Description:	Gridded meteorological estimates are essential for many applications. Most existing meteorological datasets are deterministic and have limitations in representing the inherent uncertainties from both the data and methodology used to create gridded products. We develop the Ensemble Meteorological Dataset for Planet Earth (EM-Earth) for precipitation, mean daily temperature, daily temperature range, and dew-point temperature at 0.1° spatial resolution over global land areas from 1950 to 2019. EM-Earth provides hourly/daily deterministic estimates, and daily probabilistic estimates (25 ensemble members), to meet the diverse requirements of hydrometeorological applications. The deterministic estimates can be used like most meteorological datasets such as ERA5, MERRA2, and GPM IMERG. The probabilistic estimates can enable ensemble hydrological simulation and support easy uncertainty analysis. Please read the README.txt before downloading. The document introduces the dataset structure, including the meaning of different folders and their total sizes, which can help you decide the best downloading option. You can also contact the authors (guoqiang.tang@usask.ca) if you have problems downloading the dataset. Reference: Guoqiang Tang, Martyn P. Clark, Simon Michael Papalexiou. EM-Earth: The Ensemble Meteorological Dataset for Planet Earth. Bulletin of the American Meteorological Society. 2022
Authors:	Tang, Guoqiang; University of Saskatchewan Clark, Martyn; University of Saskatchewan Papalexiou, Simon Michael; University of Calgary
Keywords:	Precipitation Temperature Dew Point Temperature Ensemble data Probabilistic Global
Field of Research:	Earth and related environmental sciences > Hydrology > Hydrometeorology
Publication Date:	2022-02-03
Publisher:	Federated Research Data Repository / dépôt fédéré de données de recherche
Funder:	Global Water Futures (GWF)
URI:	https://doi.org/10.20383/102.0547
Geographic Coverage:	Place Name Global land
Appears in Collections:	Global Water Futures