CondMerg: an open source implementation in R language of conditional merging for weather radars and rain gauges observations

• Published in: Earth science informatics 2017-03, Vol.10 (1), p.127-135
• Main Authors: Guenzi, D., Fratianni, S., Boraso, R., Cremonini, R.
• Format: Article
• Language: English
• Subjects: Climatology; Computer programs; Earth and Environmental Science; Earth Sciences; Earth System Sciences; Environmental monitoring; Extreme weather; Freeware; Geographic information systems; Information Systems Applications (incl.Internet); Merging; Ontology; Open source software; Radar; Rain; Rain gauges; Rainfall intensity; Rainfall measurement; Simulation and Modeling; Software; Software Article; Source code; Space Exploration and Astronautics; Space Sciences (including Extraterrestrial Physics; Weather; Weather forecasting
• ISSN: 1865-0473; 1865-0481
• DOI: 10.1007/s12145-016-0278-y

Monitoring of extreme events requires accurate measurement of rainfall intensities and merging weather radar data with ground information is a very common technique used to obtain the required precision. In order to do this, several methods exist but very few open source implementations are available. CondMerg is the first open source software developed in R language implementing the conditional merging method and some other experimental variants based on it. It is a cross-platform software, easily adaptable to different needs, optimized for batch processing of multiple events but also usable in near real time applications. For its execution it requires two inputs: a CSV file with rain gauges measurements and a geo-referred TIF file with weather radar quantitative precipitation estimations; main outputs are TIF files with merged observations although the code also returns information about cross-validation, with scatter plots and indexes. All TIF files are ready to be managed by common GIS software for easy visualization and analysis. Use of the program is very simple: execution can be interactive or non-interactive and, in both cases, it just requires to set some parameters at the beginning of the program and run it. The code has been tested on different extreme rain events occurred in the Piedmont region (northwestern Italy) showing improved accuracy of reconstructed rainfall fields.