A dynamical–system description of precipitation over the tropics and the midlatitudes

Yano, J.-I., Ambaum, M. ORCID: https://orcid.org/0000-0002-6824-8083, Dacre, H. ORCID: https://orcid.org/0000-0003-4328-9126 and Manzato, A. (2020) A dynamical–system description of precipitation over the tropics and the midlatitudes. Tellus Series A: Dynamic Meteorology and Oceanography, 72 (1). pp. 1-17. ISSN 0280-6495 doi: 10.1080/16000870.2020.1847939

Abstract/Summary

A dynamical–system approach is proposed to describe the relationship between precipitation and a chosen predictor. This is done by constructing a two dimensional phase space spanned by predictor and predictant. This study uses two sounding data sets from the Tropical Western Pacific and Friuli Venezia Giulia (FVG) over North–East Italy as representatives of the tropics and midlatitudes, in addition to a basin–scale average over the winter–period North Atlantic from global re–analysis data. In contrast to conventional correlation-based approaches, the proposed approach depicts periodic cycles, as well as discharge–recharge cycles as its nonlinear extension. Discharge–recharge cycles for tropical convection are identified by using both the convective available potential energy (CAPE) and the column–integrated water vapor (CIW) as predictors, as well as the baroclinicity for the winter–period North–Atlantic rain. On the other hand, the midlatitude rain, as seen over FVG as well as the winter–period North Atlantic, does not constitute a well–defined periodic cycle either with CAPE or CIW as a predictor. The inferred phase–space trajectories are more deterministic at peripheries of dense data areas rather than at a middle in the phase space. Data–dense areas in phase space, where traditional approaches primarily focus, are associated with more prediction uncertainties in our analysis due to more phase-velocity fluctuations.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/94526
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Taylor & Francis
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