Welcome to Changming "Charles" Dong's Research Website  

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My research interests:

1. multiple-scale regional oceanic dynamics using numerical downscaling modeling and observational data analysis;
2. Remote  sensing data  analysis: eddy automated detection from SST, SSHA, drifters and Argo;
3. Meso- and submeso-scale eddy dynamics analysis.

I. Multiple-scale regional oceanic dynamics

Employing the Regional Oceanic Model System (ROMS), Dong et al (2009) developed a high-resolution numerical model (1km) to hindcast the oceanic circulation in the Southern California Bight (1996-2003). The product has been used to study the multiple-scale variability in the current, upwelling event, laval connectivity and eddy evolution. See publication page for references.

Using sea ice coupled oceanic model, Dong et al (2010) hindcasted 15 years of oceanic circulation and sea ice variation in the Bering Sea. Click a poster which is presented at OS 2010 meeting. The integration is being extended to multiple decades.

We have developed high-resolution nesting grids for regions of Hawaii Islands and Canary Islands to study effects
of islands on the circulation.

Recently Mr. Yu Liu, a graduate student, is working with me to develop a long-term high-resolution Northwestern Pacific Model to study the NWP response to the climate change


An island (headland) is one of prominant candidates for eddy generation in ocean. That is why I am interested in studying of island wakes.


After their simulation and analysis of island wakes in deep water (Dong et al, 2007), Dong et al (2010) simulated wakes in shallow water. For realistic islands, Dong and McWilliams (2007) simulated the wakes in Southern California Bight where eight substantial islands are presented; Dong et al (2010) simulated the wake of the Gran Canaria Island where a close-to-perfect-cylinder island exists; Dong et al (2009) simulated an island wake of Hawaii Islands. See publication page for references.


I participated in laboratory experiments to study island wakes, led by Rui Caldeira (Portuga) and Alex Stegner (France), which lasted  one month at one of the largest rotating tanks in the world: Coriolis tank at Grenoble, France. The data are under process. This study is currently funded by ONR.


1. Eulerian Eddy Detection

1) From Numerical Model Product

Francesco Nencioli (a Ph.D student from UCSB and graduated in 2010) and I, with other colleagues, developed an eddy geometry feature based Eulerian eddy detection scheme. The detailed description of the scheme has been published in Nencioli and Dong et al (2010), which can be found  on www.atmos.ucla.edu/~cdong/pub.html

If you are interested in the scheme, feel free to send your request to either Francesco at his email: francesco.nencioli@opl.ucsb.edu or me at my email: cdong@atmos.ucla.edu. Francesco and I are very happy to distribute the scheme and looking forwards to your feedbacks which will help us to improve the codes and then the community will benefit from the scheme. The codes are written in matlab.

2) From SST data

Thermal velocity field derived from the SST data can well characterize an eddy surface structure revealed by
the SST data. An automated SST eddy detection scheme is developed in combination of Nencioli and Dong et al (2010). The description of the scheme can be found a paper to be published on Dong et al (2011) to be appeared on IEEE-GRSL (it can be found on www.atmos.ucla.edu/~cdong/pub.html

If you are interested in the scheme, please contact me at cdong@atmos.ucla.edu

3) From SSHA data

 Nencioli and Dong et al (2010) can be directly applied to
the geostrophic velocity anomalies derived the altimetery SSHA data. Liu and Dong et al (2011) applied the method to one zonal band of Pacific Subtropic ocean (submitted to JGR-Ocean).

2. Lagrangian Eddy Detection: surafce drifter trajectories

Dong and Liu et al (2011) develop a new eddy detection scheme from surface drifter trajectories data, which
is documented in a paper to be appeared on Journal of Atmospheric and Oceanic Tech. The codes will be available upon request shortly. Click an example below for loops detected by the scheme.

3. Synthetic Observational Eddy Data  from SST, SSHA, drifters and Argo...

Records of realistic oceanic eddy evolution data are very sparse though we have seen many numerical simulations of eddy evolutions. Collection and analysis of such observational data will shed light on
how oceanic eddies are generated, grow and decay. Such eddy evolution information is also essential to better understand eddy's roles in climate, marine biological productivity and pollution dispersion. Especially when we are moving to the age of eddy-resolvng possible in climate model, to understand how oceanic eddies occur and evolve in realistic oceans is very important.

With a series of approaches developed above, we are ready to combine eddy data sets from SST, SSHA, drifters and Argos. A synthetic observational eddy data set is being developed, which will provide a
reliable comprehensive eddy information. 
See an example by clicking Animation to see how an eddy index (spatial and temporal) revealed by a surface drifter can be used to link remote sensing data: SST and SSHA derived velocity field to characterize an eddy evolution process.

  Other Research Pages:.
  1. High-resolution realistic simulation
  2. Bering Sea Ice-Ecological-coupled System
  3. Sediment Transport
  4. Pollution (such as DDTs) Dispersion and water quality assessment

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