Wen-wen Tung
List of Publications
- underlined =
Student author, Earth and Atmospheric Sciences, Purdue University
A. Book
- Chen, B., W.-w. Tung, and M. Yanai, 2014:
Perturbation Kinetic Energy (PKE) and its Budget in the Tropics, in Multiscale
Convection-Coupled Systems in the Tropics, AMS Monograph Tribute to Michio Yanai, submitted.
- Fovell, R. G., Y. P. Bu, K.
L. Corbosiero, W.-w. Tung, Y. Cao, H.-C. Kuo, L.-H.
Hsu, and H. Su, 2014: Influence of cloud
microphysics and radiation on tropical cyclone structure and motion: A
review, in Multiscale Convection-Coupled Systems in the Tropics, AMS
Monograph Tribute to Michio Yanai, submitted.
- Gao, J.B.,
J. Hu, and W.-w. Tung, 2012: A
unified theory for the multiscale analysis of complex time series. In Multiscale
Signal Analysis and Modeling, Eds. X.P. Shen
and A. I. Zayed, Springer, 221–231.
- Gao, J. B.,
Y. Cao, W.-w. Tung,
and J. Hu, 2007: Multiscale analysis
of complex time series --- Integration of Chaos and Random Fractal Theory,
and Beyond, Wiley Interscience,
368pp
B. Refereed journals
- Tung, W.-w., D. Giannakis, and A. J. Majda, 2014:
Symmetric and antisymmetric signals in MJO
deep
convection. Part I. Basic modes. J. Atmos. Sci., DOI:10.1175/JAS-D-13-0122.1.
- Tung, W.-w., D. Giannakis, and A. J. Majda, 2014:
Symmetric and antisymmetric signals in MJO
deep
convection. Part II. Kinematics and thermodynamics. J. Atmos. Sci., in
revision.
- Bowers, M.C., J.B. Gao, and W.-w.
Tung, 2013: Long range correlations in tree ring chronologies of the
USA: Variation within and across species, Geophys.
Res. Let., 40, 1-5, DOI:10.1029/2012GL054011. (Selected to be in the
AGU Research Spotlight)
- Gao, J.B., J. Hu, W.-w. Tung, and E. Blasch, 2012: Multiscale analysis of physiological
data by scale- dependent Lyapunov exponent. Frontiers
in Fractal Physiology, doi:
10.3389/fphys.2011.00110.
- Bowers, M. C., W.-w. Tung, J.B. Gao, 2012: On the
distributions of seasonal river flows: lognormal or power-law? Water
Resources Research, 48, W05536, DOI:10.1029/2011WR011308.
- Giannakis, D., W.-w. Tung, and A. J. Majda, 2012:
Hierarchical structure of the Madden-Julian oscillation in infrared
brightness temperature revealed through nonlinear Laplacian spectral
analysis. Conference on Intelligent
Data Understanding (CIDU), 55–62, DOI:10.1109/CIDU.2012.6382201.
- Gao, J.B., J. Hu, X. Mao,
W.-w. Tung, 2012 :Detecting low-dimensional
chaos by the “noise titration” technique: possible problems and remedies. Chaos,
Solitons, & Fractals, 45, 213–223.
- Gao, J.B., J. Hu, W.-w. Tung, 2011: Facilitating
joint chaos and fractal analysis of biosignals
through nonlinear adaptive filtering. PLoS
ONE, 6(9): e24331. DOI:10.1371/journal.pone.0024331.
- Gao, J. B., J. Hu, W.W. Tung, Y. Zheng, 2011:
Multiscale analysis of economic time series by scale-dependent Lyapunov exponent. Quantitative Finance DOI:10.1080/14697688.2011.580774
(pdf).
- Tung, W.-w.,
J.B. Gao, J. Hu, and L. Yang, 2011: Recovering
chaotic signals in heavy noise environments. Phys. Rev. E, 83, 046210. (pdf)
- Wang, Y.-C., and W.-w. Tung,
2010: Impacts of cloud-system resolving regional modeling on the
simulation of monsoon depressions, Geophys. Res. Lett., 37, L08806,
doi:10.1029/2010GL042734. (pdf)
- Gao, J. B.,
H. Sultan, J. Hu, and W.-w. Tung,
2010: Denoising nonlinear time series by
adaptive filtering and wavelet shrinkage: a comparison. IEEE Signal Processing Letters, 17, 237–240. (pdf)
- Hu, J.,
J. B. Gao, W. W. Tung, and Y.H. Cao, 2010: Multiscale analysis
of heart rate variability: A comparison of different complexity measures. Annals of Biomedical Engineering, 38, 854–864. (pdf)
- Hu, J.,
J. B. Gao, and W.W. Tung: Characterizing heart rate variability by
scale-dependent Lyapunov exponent, Chaos (special issue on Controversial Topics in
Nonlinear Science: Is the Normal Heart Rate Chaotic?) 19, 028506 (2009). (pdf)
- Ashfaq, M., S.
Ying, W.-w. Tung,
R. J. Trapp, X. Gao, J. S. Pal, N. S. Diffenbaugh, 2009: Suppression of south Asian summer
monsoon precipitation in the 21st century, Geophys. Res. Lett., 36, L01704,
doi:10.1029/2008GL036500. (pdf)
- Hu, J., W.-w. Tung, and J. B. Gao, 2009: A new way to model non-stationary sea
clutter, IEEE Signal Processing
Letters, 16,
129–132. (pdf)
- Gao, J. B., W.-w. Tung, and J. Hu, 2009:
Quantifying dynamical predictability: The pseudoensemble
approach (in honor of Professor Andrew Majda’s
60th birthday). Chi. Annals. Math
Series B, 30,
569–588. (pdf)
- Tung, W.-w., J. Hu,
J. B. Gao, and V. A. Billock,
2008: Diffusion, intermittency, and noise-sustained metastable chaos in
the Lorenz equations: Effects of noise on multistability.
Theme Issue on Multistability
in Dynamical Systems, International Journal of Bifurcations and Chaos,
18, 1749–1758. (pdf)
- Gao, J. B.,
J. Hu, W.-w. Tung,
Y.H. Cao, 2006: Distinguishing chaos from noise by scale-dependent Lyapunov exponent. Phys.
Rev. E, 74,
066204. (pdf)
- Hsu,
H.-m., M. W. Moncrieff, W.-w. Tung,
and C. Liu, 2006: Temporal variability of warm season precipitation over
North America: A study based on radar reflectivity. J. Atmos. Sci., 63, 2355–2368. (pdf)
- Hu, J.,
J.B. Gao, F.L. Posner, Y. Zheng,
and W.-w. Tung,
2006: Target detection within sea clutter:A
comparative study by fractal scaling analyses. Fractals, 14,
187–204. (pdf)
- Gao, J. B.,
V.A. Billock, I. Merk,
W.-w. Tung, K.D.
White, J.G. Harris, V.P. Roychowdhury,
2006:Inertia and memory in ambiguous visual perception, Cogn. Process. 7, 105–112. (pdf)
- Gao, J. B.,
J. Hu, W.-w. Tung,
Y.H. Cao, N. Sarshar, V. P. Roychowdhury,
2006: Assessment of longrange correlation in
time series: How to avoid pitfalls. Phys.
Rev. E, 73,
016117. (pdf)
- Hu, J., W.-w. Tung, and J.B. Gao, 2006: Detection of low observable targets within
sea clutter by structure function based multifractal
analysis. IEEE Trans. Antennas &
Propagation, 54,
135–143. (pdf)
- Tung, W.-w., Y. Qi,
J.B. Gao, Y.H. Cao, and L. Billings, 2005:
Direct characterization of chaotic and stochastic dynamics in a population
model with strong periodicity. Chaos, Solitons, and Fractals, 24, 645–652. (pdf)
- Gao, J.B., W.-w. Tung, Y.H. Cao, J. Hu, and
Y. Qi, 2005: Power-law sensitivity to initial conditions in a time series
with applications to epileptic seizure detection. Physica A, 353, 613–624. (pdf)
- Hu, J., W.-w. Tung, J.B. Gao, and Y.H. Cao, 2005: Reliability of the 0-1 test
for chaos, Phys. Rev. E, 72, 056207. (pdf)
- Gao, J.B.,
Y. Qi, Y.H. Cao, and W.-w. Tung,
2005: Protein coding sequence identification by simultaneously
characterizing the periodic and random features of DNA sequences, Journal of biotechnology and biomedicine special
issue, 139–146, DOI:10.1155/JBB.2005.139. (pdf)
- Cao,
Y.H., W.-w. Tung,
J.B. Gao, and Y. Qi, 2005: Recurrence time
statistics: Versatile tools for genomic DNA sequence analysis, Journal of Bioinformatics and Computational
Biology, 3,
677–696. (pdf)
- Cao,
Y.H., W.-w. Tung,
J. B. Gao, V. A. Protopopescu,
and L.M. Hively, 2004: Detecting dynamical
changes in time series using the permutation entropy. Phys. Rev. E, 70, 046217. (selected for the
November 1, 2004 issue of Virtual Journal of Biological Physics Research: http://www.vjbio.org).( pdf)
- Tung, W.-w., M. W.
Moncrieff, and J. B. Gao, 2004: A systematic
view of the multiscale tropical deep convective variability over the
tropical western-Pacific warm pool. J.
Climate, 17,
2736–2751. ( pdf)
- Gao, J. B., W.-w. Tung, and N. Rao, 2002: Noise induced Hopf
bifurcation-like sequence to chaos in the Lorenz equations. Phys. Rev. Lett., 89, 254101. (pdf)
- Gao, J. B.,
and W.-w. Tung,
2002: Pathological tremors as diffusional processes. Biological Cybernetics,,86, 263–270. (pdf)
- Tung, W.-w., and M.
Yanai, 2002: Convective momentum transport Observed during the TOGA COARE
IOP. Part II: Case studies. J. Atmos.
Sci., 59,
2535–2549. (,pdf)
- Tung, W.-w., and M.
Yanai, 2002: Convective momentum transport Observed during the TOGA COARE
IOP. Part I: General features. J.
Atmos. Sci., 59,
1857–1871. (pdf)
- Yanai,
M., B. Chen, and W.-w. Tung,
2000: The Madden-Julian Oscillation (MJO) observed during the TOGA-COARE
IOP: Global view. J. Atmos. Sci.,
57, 2374–2396. (pdf)
- Tung, W.-w., C. Lin,
B. Chen, M. Yanai, and A. Arakawa, 1999: Basic modes of cumulus heating
and drying observed during TOGA-COARE IOP. Geophys. Res. Lett., 26(20), 3117–3120. (pdf)
Notes:
Tung’s research areas include two major
themes:
1) physical and stochastic characterizations and
simulations of multiscale tropical convection/clouds and the two-way
interactions between the cloud systems and the environmental atmosphere, and
2) dynamical systems and the analysis of
nonlinear and multiscale signals, with the purpose of simulating, predicting,
and quantifying the dynamic predictability of observed systems.
These two areas are connected with each
other, with 1) being rooted in traditional atmospheric sciences and 2) an
interdisciplinary endeavor that can assist Tung to examine the underlying
dynamics in 1).
1) Multiscale Tropical
Cloud/Convection Systems
Organized deep convection is known to
intricately interact with larger-scale processes in the atmospheric general
circulation through cloud microphysical processes and convective transports of
heat, moisture, and momentum that greatly influence the weather and climate.
General circulation model (GCM) inter-model comparisons have indicated that
cloud feedbacks remain the primary source of uncertainty in determining Earth's
equilibrium climate, as cloud processes are pivotal in the coupled
land-ocean-atmosphere system by interacting with dynamical, chemical,
hydrological, radiation, and boundary-layer processes. On the regional scales,
biases in cloud-related fields may induce strong control on the local energy
balance and ensuing responses.
Tropical deep convection represents a large
fraction of global precipitation. The latent heat release associated with deep
convection is an important component of the Earth's energy budget. The
convection-coupled tropical variability exhibits multiscale characters across a
wide range of scales in space and time as a result of the nonlinear and
stochastic interactions among its component systems and hierarchical
regulations imposed by the operating environment. For example, convective
organizations over the Indian Ocean-Western Pacific warm pool appear to have
spatial scales from O(100) to O(1000) km and temporal scales from O(1) to O(10) days. In other words, the observed organizations range
from the mesoscale convective systems (MCSs)
following the course of the diurnal cycle to organized super-cloud clusters
embedded in the eastward-propagating planetary-scale, 20–90-day Madden-Julian
oscillation (MJO).
The representations of the multiscale
tropical clouds and convection in models have long been recognized as the
critical barrier in weather and climate predictions. Failures of prediction in
the tropics are known to corrupt predictions in higher latitudes through the
pathways of planetary wave-trains and take a toll on the global society in
extreme events and faulty policy-making. Therefore, the major motivation behind
Tung’s research is to physically and/or mathematically characterize and
simulate the multiscale tropical clouds/convective-coupled systems. Major
topics in this area are:
- Effects
of Microphysics Assumptions and Cloud-Radiative
Forcing on the Asian Summer Monsoon.
- The
cumulus momentum transport (CMT) associated with the Madden-Julian
Oscillation (MJO).
- Systematic
analysis of the MJO and MJO predictability
Her method of inquisition has led her into
collaborative interdisciplinary research in which she and collaborators have
been developing general methods to quantify nonlinear dynamical systems with
multiscale characteristics.
2) Dynamical Systems and the
Analysis of Nonlinear and Multiscale Signals
This aspect of Tung’s research started from
her processing of the TOGA-COARE IOP station soundings and wind profiler data
in 1998. Applications of the wavelet transform, FFT, structure function, and
singular measure techniques to bring out the nonlinear and multiscale characteristics
of the tropical convective variability in time have been documented in her work
from 2002-2004. Perplexed by the complexity of the signals and systems being
studied, troubled by the inadequacy of conventional physical and analytical
approaches, and excited by the rich understanding obtained by systematically
applying approaches based on dynamical systems theory and information theory,
Tung has taken on a long (and non-ending) journey of interdisciplinary research
with a core group of scientists of similar convictions, with the goal of
creating a suite of nonlinear and multiscale signal analysis methods that can
be used to solve a vast range of problems in science and engineering and have
lasting values. The major topics in this area are:
- Dynamical
systems and nonlinear signal processing methods
- Biomedical
signal analyses
- Sea
clutter modeling and target detection within sea clutter:
'sky above, sky beneath, cloud
self, water origin.' --- Dogen Kigen
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