Abstract
Numerical forecasts of heavy warm-season precipitation events are verified using simple composite collection techniques. Various sampling methods and statistical measures are employed to evaluate the general characteristics of the precipitation forecasts. High natural variability is investigated in terms of its effects on the relevance of the resultant statistics. Natural variability decreases the ability of a verification scheme to discriminate between systematic and random error. The effects of natural variability can be mitigated by compositing multiple events with similar properties. However, considerable sample variance is inevitable because of the extreme diversity of mesoscale precipitation structures. The results indicate that forecasts of heavy precipitation were often correct in that heavy precipitation was observed relatively close to the predicted area. However, many heavy events were missed due in part to the poor prediction of convection. Targeted composites of the missed events ind... Abstract Numerical forecasts of heavy warm-season precipitation events are verified using simple composite collection techniques. Various sampling methods and statistical measures are employed to evaluate the general characteristics of the precipitation forecasts. High natural variability is investigated in terms of its effects on the relevance of the resultant statistics. Natural variability decreases the ability of a verification scheme to discriminate between systematic and random error. The effects of natural variability can be mitigated by compositing multiple events with similar properties. However, considerable sample variance is inevitable because of the extreme diversity of mesoscale precipitation structures. The results indicate that forecasts of heavy precipitation were often correct in that heavy precipitation was observed relatively close to the predicted area. However, many heavy events were missed due in part to the poor prediction of convection. Targeted composites of the missed events ind...

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