I attended the Joint Statistical Meeting (JSM) 2018 in Vancouver, Canada. There I competed in the Sections on Statistical Computing and Graphics' Data Expo challenge, and my presentation on precipitation forecast accuracy won first prize amongst students. The presentation became a paper, and now it is set to be published in a special issue of Computational Statistics in 2021. PDF on page.
Executive summary: Rain forecasts consistently over-predict how often rain will fall. This is because the definition of a rainy day has a low bar: when 0.01 inches or more of precipitation falls. If this threshold is raised to 0.07 inches, accuracy improves dramatically by not defining days where it hardly rains as "rainy". Forecasts can be improved further by setting a unique threshold for each city.