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Pre-Operational Sentinel-3 snow and ice products (SICE)



Land ice mass loss is the largest source of global sea level rise. Since 1992, two thirds of sea level contribution from land ice comes from the Arctic. Roughly half of Greenland ice sheet mass loss is from increased surface melting. The fraction from surface melting is even higher for smaller Arctic ice masses. The dominant energy source for melt is absorbed sunlight controlled by surface albedo. Bare ice and snow impurities, including biological effects present strong melt amplifiers through surface albedo. NASA MODIS sensors provide a climate data record (CDR) of snow extent and ice albedo since 2000 with the hosting Terra and Aqua missions now several years beyond design lifetime. The NOAA VIIRS sensor bridges the need for a satellite-derived albedo. However, Copernicus Sentinel-3 also fulfils the WMO essential climate variable mandate and for decades to come with the following additional advantages over VIIRS and MODIS:
1. The Sentinel-3 OLCI instrument offers higher (300 m) finest spatial resolution (SR). The finest SR for MODIS is 500 m. For VIIRS, the finest SR is 750m.
2. Sentinel-3 OLCI and SLSTR instruments offer more spectral coverage than MODIS or VIIRS, with the OLCI channel 21 being of particular value being located in the part of the spectrum most sensitive to snow grain size. Neither MODIS nor VIIRS measure in this spectral channel.
3. The algorithms proposed here are a full physics based retrievals vs often used empirical techniques.
4. The recently completed Scientific Exploitation of Operational Missions (SEOM) Sentinel-3 for Science (S34Sci) Land Study 1: Snow (S3 Snow) albedo algorithm outperforms NASA MODIS MOD10A1 product for dry clean snow.

Main objectives / end goals of the study are:
1. deliver an automated open source processing chain using Sentinel-3 OLCI and SLSTR sensors to determine a dry/wet snow and clean/polluted bare ice spectral and broadband optical albedo 1 km daily product for land ice (glaciers, ice caps, ice sheet).
2. determine an optimal cloud clearing process for cryospheric application leveraging cloud ID
insight from SEOM Sentinel-3 for Science, Land Study 1: Snow
3. test the above for application to sea ice (as opposed to land ice).
4. implement terrain correction for slopes under 4 degrees typical of more than 90% of land ice.
Justification: terrain slope and azimuth has a strong impact on snow and ice anisotropic reflectance
in optical wavelengths. Above 4 degrees remains in development elsewhere, and does not comprise
a significant portion of the ice sheet.
5. validate the algorithms using field data.
6. deliver daily 15 March – 30 September 1km pan-Arctic glacierized region albedo products for years
2017 and 2018 via the web portal.
7. demonstrate a pre-operational near-realtime (under 6 hours latency) capability for Sentinel-3A and
Sentinel-3B for delivering spectral and broadband albedo.


Prime contractor