We play a series of incentivized laboratory games with risk-exposed coffee farmers in Guatemala to understand the demand for index-based excess rainfall insurance. By varying risk in systematic ways over a large number of games, we can use numerical techniques to estimate explicit flexible utility functions for each player, and with these to simulate demand under alternate scenarios. We introduce the presence of the types of novel drought risks likely to be driven by global warming and find that these lead to sharp decreases in flood insurance demand, even when the objective benefit of the flood insurance is held constant. The possibility of using group-based mechanisms to smooth idiosyncratic risk is introduced by playing games with group-based products, and by asking farmers to anticipate and deliberate on the extent to which their groups would effectively smooth risk. Our results indicate that elevated weather-driven variance has very different effects if it occurs inside of insured or uninsured states, and that groups provide a very imperfect way of protecting farmers from these risks.