Ocean Dynamics 
4) Springer 
packages forming the regional monitoring and forecasting 
centers for the Northwest Shelf (NWS) and the Baltic Sea 
(BAL) which have been transformed to parts of CMEMS in 
May 2015. The nominal forecast products for the two regions, 
namely, FOAMAMM for NWS and DMI HBM for BAL 
(see Table 1), are implemented in the MME. One goal in both 
MyOcean work packages was to provide additional uncertain 
ty information on the nominal products. In addition, the MME 
is now established as an independent service, taking advan 
tage of the various existing operational ocean forecasting 
models, and benefitting the participating agencies and insti 
tutes. This service is basically a supplement to validation and 
provides a comparison of the contributing forecasts in order to 
reveal the degree of agreement and deviation for different 
parameters. The comparison is done on a daily basis to keep 
track of the actual variations and to detect potential problems 
in individual model systems. Based on the daily and long-term 
results, the model systems can be improved and further 
developed. 
To enhance the sustainability and user uptake of the MME, 
the development is done in close cooperation with the com 
munities of the Baltic Operational Oceanographic System 
(BOOS, www.boos.org, accessed 24 October 2014) and the 
Northwest European Shelf Operational Oceanographic 
System (NOOS, www.noos.ee, accessed 24 October 2014). 
These two communities are regional services integrated in 
the European Global Ocean Observing System 
(EuroGOOS). Both systems focus on the provision and 
improvement of high-quality operational marine data. 
This study is carried out for the North Sea and the Baltic 
Sea which are connected by a Transition Area, the Skager- 
rak and Kattegat. The Baltic Sea is characterized by brack 
ish waters with a surface salinity around 20 in the south 
decreasing towards the north and east (about 2 in the 
Bothnian Sea and the eastern Gulf of Finland). During 
winter months, the northern parts of the Baltic Sea are 
regularly covered by sea ice. The surface salinity is influ 
enced by freshwater inflow from rivers and melting sea ice 
in spring (Feistel et al. 2008; Lepparanta and Myrberg 
2009). The exchange of water masses between the North 
Sea and Baltic Sea is characterized by high-saline water 
entering the Baltic Sea via the Great Belt, the Little Belt, 
and the Oresund by near-bottom currents. Low-saline sur 
face water is flowing out of the Baltic Sea. Sea surface 
currents are mainly induced by wind and density gradients, 
as well as by differences of water level. The dominant 
feature of currents in the North Sea is the tidal motion 
(Otto et al. 1990). The residual circulation is characterized 
by a major inflow from the North Atlantic and the English 
Channel and a major outflow from the Baltic Sea as the 
Norwegian Costal Current. The surface salinity averages 
between 34 and 35 in the central North Sea. There are 
freshwater inflows from rivers, such as Rhine and Elbe, 
and from the Baltic Sea affecting the surface salinity. The 
surface temperature has a strong annual cycle in both 
regions. 
The MME systems of the North Sea and Baltic Sea as well 
as the contributing models are presented in Sect. 2. Ensemble 
statistics of the MME are explained and some examples are 
displayed in Sect. 3. The uncertainty estimates between the 
products are based on spatio-temporal statistics of the data 
collected. As a result, regions with high and low uncertainties 
as well as seasonal patterns can be identified. A comparison to 
satellite data is presented. Results of the spatio-temporal sta 
tistics are shown in Sect. 4 and a summary is given in Sect. 5. 
2 MME system 
2.1 Overview of contributing models 
Thirteen different operational ocean forecasting models cov 
ering either the North Sea or the Baltic Sea or both regions 
contribute to the MME. Details on model area, boundary con 
ditions, and forcing are listed in Table 1. A brief overview of 
each system is provided below. It should be noted, however, 
that the forecasts are not frilly independent of each other since 
most of the models covering the Baltic Sea are based on the 
same kernel of model code (CMOD) and are therefore related 
to a certain degree (Berg and Poulsen 2012). Furthermore, 
some models are using the same forcing and boundary condi 
tions. Accordingly, it could be expected that the statistical 
evaluation might be influenced by this dependency. 
CMOD and HBM at BSH The Federal Maritime and Hydro- 
graphic Agency (BSH) runs two forecast models with dynam 
ical vertical coordinates covering the North and Baltic Sea: the 
operational Circulation Model CMOD (Dick et al. 2001; Dick 
and Kleine 2008) and the pre-operational HIROMB-BOOS 
Model, HBM (Berg and Poulsen 2012). Both model setups 
consist of a coarse grid with a horizontal resolution of 3 nauti 
cal miles (NM) and a maximum of 35 vertical layers, and a 
two-way nested fine grid with a horizontal resolution of 
0.5 NM and a maximum of 25 vertical layers covering the 
inner German Bight and Western Baltic. While CMOD uses 
a simple algebraic turbulence model (Kleine 1994), HBM 
runs with a k-omega turbulence model (Berg 2012). 
DKSS2013 and HBM at DMI The Danish Meteorological 
Institute (DMI) runs the storm surge model DKSS2013 and 
HBM as the nominal MyOcean product, which both cover the 
North Sea and Baltic Sea (Berg and Poulsen 2012). The model 
runs on a two-way nested rectangular grid. The horizontal 
resolution of DKSS2013 is 3 NM in the main domain, 
1 NM in the Wadden Sea, and 0.5 NM in the Transition Area. 
The model setup consists of vertical z-coordinates with a