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Thinking Strategically: The Appropriate Use of Metrics for the Climate Change Science Program
CCSP strategic goals
Milestones, products, payoffs
The CCSP strategic plan does not contain operational performance goals, and the committee found that the five CCSP goals are indeed stated in terms that are too broad to serve as a framework for developing meaningful metrics. Consequently, the committee considered the 224 milestones, products, and payoffs identified in the CCSP strategic plan, which provide greater specificity about what the program is trying to achieve. The committee found that the milestones, products, and payoffs could be grouped into eight themes for which metrics could be developed. These themes are
improve data sets in space and time (e.g., create maps, databases, and data products; densify data networks);
improve estimates of physical quantities (e.g., through improvement of a measurement);
improve understanding of processes;
improve representation of processes (e.g., through modeling);
improve assessment of uncertainty, predictability, or predictive capabilities;
improve synthesis and assessment to inform;
improve the assessment and management of risk; and
improve decision support for adaptive management and policy making.
The phrasing of these eight themes either matches or is closely allied with the phrasing of nearly all of the program’s milestones, products, and payoffs. In addition, the themes represent a sequence in scientific investigation, starting from the development of new or better observations, to an improved understanding of processes, to an improved capability to predict or forecast future climate changes, and finally to improved use of information to better serve society. As such, they offer an organizing framework for developing metrics for assessing the full range of CCSP activities.
The committee proceeded under the assumption that metrics would be very different for each of these themes and that developing quantifiable measures for many elements of the CCSP would be difficult. For example, metrics to assess improvements in CO2 observing systems seemed likely to differ from metrics to evaluate new knowledge about processes that control