PC Proxy: A Method for Dynamical Tracer Reconstruction

TL;DR

This paper introduces the PC Proxy method for dynamical tracer reconstruction, demonstrating improved accuracy over traditional proxy methods in reconstructing ozone concentrations using principal components and error analysis.

Contribution

The paper presents a novel principal component proxy method that enhances global tracer reconstruction accuracy, especially for short-lived tracers, by incorporating error analysis and Lyapunov spectrum insights.

Findings

Achieved lower RMS errors in ozone reconstruction compared to classic proxy methods.

More effective for short-lived tracers and global reconstruction.

Demonstrated improved accuracy in Southern Hemisphere ozone prediction.

Abstract

A detailed development of the principal component proxy method of dynamical tracer reconstruction is presented, including error analysis. The method works by correlating the largest principal components of a matrix representation of the transport dynamics with a set of sparse measurements. The Lyapunov spectrum was measured and used to quantify the lifetime of each principal component. The method was tested on the 500 K isentropic surface with stratospheric ozone concentration measurements from the Polar Aerosol and Ozone Measurement (POAM) III satellite instrument during October and November 1998 and compared with the older proxy tracer method which works by correlating measurements with a single other tracer or proxy. Using a 60 day integration time and five (5) principal components, cross validation of globally reconstructed ozone and comparison with ozone sondes returned root-mean-square errors of 0.16 ppmv and 0.36 ppmv, respectively. This compares favourably with the classic proxy tracer method in which a passive tracer equivalent latitude field was used for the proxy and which returned RMS errors of 0.22 ppmv and 0.59 ppmv for cross-validation and sonde validation respectively. The method seems especially effective for shorter lived tracers and was far more accurate than the classic method at predicting ozone concentration in the Southern hemisphere over the same time period. It is also more effective when reconstruction is performed over the entire Earth rather than a single hemisphere allowing for seamless reconstruction of global fields.