Category Archives: Azimuth Project

Complexity vs Simplicity in Geophysics

Originally posted on GeoEnergy Math:
In our book Mathematical GeoEnergy, several geophysical processes are modeled — from conventional tides to ENSO. Each model fits the data applying a concise physics-derived algorithm — the key being the algorithm’s conciseness but not…

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Posted in abstraction, American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, Azimuth Project, complex systems, control theory, differential equations, dynamical systems, eigenanalysis, information theoretic statistics, mathematics, Mathematics and Climate Research Network, mechanistic models, nonlinear systems, Paul Pukite, spectra, spectral methods, spectroscopy, theoretical physics, wave equations, WHT | Leave a comment

“Applications of Deep Learning to ocean data inference and subgrid parameterization”

This is another nail in the coffin of the claim I heard at last year’s Lorenz-Charney Symposium at MIT that machine learning methods would not make a serious contribution to advancements in the geophysical sciences. T. Bolton, L. Zanna, “Applications … Continue reading

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Posted in American Meteorological Association, American Statistical Association, artificial intelligence, Azimuth Project, deep learning, deep recurrent neural networks, dynamical systems, geophysics, machine learning, Mathematics and Climate Research Network, National Center for Atmospheric Research, oceanography, oceans, science, stochastic algorithms | Leave a comment