Research publications
| Year | Publication details |
| 2022 | Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) Clouds. Tazi, Kenza, Emiliano Díaz Salas-Porras, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, Nis Meinert. https://arxiv.org/abs/2211.13052 |
| 2022 | Identifying the Causes of Pyrocumulonimbus (PyroCb). Salas-Porras, Emiliano Diaz, Kenza Tazi, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, and Nis Meinert. " arXiv preprint arXiv:2211.08883 (2022). |
| 2022 | Kernel Learning for Explainable Climate Science. Lalchand, Vidhi, Kenza Tazi, Talay M. Cheema, Richard E. Turner, and Scott Hosking. arXiv preprint arXiv:2209.04947 (2022). |
| 2022 | Using Probabilistic Machine Learning to Better Model Temporal Patterns in Parameterizations: a case study with the Lorenz 96 model. Parthipan, Raghul, Hannah M. Christensen, J. Scott Hosking, and Damon J. Wischik. EGUsphere (2022): 1-27. |
| 2022 | Don't Waste Data: Transfer Learning to Leverage All Data for Machine-Learnt Climate Model Emulation. Parthipan, Raghul, and Damon J. Wischik. arXiv preprint arXiv:2210.04001(2022). |
| 2022 | Localized impacts and economic implications from high temperature disruption days under climate change. Summers, Tim, Erik Mackie, Risa Ueno, Charles Simpson, J. Scott Hosking, Tudor Suciu, Andrew Coburn, and Emily Shuckburgh. Climate Resilience and Sustainability 1, no. 2 (2022): e35. |
| 2022 | Optimisation of a global climate model ensemble for prediction of extreme heat days. Virdee, Mala, Emily Shuckburgh, Carl Henrik Ek, Ieva Kazlauskaite, and Markus Kaiser. arXiv preprint arXiv:2211.16367 (2022). |
| 2022 | Cohort-based long-term ozone exposure-associated mortality risks with adjusted metrics: A systematic review and meta-analysis. Sun, Haitong Zhe, Pei Yu, Changxin Lan, Michelle WL Wan, Sebastian Hickman, Jayaprakash Murulitharan, Huizhong Shen, Le Yuan, Yuming Guo, and Alexander T. Archibald. " The Innovation (2022): 100246. |
| 2022 | Attention‐Based Machine Vision Models and Techniques for Solar Wind Speed Forecasting Using Solar EUV Images. Brown, Edward JE, Filip Svoboda, Nigel P. Meredith, Nicholas Lane, and Richard B. Horne. Space Weather 20, no. 3 (2022): e2021SW002976. |
| 2022 | AI applications in forest monitoring need remote sensing benchmark datasets. Lines, E., Allen, M., Cabo, C., Calders, K., Debus, A., Grieve, S., Miltiadou, M., et al.2022 IEEE International Conference on Big Data Workshop BDA4S 2021. https://doi.org/10.17863/CAM.91304 |
| 2022 | On the Expressive Power of Geometric Graph Neural Networks. Joshi, Chaitanya K., Cristian Bodnar, Simon V. Mathis, Taco Cohen, and Pietro Liò. In NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations. |
| 2022 | Beobench: a toolkit for unified access to building simulations for reinforcement learning, Arduin Findeis, Fiodar Kazhamiaka, Scott Jeen, Srinivasan Keshav. e-Energy '22: Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, June 2022 Pages 374–382. |
| 2022 | Accurate tropical forest individual tree crown delineation from RGB imagery using Mask R-CNN. Hickman, Sebastian HM, James George Clifford Ball, Tobias D. Jackson, Xian Jing Koay, James Hirst, William Jay, Melaine Aubry-Kientz, Gregoire Vincent, and David A. Coomes. bioRxiv (2022). |
| 2022 | Tree species classification from complex laser scanning data in Mediterranean forests using deep learning. Matthew J. Allen, Stuart W. D. Grieve, Harry J. F. Owen, Emily R. Lines. Methods in Ecology and Evolution, 18 Sep 2022. |
| 2021 | Multivariate climate downscaling with latent neural processes. Vaughan, Anna, Nicholas D. Lane, and Michael Herzog. Climate Change AI Workshop. 2021 |
| 2021 | Defining Southern Ocean fronts using unsupervised classification. Simon D. A. Thomas, Daniel C. Jones, Anita Faul, Erik Mackie, and Etienne Pauthenet. Ocean Sci., 17, 1545–1562, 2021 https://doi.org/10.5194/os-17-1545-2021 |
| 2021 | Spatial Resolved Surface Ozone with Urban and Rural Differentiation during 1990–2019: A Space–Time Bayesian Neural Network Downscaler. Sun, Haitong, Youngsub Matthew Shin, Mingtao Xia, Shengxian Ke, Michelle Wan, Le Yuan, Yuming Guo, and Alexander T. Archibald. Environmental Science & Technology (2021). |
| 2021 | Vision transformers and techniques for improving solar wind speed forecasts using solar EUV images. Svoboda, Filip, Edward Brown, Nigel P. Meredith, and Nicholas D. Lane. NeurIPs, (2021). |