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Paul A. Hirschberg, Richard J. Lind, Steven J. Bolduc, and Russell L. Elsberry

Mesoscale weather systems that develop in the central United States are often forced by environmental features that have formed far upstream over the conventional data-sparse Pacific Ocean. Although remotely sensed observations, such as satellite retrievals, are becoming more numerous and accurate, they still may not have the resolution necessary to enhance global model-based analyses and forecasts over this region. These global model products are the primary source of lateral boundary conditions that have been found to have large impacts on the downstream forecast skill of regional mesoscale models over the United States. In addition, the temporal and spatial resolution of the current rawinsonde network along the West Coast may not be sufficient to detect and measure mesoscale flow features as they move inland. During the STORM-FEST experiment in February–March 1992, a “Picket Fence” of seven special rawinsonde stations were interspersed among the seven regular rawinsonde sites from Port Hardy, British Columbia, to San Diego, California. All sites obtained observations every 3 h rather than the normal 12 h. The objective of the Picket Fence was to examine the feasibility of using extra observations in time and space to improve upstream boundary conditions for forecasts of mesoscale weather events in the central United States. As a first step in examining the potential boundary condition impact of the Picket Fence, fluxes of mass, heat, momentum, potential energy, kinetic energy, and moisture across the West Coast resolved with various spatial and temporal combinations of Picket Fence data are compared with the 12-h regular upper-air sites as the standard. When a wave system crossed the middle of the Picket Fence, significantly different fluxes were calculated with the full spatial and 3-h Picket Fence observations. For other systems that crossed near the margins of the Picket Fence, only small changes were detected by the additional observations.

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Paul A. Hirschberg, Elliot Abrams, Andrea Bleistein, William Bua, Luca Delle Monache, Thomas W. Dulong, John E. Gaynor, Bob Glahn, Thomas M. Hamill, James A. Hansen, Douglas C. Hilderbrand, Ross N. Hoffman, Betty Hearn Morrow, Brenda Philips, John Sokich, and Neil Stuart

The American Meteorological Society (AMS) Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty (the Plan) is summarized. The Plan (available on the AMS website at is based on and intended to provide a foundation for implementing recent recommendations regarding forecast uncertainty by the National Research Council (NRC), AMS, and World Meteorological Organization. It defines a vision, strategic goals, roles and respon- sibilities, and an implementation road map to guide the weather and climate enterprise (the Enterprise) toward routinely providing the nation with comprehensive, skillful, reliable, and useful information about the uncertainty of weather, water, and climate (hydrometeorological) forecasts. Examples are provided describing how hydrometeorological forecast uncertainty information can improve decisions and outcomes in various socioeconomic areas. The implementation road map defines objectives and tasks that the four sectors comprising the Enterprise (i.e., government, industry, academia, and nongovernmental organizations) should work on in partnership to meet four key, interrelated strategic goals: 1) understand social and physical science aspects of forecast uncertainty; 2) communicate forecast uncertainty information effectively and collaborate with users to assist them in their decision making; 3) generate forecast uncertainty data, products, services, and information; and 4) enable research, development, and operations with necessary information technology and other infrastructure. The Plan endorses the NRC recommendation that the National Oceanic and Atmospheric Administration and, in particular, the National Weather Service, should take the lead in motivating and organizing Enterprise resources and expertise in order to reach the Plan's vision and goals and shift the nation successfully toward a greater understanding and use of forecast uncertainty in decision making.

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