The Costs and Losses of Integrating Social Sciences and Meteorology

Abstract

I would like to talk about some of the challenges (and opportunities) we face in a highly interdisciplinary journal such as Weather, Climate, and Society (WCAS). A recent discussion with a colleague here at the National Center for Atmospheric Research (NCAR) helped crystallize some of my thoughts about what we are trying to do with WCAS. This colleague stopped by to ask my advice on a manuscript concept he was considering submitting to Weather, Climate, and Society. He is an outstanding research meteorologist who has been working with a team on models to improve flood warning systems in developing countries. He was interested in demonstrating the economic benefits of the improved warning system and wanted to apply a cost‐loss model. Based on his reading of a number of articles in meteorological journals, the cost‐loss model was the method of choice for demonstrating economic value. My initial reaction was largely visceral, because I have a dislike for the cost‐loss model. The cost‐loss model has been used extensively in the meteorology literature as ‘‘the economic model,’’ but it does not really show up in the economics literature (I should note that my Ph.D. is in economics and, in six years of graduate school, I never once heard of the cost‐lossmodel).Asimplesearchfor‘‘cost‐lossmodel’’inAMSpublicationsyields161hits. A similar search of the economic literature yielded none. Meteorologists have used and built upon the cost‐loss model to explore issues of forecast value for at least 50 yr (e.g., Savage 1951). It is reasonable then that when meteorologists look to extend the meteorology‐economics literature that they come upon the cost‐loss model because that is the most prevalent approach in their literature. The problem this economist has withthe model is not that it is incorrect.In fact,the basic modelisconsistent with economic theory on a very basic level. My concern is that the cost‐loss model as used in most articles in the meteorology literature does not even begin to capture the full value of economics and build upon the extensive literature in economics on the value of information and decision making under uncertainty. It is simply too simple. As stated in Katz and Lazo (2010), ‘‘Prototypical decision-making models can be viewed as greatly simplified versions of real-world situations,retainingonlytheirmost salient features.Thecost–loss decision-making modelisthe most basic and frequently used member of this category.’’ However, although there certainly are exceptions, in the meteorology literature ‘‘economics’’ has largely come to mean ‘‘cost‐loss model.’’ That said, the first issue of Weather, Climate, and Society contained an article based on a theoretical extension of the cost‐loss model (Millner 2009; in fact, I recommend reading Millner for an explanation of the cost‐loss model). In that article, Millner showed that incorporating a specific behavioral feature in the cost‐loss model resulted in net benefit estimates potentially significantly lower than those derived from the basic model. His article demonstrated that behavioral aspects limit the effectiveness of the cost‐loss model. I feel this should be read as a demonstration that the meteorological community needs to move beyond the cost‐loss model. Building in part on the limitations of the cost‐loss model that