CycloneCenter presents at another conference: AMS Annual Meeting
While there are only some results to talk about, the CycloneCenter science team is still active in presenting at national conferences. Last month was the AGU annual meeting, and this month was the annual meeting of the American Meteorological Society. Dr. Ken Knapp of NCDC presented an overall view about the science of CycloneCenter to a nearly packed group of tropical meteorologists. There was a lot of interest in the subject, including some chatter on the official AMS twitter account. This is a great example of how powerful social media can be.
Speaking of which, don’t forget that we have our own Twitter account, as well as a Facebook page. Make sure to like / follow us, as well as tell your friends and colleagues!
3 responses to “CycloneCenter presents at another conference: AMS Annual Meeting”
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- - August 31, 2016
Cyclone Center 
While I applaud the effort to engage users in the science of tropical cyclones, I really struggle to understand what benefit will come of this project.
What point is there on using voting systems to determine the validity of complex science? None other than to perhaps prove it is complex (if you need proof)! The fact that it takes years to train scientists how to do Dvorak properly should indicate that a few pages of instructions isn’t enough.
Some failings I can immediately think of include the following:
1. The Dvorak technique is not based on individual images – it is impossible to tell the intensity of a cyclone from one image – it is far more complex than that.
2. Determining the centre is the first step and can make a huge difference to the answer. Warning centres have access to more information than those single images to get that answer (microwave, scatterometry, Vis, observations, radar etc).
3. Visible imagery gives better answers than IR during the day-time for curved band images.
4. Your results will be biased to the images you provide as examples. In that regard the project is more about a pattern matching exercise – and Dvorak is much more than that.
5. Perhaps you would be better off having the expert discussion of the Dvorak image at that time of a selection of images that would help train users. The brief popup ‘training’ information is not sufficient.
6. No warning centre in their right mind will pay any credence to the output of this project, although they will be curious.
Your team are obviously talented, creative and motivated – how about engaging with warning centres to see what real value you can make to the science?
Thank you for your comments. One of the biggest challenges was balancing the rigor and complexity of the full Dvorak technique with the needs of communicating with a broader audience. We’re also aiming to create a homogeneous dataset that applies the same methods and data to analyze the full 32-year record.
We’re looking forward to having enough classifications to begin analyzing the results.