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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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AMT | Articles | Volume 13, issue 3
Atmos. Meas. Tech., 13, 1213–1226, 2020
https://doi.org/10.5194/amt-13-1213-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 13, 1213–1226, 2020
https://doi.org/10.5194/amt-13-1213-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 11 Mar 2020

Research article | 11 Mar 2020

Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles

Kaixu Bai et al.

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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 Jianping Guo on behalf of the Authors (02 Dec 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (05 Dec 2019) by Jun Wang
RR by Anonymous Referee #1 (21 Dec 2019)
RR by Anonymous Referee #2 (03 Jan 2020)
ED: Publish subject to minor revisions (review by editor) (09 Jan 2020) by Jun Wang
AR by Jianping Guo on behalf of the Authors (14 Jan 2020)  Author's response    Manuscript
ED: Publish as is (09 Feb 2020) by Jun Wang
Publications Copernicus
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Short summary
A novel gap-filling method called the diurnal-cycle-constrained empirical orthogonal function (DCCEOF) is proposed. Cross validation indicates that this method gives high accuracy in predicting missing values in daily PM2.5 time series by accounting for the local diurnal phases, especially by reconstructing daily extrema that cannot be accurately restored by other approaches. The DCCEOF method can be easily applied to other data sets because of its self-consistent capability.
A novel gap-filling method called the diurnal-cycle-constrained empirical orthogonal function...
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