Contact: ana.marza@unil.ch
Office 3239, Géopolis Building
Ana Marza is a PhD student with a background in Earth Sciences and a passion for automation. Her current research (in partnership with Bern University of Applied Sciences) is in using machine learning algorithms to investigate the sources of sub-seasonal predictability. For example, do certain precursor patterns in Atlantic sea surface temperatures predict European weather in the coming 2-8 weeks?
Understanding when and why current numerical weather prediction models fail to make accurate predictions at sub-seasonal lead times is of great interest to stakeholders in the renewable energy industry.
Publications:
Towards the construction of regional marine radiocarbon calibration curves: an unsupervised machine learning approach.
Marza, A.-C., Menviel, L., and Skinner, L. C., Geochronology Discuss. [preprint] doi.org/10.5194/gchron-2023-26, in review, 2023.
Urban wildflower meadow planting for biodiversity, climate and society: An evaluation at King’s College, Cambridge.
Marshall, C. A. M., Wilkinson, M. T., Hadfield, P. M., Rogers, S. M., Shanklin, J. D., Eversham, B. C., Healey, R., Kranse, O. P., Preston, C. D., Coghill, S. J., McGonigle, K. L., Moggridge, G. D., Pilbeam, P. G., Marza, A. C., Szigecsan, D., Mitchell, J., Hicks, M. A., Wallis, S. M., Xu, Z., Eves-van den Akker, S. (2023)
Ecological Solutions and Evidence, 4, e12243.
doi.org/10.1002/2688-8319.12243