### High Performance Computing: Download and prepare data in a batch mode

Over the time, I need to manipulate a lot of data on a Linux cluster. Some of these manipulations actually read/write data, whereas some are essentially file system operations, such as downloading the files.
Here I present a list of similar operations suitable for HPC using pbs job approach whenever possible.
I do not attempt to include all possible methods but only the ones that I find useful and easy to prepare in seconds.
wget -r --no-parent -R "index.html*" --retr-symlinks -A "*.nc" ftp-url
wget -r --no-parent -R "index.html*" -A "MOD17A2.A2000*.hdf" -A "MOD17A2.A2000*.xml" http-url
wget -r --no-parent -R "index.html*" -A "MOD17*.hdf" -A "MOD17*.xml" http-url
You can basically setup filter for file type, year and granule id.
A live example:
///==========================================================
#!/bin/bash
#PBS -l nodes=1:ppn=1
#PBS -l naccesspolicy=singleuser
#PBS -l walltime=40:00:00
#PBS -m ae
#PBS -q standby
cd $PBS_O_WORKDIR wget -r --no-parent -R "index.html*" --retr-symlinks -A "*.tar" ftp://somwhere ///========================================================== Compress and extract Examples: ///========================================================== #!/bin/bash #use this script to extract tar files under the sub directory for dir in find -mindepth 1 -maxdepth 1 -type d do cd$dir
echo $dir tar xf *.tar ./ cd .. done ///========================================================== #!/bin/bash # Pass the name of the file to unpack on the command line$1
for file in *.gz
do
gunzip -d "\$file"
done
///==========================================================

Search

grep -rnw '/path/to/somewhere/' -e "pattern"
find . -maxdepth 1 -name "*string*" -print
Comiple

make &> results.txt

Count

find . -name '*.cpp' | xargs wc -l

Debug

qsub -I -lnodes=1:ppn=20 -lwalltime=04:00:00 -q boss  -X

Simply organize these above bash script and replace with commands, most file system related tasks can be resolved. I will add more related scripts later.

### 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.,

https://www.researchgate.net/post/What_does_one_mean_by_Model_Spin_Up_Time

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.
https://en.wikipedia.org/wiki/Initial_value_problem
https://en.wikipedia.org/wiki/Boundary_value_problem

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…