Picture: Autumn leaves in a puddle. Credit: Hannah Domsic (Unsplash).
Despite the importance of understanding the global water cycle, high quality long-term global rainfall datasets are hard to find. For this reason, we developed a new global land-based daily precipitation dataset called Rainfall Estimates on a Gridded Network – REGEN aimed at facilitating studies to understand changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity.
REGEN utilises multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network – Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA, and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD).
This resulted in an unprecedented station density compared to existing datasets. After performing substantial quality control and gridding the data using advanced methods to cover the globe this study documents the development of the dataset and guidelines for best practices for users.
- Paper: Contractor, S., Donat, M. G., Alexander, L. V., Ziese, M., Meyer-Christoffer, A., Schneider, U., Rustemeier, E., Becker, A., Durre, I., and Vose, R. S.: Rainfall Estimates on a Gridded Network (REGEN) – a global land-based gridded dataset of daily precipitation from 1950 to 2016, Hydrol. Earth Syst. Sci., 24, 919–943, https://doi.org/10.5194/hess-24-919-2020, 2020.