An open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST v0.1.1)

Förster, Kristian; Hanzer, Florian; Winter, Benjamin; Marke, Thomas; Strasser, Ulrich

doi:https://doi.org/10.5194/gmd-9-2315-2016

Articles | Volume 9, issue 7

https://doi.org/10.5194/gmd-9-2315-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-9-2315-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 7

Model description paper

|

06 Jul 2016

Model description paper |

| 06 Jul 2016

An open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST v0.1.1)

Kristian Förster, Florian Hanzer, Benjamin Winter, Thomas Marke, and Ulrich Strasser

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Final revised paper (published on 06 Jul 2016)
Preprint (discussion started on 22 Mar 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'An open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST v0.1.0)', Ina Pohle, 03 May 2016
- AC1: 'Reply to Ina Pohle', Kristian Förster, 11 May 2016
RC2: 'Review comments on MELODIST paper, gmd-2016-51', Anonymous Referee #2, 23 May 2016
- AC2: 'Reply to Anonymous Referee #2', Kristian Förster, 01 Jun 2016

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Kristian Förster on behalf of the Authors (08 Jun 2016) Author's response Manuscript

ED: Publish as is (09 Jun 2016) by Rolf Sander

AR by Kristian Förster on behalf of the Authors (09 Jun 2016)

Short summary

For many applications in geoscientific modelling hourly meteorological time series are required, which generally cover shorter periods of time compared to daily time series. We present an open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST) capable of disaggregating temperature, precipitation, humidity, wind speed, and shortwave radiation (i.e. making 24 out of 1 value). Results indicate a good reconstruction of diurnal features at five sites in different climates.