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  • 👋 Hi, I’m Dong
  • 👀 I’m interested in ocean modeling, data assimilation, machine learning ...
  • 🌱 I’m currently investigating Watermass Formation in the Deep Red Sea ...
  • 💞️ I’m looking for PhD opportunity ...
  • 📫 How to reach me via [email protected]

Dong's Projects

adjointanalysis icon adjointanalysis

Create animations, plots, and calculate summary statistics for MITgcm adjoint output

cdt icon cdt

The Climate Data Toolbox for MATLAB

charleston_prediction_jgr icon charleston_prediction_jgr

Supplement for 'A hybrid dynamical approach for seasonal prediction of sea-level anomalies: a pilot study for Charleston, South Carolina'

ecco_convolve icon ecco_convolve

Example notebooks to convolve ecco sensitivities with other fields

eccov4 icon eccov4

Ocean state estimation framework

ekman icon ekman

model Ekman spiral using a tank model

gcmfaces icon gcmfaces

gcmfaces is a Matlab / Octave toolbox that handles gridded earth variables in generic fashion. Read more at:

minimal-mistakes icon minimal-mistakes

:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

mitgcm icon mitgcm

M.I.T General Circulation Model master code and documentation repository

mitgcm_python icon mitgcm_python

Python scripts designed for my Weddell Sea and Amundsen Sea configurations of MITgcm.

nctoolbox icon nctoolbox

NCTOOLBOX A Matlab toolbox for working with common data model datasets

oceananigans.jl icon oceananigans.jl

🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs

oceanliner_backup icon oceanliner_backup

oceanliner: observing system simulation experiments (OSSEs) to subsample high-resolution model output as if by gliders, ships, or other in situ platforms

pyearthscience icon pyearthscience

The PyEarthScience repository created by DKRZ (German Climate Computing Center) provides Python scripts and Jupyter notebooks in particular for scientific data processing and visualization used in climate science. It contains scripts for visualization, I/O, and analysis using PyNGL, PyNIO, xarray, cfgrib, xesmf, cartopy, and others.

python-practical-application-on-climate-variability-studies icon python-practical-application-on-climate-variability-studies

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

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