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| Abstract |
- 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 δ¹⁵N₂ 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.
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| Citation |
- C. M. Trudinger, I. G. Enting, P. J. Rayner, D. M. Etheridge, C. Buizert, M. Rubino, . . . T. Blunier. (2013). How well do different tracers constrain the firn diffusivity profile? Atmospheric Chemistry and Physics, 13(3), 1485-1510.
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| Funding Statement (additional comments about funding) |
- This work has been undertaken as part of the
Australian Climate Change Science Program, funded jointly by the
Department of Climate Change and Energy Efficiency, the Bureau
of Meteorology and CSIRO. CSIRO’s research in this area was
also funded by the Centre for Ice and Climate at the University
of Copenhagen. The Centre of Excellence of Mathematics and
Statistics of Complex Systems (MASCOS) has been funded by the
Australian Research Council. I. Enting’s fellowship at MASCOS
was funded in part by CSIRO. P. Rayner is in receipt of an
Australian Professorial Fellowship (DP1096309). C. Buizert was supported by the NOAA Climate and Global Change Fellowship
Program, administered by the University Corporation for Atmospheric
Research.
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| Additional Information |
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Previous issue date: 2012-07-19
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