The MÉRA Data Extraction toolkit. (11th January 2023)

• Record Type: Journal Article
• Authors: Görgü, Levent; Hawtree, Daniel; O'Grady, Michael J.; Muldoon, Conor; Masterson, Bartholomew; Meijer, Wim G.; O'Sullivan, John J.; O'Hare, Gregory M. P.
• Is Part Of: Meteorological applications. Volume 30:Number 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-11
• Subjects: big data -- climate data -- forecasting data -- forecasting systems -- model development -- remote sensing; Meteorology -- Periodicals; Meteorological services -- Periodicals; 551.5
• DOI: 10.1002/met.2111
• Languages: English
• ISSNs: 1350-4827

Abstract

Abstract: Historical meteorological datasets are indispensable for forming climatic models and the generation of weather forecasts. Such data are core to the training phase of prediction models and may also be harnessed for hydrological and environmental models. GRIB is the most common data format used in meteorology and represents the de facto standard for storing historical weather data. However, GRIB datasets are complex and do not constitute analysis‐ready data without additional preprocessing. The MÉRA dataset of the Met Eireann, the Irish meteorological service, is archetypical of such datasets, emerging from a high‐resolution climatic reanalysis of Irish weather data between 1981 and 2019. This article describes the MÉRA Data Extractor toolkit. This toolkit enables the intuitive, fast extraction and preprocessing of data from this extensive dataset. The toolkit is available as open source and will be of interest to those researching climate modelling in Europe. Abstract : Historical meteorological datasets are indispensable for forming climatic models and the generation of weather forecasts. The MÉRA dataset of the Met Eireann, the Irish meteorological service, emerged from a high‐resolution climatic reanalysis of Irish weather data between 1981 and 2019. This article describes the MÉRA Data Extractor toolkit, which enables intuitive, fast extraction and preprocessing of data from this extensive dataset.