Information length as a useful index to understand variability in the global circulation
Eun-jin Kim, James Heseltine, Hanli Liu

TL;DR
This paper introduces the use of information length derived from time-dependent PDFs to analyze variability in Earth's atmosphere, revealing complex altitude-dependent patterns and emphasizing the importance of high-latitude regions.
Contribution
It presents a novel application of information length to atmospheric data, providing new insights into variability and transport processes beyond traditional statistical measures.
Findings
Information length increases with altitude, especially for flows and shears.
Time-dependent PDFs are generally non-Gaussian.
High-latitude/altitude regions are critical for atmospheric information transport.
Abstract
With improved measurement and modelling technology, variability has emerged as an essential feature in non-equilibrium processes. While traditionally, mean values and variance have been heavily used, they are not appropriate in describing extreme events where a significant deviation from mean values often occurs. Furthermore, stationary Probability Density Functions (PDFs) miss crucial information about the dynamics associated with variability. It is thus critical to go beyond a traditional approach and deal with time-dependent PDFs. Here, we consider atmospheric data from the Whole Atmosphere Community Climate Model (WACCM) model and calculate time-dependent PDFs and the information length from these PDFs, which is the total number of statistically different states that a system passes through in time. Time-dependent PDFs are shown to be non-Gaussian in general, and the information…
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Taxonomy
TopicsClimate variability and models · Atmospheric and Environmental Gas Dynamics · Complex Systems and Time Series Analysis
