Less snow means less snowpack for spring melting. The snowpack is important because snow melts slowly, rather than running off immediately. The regional models rely on the global models for input. Problems arise when interpolating to increase the number of data points 30 times. One way the researchers tested the models was to try to simulate present-day extreme events, like El Nino or the drought of 1988.
Precipitation looks like a simple variable, but it is really complex.
The simulation also had difficulty with modeling drought. But eventually the coupled atmosphere-ocean models will show us how extreme events like El Nino can moderate or exacerbate the effects of global warming. This will modulate our understanding along with regional climate model results. For example, normally the Southwestern United States has relatively dry winters, but during an El Nino, winters become much wetter. If the current climate models predict that greenhouse warming increases Southwestern aridity, then the models of the future, which can predict El Nino events, might show an El Nino year as a welcome occurrence, mitigating the effects of the warming trend.