Abstract
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.
Highlights
Continuous recordings of meteorological data are available since the late 18th century
In the late 20th century, the instrumentation of meteorological stations has been supplemented by the installation of automatic weather stations (AWS), which are capable of collecting meteorological data continuously with a frequency ranging from 1 h to 1 min or even shorter periods of time (Rassmussen et al, 1993)
Most of the methods included in MELODIST are parsimonious with respect to theory and computational costs
Summary
Continuous recordings of meteorological data are available since the late 18th century. This diagram has been compiled using two freely available data sets through querying the temporal coverage of available data of each data set: daily data are collected continuously in the Global Historical Climatology Network (GHCN) daily database (Menne et al, 2012; NOAA, 2015b), whereas the Integrated Surface Database (ISD) provides hourly time series of stations worldwide (Smith et al, 2011; NOAA, 2015a) This comparison reveals that the availability of hourly observations as provided by AWS is restricted to a few decades only.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
