pubmed/34434768 http://dx.doi.org/10.1016/j.mex.2021.101245 Text en © 2021 The Authors. Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Kersting, Arne
Brander, Sofia
Suckow, Axel
Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation
title Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation
title_full Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation
title_fullStr Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation
title_full_unstemmed Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation
title_short Modelling (85)Kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation
title_sort modelling (85)kr datasets with python for applications in tracer hydrology and to investigate atmospheric circulation
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374161/
https://www.ncbi.nlm.nih.gov/pubmed/34434768
http://dx.doi.org/10.1016/j.mex.2021.101245
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