800
U. Callies et al.: Surface drifters in the inner German Bight
Ocean Sci., 13, 799-827, 2017
www.ocean-sci.net/13/799/2017/
jor source of uncertainty (Hufnagl et al., 2017). The circula
tion model BSHcmod, which this study mainly focuses on,
is run operationally. In cases of necessity, drifter simulations
will be based on a regridded archived version of model pre
dictions with near-surface currents representative of a 5 m
deep top layer. Therefore, even for an ideal surface drifter,
introducing a direct wind drag can be helpful as a means
of compensating insufficient vertical resolution of hydrody
namic currents. The second hydrodynamic model employed
in this study, TRIM, was set up with aim deep top layer.
Comparing drift simulations based on outputs from the two
different models helps assess uncertainties possibly related
to the vertical resolution of near-surface currents.
More complex impacts of winds on surface currents may
be mediated via waves (Perrie et ah, 2003; Ardhuin et ah,
2009). Rôhrs et ah (2012) found evidence that predictabil
ity of drift trajectories can be improved by the inclusion of
numerical wave modelling. On the other hand, Stokes drift
and other wave effects are often neglected in operational sys
tems. According to Breivik and Allen (2008), the main rea
son for this is that wave processes are already taken into ac
count by empirically tuned windage coefficients that summa
rize changes of an object’s trajectory induced by combined
impacts of both winds and waves. The situation can differ
in near-shore regions, where wave refraction directs wave-
induced transports towards the coast (Sobey and Barker,
1997).
A key objective of this study is checking whether explicit
inclusion of Stokes drift calculated with a state-of-the-art
wave model (WAM) improves drift simulations. Assessing
the necessity to distinguish between effects of direct wind
drag and Stokes drift is essential to avoid overparametriza-
tion. Waves and resulting Stokes drift were calculated using
the wind forcing also employed for hydrodynamic simula
tions with TRIM. However, we did not explore effects of in
cluding wave-current interactions into hydrodynamic simu
lations (Staneva et ah, 2017).
Horizontal grid resolutions of the two hydrodynamic
data sets (900 m in BSHcmod and 1.6 km in TRIM) allow
for a proper representation of mesoscale eddies in the re
gion of interest. However, simulations may miss relevant
sub-mesoscale processes. According to Kjellsson and Dôôs
(2012) the underestimation of eddy kinetic energy by Eule-
rian flows is a common finding of many model validation
studies. This deficiency could be fixed by a transition to
an advection-diffusion equation, introducing an additional
stochastic random walk term. In this context, specification
of the proper eddy diffusivity as function of grid resolution
poses a major problem. There are, however, also concerns
regarding the simple theoretical concept. For the advection-
diffusion approach to be valid, a spectral gap should sepa
rate processes on the scale resolved from sub-grid-scale pro
cesses. Such a gap may often not exist (see, De Dominicis
et al., 2012, for instance).
Garraffo et al. (2001) compared the statistics of drifter ob
servations in the North Atlantic with those of drift simula
tions based on Eulerian velocities from a model with about
6 km horizontal resolution. Without a stochastic model of
sub-grid-scale actions, they found simulations to underesti
mate eddy energy. Simulated absolute dispersion being too
low was also reported by Kjellsson and Doos (2012) evalu
ating drifters deployed in the Baltic Sea. Referring to global
ocean data, Doos et al. (2011) tuned random turbulent veloc
ity in their drift model to achieve better agreement between
relative dispersion of simulated trajectories and correspond
ing observations. However, they found this approach was too
simple for a reasonable reproduction of Lagrangian proper
ties.
More sophisticated analyses of the relative dispersion of
pairs of particles try to distinguish the regimes of “local dis
persion” driven by eddies comparable in size to the distance
between two drifters and of “non-local dispersion” driven by
eddies with scales much larger than this distance (e.g. Kosza-
lka et al., 2009). Beron-Vera and LaCasce (2016) conducted
such an analysis for data from the Grand Lagrangian Deploy
ment experiment (GLAD), in which more than 300 drifters
were deployed in the Gulf of Mexico. Drifter launch posi
tions spaced from 100 m to 15 km apart allowed to study sub-
mesoscale dispersion characteristics in great detail. However,
referring to experimental data in the south-western Gulf of
Mexico, Sanson et al. (2017) show that for large initial dis
tances the probability density functions of pair separations
get dependent on prevailing mesoscale circulation patterns.
This aspect seems particularly relevant for the present study.
Variations of the residual current regime in the inner German
Bight can very well be approximated in terms of only 2-3
degrees of freedom, depending on prevailing winds (Callies
et al., 2017). Tidal currents dominate short-term transports.
The data available for this study (six drifters, tracked be
tween 9 and 54 days) are insufficient for studying features of
oceanic turbulence. Therefore, in the present model valida
tion study, stochastic simulation of sub-grid-scale processes
will not be considered. Ohlmann et al. (2012) provide an ex
ample that even an accurate reproduction of mean drifter pair
separation does not necessarily imply good agreement be
tween observations and corresponding simulations. Accord
ing to Coelho et al. (2015), models used in the aforemen
tioned GLAD experiment in the Gulf of Mexico had limited
success capturing the observed drift patterns. Barron et al.
(2007) provide a list of typical separation rates in different
regions worldwide. For an experiment in the Ria de Vigo es
tuary in north-west Spain, Huhn et al. (2012) reported sim
ulation errors that were relatively small compared to those
typically found in the open ocean. This study tries to pro
vide a realistic estimate of how reliable operational forecasts
in the German Bight, another shelf sea region, can be ex
pected to be. This includes gaining preliminary indications
for regions where the deterministic part of a model needs im
provement.