Modelling weather risk preferences with multi‐criteria decision analysis for an aerospace vehicle launch. (6th March 2018)

• Record Type: Journal Article
• Authors: Caruzzo, Amaury; Belderrain, Mischel Carmen Neyra; Fisch, Gilberto; Young, George S.; Hanlon, Christopher J.; Verlinde, Johannes
• Is Part Of: Meteorological applications. Volume 25:Number 3(2018)
• Page Start: 456
• Page End: 465
• Publication Date: 2018-03-06
• Subjects: weather decision index -- decision under uncertainty -- multi‐attribute decision model -- aerospace meteorology -- sounding rocket launch -- Brazilian Space Programme; Meteorology -- Periodicals; Meteorological services -- Periodicals; 551.5
• DOI: 10.1002/met.1713
• Languages: English
• ISSNs: 1350-4827

Abstract

ABSTRACT: Decision‐making under weather uncertainty is a challenge in several fields. When the decision process involves many stakeholders, frequently with different interpretations of the meteorological information, the process is even more complex. This work provides a quantitative decision model with a new index (called the weather decision index, WDI) to support the stakeholders in making real‐world choices according to their preferences regarding the uncertainty of weather information. The integrated model combines several methods such as problem structuring, multi‐criteria analysis, scenario planning and probabilistic weather forecast techniques. As a demonstration, the model was applied in the sounding rocket launch mission in the Brazilian Space Programme. The WDI captured stakeholders' behaviour related to three meteorological information attributes (probability, lead‐time and variables) and modelled the most important judgements of the decision maker; low probability or an extended lead‐time depreciates the meteorological information, and weather variables are not considered in the decisions, even with forecasts of extreme events. Modelling with the WDI brings a new perspective in weather‐related decision problems. The choice of alternatives no longer depends on a necessarily simplified optimization analysis, but rather on the decision maker's preferences about the possibly nonlinear trade‐offs between forecast reliability and lead‐time. The findings also increase understanding of the forecast decision maker's preferences and how to improve weather risk communication. The WDI provides a starting point for several applications, including early warning systems or climate change adaptation, for which reliable uncertainty estimates are accessible. Abstract : The model proposed captures a decision maker's attitude related to three meteorological information attributes: probability, lead‐time and the values of variables. The findings validate the existence of motivational risk‐decision‐making biases related to weather/climate issues. The application of the index brings a new perspective in weather‐related decisions once the decision maker's preferences about the trade‐offs between probability and lead‐time are considered.