Title: Why Weather Matters to Climate Models

Abstract: Among the joys of climate research one rarely lists the flurry of 
questions from friends, family and others following unusual weather events. 
These questions range from gleeful challenges like "Where's global warming 
now?" to breathless worries of "How bad will it get?" Maybe you don't get 
these. I do. The point is climatologists study climate not weather and as 
the old saw goes "weather is not climate." Of course this is only half-true 
as climatologists do study weather, only statistically, and weather is 
indeed a main ingredient of climate, and yes, even those pesky unusual 
weather events contribute to it.
        It shouldn't be surprising then to learn that climate models simulate  
weather. What may be surprising, though, is that the veracity of this  
simulated weather is rarely assessed in a direct way. Instead, traditional 
methods of model validation rely on long-term averages. Which is consistent 
with the "weather is not climate" sentiment.
        We will present an alternative approach to model validation, one that  
makes use of our knowledge of weather processes, such as their patterns of 
occurrence, structure and behavior to test climate models in a new and 
informative way. Our aim is to broaden traditional methods of climate model 
validation not replace them, which is to say that we preserve our 
climatologist's eye by taking a statistical view of weather rather than the 
case-by-case perspective of the meteorologist. To do this we have a method 
for identifying, following and delimiting a target weather phenomenon (in 
this case mid-latitude cyclones). We will show how this tool can be used to 
identify specific model deficiencies as well as open up new research 
possibilities. Examples and pretty pictures will be shown.