A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...

/pdf/the-empirical-mode-decomposition-and-the-hilbert-spectrum-qkmom366dy.pdf

The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

Data Mining - Concepts and Techniques.

A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and treats the mean as the final true result. Finite, not infinitesimal, amplitude white noise is necessary to force the ensemble to exhaust all possible solutions in the sifting process, thus making the different scale signals to collate in the proper intrinsic mode functions (IMF) dictated by the dyadic filter banks. As EEMD is a time–space analysis method, the added white noise is averaged out with sufficient number of trials; the only persistent part that survives the averaging process is the component of the signal (original data), which is then treated as the true and more physical meaningful answer. The effect of the added white noise is to provide a uniform reference frame in the time–frequency space; therefore, the added noise collates the portion of the signal of comparable scale in one IMF. With this ensemble mean, one can separate scales naturall...

/pdf/ensemble-empirical-mode-decomposition-a-noise-assisted-data-4htvj7tcuy.pdf

Ensemble empirical mode decomposition: a noise-assisted data analysis method

to be done in this area. Face recognition is a problem that scarcely clamoured for attention before the computer age but, having surfaced, has involved a wide range of techniques and has attracted the attention of some fine minds (David Mumford was a Fields Medallist in 1974). This singular application of mathematical modelling to a messy applied problem of obvious utility and importance but with no unique solution is a pretty one to share with students: perhaps, returning to the source of our opening quotation, we may invert Duncan's earlier observation, 'There is an art to find the mind's construction in the face!'.

Linear and nonlinear waves, by G. B. Whitham. Pp.636. £50. 1999. ISBN 0 471 35942 4 (Wiley).

If model parameterizations of unresolved physics, such as the variety of upper ocean mixing processes, are to hold over the large range of time and space scales of importance to climate, they must be strongly physically based. Observations, theories, and models of oceanic vertical mixing are surveyed. Two distinct regimes are identified: ocean mixing in the boundary layer near the surface under a variety of surface forcing conditions (stabilizing, destabilizing, and wind driven), and mixing in the ocean interior due to internal waves, shear instability, and double diffusion (arising from the different molecular diffusion rates of heat and salt). Mixing schemes commonly applied to the upper ocean are shown not to contain some potentially important boundary layer physics. Therefore a new parameterization of oceanic boundary layer mixing is developed to accommodate some of this physics. It includes a scheme for determining the boundary layer depth h, where the turbulent contribution to the vertical shear of a bulk Richardson number is parameterized. Expressions for diffusivity and nonlocal transport throughout the boundary layer are given. The diffusivity is formulated to agree with similarity theory of turbulence in the surface layer and is subject to the conditions that both it and its vertical gradient match the interior values at h. This nonlocal “K profile parameterization” (KPP) is then verified and compared to alternatives, including its atmospheric counterparts. Its most important feature is shown to be the capability of the boundary layer to penetrate well into a stable thermocline in both convective and wind-driven situations. The diffusivities of the aforementioned three interior mixing processes are modeled as constants, functions of a gradient Richardson number (a measure of the relative importance of stratification to destabilizing shear), and functions of the double-diffusion density ratio, Rρ. Oceanic simulations of convective penetration, wind deepening, and diurnal cycling are used to determine appropriate values for various model parameters as weak functions of vertical resolution. Annual cycle simulations at ocean weather station Papa for 1961 and 1969–1974 are used to test the complete suite of parameterizations. Model and observed temperatures at all depths are shown to agree very well into September, after which systematic advective cooling in the ocean produces expected differences. It is argued that this cooling and a steady salt advection into the model are needed to balance the net annual surface heating and freshwater input. With these advections, good multiyear simulations of temperature and salinity can be achieved. These results and KPP simulations of the diurnal cycle at the Long-Term Upper Ocean Study (LOTUS) site are compared with the results of other models. It is demonstrated that the KPP model exchanges properties between the mixed layer and thermocline in a manner consistent with observations, and at least as well or better than alternatives.

Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization

The multilayer perceptron (MLP) neural network have been widely used to fit non-linear transfer function and performed well. In this study, we use MLP to estimate chlorophyll-a concentrations from marine reflectance measures. The optical data were assembled from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Algorithm Mini-workshop (SeaBAM). Most bio-optical algorithms use simple ratios of reflectance in blue and green bands or combinations of ratios as parameters for regression analysis. Regression analysis has limitations for nonlinear function. Neural network, however, have been shown better performance for nonlinear problems. The result showed that accuracy of chlorophyll-a concentration using MLP is much higher than that of regression method. Nevertheless, using all of the five bands as input can derive the best performance. The results showed that each band could carry some useful messages for ocean color remote sensing. Only using band ratio (OC2) or band switch (OC4) might lose some available information. By preprocessing reflectance data with the principle component analysis (PCA), MLP could derive much better accuracy than traditional methods. The result showed that the reflectance of all bands should not be ignored for deriving the chlorophyll-a concentration because each band carries different useful ocean color information.

Application of a multilayer perceptron neural network to phytoplankton concentration using marine reflectance measures

[1] Multi-satellite sea level anomalies from January 1993 to December 2004 are used to investigate the variability of sea surface features in the South China Sea (SCS). Applying empirical orthogonal function (EOF) analysis, the dominant spatial features and corresponding temporal variability are revealed. The most remarkable characteristic of variability on an interannual time scale is the abnormal weakening of meso-scale eddy off west Luzon (west Luzon eddy, WLE) during 1998–2001. The possible mechanism inducing the weakening is found to be associated with a large-scale forcing over the Pacific intruding into the northern SCS along the northern coast of Luzon. Moreover, the tight correlation between the Nino3.4 sea surface temperature index and the interannual variability of large-scale forcing indicates that La Nina events may modulate the west Pacific water entering the northern SCS which contributes to the weakening of the WLE eventually.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2007GL030058

Mechanism of weakening of west Luzon eddy during La Niña years

In this paper, we use multi-satellite remote sensing data and Regional Ocean Model System (ROMS) to examine the physical and biological responses to Typhoon Nakri during a period from 1 to 8 June 2008 in the western North Pacific. From satellite observations, we find remarkable surface cooling (∼5 °C) and distinct phytoplankton enhancement after Nakri passage. It is interesting to note that in contrast to the well-documented rightward bias of the surface cooling response, the maximum biological response to Nakri occurred on the left of the Nakri’s track rather than the right side, where the most distinct cooling response occurred. To reveal the dynamic mechanism for this unusual phenomenon, we have done numerical experiments with and without the influence of preexisting cyclonic circulation and previous typhoon. The results from simulations show that both the physical and biological responses to Nakri are greatly affected by the preexisting cyclonic circulations. The discrepancy between the locations of maximum physical and biological responses mainly results from the advanced uplift and current advection of nutrient fields by previous typhoon Rammasun, which passed through the area about two weeks before Nakri.

Satellite observation and model simulation of upper ocean biophysical response to Super Typhoon Nakri

Underwater gliders are used to investigate the variations on the ocean surface and subsurface during the 14 typhoons that passed over the Kuroshio region near Taiwan in 2010–2013. Typhoon-induced subsurface layer warming, which was formed on the basis of the heat pump effect of the vertical mixing process, is observed in this study. In addition, the gliders observe the variations in salinity during the passage of the typhoons. Typhoons, accompanied by heavy rainfall, introduce a considerable amount of fresh water into the upper ocean, diluting the surface salinity. The diluted salinity accompanied deepening of the mixed layer which moved downward to the subsurface by vertical mixing, supplying fresh water to both the surface and subsurface layers. Additionally, because of vertical mixing, maximum temperature variations occur at the bottom of the mixed layer or at a level deeper than the mixed layer. Changes of the heat content show that a series of vertical mixing events occurs in the upper ocean. Pairs of salinity profiles indicate comprehensive vertical mixing in the upper ocean and yield schematics to compare typhoons with or without heavy rainfall. Higher sustained wind speeds may contribute to a considerable drop in sea surface temperature, but possibly not to the magnitude of the subsurface warming. The upper ocean thermocline gradient before a typhoon is an important factor to determine the magnitude of subsurface warming. This study concludes a glider observational result that typhoons cause subsurface layer warming and freshening in the Kuroshio region near Taiwan.

Typhoon-induced ocean subsurface variations from glider data in the Kuroshio region adjacent to Taiwan

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Application of a multilayer perceptron neural network to phytoplankton concentration using marine reflectance measures

Mechanism of weakening of west Luzon eddy during La Niña years

Satellite observation and model simulation of upper ocean biophysical response to Super Typhoon Nakri

Typhoon-induced ocean subsurface variations from glider data in the Kuroshio region adjacent to Taiwan