Mental models of seasonal forecasting outputs among experts and decision-makers

De Carvalho, Bianca Franca
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ABSTRACT Climate data and change model outputs (such as seasonal forecasting maps as investigated in this study) are important ways in which climate variability and change is communicated. Typically, experts in climate science have used this data, however an increasing number of decision- and policy-makers have been making use of these outputs. A problem arises when climate scientists and decision-makers have different needs in terms of the ways in which these outputs should be composed. Thus, some of the outputs are deemed unusable by decision-makers. Mental models refer to the mental interpretations’ individuals have of situations or objects in the external world. These interpretations allow individuals to understand topics, draw conclusions and make predictions for the future. These ideas help individuals decide what sort of decisions they should be making. This study intended on matching the design models of the experts versus the mental models of the users. Non-probability, purposive, convenience sampling was used to draw a sample of experts and users of seasonal forecasting outputs. The study utilised semi-structured in-depth interviews where a set of seasonal forecasting outputs were shown to participants to determine if there were any noteworthy differences and similarities between the two. This was done using Interpretative Phenomenological Analysis (IPA). The sample consisted of four experts and ten users. Users were obtained from various sectors such as the Agricultural, Disaster Management, and Research sectors. It was found that there are considerable differences between the design models of the experts, and the mental models of the users. Major differences were specifically found in the interpretations of the skill maps, as well as a user’s ability to accurately decipher the acronyms used in the maps. There were also differences in interpretation found among the experts’ design models suggesting that there needs to be some level of correspondence among the seasonal forecasting expert community. This may be due to the fact that a number of organisations produce forecasts which each have their design style and way of interpreting the forecasts. Furthermore, there needs to be more collaboration between the two groups during the development and design of these forecast representations, as well as more opportunities for users to gain some knowledge on the seasonal forecasts and how to accurately utilise them in their decision-making.
A research project submitted in partial fulfilment of the requirements for the degree of ma by coursework and research report in the field of organizational Psychology in the Faculty of Humanities, University of the Witwatersrand, Johannesburg, 17 February 2020