Install and Run


  • use conda to install the environment

$ git clone
$ cd ./UrbanClimateExplorer/binder 
$ conda env create -f environment.yml
$ conda activate aws_urban


  • Locally

    $ cd ./UrbanClimateExplorer
    $ git pull
    $ cd ./docs/notebooks 
    $ jupyter notebook
  • HPC (e.g., NCAR’s Casper clusters with a GPU)

    • First, create a bash script (see below), and name it as, put it in the same folder with your UrbanClimateExplorer folder.

      source  /glade/work/zhonghua/miniconda3/bin/activate aws_urban
      echo "ssh -N -L 8889:`hostname`:8889 $USER@`hostname`"
      jupyter notebook --no-browser --ip=`hostname` --port=8889
    • Second, run the commands below

      Note: please use your own job code instead of “UIUC0021”. You can find more information about execcasper here

      $ execcasper -A UIUC0021 -l gpu_type=v100 -l walltime=06:00:00 -l select=1:ncpus=18:mpiprocs=36:ngpus=1:mem=100GB
      $ bash
    • Thrid, launch a new terminal, copy and paste the command printed by the “echo” command, and log in. Then open your browser (e.g., Google Chrome), type https://localhost:8889.

      Note: Sometimes port 8889 may be used by others. In this case, please adjust your bash script accordingly, e.g., from 8889 to 8892:

      source  /glade/work/zhonghua/miniconda3/bin/activate aws_urban
      echo "ssh -N -L 8889:`hostname`:8892 $USER@`hostname`"
      jupyter notebook --no-browser --ip=`hostname` --port=8892