Certain biases are definitely occurring in climate models, although they are able to do specific things roughly correctly. Some biases can be related to a lack of complete understanding of the climate processes, but many are caused by lack of sufficient spatial resolution to represent the processes explicitly, even when we do understand the processes quite well. Some biases do not greatly degrade a model's ability to represent departures from normal fairly well, as we simply look at the departure from the model's own historical average, even if that average is different from that of the real world. However, sometimes a model's bias can ruin its reproduction of what we are interested in knowing. In the case of climate change and ENSO, we note that many models make the current cold tongue too cold. Then, when we look for effects of climate change on SST, there is a danger that warming in the eastern tropical Pacific SST may be overdone because they have too cold a starting point. We need to work on the causes of this too cold a starting point to get a more trustworthy picture of the likely rate of warming in the coming decades. As for hurricanes, these are detected on an individual basis by weather models, not climate models, using initial observations. For changes in the expected prevalence or intensity of hurricanes in the future, the climate change models would be used, and would involve changes in the atmosphere and the SST outside of the tropical Pacific (most notably the Atlantic), and model biases would definitely come into play and affect the nature and trustworthiness of the predictions of possible changes in seasonal hurricane activity.