goes-ortho 0.2.1.5

Usage:

python ./download-goes.py --bucket <S3-BUCKET> --year <YEAR> --month <MONTH> --days <START DAY> <END DAY> --product <ABI PRODUCT CODE> --channel <ABI CHANNEL> --bounds <MIN_LAT> <MAX_LAT> <MIN_LON> <MAX_LON> --dir <DESTINATION DIRECTORY>

Examples:

This will download the GOES-16 ABI Level-1b Radiance (CONUS) product for channel/band 14, for January 1-2 2020. The NetCDF files will be cropped to within latitudes 30 - 50 and longitudes -125 - -105, and saved in /storage/spestana/scratchspace.

python ./download-goes.py --bucket noaa-goes16 --year 2020 --month 2 --days 1 2 --product ABI-L1b-RadC --channel C14 --bounds 30 50 -125 -105 --dir /storage/spestana/scratchspace

We can do the same command with short flag names:

python ./download-goes.py -B noaa-goes16 -Y 2020 -M 1 -D 1 2 -p ABI-L1b-RadC -c C14 -b 30 50 -125 -105 -d /storage/spestana/scratchspace

Usage:

df = make_abi_timeseries(directory, product, data_vars, lon, lat, elev, outfilepath)

Inputs:

• directory: Directory containing GOES ABI product NetCDF files (using glob, this function searches recursively and allows the use of Unix shell-style wildcards)

• product: GOES ABI product to search directory for (using glob, this allows the use of Unix shell-style wildcards)

• data_vars: String or list of strings, each the name of a data variable contained within the ABI product NetCDF file; If an ABI-L1b-Rad product is being read, and radiance (“Rad”) is one of the data variables in this list, an additional column will be returned (ref_or_tb) containing reflectance (for ABI bands 1-6) or brightness temperature (for ABI bands 7-16) converted from the radiance values.

• lon: Longitude in degrees (-180 to 180)

• lat: Latitude in degrees (-90 to 90)

• elev: Elevation in meters (above GRS80 ellipsoid) of the point of interest

• outfilepath: Optional filepath and filename to output a csv file of the resulting pandas dataframe

Returns:

• df: Pandas dataframe where df.index is a pandas Timestamp of the GOES ABI observation time in UTC, and a column for each of the data_vars

Examples:

See make_abi_timeseries_example.ipynb jupyter notebook.

goes_ortho.orthorectify_abi() and goes_ortho.make_ortho_map()

Functions for orthorectifying GOES-R ABI imagery using a DEM. Produces an orthorectified NetCDF at the spatial resolution of the input DEM.

This method uses the GOES satellite’s known orbital position (from ABI product NetCDF metadata) to compute the intersection of line of sight (LOS) vectors with a DEM surface.

Usage:

# import to use these functions
import goes_ortho

# specify filepaths for inputs
abi_filepath = (
    ".\OR_ABI-L1b-RadC-M4C14_G16_s20171111750224_e20171111755027_c20171111755074.nc"
)
dem_filepath = ".\dem.tif"

# download DEM (make sure to convert to GRS80 ellipsoid model GOES ABI fixed grid uses)
get_dem(
    demtype="SRTMGL3",
    bounds=(-121, 36, -118, 41),
    out_fn=dem_filepath,
    proj="+proj=lonlat +datum=GRS80",
)

# specify which data variables we want to include in the final product
data_vars = ["Rad"]

# generate the pixel mapping
pixel_map = goes_ortho.make_ortho_map(abi_filepath, dem_filepath)

# orthorectify the image
goes_ortho.orthorectify_abi(
    abi_filepath, pixel_map, data_vars, out_filename="test_ortho.nc"
)

Examples:

Note: I’ve also included a copy of asp_binder_utils.py here which has the extremely useful get_dem() function for downloading geotiffs of DEMs.

See the orthorectify_abi_example.ipynb notebook for an example of orthorectifying GOES-16 and -17 images to make a pair of RGB images.

See the goes-orthorectify notebook for an example of orthorectifying a single GOES ABI image.

See the goes-orthorectify-aster.py script for an example of orthorectifying a batch of GOES ABI images.

Flowchart:

(flowchart diagram is a work in progress)

goes-timeseries.py

NOTE: Use ``goes_ortho.make_abi_timeseries()`` rather than this script.

Creates a time series of GOES ABI radiance values for a specified point location. This takes into account the point’s elevation (in meters) to correct for terrain parallax from off-nadir view angles of GOES.

Usage:

python ./goes-timeseries.py -d /storage/GOES/goes16/2017/03 -l <LATITUDE> <LONGITUDE> <ELEVATION>

Examples:

Gaylor Pit @ lat=37.88175, lon=-119.31212, elev=2811:

python ./goes-timeseries.py -d /storage/GOES/goes16/2017/03 -l 37.88175 -119.31212 2811

Grand Mesa West @ lat=39.0339, lon=-108.2140, elev=3033:

python ./goes-timeseries.py -d /storage/GOES/goes16/2017/03 -l 39.0339 -108.2140 3033

CUES site @ lat=37.643103, lon=-119.029146, elev=2940:

python ./goes-timeseries.py -d /storage/GOES/goes16/2017/03 -l 37.643103 -119.029146 2940