NOVEMBER 2020 
LIN ET AL. 
3249 
The results presented here suggest that the dominant variation 
ın alongstream velocity at the sill is wind-driven, rather than 
’eing associated with the amount of overflow water present. 
There are several factors that may help explain this apparent 
discrepancy. 
The numerical model results of Almansi et al. (2017) show 
:hat, relative to the background state, the biggest difference in 
:he alongstream velocity signature of the boluses and pulses is 
che bottom intensification associated with the latter. While we 
do not have enough realizations of the Lätrabjarg section with 
velocity to determine a background state, our composite of 
oulse realizations shows significantly more bottom intensifi- 
cation in the trough versus the composite of bolus realizations, 
in line with Almansi et al.’s (2017) results. Another thing to 
xeep in mind is that the mooring analysis of von Appen et al. 
(2017) showed that the most conspicuous difference between 
the passage of boluses versus pulses pertains to the cross- 
stream velocity signal (cyclonic for boluses, anticyclonic for 
ulses), which we are unable to assess. Both features were 
associated with an enhancement of the alongstream velocity in 
«he overflow layer. The maximum flow in von Appen et al.’s 
(2017) bolus composite exceeded 0.40ms”*, while that for 
'heir pulse composite exceeded 0.60ms *. In our composite 
vertical sections, the mean near-bottom flow of the pulses is 
only slightly larger than for the boluses (0.30 vs 0.24 m s 7), but 
it must be kept in mind that the mooring composites were 
vased on vastly more data. In any event, both the shear and the 
mnagnitude of the alongstream flow—together with the strong 
aydrographic signals—suggest that we indeed detect these 
nesoscale features. 
A final consideration regarding the velocity variability seen 
in our dataset is the short time scale associated with the passage 
of the boluses and pulses. The mooring composites of von 
Appen et al. (2017) indicate that, for both types of features, the 
strongest signals in alongstream velocity persist for approxi- 
mately 12h. Typical occupations of the Lätrabjarg line take a 
day or more to complete. This means that the timing has to be 
serfect for a shipboard transect to capture the peak along- 
stream velocity signature of one these mesoscale features in the 
:rough. On the other hand, the wind-driven flow variability 
:akes place over longer time scales. The ERAS data indicate 
that the autocorrelation time for the along-strait winds is 73 h. 
Therefore, it is more likely that a given transect will be under 
che influence of a single wind state. As the collection of 
Lätrabjarg occupations with velocity continues to increase 
over time, we will be better positioned to elucidate the impacts 
of external versus internal forcing of the overflow water. 
Acknowledgments. An inordinate amount of effort was re- 
quired to obtain, processes, and quality-control the data used 
.n this study. The authors are thankful for the efforts of the 
nany individuals, both at sea and ashore, that made the anal- 
ysis possible. We are also indebted to M. Spall, T. Haine, and S. 
Tan for valuable discussions and insights. Funding for the study 
was provided by National Science Foundation (NSF) Grants 
OCE-1259618, OCE-1756361, and OCE-1558742. The German 
research cruises were financially supported through various 
EU Projects (e.g. THOR, NACLIM) and national projects 
“most recently TRR 181 “Energy Transfer in Atmosphere 
and Ocean” funded by the German Research Foundation 
ınd RACE II “Regional Atlantic Circulation and Global 
Change” funded by the German Federal Ministry for Education 
and Research). GWKM acknowledges the support of the Natural 
Sciences and Engineering Research Council of Canada. LP 
was supported by NSF Grant OCE-1657870. 
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