Principal component proxy tracer analysis

TL;DR

This paper presents a novel method for reconstructing long-lived tracers like ozone by correlating principal components with sparse measurements, validated on simulated and satellite data, achieving accurate ozone reconstructions.

Contribution

The paper introduces a principal component-based proxy tracer analysis method for dynamical reconstruction of tracers, applicable to satellite and simulated data.

Findings

Root-mean-square error of 0.20 ppmv for ozone reconstruction

Effective 60-day lead time with five principal components

Validated on both simulated tracer and satellite ozone data

Abstract

We introduce a powerful method for dynamical reconstruction of long-lived tracers such as ozone. It works by correlating the principal components of a matrix representation of the tracer dynamics with a series of sparse measurements. The method is tested on the 500 K isentropic surface using a simulated tracer and with ozone measurements from the Polar Aerosol and Ozone Measurement (POAM) III satellite instrument. The Lyapunov spectrum is measured and used to quantify the lifetime of each principal component. Using a 60 day lead time and five (5) principal components, cross validation of the reconstructed ozone and comparison with ozone sondes return root-mean-square errors of 0.20 ppmv and 0.47 ppmv, respectively.