Weather forecasts of all durations are dependent on accurate forecasts of clouds. Even the well-known 3-km NOAA HRRR model was found to have errors in clouds resulting in forecasts of too warm temperatures and too little precipitation. In our study including model experiments in three different seasons, we found two key ideas that can improve future storm forecasts: better use of observations to start the weather models to avoid initial dryness and to brighten model cloud forecasts by assuming that cloud droplets are slightly smaller than previously prescribed. These changes can improve NOAA forecasts for aviation, energy, and severe weather in successors to the current HRRR weather model. Moreover, we show that comparisons with surface radiation measurements are essential for identifying causes for systematic biases in NWP models.