Skip to main content

About Me

I am a Ph.D. and my research stands in the intersection of Earth Science interdisciplinary.

I started programming and using GIS/Remote Sensing since 2005. I have been acquiring new skills ever since and am still learning. I use and build tools/models to solve problems across scales.

My ultimate goal is trying to understand how our nature works, especially under the changing climate. Without understanding our nature, we cannot appreciate how important it is to protect our only home, Earth.

In my opinion, science communication is very important and has always been understated. If I cannot explain my work to my wife, I cannot expect our public community to understand as well.

We all know it is not easy to understand nature, that is why we explore various ways to improve.

In a word, most of the articles I post here are related but not limited to Earth Science. These topics may cover:
  • Carbon cycle
  • Ecosystem
  • GIS
  • Hydrology (groundwater and surface water)
  • High Performance Computing
  • Permafrost
  • Programming
  • Remote Sensing
  • Snow dynamics
  • ...
All the posts will be original and are actual reflections of my research and potential publications. While publications do not always tell the whole story given limited resources and editors' preferences, it can be very difficult for audiences to fully understand a good research. That is why I am here to close the gap, a behind scene illustration of how science is actually done.

When I am not doing research, I do lots of activities including
  • basketball
  • BBQ (if it counts)
  • camping
    Yellowwood, IN
    Sugar Valley, IN
  • fishing
  • biking
  • hiking
    Death Valley, CA

    Ancient Lakes, WA
  • kayaking
    Columbia, WA

    South Ben, IN
  • swimming
    Colchuck Lake, WA
  • watching games

    Clemson, SC
  • ...
I am also active in several social networks including Twitter (@changliao1025).
Feel free to contact me if you have questions.

Popular posts from this blog

Spatial datasets operations: mask raster using region of interest

Climate change related studies usually involve spatial datasets extraction from a larger domain.
In this article, I will briefly discuss some potential issues and solutions.

In the most common scenario, we need to extract a raster file using a polygon based shapefile. And I will focus as an example.

In a typical desktop application such as ArcMap or ENVI, this is usually done with a tool called clip or extract using mask or ROI.

Before any analysis can be done, it is the best practice to project all datasets into the same projection.

If you are lucky enough, you may find that the polygon you will use actually matches up with the raster grid perfectly. But it rarely happens unless you created the shapefile using "fishnet" or other approaches.

What if luck is not with you? The algorithm within these tool usually will make the best estimate of the value based on the location. The nearest re-sample, but not limited to, will be used to calculate the value. But what about the outp…

Numerical simulation: ode/pde solver and spin-up

For Earth Science model development, I inevitably have to deal with ODE and PDE equations. I also have come across some discussion related to this topic, i.e.,

In an attempt to answer this question, as well as redefine the problem I am dealing with, I decided to organize some materials to illustrate our current state on this topic.

Models are essentially equations. In Earth Science, these equations are usually ODE or PDE. So I want to discuss this from a mathematical perspective.

Ideally, we want to solve these ODE/PDE with initial condition (IC) and boundary condition (BC) using various numerical methods.

Because of the nature of geology, everything is similar to its neighbors. So we can construct a system of equations which may have multiple equation for each single grid cell. Now we have an array of equation…

Lessons I have learnt during E3SM development

I have been involved with the E3SM development since I joined PNNL as a postdoc. Over the course of time, I have learnt a lot from the E3SM model. I also found many issues within the model, which reflects lots of similar struggles in the lifespan of software engineering.

Here I list a few major ones that we all dislike but they are around in almost every project we have worked on.

Excessive usage of existing framework even it is not meant to Working in a large project means that you should NOT re-invent the wheels if they are already there. But more often, developers tend to use existing data types and functions even when they were not designed to do so. The reason is simple: it is easier to use existing ones than to create new ones. For example, in E3SM, there was not a data type to transfer data between river and land. Instead, developers use the data type designed for atmosphere and land to do the job. While it is ok to do so, it added unnecessary confusion for future development a…