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Data Analysis and Non-local Parametr...

Brenowitz, Noah D.

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Data Analysis and Non-local Parametrization Strategies for Organized Atmospheric Convection.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data Analysis and Non-local Parametrization Strategies for Organized Atmospheric Convection./
作者:	Brenowitz, Noah D.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	170 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:	Dissertation Abstracts International78-12B(E).
標題:	Atmospheric sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10261197
ISBN:	9780355128321

Data Analysis and Non-local Parametrization Strategies for Organized Atmospheric Convection.
Brenowitz, Noah D.

Data Analysis and Non-local Parametrization Strategies for Organized Atmospheric Convection. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 170 p.

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--New York University, 2017.

The intrinsically multiscale nature of moist convective processes in the atmosphere complicates scientific understanding, and, as a result, current coarse-resolution climate models poorly represent convective variability in the tropics. This dissertation addresses this problem by 1) studying new cumulus convective closures in a pair of idealized models for tropical moist convection, and 2) developing innovative strategies for analyzing high-resolution numerical simulations of organized convection.

ISBN: 9780355128321Subjects--Topical Terms:

3168354
Atmospheric sciences.

Data Analysis and Non-local Parametrization Strategies for Organized Atmospheric Convection.
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245 1 0 $a Data Analysis and Non-local Parametrization Strategies for Organized Atmospheric Convection.
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300 $a 170 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
500 $a Adviser: Andrew J. Majda.
502 $a Thesis (Ph.D.)--New York University, 2017.
520 $a The intrinsically multiscale nature of moist convective processes in the atmosphere complicates scientific understanding, and, as a result, current coarse-resolution climate models poorly represent convective variability in the tropics. This dissertation addresses this problem by 1) studying new cumulus convective closures in a pair of idealized models for tropical moist convection, and 2) developing innovative strategies for analyzing high-resolution numerical simulations of organized convection.
520 $a The first two chapters of this dissertation revisit a historical controversy about the use of convective closures based on the large-scale wind field or moisture convergence. In the first chapter, a simple coarse resolution stochastic model for convective inhibition is designed which includes the non-local effects of wind-convergence on convective activity. This model is designed to replicate the convective dynamics of a typical coarse-resolution climate prediction model. The non-local convergence coupling is motivated by the phenomena of gregarious convection, whereby mesoscale convective systems emit gravity waves which can promote convection at a distant locations. Linearized analysis and nonlinear simulations show that this convergence coupling allows for increased interaction between cumulus convection and the large-scale circulation, but does not suffer from the deleterious behavior of traditional moisture-convergence closures.
520 $a In the second chapter, the non-local convergence coupling idea is extended to an idealized stochastic multicloud model. This model allows for stochastic transitions between three distinct cloud types, and non-local convergence coupling is most beneficial when applied to the transition from shallow to deep convection. This is consistent with recent observational and numerical modeling evidence, and there is a growing body of work highlighting the importance of this transition in tropical meteorology. In a series of idealized Walker cell simulations, convergence coupling enhances the persistence of Kelvin wave analogs in dry regions of the domain while leaving the dynamics in moist regions largely unaltered.
520 $a The final chapter of this dissertation presents a technique for analyzing the variability of a direct numerical simulation of Rayleigh-Benard convection at large aspect ratio, which is a basic prototype of convective organization. High resolution numerical models are an invaluable tool for studying atmospheric dynamics, but modern data analysis techniques struggle with the extreme size of the model outputs and the trivial symmetries of the underlying dynamical systems (e.g. shift-invariance). A new data analysis approach which is invariant to spatial symmetries is derived by combining a quasi-Lagrangian description of the data, time-lagged embedding, and manifold learning techniques. The quasi-Lagrangian description is obtained by a straightforward isothermal binning procedure, which compresses the data in a dynamically-aware fashion. A small number of orthogonal modes returned by this algorithm are able to explain the highly intermittent dynamics of the bulk heat transfer, as quantified by the Nusselt Number.
590 $a School code: 0146.
650 4 $a Atmospheric sciences. $3 3168354
650 4 $a Applied mathematics. $3 2122814
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773 0 $t Dissertation Abstracts International $g 78-12B(E).
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