Machine Learning for Environmental Sciences
Rachel Furner is a PhD student at British Antarctic Survey, which has recently opened up its new AI Lab, that aims to foster the application of various machine learning (and […]
Rachel Furner
PhD Student
Career
- 2018-present: PhD student at DAMTP, partnered by the British Antactic Survey (BAS), supervised by Emily Shuckburgh at BAS and Peter Haynes at DAMTP
- 2016-2018: Coordinator of the CCIMI and CMIH
- 2008-2016: Coastal modelling scientist, UK Met Office
- 2004-2007: BA Mathematics, University of Oxford
Research
Rachel is part of the Dynamical Meteorology & Oceanography research group at DAMTP, and the Polar Oceans group at BAS. Her current research looks at novel modelling techniques for the ocean carbon cycle, with a focus on big data approaches, such as machine learning. Her past work involved process based modelling of the phsical ocean, specifically the UK shelf seas.
Research interests
- Data Driven methods for Carbon Cycle Modelling
- Physical Oceanography
- Ocean Modelling
- Machine Learning
O’Dea, E., Furner, R., Wakelin, S., Siddorn, J., While, J., Sykes, P., . . . Hewitt, H. (2017). The CO5 configuration of the 7 km Atlantic Margin Model: large-scale biases and sensitivity to forcing, physics options and vertical resolution. Geoscientific Model Development, 10(8), 2947-2969. doi:10.5194/gmd-10-2947-2017
Furner, R., Williams, J., Horsburgh, K., Saulter A. (2015). “Adapting NEMO for use as the UK operational storm surge forecasting model – initial tidal results”. Paper presented at the 2nd JCOMM Scientific and Technical Symposium on Storm Surges, Key West, Florida, November
Siddorn, J., & Furner, R. (2013). An analytical stretching function that combines the best attributes of geopotential and terrain-following vertical coordinates. Ocean Modelling, 66, 1-13. doi:10.1016/j.ocemod.2013.02.001
Hyder, P., While, J., Arnold, A., O’Dea, E., Furner, R., Siddorn, J., . . . Sykes, P. (2013). Evaluating a new NEMO-based Persian/Arabian Gulf tidal operational model. Journal of Operational Oceanography, 6(1), 3-16. doi:10.1080/1755876x.2013.11020140
O’Dea, E. J., Arnold, A. K., Edwards, K. P., Furner, R., Hyder, P., Martin, M. J., . . . Liu, H. (2012). An operational ocean forecast system incorporating NEMO and SST data assimilation for the tidally driven European North-West shelf. Journal of Operational Oceanography, 5(1), 3-17. doi:10.1080/1755876x.2012.11020128
Publications from NERC Open Research Archive
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Read more of: Machine Learning for Environmental Sciences
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Celebrating International Women’s Day
Read more of: Celebrating International Women’s DayOn International Women’s Day (8 March 2021), we mark and celebrate women working at British Antarctic Survey (BAS). We showcase the diversity of roles and specialities of those working in […]
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CCfCS event: Panel discussion on IPCC special reports
Read more of: CCfCS event: Panel discussion on IPCC special reportsIf you would like to hear more about the recent IPCC special reports on Oceans and Cryosphere in a Changing Climate and Climate change and Land Use, come to our panel discussion on Thursday 28 November. You will hear short summaries of the reports and join in the debate.
