MERCATOR OCEAN JOURNAL 
SEPTEMBER 2021 
With the introduction of Sentinel-1B satellite in mid 
2016, the combined data volume from the two active 
Sentinel-1 SAR instruments enabled the introduction of 
aggregatable daily composite products (mosaics) on fixed 
grids, as opposed to the low latency high detail NRT product, 
which was complicated to handle for the general user. The 
composite product combines the smaller NRT sea ice drift 
data patches over a 24 hour period into a manageable fixed 
grid. 
At the end of 2019, the composite product was enhanced 
with derived vector flow divergence, vorticity, shear layers, 
thus including information for the user describing the sea 
ice dynamics in more detail than raw measurements. 
Given the derivative nature of the vector flow, it quickly 
became obvious that even though the produced drift 
values were reliable, even small noise contributions had a 
significant influence on divergence values included in the 
24h composite product. This resulted in the introduction 
of an intermediate step where the accuracy of each NRT 
drift measurement was recalculated using data at higher 
spatial resolution going from the original 300 m image 
data down to 100 m, thereby much improving the quality of 
divergence values of the composite. 
1.8 Arctic multiyear sea ice drift 
In 2015, Ifremer products were the Arctic sea ice drift at low 
resolution for the period from 1992 up to the present, in the 
ice season from October until April. This product is inferred 
from the timeseries data available at CERSAT/Ifremer. SSM/I 
radiometer data is merged with several scatterometer 
sensors such as QuikSCAT/ASCAT-A/ASCAT-B, and 
processed at 3- and 6-day lags. This product was delivered 
once a year as a long-term reanalysis product. 
One evolution of the product was to add the months of 
September and May to the estimate of sea ice drift. These 
months are not easy to handle because it is the time 
for freeze and melt of sea ice in the Arctic. Microwaves 
sensors are indeed very sensitive to these processes. 
The merging of radiometer and scatterometer data is in 
particular interesting to use for these months because it 
enables having at least 80% more drift vectors on the sea 
ice cover. 
Ifremer developed an algorithm to estimate sea ice drift at 
medium resolution from the AMSR series. This timeseries 
‚2002-present) is provided at 2-, 3- and 6-day lags from 
Jctober until April. The benefit of the resolution enables a 
algher angle resolution, and is useful in particular for high 
magnitude drift (Fram strait for example) thanks to the 
detection at 2 day-lag. 
Sea ice drift in the Arctic at low and medium resolution are 
now processed, qualified and provided monthly to CMEMS. 
New sensors such as ASCAT-C and CFOSAT have been 
tested and will be integrated to continue the timeseries. 
1.9 Arctic NRT Sea Ice Thickness based on merged 
Cryosat2 and SMOS data 
The NRT sea ice thickness (SIT) product provides a 
weekly mean SIT over the Arctic, and is a product 
based on merged SMOS and CryoSat2 data. The SMOS 
mission provides L-band observations. Adjacently, the ice 
thickness-dependency of brightness temperature enables 
to estimate of the sea-ice thickness for thin ice regimes. 
CryoSat2 uses radar altimetry to measure the height of the 
ice surface above the water level, which can be converted 
into sea ice thickness. As SMOS loses sensitivity near 1 
meter ice thickness and the SIRAL altimeter of CryoSat2 
at below 1 m (Wang et al., 2016), in the merged SIT the two 
methods complement each other. 
The merging algorithm, developed in Alfred Wegener 
ınstitute (Ricker et al., 2017), leverages daily Soil Moisture 
and Ocean Salinity (SMOS) observations and CryoSat2 
measurements of one week to produce SIT fields in a 25 km 
FASE2 grid. The sensors have significantly different swath 
widths, surface resolutions and revisit times. To merge 
the satellite data with different update rates of thickness 
observations, the algorithm uses an optimal interpolation 
'Ol) scheme. SMOS data are rejected over multiyear ice and 
when uncertainties are more than 1 m. 
Due to poorly known properties of melting ice and snow the 
SIT retrieval is only performed during the freezing season 
between October and April. FMI has produced the weekly 
merged SIT product for CMEMS since April 2020. Since 
2021, the update frequency of thickness fields has been 
increased, and a rolling weekly mean SIT is provided daily 
1.10 Arctic Sea and Ice Surface Temperature 
The operational Arctic sea and sea ice surface temperature 
(SST/IST) product is a Level 4 (L4) gap-free field covering 
surface temperatures of the sea ice, the marginal ice 
zone and the ocean north of 58° northern latitude 
Temperatures have a spatial resolution of 1/20°. In 2015, 
the input to the operational product consisted of Level 2, 
swath-based Metop AVHRR SST/IST observations from 
the OSI SAF project, supplemented with operational NOAA 
SST products. A dynamical and spatially varying bias 
adjustment scheme was introduced in 2017 where the 
S5ST products were referenced to each other, resulting in 
improved performance for SST fields. 
The launch of Sentinel 3-A and B provided a significant 
amount of additional SST observations. The Sentinel 3A 
data were included in April, 2019 and the Sentinel 3B was 
included in December, 2019 together with NOAA 20 SST 
observations and a new SST/IST product from the NPP 
VIIRS satelliteNo full text available for this image