Wednesday, 25 January 2017
4E (Washington State Convention Center )
Run in real-time, with 10 members at 3-km, the National Center for Atmospheric Research’s (NCAR) experimental ensemble prediction system (EPS) represents the next generation of short range numerical weather prediction (NWP). While most convection permitting EPSs use external models to produce initial conditions, the NCAR Ensemble is unique in that it utilizes a limited-area, continuously cycling mesoscale ensemble Kalman filter (EnKF) data assimilation system to generate diverse initial conditions. Its high resolution ensembles, computed from adequately diverse initial conditions, allow the NCAR ensemble to capture the large spatial variability and quantify the inherent uncertainty of precipitation forecasts in areas of complex terrain. To date, quantitative precipitation forecasts (QPF) remain largely untested at cloud-permitting grid spacings (i.e., 4-km or less) over complex terrain in the western U.S. In this study, we assess the capabilities of QPF produced by the NCAR Ensemble using observations collected by Snow Telemetry (SNOTEL) stations at mountain locations across the western U.S. Emphasis is placed on identifying the capabilities of the control member (and hence individual members) in capturing the characteristics of precipitation events at these locations, as well as the reliability and resolution of probabilistic forecasts derived from the EPS.
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