Multiscale Window Transform

2017

Atmosphere

Self Cite

Abstract:The typhoon Damrey that hit Jiangsu the populous coastal province of China on 2 August 2012 is a rarely seen tropical cyclone in that it has a higher latitude origin, and it is part of a twin typhoon. In this study, a recently developed analysis tool-multiscale window transform (MWT) and the MWT-based localized multiscale energy and vorticity analysis (MS-EVA)-is applied to investigate its genesis and maintenance. The fields are reconstructed onto three scale windows: large-scale, tropical cyclone-scale, and cumulus convection-scale windows. It is found that the track of Damrey is well along the edge of the subtropical high. Its birth is mainly caused by a strong barotropic instability in the lower troposphere around 24 • -25 • N. Its later amplification, however, is quite different, related to a baroclinic instability in the upper troposphere. Also discovered in this study is that a strong center of upscale canonical transfer exists over the East China Sea at the mouth of Yangtze River, which accounts for the rapid decay of Damrey before landing.

Section: Multiscale Window Transform (Mwt) and Localized Multiscale Ementioning

confidence: 99%

Section: Multiscale Window Transform (Mwt) and Localized Multiscale Ementioning

confidence: 99%

A Diagnosis of Some Dynamical Processes Underlying a Higher-Latitude Typhoon Using the Multiscale Window Transform

Wang

2017

Atmosphere

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“…The large‐scale temperature distribution reconstructed with (a) observation, and (b) model prediction for the fifth forecast day. A window index j 0 = 1 is used for the 2‐D cubic spline scaling basis [ Liang and Anderson , ].…”

Section: Sensitivity Studiesmentioning

confidence: 99%

“…The large‐scale features, by which we mean here the basin‐scale trend, is obtained through reconstruction using a 2‐D cubic spline scaling basis [ Liang and Anderson , ], with a spatial scale level index j 0 = 1. Figure shows the basin‐scale distributions of both the predicted and observed temperatures,

{\overset{T}{true}}_{o}

and

{\overset{T}{true}}_{p}

, for the forecast day 5 (19 August).…”

Section: Zigzag Data Assimilation and The F5 Forecastmentioning

confidence: 99%

Absolute and convective instabilities and their roles in the forecasting of large frontal meanderings

J. Geophys. Res. Oceans

Robinson

2013

Self Cite

[1] Frontal meanderings are generally difficult to predict. In this study, we demonstrate through an exercise with the Iceland-Faeroe Front (IFF) that satisfactory predictions may be achieved with the aid of hydrodynamic instability analysis. As discovered earlier on, underlying the IFF meandering is a convective instability in the western boundary region followed by an absolute instability in the interior; correspondingly the disturbance growth reveals a switch of pattern from spatial amplification to temporal amplification. To successfully forecast the meandering, the two instability processes must be faithfully reproduced. This sets stringent constraints for the tunable model parameters, e.g., boundary relaxation, temporal relaxation, eddy diffusivity, etc. By analyzing the instability dispersion properties, these parameters can be rather accurately set and their respective ranges of sensitivity estimated. It is shown that too much relaxation inhibits the front from varying; on the other hand, too little relaxation may have the model completely skip the spatial growth phase, leading to a meandering way more upstream along the front. Generally speaking, dissipation/diffusion tends to stabilize the simulation, but unrealistically large dissipation/diffusion could trigger a spurious absolute instability, and hence a premature meandering intrusion. The belief that taking in more data will improve the forecast does not need to be true; it depends on whether the model setup admits the two instabilities. This study may help relieve modelers from the laborious and tedious work of parameter tuning; it also provides us criteria to distinguish a physically relevant forecast from numerical artifacts.Citation: Liang, X. S., and A. R. Robinson (2013), Absolute and convective instabilities and their roles in the forecasting of large frontal meanderings,

“…By a scale window we mean, loosely, a subspace with a range of scales included (cf. [57]). In atmosphere-ocean science, important phenomena are usually defined on scale windows, rather than on individual scales (e.g., [58]).…”

Section: Langevin Equationmentioning

confidence: 99%

The Liang-Kleeman Information Flow: Theory and Applications

2013

Entropy

Abstract:Information flow, or information transfer as it may be referred to, is a fundamental notion in general physics which has wide applications in scientific disciplines. Recently, a rigorous formalism has been established with respect to both deterministic and stochastic systems, with flow measures explicitly obtained. These measures possess some important properties, among which is flow or transfer asymmetry. The formalism has been validated and put to application with a variety of benchmark systems, such as the baker transformation, Hénon map, truncated Burgers-Hopf system, Langevin equation, etc. In the chaotic Burgers-Hopf system, all the transfers, save for one, are essentially zero, indicating that the processes underlying a dynamical phenomenon, albeit complex, could be simple. (Truth is simple.) In the Langevin equation case, it is found that there could be no information flowing from one certain time series to another series, though the two are highly correlated.Information flow/transfer provides a potential measure of the cause-effect relation between dynamical events, a relation usually hidden behind the correlation in a traditional sense.