She et al.
Operational Oceanography and Earth System Science
Frontiers In Earth Science | www.frontlersln.org
6
February 2020 | Volume 8 | Article 7
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FIGURE 1 I Station distribution of operational observations In the Baltic Sea.
Nielsen, 1999; Tuomi et al., 1999) based on the WAM model.
Ocean, ice and oil drift forecast models BSH-Cmod, BSH-Dmod,
HIROMB, and HELMI had been developed and operationalized
in the early and mid-1990s (Haapala and Lepparanta, 1996; Dick
et al., 2001; Wilhelmsson, 2002; Funkquist and Kleine, 2007).
They are currently updated by more advanced coupled ocean-
ice forecasting systems HBM (HIROMB-BOOS Model, Berg and
Poulsen, 2012), NEMO-Nordic (Hordoir et al., 2018), and GETM
(General Estuarine Transport Model, Burchard and Bolding,
2002; Biichmann and Soderkvist, 2016). HBM is a dynamically
two-way nested model with excellent hybrid parallel computing
performance (Poulsen et al., 2014). NEMO is the European
operational model with the largest user community. GETM
has advantages in resolving the coastal-estuary continuum with
specific advances in turbulence closure schemes and reduced
diapycnal mixing due to the usage of vertically adaptive
coordinates (Burchard et al., 2009). Biogeochemical models
such as ERGOM (Neumann, 2000; Maar et al., 2011) and
SCOBI (Swedish Coastal and Ocean Biogeochemical model,
Eilola et al., 2009) have been developed in this century for
setting up operational ecological service. The former has been
used to provide basin-scale biogeochemical forecasts for CMEMS
since 2009 (Tuomi et al., 2018) while the latter was used for
producing biogeochemical reanalysis (Liu et al., 2017). The
above operational model systems have been applied for basin-
scale forecasts in 0.5-1 nautical mile (nm) resolution and
a up to 60 m resolution for local scale forecasts (She and
Murawski, 2018). Coupled model development, especially wave
related coupling processes, e.g., ocean-wave, atmosphere-wave,
and wave-ice interaction, is an on-going activity by BOOS
partners. In the Phase II of CMEMS BAL MFC (2018-2021),
a fully coupled ocean-wave-ice-biogeochemical model system
NEMO-LIM-WAM-ERGOM together with PDAF (Parallel Data
Assimilation Framework) assimilation is under development.
Data Assimilation
Significant data assimilation capacity has also been developed
in the operational community, ranging from a simplified
Kalman Filter for sea surface temperature (SST) assimilation
in BSH-Cmod (Larsen et al., 2007), pre-operational 3DVAR
(3D Variational method), and EnOI (Ensemble OI) for T/S
assimilation and reanalysis production in HBM (Zhuang et al.,
2011; Fu et al., 2012) to the ensemble variational method
and PDAF simplified Karman filter for physical-biogeochemical