The Bristol CMIP6 Data Hackathon
The Bristol CMIP6 Data Hackathon formed part of the Met Office Climate Data Challenge Hackathon series during 2021, bringing together around 100 UK early career researchers from a wide range of environmental disciplines. The purpose was to interrogate the under‐utilised but currently most advanced c...
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Published in | Weather Vol. 77; no. 6; pp. 218 - 221 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
01.06.2022
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Abstract | The Bristol CMIP6 Data Hackathon formed part of the Met Office Climate Data Challenge Hackathon series during 2021, bringing together around 100 UK early career researchers from a wide range of environmental disciplines. The purpose was to interrogate the under‐utilised but currently most advanced climate model inter‐comparison project datasets to develop new research ideas, create new networks and outreach opportunities in the lead up to COP26. Experts in different science fields, supported by a core team of scientists and data specialists at Bristol, had the unique opportunity to explore together interdisciplinary environmental topics summarised in this article. |
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AbstractList | The Bristol CMIP6 Data Hackathon formed part of the Met Office Climate Data Challenge Hackathon series during 2021, bringing together around 100 UK early career researchers from a wide range of environmental disciplines. The purpose was to interrogate the under‐utilised but currently most advanced climate model inter‐comparison project datasets to develop new research ideas, create new networks and outreach opportunities in the lead up to COP26. Experts in different science fields, supported by a core team of scientists and data specialists at Bristol, had the unique opportunity to explore together interdisciplinary environmental topics summarised in this article. |
Author | Goldsworth, Fraser Cole, Sebastian Turner, Charles Wilson, Jamie D. Thomson, Stephen I. Seviour, William Lord, Natalie Kennedy‐Asser, Alan Chen, Ying Evans, Dafydd Gwyn Smith, Christopher Turner, Katherine Screen, James Amos, Matt Worthington, Emma Walker, Erin Hudson, Phoebe Bamber, Jonathan Lo, Eunice Sieradzan, Katie Lo, Brian Harbord, Sophie Williams, Daniel Hughes, Chris Bilge, Tarkan Stone, Emma J Chaudhri, Alex Mitchell, Dann Booth, Alice Vishwakarma, Bramha Dutt Williams, Shannon Vosper, Emily Tomson, Stephen Ball, Emily Mitchell, Dann M. Weeks, Jennifer Williams, Ned Fulton, James Grinsted, Aslak Kelly, Stephen MacLeod, David Henry, Matthew Zaforemska, Aleksandra Gohar, Laila Masukwedza, Innocent Hemani, Gibran Harris, Bethan Mecking, Jennifer Tanner, Al Mackie, Anna Bamber, Jonathan L. Avrutin, Sandy Brimicombe, Chloe Stone, Emma J. Baker, Jessica Li, Xiaorong Vogt‐Vincent, Noam Thurlby, Natalie Holley, Patricia Browse, Jo MacLeod, David M. Sauter, Christoph Walsh, Amber Ying, Rui Kuwertz, Emma Ng, Kevin Morten, Joanne Adloff, Markus Tunnicli |
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Cites_doi | 10.1126/sciadv.1500682 10.5194/os-17-181-2021 10.1002/asl.946 10.7163/GPol.2013.1 10.1002/gdj3.102 10.1073/pnas.0909493107 10.1357/0022240054663231 10.1016/j.biocon.2019.06.033 10.1016/j.tree.2006.06.004 10.3354/meps09985 10.1126/science.1237190 10.1029/2019GL085782 10.1002/wea.4199 |
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Copyright | 2022 The Authors. Weather published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society 2022. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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References | 2021; 8 2012; 470 2015; 1 2010; 107 2019; 20 2021 2021; 17 2013; 86 2019; 237 2007 2005; 64 2020; 47 2013; 341 2022; 77 e_1_2_3_2_1 e_1_2_3_6_1 e_1_2_3_5_1 e_1_2_3_4_1 e_1_2_3_3_1 e_1_2_3_12_1 e_1_2_3_9_1 e_1_2_3_13_1 e_1_2_3_8_1 e_1_2_3_14_1 e_1_2_3_7_1 e_1_2_3_15_1 e_1_2_3_10_1 e_1_2_3_11_1 |
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