What is already known:
What this study adds:
While non-severe hail is perceived as having little direct societal impact, it can negatively impact the quantitative precipitation estimation (QPE), something that can have significant societal impact. Miscalculated QPE can lead to mismanagement of emergency services, poor hydrologic forecasts, and mismanagement of water resources. By determining the proportion of convective storms that are associated with any hail but, particularly small or non-severe, we can begin to understand the extent to which QPE is affected by small hail. The current hydrometeor classification algorithms have little skill at discriminating between small hail and large raindrops. Thus choosing a threshold at which to make adjustments to QPE due to hail is difficult. We can use meteorological Phenomena Identification near the Ground (mPING) crowd-sourced weather reports to make a rough estimate of how common small hail is at the surface within convective storms. By pairing mPING data with composite reflectivity within identified storms, no clear hail/no hail threshold emerges, and so adjusting QPE based on reflectivity values is unlikely to result in much improvement in QPE.