The PIs propose to examine tropical Pacific biases. They propose a different approach for understanding the systematic errors and why promising sensitivities fail to translate from one model to the next. They suggest that the errors in the mean state are, at least in part, due to errors in the simulated ENSO; and that the errors in the simulated ENSO are due to errors in the statistics of the tropical atmospheric weather. That is, if there are large errrors in the simulation of weather statistics, then the climatic simulation is seriously degraded. The PIs hypothesize that the changes – or lack thereof – in the weather statistics can explain the large differences in model sensitivity. They propose a series of novel weather noise forced CGCM simulations designed to understand the differences in coupled model biases and sensitivities. These experiments leverage their experitise with the NOAA Climate Forecast System, the NCAR Community Climate System Model and the interactive ensemble coupling strategy that has been developed by the PI.