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%0 Journal Article
%1 kelder2022workflow
%A Kelder, T.
%A Marjoribanks, T. I.
%A Slater, L. J.
%A Prudhomme, C.
%A Wilby, R. L.
%A Wagemann, J.
%A Dunstone, N.
%D 2022
%I Wiley
%J Meteorological Applications
%K casestudy climateservices colleagues unseen
%N 3
%R 10.1002/met.2065
%T An open workflow to gain insights about low-likelihood high-impact weather events from initialized predictions
%U https://doi.org/10.1002/met.2065
%V 29
@article{kelder2022workflow,
added-at = {2022-05-05T15:44:50.000+0200},
author = {Kelder, T. and Marjoribanks, T. I. and Slater, L. J. and Prudhomme, C. and Wilby, R. L. and Wagemann, J. and Dunstone, N.},
biburl = {https://www.bibsonomy.org/bibtex/284d9b3ca9f9e8e8f505d075f8cc7b611/pbett},
doi = {10.1002/met.2065},
interhash = {59ce2059f7b71d47c3408061d0f4811b},
intrahash = {84d9b3ca9f9e8e8f505d075f8cc7b611},
journal = {Meteorological Applications},
keywords = {casestudy climateservices colleagues unseen},
month = may,
number = 3,
publisher = {Wiley},
timestamp = {2022-05-05T15:44:50.000+0200},
title = {An open workflow to gain insights about low-likelihood high-impact weather events from initialized predictions},
url = {https://doi.org/10.1002/met.2065},
volume = 29,
year = 2022
}