MERCATOR OCEAN JOURNA: 
SEPTEMBER 2021 
NEMOWV3.4 + WW3 
DA (T/S/SLA) 
Res: 1/16 deg 
71 zlev. 
ECMWF 1/8° 
7 Clim, rivers 
Atlantic LOBC 
OGSTMv3 BFMvz 
3DVarBio (sat chl) | 
Res: 1/16 deg 
71 z lev.; biweekdy 
workflow 
Clim. rivers | 
& Dardanelles 
DA: monthly 
and grid point 
EOFs, vertical 
arror varying 
with depth 
Daily ECMWFI! 
precip. 
BFM: 
tarbonate 
öystem (DIC, 
CO2 flux) 
DA: coastal 
hl 
TüN 
NEMOv3.6 
DA updated 
Res: 1/24 deg 
141 zHev. 
New bathy 
39 rivers 
OGSTMv4 
with z*lev 
Res: 1/24 deg 
141{125) 
zHev. 
New bathy 
39 rivers 
WAM 4.5.4 
FC: 12 UTC 
Res: 1/24 deg 
Forecast days: 5 
ECMWF 1/8° 
Daily SSUV 1716° 
Atlantic LOBC 176° 
NEMOv3.6 + 
WW3; 
DA updated; 
Timestep 240’ 
BFMv5: N/P 
formulation 
DA (SWH) 
/Obs fram 2 
Satellites}) 
Daily SSUV 
1/7409 
DA: Assim 
S3A/B: 
mproved SST 
nudging 
Dardanelles 
LOB 
3DVarBio 
parallel 
Dardanelles 
LOBC 
WAM 4.6.2: 
vave age & tal 
of spectrum 
tuning; 
DA (+2 Sat) 
Forecast 
days: 10 
de 
DA: 
OceanVar 
parallel 
ECMWF 
1/10° 
DA: 
BGC-Argo 
daily assim; 
3FM: day/nighi 
Forecast dail} 
warkflow 
DA (+1 Sat) 
Change time 
of 
FC: 00 UTC 
O2 
Fides 
{8 comp): 
DA updated; 
TS = 120°; 
*Adified bathy 
Tidal Atlantic 
LOBC 
BFM: 
new variables 
ZOO, NH4, 
SiO4, Alk, pH 
[Atlantic LOBC 
DA (+ 2 Sat) 
FC: 00 & 12 
JTC 
Hourly 
Durrents & 
Sea level 
24° 
‚a: Med-MFC NRT systems evolutions since 2015 
1.1 Med-MFC Physical Systems 
In 2015 the Med-MFC physical component was delivering 
both NRT and RAN products. The Mediterranean analysis 
and forecast system, MedFS, (Pinardi and Coppini, 2010; 
Tonani et al., 2014) was composed of a two-way coupled 
hydrodynamic-wave modelling system (Clementi et al,, 
2017a). It was based on NEMO v3.4 and WaveWatch- 
Ill models implemented over the whole Mediterranean 
Sea with a horizontal resolution of 1/16° (ca. 6 km) and 
72 vertical levels. The Atlantic lateral open boundary 
conditions were provided by nesting into the Global Ocean 
daily analyses and forecasts fields. ECMWF (European 
Centre for Medium-Range Weather Forecasts) 1/8° surface 
atmospheric analyses and forecast fields (sea level 
pressure, cloud cover, humidity, air temperature, winds) 
were used with a temporal frequency of 6 hours (3 hours 
for the first 3 days of forecast). Meanwhile climatological 
monthly precipitations were exploited to constrain the 
Mediterranean Sea long-term water budget. Surface non- 
solar heat fluxes were corrected through a whole day 
relaxation to the Sea Surface Temperature (SST) satellite 
Level 4 Copernicus Marine Service product. The land river 
-unoff was imposed as monthly climatologies for seven 
major rivers around the Mediterranean Sea (Ebro, Rhone, 
Po, Vjos&, Seman, Buna-Bojana, Nile). The Dardanelles 
strait inflow was also parameterized as a river input. 
The OceanVar (3D variational) data assimilation system 
(Dobricic and Pinardi, 2008) was used to assimilate Sea 
Level Anomalv (SLA) alona tracks data from altimeters 
(Sea Level Thematic Assembly Center/SL TAC) and in 
situ vertical profiles of temperature and salinity (In-Situ 
Thematic Assembly Center/INS TAC) by means of a daily 
assimilation cycle. The modelling system has continuously 
avolved since 2015 (see Figure 1) to meet the increasina 
demand for: 
- higher model accuracy, 
more complete representation of dynamica; 
processes, 
-finer spatial scales, 
improved capability in storm surge forecasting 
including tidal forcing, 
improved representation of boundary conditions. 
Following those objectives, model evolutions in the last 6 
vears included: 
increase of system resolution to 1/24° (ca 3.5 km) and 
141 vertical levels (Clementi et al., 2017b), 
update of the hydrodynamic model to NEMO v3.6, 
increase of the river inputs (from 7 to 39), 
implementation of lateral open boundary conditions 
in the Dardanelles strait (Delrosso, 2020), 
use of higher ECMWF atmospheric forcing (1/10°), 
inclusion of tides. 
Furthermore, a continuous upgrade of the data 
assimilation component together with the assimilation of 
new observations such as SLA Sentinel-3A/B data anc 
an Improved SST nudging were achieved. Those mode 
upgrades led to a quality increase of the analysis and 
forecast product, which is continuously monitored