TY - JOUR
T1 - Modelling weather risk preferences with multi-criteria decision analysis for an aerospace vehicle launch
AU - Caruzzo, Amaury
AU - Belderrain, Mischel Carmen Neyra
AU - Fisch, Gilberto
AU - Young, George S.
AU - Hanlon, Christopher J.
AU - Verlinde, Johannes
N1 - Funding Information:
This study was supported by the National Council for Scientific and Technological Development of Brazil – CNPq (grant 142212/2011-3 and 232898/2014-6) and CAPES (grant 14552/2013-2). The authors are grateful to the Editors and the anonymous reviewers who offered valuable comments to improve the quality of this work, to Maria A. Pirone and William H. Brune for support and also to all the Brazilian Space Programme interviewees for their availability and their help in our research. This research started while the first author was affiliated with the Aeronautics Institute of Technology – ITA (Brazil). The process presented in this paper is subject to an International Patent Application (PCT/BR2016/050232) filed by ITA.
Publisher Copyright:
© 2018 Royal Meteorological Society
PY - 2018/7
Y1 - 2018/7
N2 - 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.
AB - 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.
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U2 - 10.1002/met.1713
DO - 10.1002/met.1713
M3 - Article
AN - SCOPUS:85043234741
SN - 1350-4827
VL - 25
SP - 456
EP - 465
JO - Meteorological Applications
JF - Meteorological Applications
IS - 3
ER -