Data underlying the moisture tracking intercomparison project INSPIRE (IdentificatioN of Sources of Precipitation through an International Research Effort)

DOI:10.4121/0fb9c4e7-5596-4fec-9390-6da856bc3ba5.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/0fb9c4e7-5596-4fec-9390-6da856bc3ba5

Datacite citation style

Benedict, Imme; Weijenborg, Chris; Keune, Jessica; Ent, Ruud van der; Kalverla, Peter et. al. (2025): Data underlying the moisture tracking intercomparison project INSPIRE (IdentificatioN of Sources of Precipitation through an International Research Effort). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/0fb9c4e7-5596-4fec-9390-6da856bc3ba5.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset contains all simulations produced and used in the moisture tracking intercomparison project (INSPIRE) and is the base for all figures in the accompanying paper.

In this research we compare output from 14 moisture tracking methods that all simulated the moisture sources of precipitation for three selected extreme precipitation events (10-24 August 2022 over Pakistan, 22-28 February 2022 over Australia, 6-8 October over Scotland).

We also provide the re-analysis data to reproduce the figures on the synoptic weather situation during the events, and to compare the events with climatological values.

History

  • 2025-10-03 first online, published, posted

Publisher

4TU.ResearchData

Format

netCDF (.nc & .nc4) and text and csv files

Organizations

Meteorology and Air Quality, Environmental Sciences, Wageningen University & Research; Complete list of involved organizations is provided in the README file.

DATA

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