For decades there has been a mismatch between the expectations of the operational numerical weather prediction (NWP) and climate prediction community and the model research and development community. The principal measure of success of work that is supported by a typical short-term (e.g., 3-year) research grant is the number, quality, and impact of the research publications that result from any project. Researchers receive no reward for developments that become “operational,” so there is little incentive to do what is viewed as extra work to transform research results into operational methods or procedures. There is a view that the scholarly publications speak for themselves, which has been described as a “loading dock” approach—the research results are made available to the operational prediction community via peerreviewed publications (left on the loading dock), and it is up to users to figure out how to use the results. There are some nascent efforts in which the transition to operations is the objective rather than a by-product of research, e.g., the NOAA Climate Test Bed activity.4
From the operational community point of view, there are a great many constraints imposed by operations that should be taken into account by the researchers who seek to improve the operational predictions. In order to effect a transition from research to operations, they argue, the research community needs to modify its developments to conform to the constraints of operations so that their results can become useful, and the operational center needs to provide infrastructure support for the research community to use the operational model to conduct its research. The mismatch between the two communities’ expectations has been called the “valley of death,” that is, a communication and interaction gap. There is clearly a need to better align the two communities and provide adequate resources so that good ideas can be more rapidly and effectively transformed into operational practice.
Finding 9.3: The expectations of the research community and the operational prediction community are not well aligned.
As indicated throughout this report (Chapters 1 and 10), a market for climate model information already exists. Given the growing need for information about future climate from climate models, involvement of the private sector could be beneficial. The private sector is already engaged through consulting companies that provide customized and downscaled climate information. A number of private companies successfully sell climate information that depends on climate models. Examples include Prescient Weather, Ltd.,5 Atmospheric and Environmental Research Inc.,6 Risk Management