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data http://eprints.org/relation/isVersionOf http://edata.bham.ac.uk/id/document/5947 http://eprints.org/relation/isVolatileVersionOf http://edata.bham.ac.uk/id/document/5947 http://eprints.org/relation/issmallThumbnailVersionOf http://edata.bham.ac.uk/id/document/5947 archive 568 disk0/00/00/11/50 2024-08-01 13:59:04 2024-08-01 14:12:08 2024-08-01 13:59:04 data_collection show Ng Kelvin S. k.s.ng@bham.ac.uk 0000-0002-1464-1701 Leckebusch Gregor C. g.c.leckebusch@bham.ac.uk 0000-0001-9242-7682 Hodges Kevin I. k.i.hodges@reading.ac.uk 0000-0003-0894-229X 10col_life Extreme rainfall, Mei-yu front, causality-guided approach, decadal prediction system This data accompanies the peer-reviewed article Kelvin S. Ng et al. (2024): Improvement of decadal predictions of monthly extreme Mei-yu rainfall via a causality guided approach. Environ. Res.: Climate https://doi.org/10.1088/2752-5295/ad6631 Please see Data_description.pdf for more details. 2024-08-01 published University of Birmingham https://doi.org/10.25500/edata.bham.00001150 Dataset research-data@contacts.bham.ac.uk School of Geography, Earth and Environmental Sciences other UK-China Research and Innovation Partnership Fund, Newton Fund na na na TRUE East Asia