What motivates model developments? A multi-perspective case study from snow physics models.

Historically, snow physics models were developed to forecast avalanches. Over the years, their application has broadened to hydrological, climatological, ecological and permafrost studies to cite but a few. However, the structure of mid-latitude mountain snowpacks upon which snow physics models are based (generally deep snowpack with snow denser at the bottom than at the top because of compaction) differs considerably from the structure of high latitude snowpacks (generally shallow snowpack with dense wind-compacted snow at the top and large snow crystals at the bottom). This difference has been known for decades to be a potentially large source of uncertainty when simulating heat exchanges in the Arctic and Antarctic. Therefore, with Arctic warming having consequences on the global climate, why have snow physics modellers not developed a model with a high latitude or “arctic snowpack” yet? Taking this question as a case-study to understand the role that subjective decisions play at every phase of model developments, we interviewed more than twenty snow physics model users (e.g. ecologists, anthropologists, remote sensing and climate scientists) and developers to understand the following: what motivates model developments? What or who determines which parametrization, which process is to be prioritised over others? What role does the research question play? What about funding or staff availability? We will show that positionality, anchoring bias and interpersonal relationships play far more prominent roles in the physical sciences that commonly acknowledged and will draw lessons from the social sciences to increase transparency in our modelling practice.