Keywords
uncertainty, model selection, model decisions, interviews, science and technology studies
Start Date
16-9-2020 10:40 AM
End Date
16-9-2020 11:00 AM
Abstract
Give different people the same recipe and ingredient, the final dish will still taste different. The same is true when talking about modelling; give different modelers the same model, the results might still look different. It is widely acknowledged that environmental models are prone to uncertainty, still scientists and decision makers often perceive models as being something “objective”. However, in the process from problem to simulation, there are several steps that require the modeler’s input and decisions. These can influence or even steer the model’s result. As such, models should be perceived as social constructs. Addor & Melsen (WRR, 2019) demonstrated that model choice is closely related to the institute of the first author. This leads to a geographical bias in model use across the world. In this follow-up study, modelers from three different institutes were interviewed (interviews took place in Feb – May 2020), to track their motivations for certain model decisions, for instance related to resolution and data use. The interviews provided insights into idiosyncrasies of modelers, and revealed modelling cultures. Based on these insights, we will eventually be able to quantify the role of the modeler on model output.
Model decisions and modelling cultures
Give different people the same recipe and ingredient, the final dish will still taste different. The same is true when talking about modelling; give different modelers the same model, the results might still look different. It is widely acknowledged that environmental models are prone to uncertainty, still scientists and decision makers often perceive models as being something “objective”. However, in the process from problem to simulation, there are several steps that require the modeler’s input and decisions. These can influence or even steer the model’s result. As such, models should be perceived as social constructs. Addor & Melsen (WRR, 2019) demonstrated that model choice is closely related to the institute of the first author. This leads to a geographical bias in model use across the world. In this follow-up study, modelers from three different institutes were interviewed (interviews took place in Feb – May 2020), to track their motivations for certain model decisions, for instance related to resolution and data use. The interviews provided insights into idiosyncrasies of modelers, and revealed modelling cultures. Based on these insights, we will eventually be able to quantify the role of the modeler on model output.
Stream and Session
false