Scottish Alliance for Geoscience, Environment and Society

Dr Cecile Menard

Research interests:

Decision-making in modelling
Reducing uncertainty in snow models
The modeller as subject

Career history:

My research background is in snow modelling. During my PhD (2010) and first postdoc at the University of Edinburgh, I combined field work and model development to represent snow-vegetation interactions in snow models. Over the years, between a position at the Finnish Meterological Institute, one as a freelance scientist at CORES science and engineering and a return to the University of Edinburgh since 2017, my research has increasingly focused on uncertainties and errors in physically-based (snow) models. Most particularly, my research has shifted from the models to the modellers, but more broadly to the people doing the research. I am particularly interested in how the decisions, assumptions and biases researchers make and have influence the interpretation of our research.

Active research projects:

H2020 CHARTER (2020 – 2024) Advancing the adaptive capacity of Arctic communities to climatic and biodiversity changes.

The Big Thaw: gauging the past, present and future of our mountain water resources (2022 – 2026)

Recent publications:

Menard, C. B., & Shinton, S. (2022). The career paths of researchers in long-term employment on short-term contracts: Case study from a UK university. PLoS ONE, 17(9 September) doi:10.1371/journal.pone.0274486
Lemmetyinen, J and 25 others (2022). Airborne SnowSAR data at X and ku bands over boreal forest, alpine and tundra snow cover. Earth System Science Data, 14(9), 3915-3945. doi:10.5194/essd-14-3915-2022
Menard, C. B., and 31 others (2021). Scientific and Human Errors in a Snow Model Intercomparison, Bulletin of the American Meteorological Society, 102(1), E61-E79. DOI:10.1175/BAMS-D-19-0329.1
Essery, R. and 31 others (2020). Snow cover duration trends observed at sites and predicted by multiple models. Cryosphere, 14(12), 4687-4698. doi:10.5194/tc-14-4687-2020
Menard, C. B and 14 others (2019).: Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data, Earth Syst. Sci. Data, 11, 865–880,, 2019.

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