U. Callies et al.: Surface drifters in the inner German Bight 
801 
www.ocean-sci.net/13/799/2017/ 
Ocean Sci., 13, 799-827, 2017 
Table 1. Drifters deployed in May 2015. 
No. 
Type 
Start 
End 
Length 
(km) 
Dist 
(km) 
AT 
(days) 
Time (UTC) 
° E 
° N 
Time (UTC) 
° E 
° N 
1 
MD03i 
19 May (12:31) 
7.5216 
54.2160 
2 Jun (21:12) 
8.8338 
54.5180 
1032.1 
91.7 
14.4 
2 
MD03i 
21 May (17:13) 
7.1484 
55.0752 
25 May (09:47) 
7.3080 
55.1360 
87.4 
12.2 
3.7 
3 
MD03i 
21 May (17:13) 
7.1480 
55.0750 
25 May (09:59) 
7.2526 
55.1160 
85.7 
8.1 
3.7 
4 
MD03i 
21 May (17:36) 
7.1426 
55.0786 
24 May (15:00) 
7.2960 
55.0626 
66.6 
10.0 
2.9 
5 
MD03i 
27 May (09:49) 
5.9126 
54.3752 
15 Jul (01:28) 
8.4680 
55.1232 
1264.0 
184.4 
48.7 
6 
MD03i 
27 May (16:01) 
6.0446 
54.2024 
20 Jul (23:15) 
8.0944 
55.1930 
1467.7 
172.1 
54.3 
7 
ODi 
30 May (08:36) 
6.7516 
54.6712 
8 Jun (09:59) 
8.2360 
55.7702 
273.2 
154.6 
9.1 
8 
ODi 
30 May (12:09) 
6.7476 
54.2554 
9 Jul (19:15) 
8.5282 
55.2812 
1203.0 
161.8 
40.3 
9 
ODi 
31 May (07:46) 
7.8816 
54.0842 
24 Jun (03:28) 
8.8360 
54.1316 
844.3 
62.6 
23.8 
Type: two drifter types used (see Fig. 1). Length: sum of the lengths of linear segments connecting observed drifter locations. Dist: linear distance between the first 
and last drifter locations observed. AT: days between the first and the last observation. Drifter nos. 2, 3 and 4 travelling for only few days were ignored for this study. 
The paper is organized as follows: Sect. 2 documents how 
observations were taken (Sect. 2.1) and how corresponding 
model simulations were performed (Sect. 2.2). Section 2.3 
describes two data sets used for characterizing residual cur 
rent variability in the German Bight on a daily basis. Re 
sults (Sect. 3) are presented in two parts: Sect. 3.1 provides 
a synoptic description of all drifters deployed and places 
observations into the context of ambient atmospheric and 
marine conditions; Sect. 3.2 provides the analysis of how 
corresponding model simulations match observations. First, 
full simulated trajectories are presented using currents from 
TRIM or BSHcmod, the latter also combined with wind drag 
and Stokes drift, respectively. A more detailed evaluation of 
model performance is then based on subdividing drift trajec 
tories into segments of 25 h length. Results are discussed in 
Sect. 4; main conclusions are provided in Sect. 5. 
2 Material and methods 
2.1 Drifter observations 
In May 2015, a total of nine drifters were deployed at dif 
ferent locations in the German Bight (North Sea) during the 
FS Heincke cruise HE 445. The raw data are freely acces 
sible at Carrasco and Horstmann (2017). Table 1 specifies 
each drifter’s launch position and launch time as well as its 
last position, the total length of its trajectory and the simple 
linear distance between its initial and final locations. Drifter 
nos. 2, 3 and 4, travelling for only few days, were ignored 
for this study. All drifters obtained their positions via the 
Global Positioning System (GPS) and communicated them 
to the lab via the satellite communication network Iridium. 
Three drifters could successfully be tracked for between 40 
and 54 days. In order to conserve battery power, an initial 
sampling rate of about once every 15 min was later reduced 
to once every 30 min. 
Two different drifter types were utilized (see Table 1). The 
first drifter type, MD03i, from Albatros Marine Technolo 
gies (Fig. la) is cylinder shaped with a diameter of 0.1m 
and a length of 0.32 m. Only ~ 0.08 m of the drifter protrude 
from the water surface when deployed (Fig. lb). The sec 
ond drifter type, ODi from the same manufacturer (Fig. lc), 
has a spherical shape with 0.2 m diameter, with about half 
of it protruding from the water surface. The ratio of drag 
area in the water to drag area outside the water was 33.2 
for the MD03i and 16.9 for the ODi model, respectively. To 
both drifters, a drogue with 0.5 m length and diameter (e.g. 
Fig. la) was attached 0.5m below the sea surface. Due to 
this drogue and the small sail area exposed to winds above 
the water surface, drifter movements are supposed to be rep 
resentative of currents in a surface layer of about 1 m depth. It 
must be noted, however, that drifters deployed had no drogue 
presence sensors. 
2.2 Drifter simulations with PELETS-2D 
For drifter simulations, we used the Lagrangian transport 
module PELETS-2D (Program for the Evaluation of La 
grangian Ensemble Transport Simulations; Callies et al., 
2011) developed at Helmholtz-Zentrum Geesthacht (HZG). 
The PELETS algorithm was designed for particle tracking on 
two-dimensional unstructured triangular grids. As both mod 
els underlying this study use regular grids, the grid topology 
was preprocessed, splitting each rectangular grid cell into 
two triangles. Neither the number of nodes nor the informa 
tion content of underlying hydrodynamic fields is affected 
by this formal procedure. The integration algorithm used is 
a simple Euler forward method. Particle velocities are up 
dated (linear interpolation between two neighbouring nodes) 
each time a particle leaves a cell of the triangular grid. If no 
edge is reached within the maximum time step of 15 min, 
velocities are updated based on linear interpolation between 
three nodes.