Is precipitation a good metric for model performance?

Precipitation has often been used to gauge the performances of numerical weather and climate models, sometimes together with other variables such as temperature, humidity, geopotential, and clouds. Precipitation, however, is singular in that it can present a high spatial variability and probably the sharpest gradients amongst all meteorological fields. Moreover, its quantitative measurement is plagued with difficulties and there are even notable differences among different reference datasets. Several additional issues have yield to sometimes question its usefulness in model validation. This essay discusses the use of precipitation for model verification and validation, and the crucial role of highly precise and reliable satellite estimates, such as those from the core observatory of NASA's Global Precipitation Mission (GPM).