10.4 Statistical Reliability of Quantitative Precipitation Forecasts from the High-Resolution Rapid Refresh

Wednesday, 25 January 2017: 4:45 PM
604 (Washington State Convention Center )
Eric P. James, CIRES/Univ. of Colorado and NOAA/ESRL/GSD, Boulder, CO; and T. Alcott and C. R. Alexander

Quantitative precipitation forecasts (QPF) from the 3-km High-Resolution Rapid Refresh (HRRR)

model fill a variety of needs within the user community, from short-term flash flood forecasting

to day-ahead probability of precipitation outlooks. Comparison with Stage IV quantitative

precipitation estimates (QPE) reveals that HRRR QPF is relatively reliable for many 6-h

precipitation thresholds, but exhibits a high bias in occurrence of heavy rainfall rates. In

conjunction with the development of a HRRR “time-lagged ensemble” (HRRR-TLE), a realtime

bias correction has been implemented, using the last several weeks of forecasts, to permit

statistically reliable forecasts of the probability of exceedance of precipitation thresholds. In a

novel application, a five-year dataset of HRRR QPF is also being interrogated to derive an

estimate of the “probable maximum precipitation” (PMP) quantity at each gridpoint, a value

that is important for safe dam engineering.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner