An Evaluation of QPF from the WRF, NAM, and GFS Models Using Multiple Verification Methods over a Small Domain
AbstractThe ARW model was run over a small domain centered on Iowa for 9 months with 4 km grid spacing to better understand the limits of predictability of short term (12 h) quantitative precipitation forecasts (QPFs) that might be used in hydrology models. Radar data assimilation was performed to reduce spinup problems. Three grid to grid verification methods, as well as two spatial techniques, neighborhood and object based, were used to compare the QPFs from the high resolution runs with coarser operational GFS and NAM QPFs to verify QPFs for various precipitation accumulation intervals and on two grid configurations with different resolutions. In general, NAM had the worst performance not only for model skill but also for spatial feature attributes as a result of the existence of large dry bias and location errors. The finer resolution of NAM did not offer any advantage in predicting small scale storms compared to the coarser GFS. WRF had a large advantage for high precipitation thresholds. A greater i.