The linkage between Numerical Weather Prediction (NWP) and climate modeling existed since the 60s when the "Geophysical Fluid Dynamics Laboratory" (GFDL), a predominantly climate modeling center, was formed owing to the success of the first experimental NWP led by pioneers such as von Neumann, Charney, and many others, including the GFDL founding father Joe Smagorinsky, at Princeton's Institute for Advanced Studies. Smagorinsky's vision was that "the increasing power of computers would allow one to move beyond simulating the evolution of the atmosphere for a few days, as in weather prediction, and move toward the simulation of the Earth's climate". Climate modeling, that emphasizes robustness of the "weather statistics", has underwent significant transformation since that time, including advancements in dynamical and physical processes that were beyond reach just a decade ago. While global climate models are highly diversified (partially due to the need for IPCC ensembles), Regional NWP developments in the US during past few decades, on the other hand, take on a different philosophy. In particular, there is what I called a "C-grid superiority complex" that may have hindered the advancement of "meso-scale" model since the 90s, with effectively a single model 
dominates the mesoscale NWP research.