Satellite Information Familiarization Tool (SIFT) was designed by the SSEC to support scientists during forecaster training events. It provides a graphical interface for visualization and basic analysis of geostationary satellite data.
The Project Wiki and Git repository can be accessed at https://gitlab.ssec.wisc.edu/SIFT/sift/wikis/home.
SIFT is built on open source technologies like Python, OpenGL, and PyQt4. It can be run from Mac, Windows, and Linux.
SIFT currently accepts a limited number of input formats. It is able to load NetCDF4 L1B files for the GOES-16 ABI instrument. It will accept more input files in the future. Please contact Jordan Gerth, Ray Garcia, or David Hoese to get access to this early release data set.
SIFT installers and bundles are available on the SIFT FTP location:
ftp://ftp.ssec.wisc.edu/pub/sift/dist
The Windows installers end in .exe, Linux with .tar.gz, and Mac OSX with
.dmg. See the sections below for details on installing SIFT for each
operating system.
After executing the downloaded .exe installer follow the installation
wizard to install SIFT. SIFT can then be run from the "SIFT" shortcut
in the start menu. By default SIFT caches files in a "Workspace" located
at the user's Documents/sift_workspace. The installation wizard allows
you to customize this location.
The downloaded tarball .tar.gz can be extracted by running:
tar -xf SIFT_X.Y.Z.tar.gz
SIFT can then be run by executing the SIFT/SIFT. Run SIFT/SIFT -h
for available command line options.
If SIFT will not start please ensure that the LD_LIBRARY_PATH environment
variable is not set.
The downloaded DMG file can be extracted opened by double clicking on it.
The available .app should then be moved to the appropriate Applications
folder. Double clicking the .app icon from Applications will execute
SIFT.
SIFT can also be installed with the Anaconda/Conda package manager. Python 3.6 is currently the only supported python environment. It can be installed by running:
conda install -c http://larch.ssec.wisc.edu/channels/sift sift
And then run with:
python -m sift
The -h flag can be added for documentation on additional command line
options.