Ocean Dynamics 
Ö Springer 
Fig. 9 Monthly mean (a) and 
annual mean (b) RMSD of SST 
from the MME mean, MME 
median, and the ensemble 
members in the North Sea in 
2014. The percentage of available 
satellite data per month is marked 
as dotted line 
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 
FCOO DMIDKSS BSHcmod BSHHBM SMHI METNO RBINS METUK MMEmeanMMEmedian 
and 0.8 °C (Fig. 11). Some ofthe forecasts like FCOOGETM 
and BSH CMOD have positive biases in winter but negative 
biases in summer. The two forecasts from SMHI show an 
opposed pattern compared to the other forecasts. Data assim 
ilation is applied in these models by using various observa 
tions, i.e., in situ and ferry box data and satellite data, which 
could be a reason that none of these forecasts is very close to 
the satellite observations used for this study. 
Most forecasts have the highest negative biases in July, 
where the bias from FCOO GETM even reaches -2.5 °C 
(Fig. 11). It indicates that the surface temperature is 
underestimated by most ofthe forecasts in July. The MyOcean 
product (DMIHBM) has a negative bias in all months. Com 
pared to the ensemble members, the biases of the MME prod 
ucts have less significant changes ranging from slightly above 
0 to -0.6 °C with largest absolute values in July. 
Differences in the annual mean biases of the MME prod 
ucts and the forecasts are quite distinct (Fig. 11). The only 
forecast with slightly positive bias is FMIHBMec while 
FMIHBMhirlam exhibits a slightly negative bias. The 
biases of the remaining ensemble members vary between 
-0.2 and -0.6 °C, where the values for the MME products 
are similar around approximately -0.32 °C. 
The RMSD ofthe MME products and the ensemble members 
vary strongly with time (Fig. 12). None of the products has the 
lowest error throughout the whole year. For instance, the lowest 
error in February and June is calculated for BSH CMOD, while 
in May, the error of BSH_HBM is lowest and, in August, the 
RMSD of SMHI HIROMB NS03 has the lowest value. Except 
for February and between June and August, the MME mean has 
the lowest errors with values less than 0.6 °C. In addition, a 
seasonal pattern can be distinguished in the monthly mean 
RMSDs. Between May and August, the errors of all forecasts 
are approximately two times higher than the values in the other 
months, accompanied by a large spread between the errors. The 
errors of the MME products are higher than the RMSD of some 
of the ensemble members in these months. This indicates that, if 
there are large uncertainties among the forecasts, the improve 
ment gained through the ensemble process is decreased. To ex 
amine the physical reasons causing these seasonal features, more 
studies focusing on the atmospheric forcing of each forecast are 
necessary, which is not part of this study. 
Although the MME products do not have the lowest errors 
throughout the whole year in the Baltic Sea, the MME mean 
still has the lowest annual mean RMSD of about 0.65 °C, 
which is slightly lower than the value from BSH CMOD 
(Fig. 12). It shows that the ensemble process can improve 
the accuracy of the forecasts. 
Figure 13 shows the spatial distribution of RMSD from each 
ensemble member and the MME products in the Baltic Sea in 
July 2014. The distribution of regions with high RMSD is dif 
ferent between the individual forecasts and the MME products, 
whereby the errors seem to increase from the southern part of 
the Baltic Sea to the North in all plots. This feature is most 
obvious in the plots showing FCOO GETM, DMI DKSS, 
FMI HBM ec, and FMI HBM hirlam. Some forecasts, such 
as BSH HBM, DMI HBM, DMI DKSS, FMI HBM hirlam, 
and FMI HBM ec, have large errors along the southern bound 
ary of the Baltic Sea. RMSDs are also high in the Gulf of 
Finland in all plots. A similar but slightly weaker pattern is