End users of urban meteorological information are heterogeneous and cover a vast spectrum of job roles, goals, needs, and understanding. Moreover, different end users may be more or less “advanced” in their use of meteorological data for a host of reasons. For example, some users have been working with the meteorological community and using weather data for a longer period of time. Some users have more resources (people, time, money, etc.). Some users have different knowledge (educational or experiential) bases. These differences can vary within and among groups and geographic areas. A given end user’s needs may also vary depending on the type of weather observation or phenomenon being considered. Acknowledging and understanding this heterogeneity is important for the urban meteorological community to better understand, interact with, and meet the needs of end users.

Furthermore, end users may be viewed as a “cascade” or “web” of individuals and groups with varying information needs and at varying levels of distance from raw urban meteorological data (Box 2.2). Given this interconnected relationship, it is important to recognize that there are multiple types of urban meteorological phenomena that have impacts on different types of users with different types of needs (see discussion in Dabberdt Abstract, Appendix A). Accurate information on low-risk, high-frequency events (e.g., regular weather patterns) may be of importance to a broad range of end users; whereas knowledge of high risk, low frequency events (e.g., a chemical release emergency) are of utmost importance to emergency planners responsible for public safety in such circumstances. To complicate long-term planning, both types of events will be affected by climate change. As such, end user needs span a wide range of urban meteorological information, from high frequency and low frequency events that may occur over the short and the long term.

As many participants noted at the workshop, end user needs with regard to urban meteorological information currently are not sufficiently being met (Table 2.1). In many cases, urban meteorologists are simply unaware of the precise data and information needs of the various information groups. However, there is a risk that if urban meteorologists do not provide the required information, disparate groups of end users will start generating (or will more fully develop) their own data streams, not necessarily following best practices in data collection, analysis, or interpretation, and producing not only redundant but also inconsistent information. More importantly, if the urban meteorological community does not provide required information, end users’ needs will not be met, reducing the effectiveness of their decision-making.



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