Python scripts behind the SICE toolchain for albedo retrieval.
by B. Vandecrux (2), A. Kokhanovsky (1), J. Box (2)
(1) German Research Centre for Geosciences, Potsdam, Germany (2) Geological Survey of Denmark and Greenland (GEUS) Øster Voldgade 10, 1350 Copenhagen, Denmark
- Running environment
- Theoretical background
- Script overview
- Input preparation
- Outputs
- Installation
- Example data
- Python interface for the fortran script sice.f
developped on Python 3.7.6 uses numpy, rasterio, time and sys packages
The snow surface characteristics retrieval is based on the following work:
- Kokhanovsky et al. (2018) On the reflectance spectroscopy of snow
- Kokhanovsky et al. (2019) Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument
- Kokhanovsky et al. (2020) The Determination of Snow Albedo from Satellite Measurements Using Fast Atmospheric Correction Technique
- Vandecrux et al. (2022) The Determination of the Snow Optical Grain Diameter and Snowmelt Area on the Greenland Ice Sheet Using Spaceborne Optical Observations
The ozone total ozone retreival is described in
The Algorithm Theoretical Basis Document is available here
Input files:
| File | Description |
|---|---|
| height.tif | Height in metre |
| mask.tif | Ice mask |
| O3.tif | Total column ozone |
| OZA.tif | Observation zenith angle |
| OAA.tif | Observation azimuth angle |
| r_TOA_01..21.tif | Top of the atmosphere OLCI reflectance |
| SZA.tif | Solar Zenith angle |
| SAA.tif | Solar azimuth angle |
| File Name | Description | Units |
|---|---|---|
| grain_diameter.tif | Snow grain diameter | mm |
| snow_specific_surface_area.tif | Snow specific surface area | m^{2}kg^{-1} |
| albedo_bb_planar_sw.tif | shortwave broadband planar albedo | 300-2400 nm |
| albedo_bb_spherical_sw.tif | shortwave broadband spherical albedo | 300-2400 nm |
| rBRR_01..21.tif | bottom of the atmosphere surface reflectance (OLCI bands 1 through 21) | |
| albedo_spectral_planar_01..21.tif | spectral planar albedo (OLCI bands 1 to 11 and 16 to 21) | |
| albedo_spectral_spherical_01..21.tif | spectral spherical albedo (OLCI bands 1 to 11 and 16 to 21) | |
| isnow.tif | See next table | |
| impurity_load.tif | pollutant load | ppm_weight |
| pol_type.tif | type of pollutant: 1(soot), 2( dust), 3 and 4 (other or mixture) | |
| al.tif | effective absorption length | mm |
| r0.tif | reflectance of a semi-infinite non-absorbing snow layer | |
| O3_SICE.tif | total ozone product (OLCI) corrected for ozone scattering | |
| factor.tif | Snow covered fraction within mixed pixels | |
| cv1.tif | quality check 1 (see ATBD) | |
| cv2.tif | quality check 1 (see ATBD) |
| Diagnostic Code | Description |
|---|---|
| 1 | clean snow |
| 2 | polluted snow |
| 3 | partially snow covered pixel |
| 100 | sza<75, no retrival |
| 102 | TOA reflectance at band 21 < 0.1, no retrieval |
| 103 | TOA reflectance at band 1 < 0.2, no retrieval |
| 104 | grain_diameter < 0.1, no retrieval, potential cloud flag |
| 105 | retrieved spherical albedo negative in band 1, 2 or 3 |
| -n | impossible to solve snow spherical albedo equation at band n |
We recommend the use of Anaconda and recent version of Python (>3.7).
The package can be installed as using
pip install git+https://github.com/GEUS-SICE/pySICE.git@pySICEv2.1
The package can be run using
pysice InputFolder OutputFolder
The output is added to the OutputFolder if it exists, if not is is added to the InputFolder folder. See help for other possibilities:
pysice -h
usage: pysice.py [-h] [-i FL_IN] [-o FL_OUT] [-c [CLEAN_SNOW]]
[--no_qc [NO_QC]] [--no_oz [NO_OZ]]
[input_folder] [output_folder]
positional arguments:
input_folder Path to input folder, containing OLCI radiance files
output_folder Path to output folder (same as input folder if non-
existent or not specified)
optional arguments:
-h, --help show this help message and exit
-i FL_IN, --fl_in FL_IN, --input FL_IN
Path to input folder, containing OLCI radiance files
(or use first positional argument)
-o FL_OUT, --fl_out FL_OUT, --output FL_OUT
Path to output folder (or use last positional
argument)
-c [CLEAN_SNOW], --clean_snow [CLEAN_SNOW]
If present, processes all pixels as clean snow
--no_qc [NO_QC] If present, does not run quality check
--no_oz [NO_OZ] If present, does not retrieve ozone
Post questions, suggestions, patches at https://github.com/GEUS-SICE/pySICE
Test input files are available here. Download and unzip using browser or with:
wget https://www.dropbox.com/s/b7wbervqls0p5cc/S3_test_data.zip
unzip S3_test_data.zip -d S3_test_data
sice_f.py reads the SICE-generated S3 geotiff files, converts them into ascii files, compiles and runs sice.f, reads the text outputs and save them into geotiff again.
Compile sice.f:
gfortran ./fortran/sice.f -o ./fortran/sice.exe
Create the output folder and run the script:
mkdir S3_test_data/fortran
python fortran/sice_f.py ./S3_test_data