intellectual interest, requiring backgrounds in advanced mathematics and physics—and that are equally as challenging as these fields in and of themselves—generally is lost. The field seems to be more successful in recruiting students attracted to the idea of weather forecasting or policy-oriented climate research than in recruiting students with a fundamental mathematical and physical curiosity about the atmosphere and ocean. This state of affairs may result in part from the way the atmospheric sciences and climate science promote research to funding agencies by promising improved forecasts.

Once enrolled at a university, the contemporary graduate student often finds himself or herself beholden to the goals of his or her professor’s research grant, goals that are increasingly burdened by the necessity of producing short-term deliverables or of demonstrating broader impacts on society. This system blurs the line between student and employee. The student with a bright idea or who is singularly motivated to pursue a particular problem, however important that problem may be, may not be able to fit his or her interests into the available funding slots, even if the faculty are sympathetic to the idea.

Workshop participants noted that another challenge of engaging new people in the field is that the development and refinement of model parameterizations is not seen as an attractive career path by most young researchers. In the United States, most large modeling centers maintain groups dedicated to developing and improving parameterizations, but these groups tend to be small and, consequently, overtaxed. Moreover, these positions often are funded as support scientist or software engineer positions.

The current funding environment is subtly influencing the choices that researchers make, in ways that may inhibit progress in understanding and simulating climate and weather. For example, the development of instrumentation and the execution of field measurement programs, which are crucial for progress in a number of areas discussed at the workshop, require relatively long time horizons. Increasing emphasis on deliverables in some funding agencies together with tenure cycles at universities acts to discourage such labor-intensive and time-consuming endeavors in favor of activities such as simulation experiments with existing numerical models, where deliverable results often can be obtained in a short time.

In many areas the development of improved representations of physical processes requires knowledge of a broad variety of physics. For



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