Articles | Volume 27, issue 1
Research article
19 Feb 2020
Research article |  | 19 Feb 2020

Application of a local attractor dimension to reduced space strongly coupled data assimilation for chaotic multiscale systems

Courtney Quinn, Terence J. O'Kane, and Vassili Kitsios

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Subject: Predictability, probabilistic forecasts, data assimilation, inverse problems | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere | Techniques: Theory
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Cited articles

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Short summary
This study presents a novel method for reduced-rank data assimilation of multiscale highly nonlinear systems. Time-varying dynamical properties are used to determine the rank and projection of the system onto a reduced subspace. The variable reduced-rank method is shown to succeed over other fixed-rank methods. This work provides implications for performing strongly coupled data assimilation with a limited number of ensemble members on high-dimensional coupled climate models.