%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 }