Oceanography | Early Online Release
refracted upward from the SLD and refected downward by the
surface, allowing acoustic energy to travel long distances. Te
sound speed gradient below the SLD, called the below-layer gra-
dient (BLG), can infuence the potential of this surface-layer duct
to trap energy.
For this project, sound speed, its variability, the SLD, and
the BLG were compared between simulations with and with-
out tidal forcing. Acoustic transmission loss (TL), an estimate
of acoustic pressure, was calculated from a virtual source using
a three-dimensional ray-tracing acoustic model, Bellhop 3D
(Porter, 2011). TL exemplifes how the diferences in sound
speed between diferently forced ocean simulations can afect
acoustic propagation models.
PROGRESS IN IGW MODELING
Bringing Models Closer to Observations
Realistically capturing ocean variability at diferent length scales,
from large-scale eddies to smaller coastal features, is a central
goal of global ocean models. Sea surface height (SSH) variability
is a useful proxy for mesoscale ocean variability. Te SSH wave-
number spectrum was used as a single descriptor of the rela-
tive strength of ocean variability as a function of length scale.
Wavenumber, defned as one divided by wavelength, is large
where spatial scales are small. Figure 1f shows an example of
the wavenumber spectra and the spectral slope of the mesoscale
variability (the steepness of the spectrum from 250 km to 70 km
wavelength). Te SSH spectral slope varies greatly by location
(Figure 1e; Zhou et al., 2015). Te slope is steepest (–5) along
the western boundary current (Gulf Stream), which has large-
scale currents and high mesoscale eddy variability. Te slopes
are fatter (close to –3) in the mid-latitude interior, such as the
eastern North Atlantic, and much fatter (close to –1) in the
equatorial region.
Te inclusion of tidal forcing in ocean models is paramount
to bringing SSH variability in simulations closer to observations.
Figure 1 compares a series of high-resolution regional 1/50°
North Atlantic HYCOM simulations to satellite altimetry obser-
vations. Without tidal forcing, high-resolution models could not
replicate this spatial SSH variability (e.g., Figure 1a,b; Chassignet
and Xu, 2017). With tidal forcing (Figure 1c,d), the SSH spec-
tral slope in the equatorial Atlantic and the eastern subtropi-
cal North Atlantic began to match observations. Here, there are
strong barotropic tides and strong stratifcation in the upper layer
of the water column. In these regions, SSH variability at length
scales of 70–120 km increased, fattening the spectral slope in the
70–250 km mesoscale range (Figure 1f). High-resolution bathym-
etry (Figure 1b) and high-frequency wind variability (Figure 7b
in Xu et al., 2022) had comparably minor impacts on the spec-
tral slope, except at local scales where internal tides are generated
along topography, such as near the shelf break (Xu et al., 2022).
NEATL
NEATL-T-HB
Zhou et al. (2015)
Wavenumber Spectra
NEATL-HB
NEATL-T
FIGURE 1. (a–e) Mesoscale sea surface height (SSH) wavenumber spectral slope in the
Atlantic Ocean based on a series of 1/50° numerical simulations and observations: (a) NEATL
(no tides), (b) NEATL-HB (no tides, with high-resolution bathymetry), (c) NEATL-T (with tides),
(d) NEATL-T-HB (with tides, high-resolution bathymetry), and (e) satellite observations from
Zhou et al. (2015). (f) Example of the wavenumber spectra averaged from 10°S–10°N and
35°–15ºW from observations and four model configurations. The mesoscale spectral slope
in panels a–e was calculated between 70 km and 250 km. Modified from Xu et al. (2022;
their Figures 7 and 11)