Articles | Volume 11, issue 2
Research article
20 Feb 2018
Research article |  | 20 Feb 2018

Importance of interpolation and coincidence errors in data fusion

Simone Ceccherini, Bruno Carli, Cecilia Tirelli, Nicola Zoppetti, Samuele Del Bianco, Ugo Cortesi, Jukka Kujanpää, and Rossana Dragani


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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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
AR by Simone Ceccherini on behalf of the Authors (17 Jan 2018)
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.