PyAPS - Python based Atmospheric Phase Screen Estimation¶
PyAPS is a python module that estimates differential phase delay maps due to the stratified atmosphere for correcting radar interferograms. It is based on Delaypackage originally written by Romain Jolivet for estimating phase screens due to stratified atmosphere using ECMWF's ERA Interim reanalysis. 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
PyAPS includes support for ERA Interim, NARR and MERRA weather models. PyAPS uses the humidity, pressure and temperature information from meteorological models to estimate the dry and wet components of the atmospheric delay.
We recommend using standard repository managers like yum/ apt-get for linux and macports/fink for Mac OS to install the prerequisite packages. You will need
- Python (atleast 2.6 recommended)
- Numpy (atleast 1.5.1 recommended)
- Scipy (atleast 0.9 recommended)
- Matplotlib
- grib_api library (atleast 1.9.9 recommended)
- pygrib (Download from here) - Used for ERA Interim and NARR data
- hdf4 libraries (Needed for reading netcdf files / hdf4 files)
pyhdf (Download from here) - Used for MERRA data pygrib and pyhdf may be available through yum or macports or easy_install depending on your OS. If not, they need to be installed from source. Follow the instructions in the user manual or the GIAnT user manual to set these up. When all the pre-requisite packages are installed, check the code out of our svn repository.
svn co http://earthdef.caltech.edu/svn/pyaps
Add the full path to the pyaps directory to the environment variable PYTHONPATH.
a. ERA Interim Reanalysis¶
PyAPS includes support for automatic download for ERA Interim reanalysis data from two sources - ECMWF and UCAR . This dataset has a temporal resolution of 6 hours and covers the entire globe. To download this dataset using the autoget utility included in PyAPS, a filed named model.cfg needs to populated with valid login credentials. An example template file (model.cfg.template) is included in the source distribution.
Setting up downloads from ECMWF.int
To get your personal key from ECMWF, you will need to (1) register, (2) login, (3) sign the agreement, (4) copy the email adress and the key to the model.cfg file, in the ECMWF section. PyAPS only downloads the fields of interest - Humidity and Temperature as a function of pressure level. Each file (global for single time eopch) is about 28MB in size.
Setting up downloads from ucar.edu
You will need to register for access to the ERA Interim full resolution data set here. Once you have an active registered login, scroll down to the bottom of the same webpage and click on data access. You will need to agree to the terms and conditions before proceeding. You might have to wait for a email confirming your access to the data set. This dataset can only be accessed from within the United States. Each file is about 89MB in size. Our scripts do not attempt to subset this dataset.
b. North American Regional Reanalysis¶
NARR covers North America at a resolution of about 30 km and has a temporal resolution of 3 hours. The original data is distributed on a non-uniform grid. PyAPS computes delay functions on the original grid and reinterpolates these functions onto a regular lat-lon grid before estimating corrections. No special login is needed to access this dataset. Each file is about 56MB in size.
c. MERRA¶
MERRA is another global model with a temporal resolution of 6 hours. No special login is needed to access this dataset.
1. 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
2. Jolivet, R., P. Agram and C. Liu, Python-based Atmospheric Phase Screen estimation - User Guide (2012), http://earthdef.caltech.edu .
