A new observational evidence of generation and propagation of barotropic
Rossby waves induced by tropical instability waves in the Northeastern
Pacific
Kang-Nyeong Lee1, Chanhyung Jeon2,
YoungHo Seung1, Hong-Ryeol Shin3,
Seung-Kyu Son4, and Jae-Hun Park1*
1Department of Ocean Sciences, Inha University,
Incheon 22212, South Korea.
2 Department of Oceanography, Pusan National
University, Busan 46241, South Korea.
3Department of Atmospheric Sciences, Kongju National
University, Kongju 32588, South Korea.
4Deep-sea and Seabed Mineral Resources Research
Center, Korea Institute of Ocean Science & Technology, Busan 49111,
South Korea.
Corresponding author: Jae-Hun Park
(jaehunpark@inha.ac.kr)
Key Points:
- In-situ near-bottom current velocity records are coherent with
satellite-measured sea surface height related to tropical instability
waves.
- The near-bottom current variations are likely caused by northward
propagating tropical instability wave-induced barotropic Rossby waves.
- Tropical instability wave-induced barotropic Rossby waves vary
inter-annually with maxima during the La Niña periods.
Abstract
Tropical instability waves (TIWs) in the equatorial eastern Pacific
(EEP) exhibit 25–40-day westward-propagating fluctuations with seasonal
and inter-annual variations, which are stronger during July–December
and La Niña periods. They likely transfer their energy northward by
forming barotropic Rossby waves (BTRWs). Long-term near-bottom current
measurements at 10.5°N and 131.3°W during 2004–2013 revealed a spectral
peak at 25–40 days, where significant coherences were found with
satellite-measured sea surface height in a wide region of EEP with
maxima approximately 5°N. Simulated deep currents from a
data-assimilated ocean model concur with the observed near-bottom
currents, and both currents vary seasonally and interannually,
consistent with the typical characteristics of TIW. Further analyses
using 25–40-day bandpass-filtered barotropic velocity data from the
model revealed that they reasonably satisfied the theoretical dispersion
relation of TIW-induced BTRW (BTRWTIW). We reconfirmed
BTRWTIW propagating northward above 10°N in the
northeastern Pacific by in-situ observations.
Plain Language Summary
Tropical instability waves (TIWs), which are located at the boundary
between the warm pool and the cold tongue in the eastern Pacific,
propagate westward with 25–40-day periods and vary seasonally and
interannually, which are stronger during July–December and La Niña
periods. Near-bottom velocity measured over a 10-year period at 10.5°N,
131.3°W just above the northern boundary of the waves fluctuates with
25–40-day periods, coinciding with that of sea surface height (SSH) in
the equatorial eastern Pacific, especially around 5°N. We find that the
wavelike pattern has wave crests oriented southeast-northwest from the
model, and that this pattern appears across the study area and has
characteristics consistent with TIWs including seasonal and interannual
variations with the typical wavenumber and frequency. This pattern was
verified to be a barotropic Rossby wave (BTRW) through a model result
analysis. Thus, TIWs induce BTRWs that transfer their energy to the
abyssal ocean above 10°N in the northeastern Pacific. This study
provides a new observational evidence that near-bottom currents vary
with BTRWs induced by TIW.
1 Introduction
Tropical instability waves (TIWs), which propagate westward and have a
cusp-like shape with repetitive high amplitudes near 5°N around the
boundary of the cold tongue in the equatorial eastern Pacific Ocean, can
be observed using satellite-measured sea surface temperature (Legeckis,
1977; Legeckis et al., 1983) and sea surface height (SSH) (Lyman et al.,
2005; Farrar, 2011; Holmes and Thomas, 2016; Tchilibou et al., 2018). It
is known that TIWs result from instability by interactions between
equatorial current system such as the Equatorial Undercurrent, the South
Equatorial Current, the North Equatorial Current, and the North
Equatorial Countercurrent (Philander, 1976; Lyman et al., 2005).
Previous studies described broad ranges of wavenumber and frequency of
TIWs depending on measurements utilized for them. Lee et al. (2017)
summarized the previous estimates of the wavenumbers and frequencies of
TIWs over the spectrum and reported that the TIWs observed by SSH
measurements show peak near periods of 33 days and wavelengths of
12°–16° in the wavenumber-frequency spectrum.
The waves are representative phenomena with intraseasonal periods in the
tropical eastern Pacific Ocean, although these properties are not always
remarkable (Chelton et al. , 2000; An, 2008; Shinoda et
al. , 2009). TIWs exhibit seasonal variations in the occurrence of
intense growth from July to December, with more energetic activities
during La Niña periods, linked to the strengthening of upwelling in
response to strong trade winds in the equatorial eastern Pacific
(Contreras, 2002; Warner & Moum, 2019).
Previous studies have focused mainly on the effects of TIWs near the
equatorial ocean because it is known that the waves play an important
role in regional ecosystems and the balance of heat associated with
advection in the equatorial surface ocean (Willett et al., 2006; Moum et
al., 2009). However, Farrar (2011) identified that TIWs can affect their
energy up to approximately 20°N. The longitude-time band-pass filtered
SSH shows a structure of TIW at 0°−10°N and a propagation of barotropic
Rossby waves (BTRWs) induced by TIW north of 10°N. Furthermore, using
both results from barotropic ocean model and newly gridded
satellite-measured SSH with a mapping algorithm without latitudinal
variation in its filtering properties, Farrar et al. (2021)
showed that the propagation of the BTRWs continues until 35°N. However,
these studies lacked in-situ observations.
Here, we used 10-year-long in-situ near-bottom current measurements that
were recorded at a site located north away from the active region of
TIW. The in-situ near-bottom current measurements clearly show that the
energy of the TIW-induced BTRWs propagate northward. The processes of
energy propagation in the form of BTRWs were also analyzed through the
satellite-measured SSH as well as the results of data-assimilated
numerical simulation (GLORYS12V1). In addition, the long-term in-situ
measurements, satellite measurements, and results of GLORYS12V1 between
2004 and 2013 enable the verification of interannual variations
according to the El Niño-Southern Oscillation (ENSO).
2 Data and Methods
2.1 In-situ and satellite measurements and GLORYS12V1 model results
Long-term, half-hour interval
near-bottom current data (Uobs, Vobs)
were recorded at a depth of ~5000 m in the northeastern
Pacific (10.5°N, 131.3°W; black star in Figure 1a) from August 21, 2004
to July 27, 2013. The observations were conducted as part of the Korea
Deep Ocean Study (KODOS). To compare in-situ data with other data
explained below, the former were averaged over a day.
Farrar et al. (2021) noted that the SSH data product by Copernicus
Climate Change Service causes barotropic signals with 30-day periods to
disappear at higher than 20°N due to a mapping algorithm. They produced
a special-purpose gridded SSH product which has latitudinally uniform
filtering properties. In this paper, we used the newly gridded SSH data
product (hereafter referred to as Farrar SSH) with a space-time grid of
0.5° × 0.5° × 3 days to conduct the spectral analysis and squared
coherency analysis with our in-situ data subsampled at a 3-day interval.
The domain used was 0°–20°N and 140°–80°W during the same period of
near-bottom current measurements.
We also used the results of a data-assimilated global ocean reanalysis
numerical simulation (GLORYS12V1) to investigate the characteristics of
TIW-induced BTRWs. The GLORYS12V1 product is provided by the Copernicus
Marine Environment Monitoring Service (CMEMS), and its component is the
Nucleus for a European Model of the Ocean (NEMO) platform. The daily
mean GLORYS12V1 outputs have a spatial resolution of 1/12° × 1/12°. The
selected domain for the analyses is the same as that of Farrar SSH, but
the data cover the period from January 1, 2004 to December 31, 2013. The
velocity results at 4833-m depth filtered by using a band-pass filter
with cutoff periods of 25–40 days are consistent with filtered in-situ
near-bottom current measurements, showing high correlation of
~0.8.
2.2 Pre-processing of squared coherency
The squared coherency (hereafter referred to as coherence) between
Farrar SSH and the time series of in-situ near-bottom current
measurements was performed as follows. Spectral analysis was applied to
1088 -long time series with 3-day interval from August 21, 2004, to July
27, 2013. A hamming window of length 192 days was used on the segment,
and a 50% overlap was used to increase the number of segments. The 95%
significance level, determined by the number of segments and the window,
is 0.137 (Thomson & Emery, 2014).
2.3 Complex empirical orthogonal function analysis
The Complex empirical orthogonal function (CEOF) analysis
(Hernández-Guerra & Nykjaer, 1997) using the barotropic velocity
results, calculated from the depth average of the numerical simulation,
requires a preprocessing procedure. The results of the numerical
simulation were filtered using a longitude-latitude-time band-pass
filter (zonal wavelengths of 9°−20° in longitude, meridional wavelengths
of 9°–20° in latitude, and periods of 25–40 days). The longitudinal
band-pass filter has a variable cut-off length depending on the
latitudes considered; however, the latitudinal band-pass filter has a
constant cut-off length for all longitudes. These filtering steps were
performed sequentially, first for longitude, next for latitude, and
lastly for time. The three dimensions (longitude-latitude-time) filtered
data were converted to two dimensions (spatio-temporal section) and the
two components were concatenated along the row to consider a spatial
relationship between them. The results of CEOF analyses are shown
separately for zonal (Ubt) and meridional
(Vbt) components.
3 Results
To compare the Farrar SSH and in-situ near-bottom current velocity
(Uobs,Vobs) with each other, two time
series of SSH located at different latitudes, indicated by black and red
stars in Figure 1a, were used. One is located at the mooring observation
site (SSHhigh), and the other is located at 5°N, 131.3°W
(SSHlow). Figure 1b shows the time series of Farrar
SSHlow, SSHhigh, and in-situ near-bottom
current velocity (Uobs, Vobs) that were
filtered by using a band-pass filter with cutoff periods of 25−40 days.
Gray lines superimposed on the filtered data show the original time
series. The time series corresponding to a red star are surrounded by a
box with red dashed lines, and those to a black star are surrounded by a
box with black dashed lines. The maximum speed of the original
(filtered) Uobs and Vobs are 13.5 (2.8)
cm/s and 16.7 (3.2) cm/s. The filtered time series of
Uobs and Vobs exhibit similar variations
to SSHlow in approximately a month period, which is
consistent with the temporal variation of TIWs reported by Lyman et al.,
(2007). They are strengthened during the late summer and early winter
months, with inter-annual variations. In contrast, the
SSHhigh shows no resemblance to others and has
substantially smaller values than the original time series. The results
of the spectral analysis also show the same tendency. The spectral peak
around the periods of 32 days clearly shows that the filtered time
series has the similar periodicity to the TIW (top panels in Figure 1c).
In contrast, the power spectral density (PSD) of the
SSHhigh does not show any significant peaks around that
period (gray line in Figure 1c).
Coherences between the SSHlow and the
Uobs exhibit a maximum value (> 0.75) at
the periods of 32 days and the Vobs show higher values
(~0.4) than the significance level around the periods of
32 days (middle panel in Figure 1c). In the 32-day periods, the
SSHlow leads the Uobs by 119°, and the
Vobs leads the SSHlow by -7°.
Conversely, coherences between the SSHhigh and either
the Uobs or the Vobs appear to be much
smaller than the significance level (0.137) in the 32-day periods. This
disparate results seen at two latitudes will be discussed in Figure 3,
by using Farrar SSH data and numerical simulation results.