The MÉRA Data Extraction toolkit

Meteorological applications

article

Levent Görgü¹  Daniel Hawtree²  Michael J. O'Grady¹  Conor Muldoon¹  Bartholomew Masterson³  Wim G. Meijer³  John J. O'Sullivan²  Gregory M. P. O'Hare⁴ 

[1] UCD School of Computer Science, University College Dublin;Dooge Center for Water Resources Research, UCD School of Civil Engineering, University College Dublin;UCD School of Biomolecular & Biomedical Science, University College Dublin;School of Computer Science and Statistics, Trinity College Dublin

关键词: big data;    climate data;    forecasting data;    forecasting systems;    model development;    remote sensing;   

DOI  :  10.1002/met.2111

学科分类：社会科学、人文和艺术（综合）

来源: Wiley

【 摘 要 】

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.

【 授权许可】

CC BY|CC BY-NC|CC BY-NC-ND