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Efficient Statistical Characterization for High-Resolution Geophysical Fields

This study introduces a fast method for robust statistical characterization of high-resolution geophysical data through efficient PDF estimation. By utilizing a non-uniform Fast Fourier Transform approach, the method achieves a remarkable 100x speed-up, enabling quick analysis of large datasets with significant computational savings. The enhanced efficiency of this approach allows for broader application in geophysics research and big data analyses, contributing to ongoing theoretical advancements. (Limit: 500 characters)

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Efficient Statistical Characterization for High-Resolution Geophysical Fields

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  1. A Fast New Method for Statistically Characterizing High-Resolution Geophysical Fields Objective Geophysical research often calls for robust and thorough statistical characterization of model output and data (e.g., estimating probability density functions—PDFs). Existing methods for estimating PDFs are generally computationally expensive, which inhibits their use for high-resolution datasets. 100x speed-up • Approach • Used a non-uniform, Fast Fourier Transform method to speed-up a robust new PDF estimation method by 100x • Applied this method to estimate PDFs of atmospheric wind from 1TB of high-resolution model output in ~1K CPU hours (vs the previously-required 100K) • Used this characterization to inform ongoing theoretical developments. Impact This work provides a computationally efficient statistical method that can be applied to a wide range of geophysics analyses. The 100x speed-up allows this method to be routinely used in big-data analysis problems. O'Brien, T. A., Collins, W. D., Rauscher, S. A., Ringler, T. D. (2014), Reducing the computational cost of the ECF using a nuFFT: A fast and objective probability density estimation method, Computational Statistics and Data Analysis, In Press, doi:10.1016/j.csda.2014.06.002

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