Research


Environmental Fluid Dynamics

 


   


A study of boundary layer flows in a rotating frame is one of active research topics in fluid dynamics. In our research, the primary ingredient of boundary layer flows is the fluid in coastal regions interfaced with air, land or both, which is closely related to interdisciplinary subjects in fluid mechanics, coastal oceanography, electronic engineering, and civil engineering. We pursue to build concrete frameworks and to derive potential applications on engineering issues based on understanding of physics and bio-geo-chemistry, and their interactions. For these purposes, we have used observations, numerical simulations, and theories such as environmental sensing and data analysis, computational fluid dynamics, and theoretical studies on geophysical fluid dynamics. Particularly, understanding physics of coastal waters is vital for tracking of water-borne materials (e.g., search & rescue, oil spill, and larvae) and studies of submesoscale processes, beach erosion, sea level rise, and fishery science. The tide-driven, wind-driven, and wave-driven coastal circulations and low-frequency currents as well as internal waves/tides are mainly examined. (images from an aerial image of red tide and A. Mahadevan, Nature 2014)


see references #4 #5 #7 #8 #10 #14 #16 #19 #20 #22 #26 #36 #37




Environmental BIG DATA


 



As much as we have been exposed in situations with numerous data, scientific communities have been struggled with the same issues. In our research, the BIG DATA obtained from observations and numerical simulations of various environmental fluids are merged and analyzed based on statistics and dynamics to have better understanding of environmental fluids. Primary datasets are satellite imageries, high-resolution observations and numerical model outputs, reanalysis data at regional and global scales. Data analysis covers several topics; e.g., Fourier analysis in the spectral (frequency and wavenumber) and physical (time and space) domains including signal processing;  harmonic analysis; multivariate regression with climate indices; pattern tracking for eddy detection; non-Gaussian process analysis; self-similar time series analysis; filter design; objective mapping, and etc. (images from the perpetual ocean from NASA satellite products and GOCI Chlorophyll)


see references #10 #14 #17 #20 #22 #25 #28 #29




Submesoscale Processes



   


Submesoscale oceanic features, which are frequently observed as filaments, fronts, and eddies, are characterized by both O(1) Rossby number and a horizontal scale smaller than the first baroclinic Rossby deformation radius. Submesoscale processes are important because they contribute to the vertical transport of oceanic tracers, mass, and buoyancy and rectify the mixed-layer structure and upper-ocean stratification. As observational studies requires to sample the waters at the O(1) km spatial scale and less than an hour temporal scale, we have used the high-frequency radars for surface current observations and intermittent in-situ CTD samplings for the vertical structure. As one of on-going research topics, the energy cascade of geophysical turbulent fluids has been investigated. (images from J. Gula @ UCLA) 



see references #5 #6 #7 #8 #27 #30 #31 #32 #34 #36 #37




Environmental Sensing




"The chief source of ideas in oceanography comes, I think, from new observations... On the whole, when it comes to the phenomenology of the ocean, there are more discoveries than predictions. Most theories are about observations that have already been made." - Henry Stommel


Environmental sensing includes 1) development and fabrication of sensors, 2) data quality assurance and quality control (QAQC), and 3) sampling design, which requires a diligent and smart team having interdisciplinary backgrounds such as fluid mechanics, electronic engineering, oceanography, and etc.  Primary topics are listed: signal processing; time-frequency domain analysis; sensor fabrications; sampling design; surface current observations using high-frequency radars; sea surface heights, temperature, and chlorophyll using satellite remote sensing (e.g., AVISO, coastal altimetry, and GOCI missions); acoustic Doppler current profilers (ADCPs); integrated coastal ocean observing programs. [images were taken during field works off Republic of Palau, California (USA), and Majorca (Spain)]


see references #1 #2 #14 #17 #24 #35




Machine Learning and Inverse Methods



  


A typical problem in science and engineering,

Ax = b,

where A and b denote the known model coefficients and given observations, respectively, and x is unknown model parameters, is tackled in various ways: e.g., least-squares fit, (multi-variate) regression, empirical Greens' function analysis, data assimilation, Kalman filter, optimal interpolation, Fourier analysis, gap filling for missing observations, statistical parameterizations, and etc. Statistical and dynamical data analyses allow us to understand the big data obtained from the nature in a dynamical framework.


see references #1 #2 #3 #4 #7 #8 #17 #18 #25 #33





Science and Engineering in Extreme Environments


  


As one of extreme environments, the arctic area is our study domain regarding on the sea-ice variability and dynamics, and infrastructure building on met-ocean data for offshore engineering. This can be extended into the studies on climate change at regional and global scales based on observations, numerical model outputs, and reanalysis data as a part of BIG DATA analysis (e.g., signal processing). The typhoon's (Hurricane and tropical cyclones) generation, migrations, and demise can be analyzed in a similar context. The storm surge and the drag variability under high speed winds are one of on-going research topics (images from NASA and N. Mantua for PDO).


see references #17 #18 #25