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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-61
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-61
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 04 Mar 2019

Research article | 04 Mar 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

The application of mean averaging kernels to mean trace gas distributions

Thomas von Clarmann and Norbert Glatthor Thomas von Clarmann and Norbert Glatthor
  • Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany

Abstract. To avoid unnecessary data traffic it is sometimes desirable to apply mean averaging kernels to mean profiles of atmospheric state variables. Unfortunately, application of averaging kernels and averaging are not commutative in cases when averaging kernels and state variables are correlated. That is to say, the application of individual averaging kernels to individual profiles and subsequent averaging will, in general, lead to different results than averaging of the original profiles prior to the application of the mean averaging kernels unless profiles and averaging kernels are fully independent. The resulting error, however, can be corrected by subtraction of the covariance between the averaging kernel and the vertical profile. Thus it is recommended to calculate the covariance profile along with the mean profile and the mean averaging kernel.

Thomas von Clarmann and Norbert Glatthor
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Status: open (until 29 Apr 2019)
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Thomas von Clarmann and Norbert Glatthor
Thomas von Clarmann and Norbert Glatthor
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Latest update: 23 Mar 2019
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Short summary
To avoid unnecessary data traffic it is sometimes desirable to apply mean averaging kernels to mean profiles of atmospheric state variables. Unfortunately, the application of individual averaging kernels to individual profiles and subsequent averaging will, in general, lead to different results than averaging of the original profiles prior to the application of the mean averaging kernels. This effect is investigated and a correction scheme is proposed.
To avoid unnecessary data traffic it is sometimes desirable to apply mean averaging kernels to...
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