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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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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. |
format | Online Article Text |
id | pubmed-8374161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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