Zobrazeno 1 - 10
of 67
pro vyhledávání: '"John K Hillier"'
Publikováno v:
Environmental Research Letters, Vol 14, Iss 8, p 084045 (2019)
Intensity-duration-frequency (IDF) curves usefully quantify extreme precipitation over various durations and return periods for engineering design. Unfortunately, sparse, infrequent, or short observations hinder the creation of robust IDF curves in m
Externí odkaz:
https://doaj.org/article/f635f3242dab4e1f8d7462c826ece502
Autor:
John K Hillier, Ioannis A Kougioumtzoglou, Chris R Stokes, Michael J Smith, Chris D Clark, Matteo S Spagnolo
Publikováno v:
PLoS ONE, Vol 11, Iss 7, p e0159489 (2016)
Sediments beneath modern ice sheets exert a key control on their flow, but are largely inaccessible except through geophysics or boreholes. In contrast, palaeo-ice sheet beds are accessible, and typically characterised by numerous bedforms. However,
Externí odkaz:
https://doaj.org/article/15195140b472426cb9c608346483d7e0
Publikováno v:
Environmental Research Letters, Vol 12, Iss 11, p 114009 (2017)
Fluvial floods are typically investigated as ‘events’ at the single basin-scale, hence flood management authorities may underestimate the threat of flooding across multiple basins driven by large-scale and nearly concurrent atmospheric event(s).
Externí odkaz:
https://doaj.org/article/1cafcc4471bd4ef486224083a3650a34
Publikováno v:
Geoscience Communication, Vol 5, Pp 11-15 (2022)
Insights from a geoscience communication activity, verified using preliminary investigations with an artificial neural network, illustrate that observation of humans' abilities can help design an effective artificial intelligence or “AI”. Even gi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e99ce775b29bad948c230658e292e13
https://gc.copernicus.org/articles/5/11/2022/gc-5-11-2022.pdf
https://gc.copernicus.org/articles/5/11/2022/gc-5-11-2022.pdf
Insights from a geoscience communication activity, verified using preliminary investigations with an artificial neural network, illustrate that observation of humans’ abilities can help design an effective machine learning algorithm - colloquially
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::685bdf4eb0a5b04295b535fd4ba45447
https://doi.org/10.5194/egusphere-egu22-1437
https://doi.org/10.5194/egusphere-egu22-1437
Publikováno v:
Nature Climate Change. 10:595-598
In risk analysis, it is recognized that hazards can often combine to worsen their joint impact, but impact data for a rail network show that hazards can also tend to be mutually exclusive at seasonal timescales. Ignoring this overestimates worst-case
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::309d2de75edfeb3b282392bf37671ba3
https://doi.org/10.1038/s41558-020-0832-y
https://doi.org/10.1038/s41558-020-0832-y
Autor:
Karin van der Wiel, Colin Manning, Tianyi Zhang, Elisa Ragno, Emanuele Bevacqua, Alexandre M. Ramos, Ana Bastos, Fabrizio Durante, Pauline Rivoire, Suzana Blesic, Carlo De Michele, Jakob Zscheischler, Joaquim G. Pinto, Wenyan Wu, Anaïs Couasnon, Kate Saunders, Edoardo Vignotto, John K. Hillier, Sérgio C. Oliveira, Andreia Ribeiro
Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be454098010bec40f2dbf1c4583c128a
https://doi.org/10.1002/essoar.10507809.1
https://doi.org/10.1002/essoar.10507809.1