Understanding User Decision Making and the Value of Improved Precipitation Forecasts: Lessons From a Case Study

Understanding User Decision Making and the Value of Improved Precipitation Forecasts: Lessons... A case study of the impact of improved precipitation forecasts on the snow-fighting operations of the New York State Thruway is reported. The goal was to use currently available data and literature on forecast process, communication, and use in conjunction with observations and interviews with key decision makers to derive a model that yields estimates of value to users based on a model of their decision processes rather than an optimal decision-making model. That goal proved too ambitious due to limitations in available data. A major lesson learned from this research is the importance of improved, ongoing data collection to support studies of use and value of weather information. A more holistic approach to understanding and realizing forecast value is needed, that is, one in which information (both of forecast skill and usage) centered on the decision process is collected in a much more intensive manner than is presently the case. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

Understanding User Decision Making and the Value of Improved Precipitation Forecasts: Lessons From a Case Study

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/BAMS-85-2-223
Publisher site
See Article on Publisher Site

Abstract

A case study of the impact of improved precipitation forecasts on the snow-fighting operations of the New York State Thruway is reported. The goal was to use currently available data and literature on forecast process, communication, and use in conjunction with observations and interviews with key decision makers to derive a model that yields estimates of value to users based on a model of their decision processes rather than an optimal decision-making model. That goal proved too ambitious due to limitations in available data. A major lesson learned from this research is the importance of improved, ongoing data collection to support studies of use and value of weather information. A more holistic approach to understanding and realizing forecast value is needed, that is, one in which information (both of forecast skill and usage) centered on the decision process is collected in a much more intensive manner than is presently the case.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Feb 22, 2004

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