ED23D-0326: Knowledge-Based Environmental Context Modeling
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GC41B-1022: Biennial-Aligned Lunisolar-Forcing of ENSO: Implications for Simplified Climate Models
In the last month, two of the great citizen scientists that I will be forever personally grateful for have passed away. If anyone has followed climate science discussions on blogs and social media, you probably have seen their contributions.
Keith Pickering was an expert on computer science, astrophysics, energy, and history from my neck of the woods in Minnesota. He helped me so much in working out orbital calculations when I was first looking at lunar correlations. He provided source code that he developed and it was a great help to get up to speed. He was always there to tweet any progress made. Thanks Keith
Kevin O’Neill was a metrologist and an analysis whiz from Wisconsin. In the weeks before he passed, he told me that he had extra free time to help out with ENSO analysis. He wanted to use his remaining time to help out with the solver computations. I could not believe the effort he put in to his spreadsheet, and it really motivated me to spending more time in validating the model. He was up all the time working on it because he was unable to lay down. Kevin was also there to promote the research on other blogs, right to the end. Thanks Kevin.
There really aren’t too many people willing to spend time working analysis on a scientific forum, and these two exemplified what it takes to really contribute to the advancement of ideas. Like us, they were not climate science insiders and so will only get credit if we remember them.
4 thoughts on “AGU 2017 posters”
Just making a all too rare visit to Context Earth. Glad to hear of the interest in your work.
Your blog post earlier this month on the use of Laplace’s tidal equations was a gem. Also, glad to see your latest ENSO modelling contains predictions out to 2020. It looks as if you have successfully predicted the current la Nina conditions. Well done.
That said, I do prefer cross-validation on existing data (including paleo) rather than relying on predictions on one peak that may or may not pan out in the coming year.
I take your point about a highly accurate reconstruction of past behaviour being more valuable scientifically than an isolated prediction of the future, but from the point of view of “impact” on the scientific community (influential co-authors…?) and certainly the public successful future predictions count for a lot.
Bill, For validating statistically against future predictions, I think it’ll require at least 5 consecutive ElNino matches. If the peaks are ~4 yrs apart, that’ll require at least 20 yrs to collect data.
On the other hand, if this approach is further evaluated against historical, experimental, theoretical, and sim results it could be more quickly accepted, or rejected as per the evidence. That’s the only way it can advance beyond the heuristic stage. Another way to frame the approach is that this model was not devised to work as a prediction tool, but to explain the geophysics.