MERCATOR OCEAN JOURNA: 
SEPTEMBER 2021 
1.3 Sea ice rheology 
The TOPAZ4 reanalysis has shown a lack of sensitivity 
of the rheological model. A new sea ice model based on 
‘he Brittle-Bingham-Maxwell rheology has thus been 
developed in a Lagrangian coordinate (the neXtSIM model, 
zampal et al., 2016) to improve sea ice drift and other 
-elated sea ice properties. This model has been set up Ir 
standalone forecast mode for the Central Arctic including a 
ıudging term to daily satellite sea ice concentrations. 
\eXtSIM-F forecasts show much more detailed sea ice 
“eatures than TOPAZ4 (Figure 2, leads and landfast ice in 
Jarticular are not visible on TOPAZ4) and their motions 
are more accurately forecasted, with drift distance errors 
cut from 8 to 4 km per day. Sea ice forecasts are used in 
ı1avigation services. 
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2: Sea ice thickness on the 12th March 2021 from the TOPAZ4 system and the recently introduced neXtSIM-F forecast (right) 
1.4 Biogeochemical modeling 
When compared to independent Chlorophyll profiles from 
BGC-Argo buoys in the Nordic Seas, the assimilation 
single-handedly reduces errors drastically (Figure 3). The 
primary production accuracy is an important prerequisite 
for carbon cycle simulation and thereby provides up to 
date information about the ocean carbon pump and ocean 
acidification. 
About data assimilation, the biogeochemical reanalysis 
adopted an Ensemble Kalman Smoother (EnKS) to assimilate 
both satellite surface Chlorophyll data and nutrient profiles. 
The EnKS optimizes biogeochemical model parameters in 
ECOSMO using data from posterior week and can correct 
the timing of the Spring bloom. The resulting reanalysis 
product is the first demonstration of an EnKS in CMEMS. 
The biogeochemical model coupled to the ocean model 
has been updated twice during Copernicus 1.0. The first 
Jpgrade in April 2016 replaced NORWECOM with ECOSMO, 
where parameters were re-tuned to avoild an excessive 
amplitude of the Spring bloom. 
In a second upgrade in May 2021, several changes were 
brought to ECOSMO: 
doubling of both horizontal and vertical resolution 
‚6 km and 50 hybrid layers), 
- simple assimilation of satellite surface Chlorophyll 
data (Uitz et al., 2006), 
inclusion of the carbon cycle, 
-inclusion of light transmission through sea ice, 
improvements of the model inputs (rivers discharge 
from Arctic-HYPE model, atmospheric deposition 
of nutrients from EMEP model and lateral boundary 
conditions from Global MFC model PISCES), 
the FABM software now couples ECOSMO to HYCOM.