How well do different tracers constrain the firn diffusivity profile?

Firn air transport models are used to interpret measurements of the composition of air in firn and bubbles trapped in ice in order to reconstruct past atmospheric composition. The diffusivity profile in the firn is usually calibrated by comparing modelled and measured concentrations for tracers with...

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Published in:Atmospheric Chemistry and Physics
Main Authors: Trudinger C. M., Enting I. G., Rayner P. J., Etheridge D. M., Buizert C., Rubino M., Krummel P. B., Blunier T.
Other Authors: Trudinger, C. M., Enting, I. G., Rayner, P. J., Etheridge, D. M., Buizert, C., Rubino, M., Krummel, P. B., Blunier, T.
Format: Article in Journal/Newspaper
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/11591/410561
https://doi.org/10.5194/acp-13-1485-2013
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spelling ftuncampaniairis:oai:iris.unicampania.it:11591/410561 2024-04-14T08:19:45+00:00 How well do different tracers constrain the firn diffusivity profile? Trudinger C. M. Enting I. G. Rayner P. J. Etheridge D. M. Buizert C. Rubino M. Krummel P. B. Blunier T. Trudinger, C. M. Enting, I. G. Rayner, P. J. Etheridge, D. M. Buizert, C. Rubino, M. Krummel, P. B. Blunier, T. 2013 http://hdl.handle.net/11591/410561 https://doi.org/10.5194/acp-13-1485-2013 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000315406100025 volume:13 issue:3 firstpage:1485 lastpage:1510 numberofpages:26 journal:ATMOSPHERIC CHEMISTRY AND PHYSICS http://hdl.handle.net/11591/410561 doi:10.5194/acp-13-1485-2013 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84873680901 info:eu-repo/semantics/article 2013 ftuncampaniairis https://doi.org/10.5194/acp-13-1485-2013 2024-03-21T16:14:41Z Firn air transport models are used to interpret measurements of the composition of air in firn and bubbles trapped in ice in order to reconstruct past atmospheric composition. The diffusivity profile in the firn is usually calibrated by comparing modelled and measured concentrations for tracers with known atmospheric history. However, in most cases this is an under-determined inverse problem, often with multiple solutions giving an adequate fit to the data (this is known as equifinality). Here we describe a method to estimate the firn diffusivity profile that allows multiple solutions to be identified, in order to quantify the uncertainty in diffusivity due to equifinality. We then look at how well different combinations of tracers constrain the firn diffusivity profile. Tracers with rapid atmospheric variations like CH3CCl3, HFCs and 14CO2 are most useful for constraining molecular diffusivity, while δ:15N2 is useful for constraining parameters related to convective mixing near the surface. When errors in the observations are small and Gaussian, three carefully selected tracers are able to constrain the molecular diffusivity profile well with minimal equifinality. However, with realistic data errors or additional processes to constrain, there is benefit to including as many tracers as possible to reduce the uncertainties. We calculate CO2 age distributions and their spectral widths with uncertainties for five firn sites (NEEM, DE08-2, DSSW20K, South Pole 1995 and South Pole 2001) with quite different characteristics and tracers available for calibration. We recommend moving away from the use of a firn model with one calibrated parameter set to infer atmospheric histories, and instead suggest using multiple parameter sets, preferably with multiple representations of uncertain processes, to assist in quantification of the uncertainties. © 2013 Author(s). Article in Journal/Newspaper South pole Università degli Studi della Campania "Luigi Vanvitelli": CINECA IRIS V: South Pole Atmospheric Chemistry and Physics 13 3 1485 1510
institution Open Polar
collection Università degli Studi della Campania "Luigi Vanvitelli": CINECA IRIS V:
op_collection_id ftuncampaniairis
language English
description Firn air transport models are used to interpret measurements of the composition of air in firn and bubbles trapped in ice in order to reconstruct past atmospheric composition. The diffusivity profile in the firn is usually calibrated by comparing modelled and measured concentrations for tracers with known atmospheric history. However, in most cases this is an under-determined inverse problem, often with multiple solutions giving an adequate fit to the data (this is known as equifinality). Here we describe a method to estimate the firn diffusivity profile that allows multiple solutions to be identified, in order to quantify the uncertainty in diffusivity due to equifinality. We then look at how well different combinations of tracers constrain the firn diffusivity profile. Tracers with rapid atmospheric variations like CH3CCl3, HFCs and 14CO2 are most useful for constraining molecular diffusivity, while δ:15N2 is useful for constraining parameters related to convective mixing near the surface. When errors in the observations are small and Gaussian, three carefully selected tracers are able to constrain the molecular diffusivity profile well with minimal equifinality. However, with realistic data errors or additional processes to constrain, there is benefit to including as many tracers as possible to reduce the uncertainties. We calculate CO2 age distributions and their spectral widths with uncertainties for five firn sites (NEEM, DE08-2, DSSW20K, South Pole 1995 and South Pole 2001) with quite different characteristics and tracers available for calibration. We recommend moving away from the use of a firn model with one calibrated parameter set to infer atmospheric histories, and instead suggest using multiple parameter sets, preferably with multiple representations of uncertain processes, to assist in quantification of the uncertainties. © 2013 Author(s).
author2 Trudinger, C. M.
Enting, I. G.
Rayner, P. J.
Etheridge, D. M.
Buizert, C.
Rubino, M.
Krummel, P. B.
Blunier, T.
format Article in Journal/Newspaper
author Trudinger C. M.
Enting I. G.
Rayner P. J.
Etheridge D. M.
Buizert C.
Rubino M.
Krummel P. B.
Blunier T.
spellingShingle Trudinger C. M.
Enting I. G.
Rayner P. J.
Etheridge D. M.
Buizert C.
Rubino M.
Krummel P. B.
Blunier T.
How well do different tracers constrain the firn diffusivity profile?
author_facet Trudinger C. M.
Enting I. G.
Rayner P. J.
Etheridge D. M.
Buizert C.
Rubino M.
Krummel P. B.
Blunier T.
author_sort Trudinger C. M.
title How well do different tracers constrain the firn diffusivity profile?
title_short How well do different tracers constrain the firn diffusivity profile?
title_full How well do different tracers constrain the firn diffusivity profile?
title_fullStr How well do different tracers constrain the firn diffusivity profile?
title_full_unstemmed How well do different tracers constrain the firn diffusivity profile?
title_sort how well do different tracers constrain the firn diffusivity profile?
publishDate 2013
url http://hdl.handle.net/11591/410561
https://doi.org/10.5194/acp-13-1485-2013
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op_relation info:eu-repo/semantics/altIdentifier/wos/WOS:000315406100025
volume:13
issue:3
firstpage:1485
lastpage:1510
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journal:ATMOSPHERIC CHEMISTRY AND PHYSICS
http://hdl.handle.net/11591/410561
doi:10.5194/acp-13-1485-2013
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84873680901
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container_title Atmospheric Chemistry and Physics
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