Rain affects us all. Even more so if you live in the tropics. We don’t fully understand the processes that link tropical rainfall to its environmental properties. Our forward models (i.e. climate models) partially capture these processes through convective parameterization schemes, which in turn host several poorly-constrained parameters. Aspects of both mean and variability in our climate simulations remain sensitive to these parameters. Our approach to surmounting these issues is to build simple models—guided by observations—for the statistics of tropical rain. In this talk, I will show two examples of how we leverage the proliferation of tropical rainfall observations to inform both our conceptual understanding and our forward models. In the first example, I demonstrate how different statistical properties of tropical rain between land and ocean regions can be unified within a single framework. In the second half, I tackle the still-open question of convective organization: why does rain tend to clump up in space? I show how a minimal stochastic model of tropical dynamics can reproduce certain observed statistics of convective organization.