ncPick: A Lightweight Toolkit for Extracting, Analyzing, and Visualizing ECMWF ERA5 NetCDF Data

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Bibliographic Details
Published in:Data vol. 10, no. 11 (2025), p. 178-188
Main Author: Sreten, Jevremović
Other Authors: Arnaut Filip, Kolarski Aleksandra, Srećković, Vladimir A
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MDPI AG
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022 |a 2306-5729 
024 7 |a 10.3390/data10110178  |2 doi 
035 |a 3275509338 
045 2 |b d20250101  |b d20251231 
100 1 |a Sreten, Jevremović 
245 1 |a <i>ncPick</i>: A Lightweight Toolkit for Extracting, Analyzing, and Visualizing ECMWF ERA5 NetCDF Data 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a The European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) datasets provide a rich source of climatological data. However, their Network Common Data Form (NetCDF) structure can be a barrier for researchers who are not experienced with specialized data tools or programming languages. To address this challenge, we developed ncPick, a lightweight, Windows-based application designed to make ERA5 data more accessible and easier to use. The software enables users to load NetCDF files, select points of interest manually or through shapefiles, and export the data directly to Comma-separated values (CSV) format for further processing in common tools such as Excel, R, or within ncPick itself. Additional modules allow for quick visualization, descriptive statistics, interpolation, and the generation of time-of-day heatmaps, as well as practical data handling functions such as merging and downsampling CSV files based on the time-axis. Validation tests confirmed that ncPick outputs are consistent with those from established tools (such as Panoply). The toolkit was found to be stable across different Windows systems and suitable for a range of datasets. While it has limitations with very large files and does not include automated data download for version 1 of the software, ncPick offers an accessible solution for researchers, students, and other professionals seeking a reliable and intuitive way to work with ERA5 NetCDF data. 
653 |a Machine learning 
653 |a Datasets 
653 |a Accessibility 
653 |a Software packages 
653 |a Toolkits 
653 |a Exports 
653 |a Interpolation 
653 |a Windows (computer programs) 
653 |a Programming languages 
653 |a Traffic control 
653 |a Researchers 
653 |a Python 
653 |a Weather forecasting 
653 |a Visualization 
653 |a Software 
653 |a Time of use 
700 1 |a Arnaut Filip 
700 1 |a Kolarski Aleksandra 
700 1 |a Srećković, Vladimir A 
773 0 |t Data  |g vol. 10, no. 11 (2025), p. 178-188 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
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856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3275509338/fulltextwithgraphics/embedded/Y2VX53961LHR7RE6?source=fedsrch 
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