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Original Research Papers

An empirical characterisation of signal versus noise in CO2 data

Author:

I. G. Enting

CSIRO Atmospheric Research, AU
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Abstract

Uncertainties in the interpretations of CO2 data arise from errors in the observations and model relations. The space–time variations of CO2 on the global scale are analysed in terms of the singular-value decomposition, in order to obtain a characterisation of observational error that matches the requirements of global-scale estimation of fluxes. It is found that for monthly-mean data, a first-order moving average model of error is a far better representation than earlier assumptions of independent white noise.

How to Cite: Enting, I.G., 2002. An empirical characterisation of signal versus noise in CO2 data. Tellus B: Chemical and Physical Meteorology, 54(4), pp.301–306. DOI: http://doi.org/10.3402/tellusb.v54i4.16667
  Published on 01 Jan 2002
 Accepted on 8 Apr 2002            Submitted on 7 May 2001

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