Articles | Volume 10, issue 9
Research article
21 Sep 2017
Research article |  | 21 Sep 2017

Smoothing data series by means of cubic splines: quality of approximation and introduction of a repeating spline approach

Sabine Wüst, Verena Wendt, Ricarda Linz, and Michael Bittner


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Sabine Wüst on behalf of the Authors (24 May 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (24 May 2017) by Gerd Baumgarten
RR by Anonymous Referee #1 (08 Jun 2017)
RR by Anonymous Referee #2 (13 Jun 2017)
ED: Publish subject to minor revisions (Editor review) (19 Jun 2017) by Gerd Baumgarten
AR by Anna Wenzel on behalf of the Authors (30 Jun 2017)  Author's response    Manuscript
ED: Publish as is (13 Jul 2017) by Gerd Baumgarten
Short summary
Cubic splines with equidistant spline sampling points are a common method in atmospheric science for the approximation of background conditions by means of filtering superimposed fluctuations from a data series. However, splines can generate considerable artificial oscillations in the background and the residuals. We introduce a repeating spline approach which is able to significantly reduce this phenomenon and to apply it to TIMED-SABER vertical temperature profiles from 2010 to 2014.