Behemoth petaflop computing systems will propel atmospheric simulation science to unprecedented scales; yet individual node speed remains key for time-critical applications such as real-time forecasting or climate prediction. Even very large simulations able to exploit weak scaling will be limited by cost-performance in terms of energy and dollars consumed. For these reasons, new generations of multi- and many-core processors being mass produced for commercial IT and "graphical computing" (video games) are being scrutinized for their ability to exploit fine-grain parallelism abundant in atmospheric models. This presentation will describe work to identify and characterize expensive computational kernels from WRF, and community weather model, in terms of computational intensity, data parallelism, bandwidth requirements and memory footprint with the aim of accelerating weather and climate model using these new processors.