Gravity waves (GWs) strongly affect atmospheric dynamics and photochemistry
and the coupling between the troposphere, stratosphere, mesosphere, and
thermosphere. In addition, GWs generated by strong disturbances in the
troposphere (e.g. thunderstorms and typhoons) can affect the atmosphere of
Earth from the troposphere to the thermosphere. However, the fundamental
process of GW propagation from the troposphere to the thermosphere is poorly
understood because it is challenging to constrain this process using
observations. Moreover, GWs tend to dissipate rapidly in the thermosphere
because the molecular diffusion increases exponentially with height. In this
study, a double-layer airglow network was used to capture concentric GWs
(CGWs) over China that were excited by Typhoon Chaba (2016). We
used ERA5 reanalysis data and Multi-functional Transport Satellite-1R
observations to quantitatively describe the propagation processes of
typhoon-generated CGWs from the troposphere, through the stratosphere and
mesosphere, to the thermosphere. We found that the CGWs in the mesopause
region were generated directly by the typhoon in the troposphere. However,
the backward-ray-tracing analysis suggested that CGWs in the thermosphere
originated from the secondary waves generated by the dissipation of the CGW
and/or nonlinear processes in the mesopause region.
Introduction
Gravity waves (GWs) can transfer momentum and energy from the lower to the
upper atmosphere, thereby affecting global circulation and the thermal and
compositional structures in the middle and upper atmospheres (Holton, 1983;
Fritts and Alexander, 2003). Studies of dynamical, photochemical, and
electrodynamics processes have indicated that GWs are fundamental for the
coupling process between the troposphere, stratosphere, mesosphere, and
thermosphere (Liu and Vadas, 2013; Smith et al., 2013; Vadas and Liu, 2013;
Xu et al., 2015; Vadas and Becker, 2019).
Concentric GWs (CGWs) are a unique type of GW and considered to be mainly
generated by convective activity in the troposphere. CGWs can also be
generated by GW-breaking (Vadas and Becker, 2019; Lund et al., 2020; Kogure
et al., 2020) volcanoes (Duncombe, 2022), nuclear explosions (Pfeffer and
Zarichny, 1962; Pierce al., 1971), and rockets (Liu et al., 2018). CGWs in
the stratosphere and mesosphere generated by thunderstorms have been widely
reported, since their sources are ubiquitous (Taylor and Hapgood, 1988;
Sentman et al., 2003; Suzuki et al., 2007; Yue et al., 2009; Vadas et al.,
2012; Xu et al., 2015; Heale et al., 2019; Smith et al., 2020). In addition,
Liu et al. (2014) utilized the Whole Atmosphere Community Climate Model to
study the global CGWs. In previous studies, CGWs induced by typhoons were
detected using ground-based optical remote sensing (Suzuki et al., 2013),
while those induced by hurricanes and tropical cyclones were detected using
the Suomi National Polar-orbiting Partnership satellite (Yue et al., 2014;
Xu et al., 2019) in the mesopause region.
Notably, GWs tend to dissipate rapidly in the upper atmosphere due to
molecular viscosity and thermal diffusion (Vadas, 2007). Thermosphere GWs
that are not dissipated can originate directly from the troposphere (Vadas,
2007; Azeem et al., 2015) or from secondary GWs, which are generated from
the breaking of primary GWs in the mesosphere or thermosphere region (Vadas et al., 2003; Vadas and Crowley, 2010; Vadas and Azeem, 2021).
Furthermore, Vadas and Becker (2019) for the first time presented global
simulations of tertiary CGWs from the dissipation of secondary CGWs in the
thermosphere. Moreover, wave–wave interaction, wave–mean flow interaction
(Franke and Robinson, 1999; Vadas and Fritts, 2001), self-acceleration, and
nonlinear breaking are other potential secondary wave generation mechanisms
(Lund and Fritts, 2012; Fritts et al., 2015; Dong et al., 2020; Fritts et
al., 2020; Zhou et al., 2002; Heale et al., 2020). At the same time, tunnelling
has been deemed a mechanism that can couple waves from tropospheric
sources to the thermosphere (Walterscheid and Hecht, 2003; Gavrilov and
Kshevetskii; 2018, Heale et al., 2021). However, the lack of observations of
the entire atmosphere limits our understanding of the fundamental process of
how GWs propagate from the lower to the upper atmosphere step by step on the
aspect of observations.
This paper presents a case study examining CGWs excited by Typhoon
Chaba (2016). To this end, we utilized Multi-functional Transport
Satellite-1R (MTSAT-1R) observations, multi-layer European Centre for
Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data (Hoffmann et
al., 2019; Hersbach et al., 2020), and high-spatiotemporal-resolution
double-layer airglow network (DLAN) (Xu et al., 2021) observations. The CGW
observations from the troposphere to the stratosphere and then to the
mesosphere were taken from MTSAT-1R, ERA5, and the DLAN. However, given the
observational limitations between the mesosphere and thermosphere, the two
layers are connected by ray-tracing theory. The objectives of this study
were to (a) investigate multi-layer CGW features produced by Typhoon
Chaba (2016) from near the ground to a height of 250 km, (b) examine the
entire propagation process of the CGWs excited by the typhoon from the lower
atmosphere to the upper atmosphere, and (c) provide new insights into the
coupling between different atmospheric layers.
(a) OH airglow all-sky imager network (15 stations). (b) Red-line
(630 nm) airglow all-sky imager network (12 stations). The circles on the
maps give the effective observation ranges of OH and red-line airglow
imagers with diameters of about 800 and 1800 km, respectively.
Data and methodsDouble-layer all-sky airglow imager network data
A DLAN, including a hydroxyl radical (OH) layer (∼ 87 km) and a layer of atomic oxygen emission at 630 nm (OI 630.0 nm)
(∼ 250 km), was established over mainland China. The research
aim of the DLAN is to explore the physical mechanism of vertical and
horizontal propagation and the evolution of atmospheric waves in the middle
and upper atmosphere triggered by severe disasters, such as typhoons,
earthquakes, and tsunamis. The OH airglow network comprises 15 stations,
including the first no-gap OH airglow all-sky imager network located in
northern China (Xu et al., 2015). The OI 630.0 nm airglow network contains
12 stations. Each imager consists of a 1024 × 1024 pixel
back-illuminated charge-coupled device (CCD) detector and a Nikon 16 mm f/2.8D fisheye lens with a
180∘ field of view (FOV). The OI 630.0 nm imager is operated at
the 3.0 nm bandwidth filter with a central wavelength of 630.0 nm.
Observations using airglow optical remote sensing require only a few airglow
imagers to cover a wide area, although it is limited by meteorological
conditions. Moreover, airglow observations can be used to monitor
multi-layer GW activities. Figure 1a and b illustrate the OH and OI 630.0 nm network station distribution maps, respectively, in China. The OI 630.0 nm network covers nearly all of mainland China. Furthermore, the DLAN
provides an excellent solution for studying the coupling processes between
the mesosphere and thermosphere.
Several standard procedures were applied to raw airglow images, including
star contamination subtraction, flat fielding to remove the van Rhijn effect, and
atmospheric extinction (Li et al., 2011). The GW structure was retrieved by
taking the deviation of each processed image from a half-hour running-average window image. Finally, the images were projected onto Earth's
surface using the standard star map software and the altitude of the airglow
layer (Garcia et al., 1997). The altitudes of the OH and OI 630.0 nm
emission layers were set to approximately 87 and 250 km, respectively.
(a) The track of Typhoon Chaba is denoted by dots from 24 September to 7 October 2016 every 12 h (date format: year-month-day, hour). (b) Central pressure of Typhoon
Chaba corresponding to the tracks in (a) (date format: month/day/hour). The red line denotes the maximum
sustained wind speed. The green shadow band denotes the time of ground-based
airglow observation from 20:00 to 04:00 LT during the night of 4–5 October 2016.
Development of Typhoon Chaba
Typhoon Chaba (2016) developed in the northwestern Pacific on 24 September 2016, and its track is shown in Fig. 2a. Initially, it moved
westward and then turned northwestward on 30 September. The central
pressure in the eye of the typhoon and the maximum wind speed are shown in
Fig. 2b. On 3 October 2016 at 20:00 LT, the typhoon was in the mature stage
with a minimum central pressure of 905 hPa and maximum sustained winds of
approximately 59 m s-1. The typhoon moved northward on 4 October 2016 at 02:00 LT until 5 October 2016 at 02:00 LT. The typhoon continued moving towards
the northeast and disappeared on 8 October 2016 at 02:00 LT. Consecutive
satellite images of the typhoon from MTSAT-1R from 18:00 LT on 3 October
2016 to 00:00 LT on 5 October 2016 are shown in Fig. 3. MTSAT-1R, which
belongs to the Japan Meteorological Agency, is part of the
Geostationary Meteorological Satellite series. MTSAT-1R is located at around
140∘ E and covers East Asia and the western Pacific region. The
MTSAT-1R consists of four infrared channels (IR1, IR2, IR3, and IR4) and one
visible channel (VIS). The MTSAT-IR1 was used in this study. The track of
the typhoon was beyond the effective FOV of the OH network and at the edge
of the effective FOV of the OI 630.0 nm network.
Consecutive satellite images of Typhoon Chaba from MTSAT-1R.
The period is from 18:00 LT on 3 October to 00:00 LT on 5 October 2016,
with an interval of 6 h.
ERA5 reanalysis data
ERA5 is a fifth-generation ECMWF atmospheric reanalysis that provides
hourly data for many atmospheric and wave parameters. ERA5 is produced
using a four-dimensional variational data assimilation algorithm based on
Integrated Forecast System (IFS), with 137 hybrid sigma–pressure (model)
levels in the vertical from 1000 to 0.01 hPa (0 to 80 km). More details of
the model, data assimilation system, and observation data used to produce
ERA5 were described by Hersbach et al. (2020). Horizontal reanalysis
temperature and wind data with a pre-interpolated resolution of
0.25∘× 0.25∘ and time resolution of 1 h were
used in this study.
Ray-tracing model
We used a ray-tracing method to estimate the source location of the
thermospheric secondary CGWs. The model was based on a dispersion relation
that considers molecular viscosity and thermal diffusivity (Vadas, 2007), as
shown in Eq. (1):
m2=kH2N2ωIr21+δ++δ2/Pr×1+ν24ωIr2K2-14H221-Pr-121+δ+/22-1-kH2-14H2,
where ωIr=ωr-(ku+lv) is the intrinsic frequency
(ωr is ground-based frequency); K2=kH2+m2;
kH2=k2+l2; H is the scale height; ν=μ/ρ‾ is the kinematic viscosity, where μ is the molecular
viscosity and ρ‾ is the background density; δ=νm/HωIr, δ+=δ(1+Pr-1), where Pr is the Prandtl number; and k, l, and m are the zonal, meridional, and vertical wave number components of
the GW, respectively. The horizontal wavelength (kH) of the CGW was
obtained from the ground-based airglow observations; N2=g/TdT/dz+g/cp is the
square of the Brunt–Väisälä frequency, where g is the
gravitational acceleration, T is the background temperature, and cp is the
specific heat at constant pressure. The background temperature T and density ρ‾ were obtained from the NRLMSISE-00 (Picone et al.,
2002). The group velocity of the wave packet is formalized by Eq. (2):
cgi=dxi/dt=∂ωIr/∂ki+Vi,
where Vi (u, v, w) is the background wind, which was obtained from the
Horizontal Wind Model 14 (Drob et al., 2015), and w is the vertical wind
velocity, which was neglected. In this study, we assume that the background
wind field is independent of time, so ground-based frequency ωr
remains constant along a ray's path (Lighthill, 1978). However, the actual
wind field changes with time, which may lead to deviation between the ray-tracing results and the wave source locations.
Using Eqs. (1)–(2), we yield the ground-based (zonal, meridional, and
vertical) group velocity equation as follows (Vadas and Fritts, 2005):
cgx=kωIrBN2m2+1/4H2K2+1/4H22-ν221-Pr-12K2-14H21+δ++δ2/Pr1+δ+/22+u,
cgz=1ωIrBm-KH2N2K2+1/4H22-ν221-Pr-12K2-14H21+δ++δ2/Pr1+δ+/22+ν41-Pr-1416H2ωIr2K2-1/4H221+δ+/23-ν2PrH2-ν+ωIr2H,
where
B=1+δ+2+δ2ν216ωIr21-Pr-14K2-1/4H221+δ+/23,ν+=ν1+Pr-1.
Temperature perturbations at (a)∼ 60 km, (b)∼ 40 km, and (c)∼ 20 km at 23:00 LT on 4 October
2016 derived from ERA5 reanalysis. (d) Wavelet power spectrum along the red
line in (a), (e) wavelet power spectrum along the red line in (b), and (f)
wavelet power spectrum along the red line in (c).
ResultsPropagation of typhoon-induced CGWs in the stratosphere
We extracted the stratospheric CGW excited by the typhoon from ERA5
reanalysis. Figure 4a, b, and c show the multi-layer temperature
perturbations at approximately 60, 40, and 20 km at 23:00 LT,
retrieved from the ERA5 reanalysis on 4 October 2016, respectively.
Temperature perturbations were calculated by subtracting the background with
a 7 × 7 grid point running mean at 20 km and 17 × 17 grid
point running mean at 40 and 60 km. We found that the temperature
disturbance was about ± 1.5–2 K at 20 km and ± 3–4 K at 40 km.
Using the ECMWF reanalysis data, Kim et al. (2009) reported a similar
temperature disturbance (± 4 K) at 40 km altitude. Becker et al. (2022)
showed that typical temperature perturbation amplitudes simulated by the High
Altitude Mechanistic general Circulation Model were ± 1–2 K in the
wintertime lower stratosphere, as well as ± 5 K in the stratopause region.
However, the temperature disturbance at 60 km in ERA5 was only ± 1.3 K and did not increase with increasing altitude, which may be caused by this
altitude being well within the sponge layer of the reanalysis model. Figure 4d, e, and f show the corresponding wavelet analysis contours of the red
line in Fig. 4a, b, and c. The expansion area of CGW at the height of 20 km (Fig. 4c) was small, and the horizontal wavelength was approximately 150 km from Fig. 4f. The CGWs were present over a large area of 0–50∘ N, 100–150∘ E at approximately 60 km. The distance of the CGWs, extending from the centre of the circle, ranged
from 500 km (at approximately 20 km height) to 3000 km (at approximately 60 km height), which suggests that a larger-scale CGW arrives earlier at
higher altitudes (faster vertical group velocities) than the
smaller-scale waves (Vadas and Azeem, 2021). The ERA5 reanalysis data were
utilized for characterizing the scale of the CGWs and indicated no
small-scale fluctuation. According to the wavelet analysis of Fig. 4d and e, the horizontal wavelengths of the northward propagating CGW at 60 km
(Fig. 4a) and 40 km (Fig. 4b) were approximately 265 and 290 km,
respectively.
Propagation of typhoon-induced CGWs in the mesosphere
As the typhoon moved along the coast of China, CGWs were identified at 10 stations in the OH network. Animation 1 shows that CGWs were observed by the
OH airglow network from 20:00–04:00 LT (the detailed data can be
downloaded from the Supplement, 10.5446/55348).
As the weather conditions in northern China during the study period were better
than those in southern China, we identified clearer wave structures at the
northern stations than at the southern stations. Nevertheless, circular wave
structures were visible for brief clear weather intervals at the Zhangzhou,
Qujing, and Chongzuo stations. The CGWs in the mesopause region extended to
2500 km, thereby nearly covering the effective FOV of the OH airglow
network.
OH airglow emission perturbations induced by CGWs observed by the
OH airglow imager network at (a) 23:21 LT, (b) 23:36 LT, and (c) 23:53 LT on
4 October 2016. (d) Wavelet power spectrum along the red line in (a), (e) wavelet power spectrum along the red line in (b), and (f) wavelet power
spectrum along the red line in (c).
As long as the CGWs do not encounter the critical layer or break, the CGWs
generated in the lower atmosphere can propagate to the OH airglow layer.
Through the propagation group velocity, we can determine the propagation
time to the OH layer. A single dominant horizontal wavelength is seen at
each altitude of 20, 40, and 60 km in the ERA5 reanalysis. In
contrast, the horizontal scales of the CGW obtained by the OH airglow
network were diverse, ranging from approximately 30 to 300 km. More
importantly, we found some CGWs in the OH airglow layer, which were close to
the CGW wavelengths at 20, 40, and 60 km altitudes. To verify whether
the same wave was propagated from the reanalysis data layer to the OH layer,
we used the group velocity to estimate the time when the CGW at the
altitudes of 20, 40, and 60 km reached the OH airglow layer. The times
required for the CGW in the three-layer disturbance diagram in Fig. 4a, b,
and c to reach the OH layer were approximately 21, 36, and
53 min. Therefore, the times when the CGWs visible in ERA5 at 60, 40, and 20 km would reach the OH airglow layer are approximately 23:21,
23:36, and 23:53 LT as shown in Fig. 5a, b, and c, respectively. The
wavelet analysis of Fig. 5f showed that the horizontal wavelength of the CGW in
the OH airglow layer (Fig. 5c) is approximately 156 km; the observed period
is approximately 23 min; and the horizontal speed is approximately 113 m s-1,
which is similar to the dominant horizontal wavelength of the CGWs in the
ERA5 reanalysis at 20 km altitude. Similarly, the horizontal wavelengths of
the CGW in the OH airglow layers (Fig. 5a and b) were approximately 270 and
295 km from the wavelet analysis of Fig. 5d and e, which is similar to the
dominant horizontal wavelength of the CGWs in the ERA5 reanalysis at 60
and 40 km altitudes. This suggests that the same CGW event can be perfectly
tracked over different altitudes and that the CGWs in the mesosphere
propagated upward from the stratosphere.
Time sequence of OI 630.0 nm airglow emission perturbation images
observed by the Donggang station from 00:57:05–01:12:22 LT on the night of 4 October 2016. Green triangles (P1–P7) in the red arcs are used as ray-tracing sampling points. The blue line in each panel represents the
coastline.
Wavelet power spectrum along the red line at 01:00:18 LT in Fig. 6.
How typhoon-induced CGWs propagate to the thermosphere
Figure 6 shows the time sequence of the OI 630.0 nm airglow images from
00:57:05 to 01:12:22 LT on the night of 4 October 2016. Three curved phase fronts are clearly visible. The wave packet observed in the OI 630 nm
airglow was quasi-monochromatic. According to the wavelet analysis spectrum
in Fig. 7, the horizontal wavelength was approximately 120 km. The observed
wave period and phase velocity were 10 min and 200 m s-1, respectively. The
horizontal wavelength was somewhat less than the typhoon-induced concentric
travelling ionosphere disturbances with a horizontal wavelength from 160 to
200 km in the GNSS-TEC (global navigation satellite system–total electron content) network as reported by Chou et al. (2017). The CGW
observed in the OI 630.0 nm airglow had a much faster phase speed and shorter
period than that observed in the mesosphere, which indicates that its
propagation trajectory was relatively vertical. This means that they will
not propagate as far horizontally as the CGWs noted as dominant in the OH
layer. Indeed, compared with the long-distance extension of the CGWs in the
mesosphere, the horizontal propagation distance of the CGWs in the
thermosphere was only 600 km from OI 630.0 nm network observation. Vadas and
Crowley (2010) showed that thermospheric GWs may be secondary GWs generated
by the breaking of primary GWs in the mesosphere and thermosphere. We argue
that the thermospheric CGW observed by the OI 630.0 nm airglow imager was
not directly generated by the typhoon but rather a secondary GW. To test this
hypothesis, backward-ray-tracing analysis was applied. In this way, we
determined the source of the CGW observed in the thermosphere.
(a) Wind profiles along the seven ray-tracing paths. (b) Ray paths
of the wave starting from the seven sampling points in Fig. 6. (c) Horizontal
area distribution of the terminal positions of the seven backward-traced
trajectories. Error bars give the standard deviation for each point from the
starting altitudes of 240, 250, and 260 km.
Double-layer CGW-superimposed graph. The blue arcs represent the
thermospheric CGW observed at 01:00:18 LT. The dotted circle represents the
approximately fitting blue arcs. The blue cross marks the centre of the
circle. The solid circles represent the approximately fitting CGWs observed by
the OH airglow network. The red dot marks the centre of the circles. The
green triangles and red diamonds represent the trace start and termination
points, respectively. The red crosses represent the sounding footprints of
the TIMED–SABER (Thermosphere Ionosphere Mesosphere
Energetics and Dynamics satellite's Sounding of the Atmosphere using Broadband Emission
Radiometry instrument) measurements. The yellow box marks the location of the
meteor radar station.
We sampled seven points (green triangles) on circular wavefronts (red arcs
in Fig. 6) at 01:00:18 LT as the starting point for backward ray tracing.
The starting height of the backward ray tracing was 250 km. The profile of
the winds used in the ray tracing is shown in Fig. 8a. The ray-tracing
trajectories of the seven sampling points are shown in Fig. 8b. We used the
following criterion to terminate the ray tracing: the square of the vertical
wavenumber should be negative. We started the ray tracing at heights of 240, 250, and 260 km and analysed the results. The maximum uncertainty
of the horizontal change of the ray-tracing termination point caused by different
starting heights was approximately ± 0.36∘ in
latitude and ± 0.17∘ in longitude (see Fig. 8c).
Subsequently, seven backward-traced trajectories took 37 min and
terminated at an altitude of approximately 95 km, thereby indicating that a
reflection layer was encountered. According to linear theory, this suggests
that the thermospheric CGW could not have come from below 95 km. The
thermospheric GW must have been generated at any altitude between 95 km and
the altitude of the OI 630.0 nm airglow. In other words, the CGW observed in
the thermosphere was excited after approximately 00:23 LT. Figure 9 presents
the CGWs observed by the OH airglow network at 00:23:22 LT. We superimposed
the thermospheric CGWs along with the starting ray-tracing points (green
triangles) reproduced from Fig. 6, as well as the backward-ray-tracing termination
points (red diamonds) on the OH airglow observation images. The dotted
circle represents the approximate fitting thermospheric CGW fronts. The
centre of the circle is marked by a blue cross. Compared with the
single-scale wave observed in the OI 630.0 nm layer, multi-scale CGWs were
visible from OH network observations. We found that the termination points
of ray tracing almost fell above the mesopause region. This suggests that
the CGW observed in the thermosphere did not directly originate from the
typhoon but may have emerged due to the dissipation and/or nonlinear
processes of a typhoon-induced CGW in the mesopause region. However, the
backward-tracing terminal positions (red diamonds in Fig. 9) did not
coincide with the fitting circle centre position (blue cross in Fig. 9).
Nevertheless, according to numerical simulation work by Vadas et al. (2009),
large winds can shift the apparent centre of concentric rings from the
location of the convective plume. Indeed, we found strong southward winds
at 100 to 140 km (with a peak value of 50 m s-1 at 150 km altitude) and 160 to 220 km (with a peak value of 25 m s-1 at 175 km altitude)
altitudes (right panel of Fig. 8a). So the centre of the thermospheric CGW
can be shifted southward from the location of the thermospheric CGW sources
in the mesopause region. For the zonal wind, the westward wind dominated
from the upper mesosphere to the thermosphere (left panel of Fig. 8a).
Similarly, the thermospheric CGW centre position shifted westward.
Therefore, the assumed centre (blue cross) of the partial concentric ring
GWs (blue arcs) actually shifted to the southwest from the real source
location, which may explain why the ray-tracing result for the assumed GW
source did not match the fitting centre of the partial concentric ring
thermospheric GWs. Another possible mechanism is that the wave phase speeds
are accelerated by accelerating background winds. As mentioned above, the
ground-based frequency ωr remains constant along a ray's path assuming
the background wind field is independent of time (Lighthill, 1978). However,
the transient effect (time derivatives of the background wind components giving
rise to the time derivative of the frequency for a particular ray) may cause the
phase speeds to be accelerated, which may lead to the ray-tracing results
not matching the real locations. As the ray-tracing model used in this
study depended on the linear theory and did not consider the wave–wave and
wave–mean flow interactions and tunnelling, the ray-tracing results were
limited and should also be taken into consideration carefully.
Time sequence of OH airglow emission perturbation images observed
by the Rongcheng station from 01:01:30–00:44:30 LT on the night of 4 October
2016. w1–w5 denote the wavefronts of the CGW. The blue line in each panel
represents the coastline.
Discussion
Figure 10 presents a time sequence of OH airglow images in the range marked
by the yellow dotted rectangle in Fig. 9. The images were retrieved from the
Rongcheng station from 00:01:30 to 00:44:30 LT on the night of 4 October 2016. At 00:01:30 LT, three distinct curved wavefronts with horizontal
wavelengths of approximately 96 km were identified. Interestingly,
wavefronts w2 and w3 collided and connected in the northeast, indicating that
wave–wave nonlinear interactions may have occurred.
Time series of the averaged OH image slices perpendicular to the
wavefronts as marked by four yellow dotted lines (a, b, c, and d) in Fig. 10.
The wavefronts propagate from left to right. The red arrows mark the
evolution of the wavefront peak.
OH (black) and OI 630 nm (red) airglow relative-intensity
variations. The OH relative-intensity variation is obtained as in Fig. 11.
The OI 630 nm relative-intensity variation is from the red dotted line in
Fig. 6 at 01:06:15 LT.
Figure 11 shows the time series of the OH image slices perpendicular to the
wavefronts (w1–w5). A dominant wavelength of approximately 150 km can be
confirmed at 00:00:25 LT. We found a significant attenuation of the
amplitude from 00:00:25 to 00:17:37 LT. At 00:00:25 LT, the
relative average power was 2.3 ×103, and the amplitude
decreased gradually with time. At 00:17:37 LT, the average power decreased
to 0.15 ×103. We also identified the generation of
approximately 110 km and 20–50 km small-scale waves from the larger scales,
which may be caused by wave–wave nonlinear interactions and/or wave
breaking. We overlaid the OI 630 nm airglow relative-intensity variation on
the OH airglow variation, and Fig. 12 shows OH and OI 630 nm airglow
relative-intensity variations. The OH plot was obtained at 00:29:27 LT, as well as
the OI 630 nm plot at 01:06:15 LT. The time interval of 37 min was
calculated by the above ray-tracing analysis. We obtained similar-scale
fluctuations in the two airglow layers. The horizontal
wavelength of the wave obtained by the OI 630 nm airglow layer was
approximately 118 km. The OH airglow layer has also obtained near-scale
fluctuations with wavelengths of approximately 109 km. These waves could be
the same waves seen in the thermosphere. Therefore, the CGW in the
thermosphere may come from breaking or nonlinear processes of primary
gravity waves.
Square of vertical wave number m2 profile (black) derived from the
temperature from the TIMED–SABER measurement location at 04:18:49 LT and the
meteor radar wind from the Beijing station marked in Fig. 9. The red line
represents the OH 1.6 µm emission intensity obtained by the TIMED–SABER.
The horizontal blue lines represent the top and bottom boundaries of the
duct region.
Note that wave amplitude fluctuations can also result from the transient
nature of the wave packet. The propagation state can be studied by using the
dispersion relationship with the GW. However, the dissipation region of the CGW
lacks the real-time background temperature and wind field. In this context,
the limb viewing of the Sounding of the Atmosphere using Broadband Emission
Radiometry (SABER) instrument on the Thermosphere Ionosphere Mesosphere
Energetics and Dynamics (TIMED) satellite can be beneficial because it
occurred near the wave-dissipation region; however, the time lag was close
to approximately 4 h. Background wind field data were obtained from an ATRAD
MDR6 all-sky VHF (very high-frequency) meteor radar at the Beijing station. We further examined the
dispersion relationship of the GW, thereby shedding some light on the possible
propagation state of dissipative waves. Figure 13 presents the square of vertical wave
number m2 profile derived from the Beijing meteor radar wind and the
temperature from the TIMED–SABER measurement location at 04:18:49 LT, as
marked in Fig. 9. The wave parameters used were from the wavefronts (w1–w5)
in Fig. 10. The average horizontal wavelength was approximately 96 km, and the
average observed phase velocity is approximately 90 m s-1. We identified a
clear duct (from 87 to 94 km) near the peak of the OH airglow layer. Note
that the duct can control the horizontal propagation of the CGW. This implies
that the CGW may indeed be dissipated. In contrast, the upper boundary of
the duct coincided with the height of the ray-tracing termination area
mentioned above. During wave dissipation, momentum deposition occurs in the
background atmosphere and can produce body forces that stimulate secondary
GWs (Fritts et al., 2006; Chun and Kim, 2008; Smith et al., 2013; Vadas et
al., 2018; Heale et al., 2020). In addition, secondary waves can be
generated by momentum transferred nonlinearly from the primary wave mode to
harmonics or subharmonics (Snively, 2017). Local momentum flux divergence
associated with wave breaking, vortex generation, and wave interactions can
also generate secondary GWs (Fritts et al., 2006).
Summary
In this study, a DLAN was used to capture CGWs over China that were excited
by Typhoon Chaba (2016). As Typhoon Chaba (2016) moved
northward along the coast of the Chinese mainland and developed to a mature
stage, remarkable multi-layer CGW features produced by the Typhoon from near
the ground to a height of 250 km were observed by ERA5 reanalysis and the
airglow network. We applied the MTSAT-1R observations, ERA5 reanalysis
data, and backward ray tracing to quantitatively describe the physical
mechanism of typhoon-generated CGWs propagating throughout the stratosphere,
mesosphere, and thermosphere.
The temperature disturbance was approximately ± 1.5–2 K at 20 km
and ± 3–4 K at 40 km. However, the temperature disturbance (± 1.3 K) at 60 km altitude did not increase with a further increase in altitude,
which may be caused by the sponge layer effect. Using reanalysis of
multi-layer temperature disturbance, group velocity of gravity wave, and
wavelet analysis, we demonstrated that the CGWs in the mesopause region were
excited directly by the typhoon.
Due to the observational limitations, a backward-ray-tracing theory was used
to connect GWs in the upper mesosphere to GWs in the thermosphere at about
250 km. We found that the termination points of ray tracing of the
thermospheric CGW almost fell above the mesopause region. Backward-ray-tracing analysis and the CGW evolution process observed by the OH
network suggested that the CGW observed in the thermosphere did not directly
originate from the typhoon but may have emerged due to dissipation and/or
nonlinear processes of typhoon-induced CGWs in the mesopause region. Airglow
network observations combined with numerical simulation to study the
generation of secondary wave in detail will be carried out in the future.
Data availability
The double-layer airglow network data are available at
https://data2.meridianproject.ac.cn/data (MPDC, 2020). The ERA5 reanalysis data are able to be downloaded from the
Copernicus Climate Change Service Climate Data Store through
https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 (Hersbach et al., 2020). The
typhoon information is provided at http://agora.ex.nii.ac.jp/digital-typhoon/year/wnp/2016.html.en (NII, 2020), with data accessible from http://weather.is.kochi-u.ac.jp/sat/GAME/2016/Oct/IR1/ (Kochi University, 2020).
Video supplement
A video of the detailed evolution of CGWs excited by the typhoon observed by the OH airglow observation network is provided (10.5446/55348, Li, 2021).
Author contributions
JX conceived the idea of the manuscript. QL carried out the data
analysis, interpretation, and manuscript preparation. HL, XL, and WY contributed to the data interpretation and manuscript preparation. All
authors discussed the results and commented on the manuscript.
Competing interests
The contact author has declared that none of the authors has any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
This work was supported by the National Natural Science Foundation of China
(grant nos. 41974179 and 41831073), the Strategic Priority Research Program of Chinese
Academy of Sciences (grant no. XDA17010301), the Informatization Plan of Chinese
Academy of Sciences (grant no. CAS-WX2021PY-0101), and the Project of Stable Support
for Youth Team in Basic Research Field of Chinese Academy of Sciences (grant no. YSBR-018). The work was also
supported by the Specialized Research Fund for State Key Laboratories. We
acknowledge the use of data from the Chinese Meridian Project. We are grateful to the three referees for many helpful comments.
Financial support
This research has been supported by the National Natural Science Foundation of China (grant nos. 41831073 and 41974179), the Strategic Priority Research Program of Chinese Academy of Sciences (grant no. XDA17010301), the Informatization Plan of Chinese Academy of Sciences (grant no. CASWX2021PY-0101), and the Project of Stable Support for Youth Team in Basic Research Field of Chinese Academy of Sciences
(grant no. YSBR-018).
Review statement
This paper was edited by Franz-Josef Lübken and reviewed by three anonymous referees.
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