README.md

PyAPS - Python based Atmospheric Phase Screen estimation

This python 3 module estimates differential phase delay maps due to the stratified atmosphere for correcting radar interferograms. It is rewritten in Python 3 language from PYAPS source code and adapted for ECMWF's ERA-5 corrections.

WARNING: PyAPS3 could not work with NARR and MERRA weather models. Feel free to modify these parts of the code.

1. Installation

via pip

pip install git+https://github.com/yunjunz/PyAPS.git

via conda

# download source code
cd ~/tools
git clone https://github.com/yunjunz/PyAPS.git

# install dependencies
conda install --file PyAPS/requirements.txt

Add the following variables in your source file (~/.bash_profile for bash users or ~/.cshrc for csh/tcsh users).

export PYTHONPATH=${PYTHONPATH}:~/tools/PyAPS

2. Account setup for global atmospheric models

ERA-5

ERA-5 data set is redistributed over the Copernicus Climate Data Store (CDS), create a new account on the CDS website if you don't own a user account yet. On the profile, you will find your user id (UID) and your personal API Key. Add the key to the model.cfg file as below:

#####key for ECMWF in Climate Data Store Application Program Interface
#Get it from https://retostauffer.org/code/Download-ERA5/
[CDS]
key = 12345:abcdefghij-134-abcdefgadf-82391b9d3f

where 12345 is your personal user ID (UID), the part behind the colon your personal API key. More details on CDSAPI can be found here.

Run examples/TestECMWF.ipynb in Jupyter Notebook in your local machine to check if everything works.

3. Citing this work

The metholody and validation of DelayPackage can be found in:

• Jolivet, R., R. Grandin, C. Lasserre, M.-P. Doin and G. Peltzer (2011), Systematic InSAR tropospheric phase delay corrections from global meteorological reanalysis data, Geophys. Res. Lett., 38, L17311, doi:10.1029/2011GL048757.

Examples in the example directory.