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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 11, 1009-1017, 2018
https://doi.org/10.5194/amt-11-1009-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
20 Feb 2018
Importance of interpolation and coincidence errors in data fusion
Simone Ceccherini et al.
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'Review', Anonymous Referee #1, 12 Nov 2017 Printer-friendly Version 
AC1: 'Reply to referee #1', Simone Ceccherini, 08 Jan 2018 Printer-friendly Version Supplement 
 
RC2: 'Review', Anonymous Referee #2, 21 Nov 2017 Printer-friendly Version Supplement 
AC2: 'Reply to referee #2', Simone Ceccherini, 08 Jan 2018 Printer-friendly Version Supplement 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Simone Ceccherini on behalf of the Authors (08 Jan 2018)  Author's response  Manuscript
ED: Referee Nomination & Report Request started (09 Jan 2018) by Brian Kahn
RR by Anonymous Referee #1 (10 Jan 2018)
ED: Publish as is (16 Jan 2018) by Brian Kahn  
CC BY 4.0
Publications Copernicus
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Short summary
Data fusion is an important tool to reduce data volume and to improve data quality. This paper introduces a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors. This upgraded algorithm extends the applicability of the technique to a wider range of cases. In fact, it also makes it possible to fuse vertical profiles of atmospheric parameters when they are represented on different altitude grids and refer to different true profiles.
Data fusion is an important tool to reduce data volume and to improve data quality. This paper...
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