Articles | Volume 9, issue 7
https://doi.org/10.5194/gmd-9-2315-2016
https://doi.org/10.5194/gmd-9-2315-2016
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

Abstract. Meteorological time series with 1 h time steps are required in many applications in geoscientific modelling. These hourly time series generally cover shorter periods of time compared to daily meteorological time series. We present an open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST). This software package is written in Python and comprises simple methods to temporally downscale (disaggregate) daily meteorological time series to hourly data. MELODIST is capable of disaggregating the most commonly used meteorological variables for geoscientific modelling including temperature, precipitation, humidity, wind speed, and shortwave radiation. In this way, disaggregation is performed independently for each variable considering a single site without spatial dependencies. The algorithms are validated against observed meteorological time series for five sites in different climates. Results indicate a good reconstruction of diurnal features at those sites. This makes the methodology interesting to users of models operating at hourly time steps, who want to apply their models for longer periods of time not covered by hourly observations.

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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.