2.5 Situational awareness and forecast confidence: new tools for anticipating high-impact events in the West

Wednesday, 9 January 2013: 11:45 AM
Ballroom F (Austin Convention Center)
Randy Graham, NOAA/NWS, Salt Lake City, UT; and T. I. Alcott, N. Hosenfeld, R. H. Grumm, and C. Smallcomb

From 18–23 Jan 2010 a series of winter storms impacted the western U.S. During this period, a record-setting system produced severe convection, high winds, and heavy rain and snow on 21–22 Jan. Standardized anomalies derived from the GFS Ensemble Forecast System (GEFS) indicated the potential for this historic storm a week in advance, demonstrating the utility of anomalies for increasing forecaster confidence and situational awareness. This event will be used to showcase an anomaly-based situational awareness display for streamlining the identification and analysis of significant forecast anomalies. This display highlights the specific elements, levels, and times where significant anomalies are forecast to occur, allowing forecasters to quickly distill information in an era where attention is divided by an overwhelming number of available datasets.

An effort is currently underway in NWS Western Region to expand the functionality of the existing situational awareness display, including (1) increased user customizability, (2) the development of a new upper-air climatology based on the 0.5x0.5-degree Climate Forecast System Reanalysis, (3) use of a wider range of ensemble data (incorporating output from multiple national centers) for analysis of major synoptic features, and (4) use of the Short-Range Ensemble Forecast system to anticipate convective, fire weather and sensible weather extremes. To complement the technical efforts, an initiative is taking place to subjectively evaluate existing forecast confidence products, including not only the GEFS anomalies but ECMWF and SREF output as well. The objective is to come up with a “top-5” type list of recommended products, both deterministic and probabilistic, to routinely evaluate forecast confidence with respect to high-impact weather events.

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