Visualization is a major part of any scientific work, serving to communicate results in an inclusive way. Whether figures, plots, or graphs, they all play a central role in publications, teaching, and public outreach. Furthermore, visualization is one of the integral parts besides automatic tests of the data that help to ensure the quality of meteorological data from one or more weather stations of measurement networks. This last aspect, in particular, requires the automatic generation of figures and their dynamic presentation.
Our homepage, named “Dolueg” for “here, look” in German dialect/Swiss-German, allows researchers and the public to view relevant and up-to-date data in an easy way that includes further information such as measurement height, device type, and other relevant metadata. Dolueg has proven its value for the detection of malfunctioning devices, showcasing interesting meteorological phenomena, and above all ensuring that the flow of data from our stations into the database can be easily checked and fixed, if need be. Because Dolueg is free, easy to use, and adjustable, it is especially suitable for measurement network operators, that is, when time series are constantly collected and are in need of visual quality control in addition to any automatic checks.
Dolueg consists of two parts: a website created in PHP, a general purpose scripting language mainly used for web servers, and a selection of Python functions that generate a suite of plots. The Python pipeline produces figures frequently which are then dynamically (and in a mobile-friendly way) presented in categories according to the file name of the figure. The grouping reduces the time and effort required to add new figures. Each component can of course be used on its own as well.
The relevant code for these two components is freely available: the website framework (Fig. 1a) and PHP functions can be found at https://github.com/spirrobe/dolueg2page, and the Python code is hosted at https://github.com/spirrobe/dolueg2figures. Both repositories contain detailed instructions for setup and examples.
Several kinds of figures for time series data are available (Figs. 1b–e): wind roses for one or several stations drawn over a map background, the default line plots, isopleth/contour graphs as time of day versus day of year, and mesh plots of measurement values at several heights. Each type can be further customized in terms of colors, titles, and more.
All figures are by default created as SVG (scalable vector graphics), making them precise, zoomable, usually small in size, and compatible with all common browsers, even without a web server. Figures can be downloaded and, if need be, edited in open-source or commercial vector graphics programs, and they can be directly inserted into documents. The choice of SVG as default makes our figures suitable for reports, lectures, and other applications.
We acknowledge the help, input, and corrections from several generations of student helpers that worked with Dolueg and thus ensured a continuous improvement.
FOR FURTHER READING
Stauffer, R., G. J. Mayr, M. Dabernig, and A. Zeileis, 2015: Somewhere over the rainbow: How to make effective use of colors in meteorological visualizations. Bull. Amer. Meteor. Soc. ,96, 203–216, https://doi.org/10.1175/BAMS-D-13-00155.1.
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