Abstract

Impact-based weather forecasting requires forecasters to predict what weather might do (impact information), rather than solely what weather might be (meteorological information). In a collaboration between the UK Met Office, UK psychologists, and weather scientists in Indonesia, Malaysia, the Philippines, and Vietnam, the present study employed Judgment Analysis and decision strategy comparisons to better understand weather scientists' impact severity judgments. In the Judgment Analysis Task, weather scientists (from Indonesia, Malaysia, the Philippines, and Vietnam) made numerical and categorical severity judgments for 70 hypothetical heavy rainfall events, each described via six impacts (e.g., number of deaths, number of people affected). The hypothetical impacts were generated from a multivariate distribution estimated from a distribution of real rainfall events. Subsequently, participants provided categorical severity classifications for a list of impact values for each type of impact (Threshold Identification Task) to aid the identification of decision strategies. In all four countries, weather scientists' severity judgments were best predicted by incorporating all six impacts via a compensatory judgment strategy. However, considerable individual differences were identified in the weights assigned to the different impacts and in the identified thresholds for each impact's categorical severity classification. To improve impact-based forecasting, meteorological agencies should seek to enhance consistency among forecasters.

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