pyaps3 0.3.2

Python based Atmospheric Phase Screen estimation

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: The current version does not work with NARR and MERRA datasets. Contributions are welcomed.

This is research code provided to you "as is" with NO WARRANTIES OF CORRECTNESS. Use at your own risk.

1. Installation

a. Install the released version [recommended]

pyaps3 is available on the conda-forge channel, PyPI and the main archive of the Debian GNU/Linux OS. The released version can be installed via conda as:

conda install -c conda-forge pyaps3

or via pip as:

pip install pyaps3

or via apt (or other package managers) for Debian-derivative OS users, including Ubuntu, as:

apt install python3-pyaps3

b. Install the development version

The development version can be installed via pip as:

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

or build from source manually as:

git clone https://github.com/insarlab/PyAPS.git
conda install -c conda-forge --file PyAPS/requirements.txt
python -m pip install -e PyAPS

Test the installation by running:

python PyAPS/tests/test_calc.py

2. Account setup for ERA5

ERA5 data set is redistributed over the Copernicus Climate Data Store (CDS). Registration is required for the data access and downloading.

• Create a new account on the CDS website if you don't own a user account yet.
• Create local key file. Create a file named .cdsapirc in your home directory and add the following two lines:

url: https://cds.climate.copernicus.eu/api/v2
key: 12345:abcdefghij-134-abcdefgadf-82391b9d3f

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

• Make sure that you accept the data license in the Terms of use on ECMWF website.

• Test the account setup by running:

git clone https://github.com/insarlab/PyAPS.git --depth 1
python PyAPS/tests/test_dload.py

3. Citing this work

The methodology and validation 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.