Latest operational SICE version developed by @RasmusBahbah.
It uses PTEP2, SentinelHub and pySICEv2.1.

This release contains the script used for @AdrienWehrle 's NRT processing active in 2021, 2022 and 2023 and the so-called "showcase" reprocessing. It is being replaced by https://github.com/GEUS-SICE/SICE-EDC that uses PTEP2, SentinelHub and pySICEv2.1. The present release is for archiving purpose.

This data was used for the following study:

Box, J. E., Wehrlé, A., van As, D., Fausto, R. S., Kjeldsen, K. K., Dachauer, A., et al. (2022). Greenland ice sheet rainfall, heat and albedo feedback impacts from the mid-August 2021 atmospheric River. Geophysical Research Letters, 49, e2021GL097356. https://doi.org/10.1029/2021GL097356

Wehrlé, A.; Box, J. E.; Niwano, M.; Anesio, A. M.; Fausto, R. S. Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bulletin, 2021, 47. https://doi.org/10.34194/geusb.v47.5284

And to produce the following datasets:

Wehrlé, Adrien; Box, Jason; Vandecrux, Baptiste; Mankoff, Ken, 2021, "Snow and ice broadband albedo from Sentinel-3 OLCI measurements and empirical regression", https://doi.org/10.22008/FK2/SNX8L6, GEUS

Wehrlé, Adrien; Box, Jason; Vandecrux, Baptiste; Mankoff, Ken, 2021, "Daily Near Real Time (NRT) Greenland snow and ice broadband albedo, SSA and cloud mask from Sentinel-3's OLCI", https://doi.org/10.22008/FK2/SD56CB, GEUS Dataverse, V27

This release is an improvement from SICEv2.3.1.

This toolchain does the following:

• Fetch S3 OLCI & SLSTR products
• Process OLCI & SLSTR using SNAP GPT
• Process using pySICE
• Build daily mosaic

Specificities of this release:

• Designed for SNAP8 and tie-point geocoding
• Using pySICEv1.4

This release is for archiving purpose.
This release archives the branch called "bav-dev".

This release is an improvement from SICEv2.4 but was never used operationally.
It has been ported successfully to PTEP2 by Sinergise but reprocessing was put on hold because a new version of pySICE was underway.

This toolchain does the following:

• Fetch S3 OLCI & SLSTR products
• Process OLCI & SLSTR using SNAP GPT
• Process using pySICE
• Build daily mosaic

Specificities of this release:

• Designed for SNAP8 and tie-point geocoding
• Using pySICEv1.6
• Optimized xarray structure allowing to process scenes by chunks

This release is for archiving purpose.
This release archives the branch called "SNAP8_500m".
This release is an improvement from SICEv2.3.1 but was never used operationally.

This toolchain does the following:

• Fetch S3 OLCI & SLSTR products
• Process OLCI & SLSTR using SNAP GPT
• Process using pySICE
• Build daily mosaic

Specificities of this release:

• Designed for SNAP8 and tie-point geocoding
• Using pySICEv1.5

This toolchain does the following:

• Fetch S3 OLCI & SLSTR products
• Process OLCI & SLSTR using SNAP GPT
• Process using pySICE
• Build daily mosaic

Specificities of this release:

• Designed for SNAP8 and tie-point geocoding
• Using pySICEv1.4
• Cloudy pixels are not removed from reflectance maps
• Using DEM provided in OLCI files
• Fixed BBA_empirical coefficients

This toolchain does the following:

• Fetch S3 OLCI & SLSTR products
• Process OLCI & SLSTR using SNAP GPT
• Process using pySICE
• Build daily mosaic

Specificities of this release:

• Designed for SNAP7 and per-pixel geocoding
• Using pySICEv1.4
• Cloudy pixels are not removed from reflectance maps
• Using DEM provided in OLCI files

This toolchain does the following:

• Fetch S3 OLCI & SLSTR products
• Process OLCI & SLSTR using SNAP GPT
• Process using pySICE
• Build daily mosaic

Specificities of this release:

• Designed for SNAP8 and tie-point geocoding
• Using pySICEv1.4
• Cloudy pixels are not removed from reflectance maps
• Using DEM provided in OLCI files

This toolchain does the following:

1. Fetch S3 OLCI & SLSTR products
2. Process OLCI & SLSTR using SNAP GPT
3. Process using pySICE
4. Build daily mosaic

Specificities of this release:

• Designed for SNAP7 and per-pixel geocoding
• Using pySICEv1.4
• Cloudy pixels are not removed from reflectance maps
• Using DEM provided in OLCI files

This toolchain does the following:

• Fetch S3 OLCI & SLSTR products
• Process OLCI & SLSTR using SNAP GPT
• Process using pySICE
• Build daily mosaic

Specificities of this release:

• Designed for SNAP7 and per-pixel geocoding
• Using pySICEv1.3
• Cloudy pixels are removed from reflectance maps

This release is for archiving purpose.

This is an old version of the SICE toolchain that uses the SNAP7 and a plugin developed by BrockmanConsult:
https://s3tbx-snow.readthedocs.io/en/latest/s3snow_processing_system.html
https://github.com/bcdev/s3tbx-snow

It was used for the following publication:

Kokhanovsky, A.; Lamare, M.; Danne, O.; Brockmann, C.; Dumont, M.; Picard, G.; Arnaud, L.; Favier, V.; Jourdain, B.; Le Meur, E.; et al. Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument. Remote Sens. 2019, 11, 2280. https://doi.org/10.3390/rs11192280