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Testing the new features of Hugo-Academic theme…


It’s been a while since I started using git. The version control system helps to track changes in computer files and coordinating work on those files among multiple people. Composing a manuscript is nothing unlike developing a program. If multiple authors work on the same manuscript, git can be very helpful to avoid conflicts. If you are the only author, git can help you to document what has been changed since the last commit or put your advisor’s comment in another branch.


One of the many advantages of Python is its abundant and often powerful Libraries. For my research, besides plotting maps, I often play with time series. When it comes to manipulating and plotting time series, no other tools can beat python pandas.


Recently, I’m looking into the Meridional Heat Transport across the 35$^{\circ}$S in our high-resolution CCSM simulation following Dong et al. 2011. To calculate the heat transport, the following formula is used:

\begin{equation} \int \rho C_{p}v\theta dx dz \end{equation}

The tricky part is whether one should use temporal and spatial-varying values of $C_{p}$ (seawater heat capacity) and $\rho$ (seawater density). Since density and heat capacity are not among the standard outputs, I went on looking for some standard libraries to calculate them using the fields I have: temperature, pressure, and salinity. Soon, I found the Python version of Gibbs SeaWater Oceanographic Package.


Sometimes I got emails requesting codes to plot certain things. Those inquiries remind me that I have an older version of my website on still up and running. That was an answer to the requirement that every student in RSMAS should have their own websites back in 2014. To fill in the blanks, I listed out some of my python works in Ipython notebooks.


Recent Talks

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Large-scale forcing dominates interannual variability of Agulhas leakage

The interannual variability of Agulhas leakage is accessed in an ocean eddy resolving coupled simulation to test the hypothesis that, on such timescales large-scale forcing dominates leakage variability, regardless of eddy structures.

Quantifying Agulhas leakage in a high-resolution coupled climate model

The senstivity of leakage estimates to the model output velocity frequency needs to be addressed before we can apply it to investigate its link to climate variability.


I am a teaching assistant for the following courses at University of Miami:

I have completed following courses:

  • MPO 503 Physical Oceanography
  • MPO 511 Geophysical Fluid Dynamics I
  • MPO 551 Intro to Atmospheric Science
  • MPO 611 Geophysical Fluid Dynamics II
  • MPO 612 Large-scale Ocean Circulation
  • MPO 665 General Circulation of Atmosphere
  • MPO 583 Special Topics in Climate study
  • MPO 668 ENSO Dynamic
  • MPO 524 Applied Data Analysis
  • MPO 675 Mesoscale Oceanography
  • MGG 676 Paleoclimatology

Course Projects:

Seminar Talks:


  • METEOR 100/2 cruise from Namibia to Mauritius, 2013
  • Community Earth System Model Tutorial, NCAR, Boulder, CO, 2013