The Momentum Budget in the Stratosphere, Mesosphere, and Lower Thermosphere. Part II: The In Situ Generation of Gravity Waves

Ryosuke Yasui Department of Earth and Planetary Science, The University of Tokyo, Tokyo, Japan

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Kaoru Sato Department of Earth and Planetary Science, The University of Tokyo, Tokyo, Japan

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Yasunobu Miyoshi Department of Earth and Planetary Sciences, Kyushu University, Fukuoka, Japan

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Abstract

The contributions of gravity waves to the momentum budget in the mesosphere and lower thermosphere (MLT) is examined using simulation data from the Ground-to-Topside Model of Atmosphere and Ionosphere for Aeronomy (GAIA) whole-atmosphere model. Regardless of the relatively coarse model resolution, gravity waves appear in the MLT region. The resolved gravity waves largely contribute to the MLT momentum budget. A pair of positive and negative Eliassen–Palm flux divergences of the resolved gravity waves are observed in the summer MLT region, suggesting that the resolved gravity waves are likely in situ generated in the MLT region. In the summer MLT region, the mean zonal winds have a strong vertical shear that is likely formed by parameterized gravity wave forcing. The Richardson number sometimes becomes less than a quarter in the strong-shear region, suggesting that the resolved gravity waves are generated by shear instability. In addition, shear instability occurs in the low (middle) latitudes of the summer (winter) MLT region and is associated with diurnal (semidiurnal) migrating tides. Resolved gravity waves are also radiated from these regions. In Part I of this paper, it was shown that Rossby waves in the MLT region are also radiated by the barotropic and/or baroclinic instability formed by parameterized gravity wave forcing. These results strongly suggest that the forcing by gravity waves originating from the lower atmosphere causes the barotropic/baroclinic and shear instabilities in the mesosphere that, respectively, generate Rossby and gravity waves and suggest that the in situ generation and dissipation of these waves play important roles in the momentum budget of the MLT region.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JAS-D-17-0337.s1.

Corresponding author: Ryosuke Yasui, yasui.ryosuke@eps.s.u-tokyo.ac.jp

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-17-0336.1

Abstract

The contributions of gravity waves to the momentum budget in the mesosphere and lower thermosphere (MLT) is examined using simulation data from the Ground-to-Topside Model of Atmosphere and Ionosphere for Aeronomy (GAIA) whole-atmosphere model. Regardless of the relatively coarse model resolution, gravity waves appear in the MLT region. The resolved gravity waves largely contribute to the MLT momentum budget. A pair of positive and negative Eliassen–Palm flux divergences of the resolved gravity waves are observed in the summer MLT region, suggesting that the resolved gravity waves are likely in situ generated in the MLT region. In the summer MLT region, the mean zonal winds have a strong vertical shear that is likely formed by parameterized gravity wave forcing. The Richardson number sometimes becomes less than a quarter in the strong-shear region, suggesting that the resolved gravity waves are generated by shear instability. In addition, shear instability occurs in the low (middle) latitudes of the summer (winter) MLT region and is associated with diurnal (semidiurnal) migrating tides. Resolved gravity waves are also radiated from these regions. In Part I of this paper, it was shown that Rossby waves in the MLT region are also radiated by the barotropic and/or baroclinic instability formed by parameterized gravity wave forcing. These results strongly suggest that the forcing by gravity waves originating from the lower atmosphere causes the barotropic/baroclinic and shear instabilities in the mesosphere that, respectively, generate Rossby and gravity waves and suggest that the in situ generation and dissipation of these waves play important roles in the momentum budget of the MLT region.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JAS-D-17-0337.s1.

Corresponding author: Ryosuke Yasui, yasui.ryosuke@eps.s.u-tokyo.ac.jp

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-17-0336.1

1. Introduction

The climatological structure of the temperature in the middle atmosphere is much different from that expected for a radiative equilibrium. The cold summer mesopause and the warm winter stratosphere are particularly outstanding (e.g., Becker 2012). Such a difference is attributed to the forcing on the mean fields from atmospheric waves, particularly those from gravity waves (GWs) (Plumb 2002). However, in the mesosphere and lower thermosphere (MLT), thermal tides (TWs) and Rossby waves (RWs) also have large amplitudes. Thus, it is important to examine each wave’s contribution to the momentum budget, including the wave–mean flow interaction and the wave–wave interaction, to better understand the climatology and variability in the MLT region.

GWs are mainly generated by various sources, such as topography, spontaneous balance adjustment (Plougonven and Zhang 2014; Yasuda et al. 2015), fronts (Snyder et al. 1993), convection (Sato 1993; Alexander et al. 1995), and the baroclinic jet–front systems in the moist atmosphere (Wei and Zhang 2014; Wei et al. 2016) in the troposphere. GWs may also be radiated from the shear instability of large-scale flows. Bühler et al. (1999) examined the GW emissions from shear instability using linearized f-plane Boussinesq equations and showed that GWs are radiated in four directions, namely, eastward upward, eastward downward, westward upward, and westward downward, from the unstable region. Such a process may be an important source of GWs in the summer lower stratosphere because the GWs with eastward-upward group velocities can propagate into the summer mesosphere without encountering a critical level in the westward vertical shear (Bühler and McIntyre 1999). A condition of the shear instability sometimes also holds when wave breaking occurs. Using a two-dimensional numerical model, Satomura and Sato (1999) showed a secondary generation of GWs via convective instability and/or shear instability in the region where mountain waves break. However, the possibility of such a secondary generation of GWs has not been well examined in the MLT region. It is necessary to confirm these secondary GW generations in the MLT region using models.

The important role of GWs in the MLT momentum budget was indicated directly and/or indirectly by previous studies using observations by satellites and radars, and a limited number of GCMs that include the MLT region. Ern et al. (2011) examined the distributions of GW momentum flux in the stratosphere and mesosphere using Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA), the High Resolution Dynamics Limb Sounder (HIRDLS), and the Sounding of the Atmosphere Using Broadband Emission Radiometry (SABER). It was shown that the GWs propagate poleward in the summer mesospheric jet and equatorward in the polar night jet. On the other hand, the ground-based radar observations allow us to estimate the GW forcing and the propagating direction. Reid and Vincent (1987) showed using medium-frequency (MF) radar located near Adelaide, Australia (35°S, 138°E), that GW forcing is 100 m s−1 day−1 near = 82 km, and decreases with height and reaches about −100 m s−1 day−1 at ~ 98 km in July. Seasonal variation in the GW forcing were also shown by using the meteor radar and the MF radar (e.g., De Wit et al. 2015; Placke et al. 2015). The global distribution of GW forcing has been examined by high-resolution GCMs. Using a GW-resolving GCM without including the GW parameterizations that cover the altitudes up to the upper mesosphere, Watanabe et al. (2008) separately showed the Eliassen–Palm (EP) flux and its divergence (EPFD) associated with planetary waves, synoptic waves, and GWs. The EPFDs in the summer and winter mesosphere and the summer stratosphere are mainly attributed to GWs, while the planetary waves are most dominant in the winter stratosphere. McLandress et al. (2006) showed that the eastward (westward) wave forcing with the zonal wavenumber > 4 is observed from z = 110 to 120 km in the winter (summer) MLT region using the extended Canadian Middle Atmosphere Model (CMAM). Note that the large wavenumber components in CMAM may be due to resolved GWs, as shown by the present study, but they did not indicate the possibility of GWs. Karlsson and Becker (2016) also showed that the wave forcing with wavenumber > 6 is large in the MLT region, and this forcing includes the resolved GW forcing. These resolved GWs may be secondarily generated by the resolved wave drag. In the thermosphere, Miyoshi et al. (2014) examined wave forcing by the resolved GWs propagating upward from the lower atmosphere using a high-resolution whole-atmosphere model in detail. The resolved GW forcing has large positive values in the summer northern thermosphere; this forcing reaches 230 m s−1 day−1. Miyoshi et al. (2015) also showed that this forcing modifies the thermospheric meridional circulation and is changed by a stratospheric sudden warming (SSW) event.

The mean flow is also modulated by momentum deposition through wave–wave interactions. Miyahara and Forbes (1994) showed that GWs propagating from the lower atmosphere break in the strong-shear region, which is caused by diurnal migrating tides, and that the magnitude of the GW forcing is modulated by the phases of migrating tides. Similar results for diurnal and semidiurnal tides are shown by Liu et al. (2014).

In a companion paper (Sato et al. 2018, hereafter referred to as Part I), we examined the momentum budget for the stratosphere to the lower thermosphere, focusing on the RW, GW, and TW contributions during all seasons using 11 years of simulation data from a whole-atmosphere model. For RWs, as is well known, EP flux is upward and equatorward oriented, and its divergence is negative in the winter stratosphere. One of the important findings is that RWs are radiated through the barotropic (BT) and/or baroclinic (BC) instabilities in the mesosphere and contribute significantly to the momentum budget in the MLT region. These characteristics are in good agreement with the satellite observations [e.g., using SABER observations (Ern et al. 2013) and Aura MLS observations (Part I, their Fig. 6)]. The BT/BC instability in the mesosphere is almost always observed and maintained by parameterized gravity wave forcing (hereafter referred to as GWFP). Another important finding is that, in spite of the relatively coarse horizontal resolution of the model, a significantly resolved GW forcing in the MLT region is observed. Very recently, Karlsson and Becker (2016), using the Kühlungsborn Mechanistic General Circulation Model (KMCM), also suggested small resolved GW forcing in the MLT region.

Our study examines the characteristics and generation mechanisms of the resolved GWs in the MLT region using simulation data from the whole-atmosphere model called the Ground-to-Topside Model of Atmosphere and Ionosphere for Aeronomy (GAIA) (e.g., Jin et al. 2011). The most probable generation mechanism will be shown to be shear instability in the MLT region. The roles of GWs originating from the lower atmosphere and the tides in the MLT region are discussed.

The remainder of this paper is organized as follows. A brief description of the data from GAIA is given in section 2. A method of analysis is described in section 3. The results of the momentum budget evaluation when dividing the resolved GWs into eastward- and westward-propagating components are shown in section 4. The in situ generation mechanisms of the resolved GWs in the MLT region are examined in section 5. Section 6 presents confirmation of the in situ GW generation in the MLT region by using data from higher-resolution model simulations over a limited time period.

2. Data description

a. GAIA simulation data

The GAIA simulation data are briefly introduced here. Details are given in Part I. GAIA is a coupled neutral and ionized atmosphere model that covers an altitude range from the ground to the thermosphere/ionosphere In this study, data from the neutral atmosphere model part (i.e., the GCM part) (e.g., Miyoshi and Fujiwara 2003) are used. The resolution of the GCM is T42L150, which has a horizontal grid point at every 2.8° and a vertical grid point at every 0.2 scale height for the range from the surface to a height of ~ 600 km. The height range analyzed in this study is = 0 to ~113 km. Accuracy of the model data below z ≈ 97 km was confirmed by comparing the data with the Aura MLS observations (see Part I). The structure of the zonal-mean temperature and zonal wind in the GAIA results is quantitatively similar to the satellite observations (e.g., Ern et al. 2013; Part I). See Part I for the details. A time interval of the model output is 1 h. The momentum deposition of the subgrid-scale GWs is represented using the GW parameterizations of McFarlane (1987) and Lindzen (1981) for orographic and nonorographic GWs, respectively. The GWFP was obtained offline because the parameterized GW forcing data were not archived. The model fields were nudged toward the JRA25/JCDAS data up to ~ 30 km in order to simulate a realistic quasi-biennial oscillation (QBO) in the equatorial lower stratosphere and wave forcing from the troposphere to the stratosphere realistically. We also performed a simulation using GAIA without the nudging, and confirmed that the momentum budget and the EPFD of each wave do not much differ in the MLT region (not shown). Moreover, the daily values of the 10.7-cm solar radio flux (F10.7) index were included in the model as a proxy of the solar UV–EUV radiation. The analyzed time period spans from 8 August 2004 to 19 June 2015.

b. HRGAIA simulation data

As shown in Part I, the GW-like disturbances were simulated regardless of the relatively coarse resolution (T42L150) of the standard GAIA for the GW simulation. As the background flow is maintained by the forcing, including that by the resolved GWs, the generation of GWs is likely. However, the structures of these resolved GWs may be largely distorted in the standard-resolution model. Thus, the simulation data from a high-horizontal-resolution version of GAIA (HRGAIA) over the limited period of a month is used to confirm the behaviors of the resolved GWs appearing in the standard GAIA. The resolution of the GCM part in HRGAIA is T106L150, which has a horizontal grid point at every 1.1° and the same vertical grids as those of the standard GAIA (Miyoshi et al. 2014, 2015). Note that nonorographic GW parameterization is not included, but the orographic GW parameterization by McFarlane (1987) is implemented in HRGAIA. The distributions of the water vapor and clouds are predicted in the model. As the lower boundary condition of this HRGAIA, climatologies are given for the mean sea surface temperature, ground wetness, and sea ice distribution. The analyzed height region is the same as that of the standard GAIA data, and the analyzed period is the month of January. Note that the HRGAIA is not nudged by reanalysis data. The HRGAIA is used here only for the purpose of validation for the existence of gravity waves as simulated in the standard GAIA.

3. Methods of analysis

To examine the characteristics of the resolved GWs and the mechanisms of the in situ generation of GWs in the MLT region, the resolved GWs are extracted from the model simulation data as follows. First, the TWs defined as a sum of the migrating tides with (,) = (1, 24), (2, 12), and (3, 8) h, where denotes a period, were removed. Next, the resolved GWs are extracted as disturbances with periods of ≤ 24 h. Note that nonmigrating tides are included in the resolved GWs because at least a part of the nonmigrating tides are regarded as global-scale inertia GWs (Sakazaki et al. 2015). The resolved GWs are divided into GWs with eastward- and westward-propagating components using a Fourier transform. The contributions of the eastward- and westward-propagating resolved GWs to the momentum budget are analyzed separately for EP flux and EPFD in the transformed-Eulerian-mean equation (Andrews et al. 1987) (see Part I for details).

4. Resolved gravity wave contribution to the momentum budget in the MLT region

Figures 1a and 1b show the latitude–height sections of the zonal-mean temperature (color shading) and zonal wind (contours) climatologies in January and July, respectively. As shown in Part I, most characteristics of the mean fields are consistent with the Aura MLS observations, except for the missing wind reversal in the vertical around ≈ 86 km in the summer hemisphere, although there exists a weak wind layer (see Part I, their Fig. 1). This difference may be due to the limitation of the representation of GWFP in the model. The differences in the zonal-mean temperature and zonal wind between GAIA and Aura MLS observations were described in Part I in detail.

Fig. 1.
Fig. 1.

Latitude–height sections of the zonal-mean temperature (color shading) and zonal wind (contours) climatologies during (a) January and (b) July. The contour interval is 10 m s−1, and the dashed lines denote negative values.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

In Part I (their Fig. 3), we have already shown the characteristics of the EP flux and EPFD associated with the resolved GWs: the EP flux is oriented downward (upward), and the EPFD is positive (negative) in the summer (winter) MLT region. Note that the downward (upward) EP flux implies the dominance of the vertical flux of the eastward (westward) momentum for GWs propagating energy upward. A pair of negative and positive EPFD regions is observed in the summer hemisphere near = 60° and z = 80 km and above, respectively. This result shows that the resolved GWs are likely generated in the summer MLT region. The GWs can propagate eastward and westward, and each propagating component may contribute differently to the EP flux and EPFD. Thus, to examine this pair of positive and negative EPFDs in detail, the EP flux and EPFD are divided into two namely that by resolved GWs propagating eastward and by those propagating westward.

Figure 2 shows the latitude–height sections of the EP flux and EPFD of the resolved GWs propagating eastward and westward during January and July. The net forcing to the mean zonal wind from the resolved GWs, which is in the same direction as GWFP in the MLT region (see Part I), is found to be mainly due to the eastward (westward) GWs in the summer (winter) MLT region. It is interesting that the westward (eastward) GWs provide wave forcing in the opposite direction of the GWFP in the summer (winter) hemisphere. The upward EP flux associated with the westward GWs in the summer hemisphere is observed above the region with a strong mean wind shear from 10°S, = 50 km to 50°S, = 100 km in January and with that from 0°, = 50 km to 45°N, = 95 km in July. It is also important that the EPFD for the westward GWs along the wind shear is positive. These features indicate the possibility that the westward GWs are in situ generated in the mesosphere via shear instability. It is also possible that eastward-resolved GWs are in situ generated in the mesosphere, although a part of the large-scale GWs originates from the latent heat release related to diurnal variations from convection at the planetary scale in the troposphere (Sakazaki et al. 2015).

Fig. 2.
Fig. 2.

Latitude–height sections of the climatologies of the EP flux and its divergence of the resolved GWs propagating eastward during (a) January and (c) July and propagating westward during (b) January and (d) July. Arrows indicate EP flux (m2 s−2). Color shading represents EP flux divergence (m s−1 day−1). Note that the contour intervals are not uniform.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

5. Gravity wave generation in the MLT region

a. Occurrence frequency of Richardson numbers smaller than 1/4

To examine the possibility of shear instability in the MLT region, the Richardson number is calculated. Here, and denote the static stability and zonal wind, respectively. Figure 3 shows the latitude–height sections of the occurrence frequencies of shear instability (i.e., Ri < 1/4) during January and July. The occurrence frequency is defined as the percentage of the cases in which Ri < 1/4 in January and July at each longitude, latitude, level, and time. In the middle latitudes of the summer hemisphere, the occurrence frequency of Ri < 1/4 is maximized at = 40.5°S and = 89 km (≈ 7.3%) in January and at = 37.7°N and = 86 km (≈ 5.2%) in July. The regions with large occurrence frequencies of Ri < 1/4 in the summer hemisphere tilt poleward with height. Figure 4 shows the time–latitude sections of the occurrence frequencies of Ri < 1/4 at = 90–100, 80–90, and 65–75 km. A smoothing of a 10-day running mean was applied to more clearly identify the characteristics. The seasonal variability is different at each level. As seen in Fig. 4c, the maximum is much clearer in the middle latitudes of the summer hemisphere at this level, and another maximum occurs at approximately 70°S in the middle latitudes of the winter hemisphere in June and July.

Fig. 3.
Fig. 3.

Latitude–height sections of the occurrence frequencies of Ri < 1/4 during (a) January and (b) July obtained from the GAIA simulation data. The contour interval is 0.5%.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

Fig. 4.
Fig. 4.

Time–latitude sections of the occurrence frequencies of Ri < 1/4 at = (a) 90–100, (b) 80–90, and (c) 65–75 km, respectively. The variabilities of the occurrence frequencies of Ri < 1/4 data are filtered by a 10-day running mean.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

On the other hand, in Fig. 3, it is interesting that the region with high-frequency occurrences extends toward the high latitudes of the winter hemisphere but that there is a secondary maximum at = 4.2° and = 98 km during both January and July in the summer hemisphere. These secondary maxima are observed not only in January and July but also in other months. For = 90–100 km (Fig. 4a), the occurrence frequencies are high in the low and middle latitudes of the summer hemisphere and in the low latitudes near the equator in the spring and autumn. Similar features are observed at = 80–90 km, but the maximum around the latitudes of 30°–40° is clearer (Fig. 4b). The maximum around the equator is not observed at = 65–75 km (Fig. 4c).

In the regions of the maxima in the middle latitudes of the summer hemisphere, there is strong vertical wind shear, as seen in Fig. 1. This feature suggests that a part of the resolved GWs in the summer MLT region is likely generated in situ by shear instability. As the region with large vertical wind shear in the summer mesosphere coincides well with strong GWFP, as indicated in Part I, the large occurrence frequency of Ri < 1/4 (i.e., strong vertical wind shear) is likely formed by the strong GWFP. In contrast, there is no mean wind structure corresponding to the secondary maximum in the low latitudes and its extension into the winter hemisphere. This secondary maximum is related to the TWs, as discussed in detail in section 5c. Note that the occurrence frequency of the convective instability ( < 0) was also examined, but it was negligible (< 0.6%) (not shown).

b. Resolved GWs propagating energy downward from the region with strong vertical wind shear in the MLT

According to recent theoretical studies by Bühler et al. (1999) and Bühler and McIntyre (1999), GWs are likely radiated eastward, westward, upward, and downward relative to the background winds from a region with strong vertical wind shear. To find evidence of the GWs propagating energy downward, the zonal mean vertical energy flux of the resolved GWs was examined in the latitude–height section. Figure 5a shows the result for the Southern Hemisphere (SH) in January. The energy flux is positive (i.e., upward) in most regions, except for in the high latitudes below = 45 km. The ratio of negative , namely, (%), is shown in Fig. 5b as a function of the latitude and height of the SH in January. Here, and , respectively, denote the absolute values of the negative and those of the positive at each time, latitude, longitude, and height. The summation was performed over time and longitude. The color shade represents the region with ≥ 18%. The value of is large below the regions with large occurrence frequencies of Ri < 1/4 in the low and middle latitudes. This result is consistent with our inference that the resolved GWs propagating energy downward are radiating from the strong wind shear, although the major part of the vertical energy flux is upward. Next, is examined for the eastward and westward GWs in Figs. 5c and 5d, respectively. The values are large for both the eastward and the westward GWs below the region with large occurrence frequencies of Ri < 1/4. However, of the eastward GWs is slightly smaller than that of the westward GWs. This is likely because a part of the eastward GWs is due to the GWs propagating upward without encountering their critical levels from the lower atmosphere. The maximum is observed below the maximum of the vertical wind shear for both the eastward and westward GWs. This fact means that at least part of both the eastward and westward GWs is generated in situ in the mesosphere.

Fig. 5.
Fig. 5.

(a) Latitude–height section of the climatology of the energy flux for the resolved GWs during January. (b) The latitude–height section of the ratio of < 0 for the resolved GWs, namely, the ratio of the GWs propagating energy downward during January. (c),(d) As in (b), but for the ratio of < 0 of the resolved GWs propagating eastward and westward, respectively. The red lines denote the occurrence frequencies of Ri < 1/4 in Fig. 3a.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

To examine the radiation of GWs with downward group velocities from shear instability in more detail, a cospectrum of and of the resolved GWs is calculated as a function of the ground-based phase speed at each height and is compared with the zonal mean zonal winds at the latitude of = 40.5°S in Fig. 6a. The vertical profiles in Fig. 6b are shown for the climatologies of , the square of the vertical wind shear, the median of Ri (as a typical value of Ri), and the occurrence frequency of Ri < 1/4 for = 40.5°S. The median of Ri is minimized and the occurrence frequency of Ri < 1/4 is maximized at ≈ 89 km. These features are due to the profile that is minimized at ≈ 89 km and the vertical wind shear, which rapidly increases with height above ≈ 75 km. Note that the occurrence frequency of Ri < 1/4 at ≈ 64 km is small, although the mean at ≈ 64 km is also small. This is because the variance of the at ≈ 64 km is smaller than that of the at ≈ 89 km (not shown). The cospectrum of the and fluctuations is negative below ~ 80 km in the range of (westward) phase speeds from −10 m s−1 to the zonal-mean zonal wind, and for a part of the positive (eastward) phase speeds below z ≈ 65 km. Note that the color contours are different between positive and negative values of the cospectrum. The smaller downward energy flux for positive phase speed is likely because a major part of the resolved GWs has upward energy flux and hides the downward energy flux of GWs. This inference is consistent with relatively small for eastward GWs (Fig. 5). This fact reinforces our inference that the resolved GWs in the middle latitudes of the summer mesosphere are generated in situ by shear instability. The most likely candidate to cause the shear instability in the middle latitudes of the summer mesosphere is the forcing of GWs propagating from the lower atmosphere, which is expressed by parameterizations in the model. Note again that these results do not differ much from the results using GAIA without nudging. This study showed that the most likely candidate for the secondary generation of GWs is the shear instability in the MLT region. However, there are other possible mechanisms. For example, GWs are radiated through a spontaneous adjustment around a possible westward jet imbalance in the summer hemisphere. Direct GW emission from the given wave forcing is also likely (i.e., Zhu and Holton 1987; Becker and Vadas 2018). The relative importance of these possible generation mechanisms in the momentum budget in the MLT region is left for future studies.

Fig. 6.
Fig. 6.

(a) Cospectrum of and for the resolved gravity waves (color), (solid line), and the standard deviation of (dashed lines) at 40.5°S during January. The horizontal axis denotes the phase speed of GWs or zonal wind speeds. (b) Vertical profiles of (left to right) , the square of the vertical wind shear, the median of Ri, and the occurrence frequencies of Ri < 1/4 at 40.5°S during January.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

c. Causes of shear instability in the summer low latitudes and winter middle latitudes of the MLT region

The occurrence frequency of Ri < 1/4 is also large in the summer low latitudes and winter middle latitudes of the MLT region (Fig. 3). However, the vertical shear of the zonal-mean zonal wind is weak (e.g., Fig. 1), and is not as small as in the middle latitudes. Thus, another mechanism must be present for the shear instability in this region. The most likely candidate is TWs.

The vertical shear of the horizontal winds in some phases of the TWs may be sufficiently large to cause shear instability. Figure 7 shows the latitude–height sections of the amplitudes of the , , and υ fluctuations of diurnal westward-migrating tides with = 1 (DW1) and semidiurnal westward-migrating tides with = 2 (SW2) in January obtained by the model data. The amplitude of DW1 (Fig. 7a) is maximized (~5.7 K) in the low latitudes for the height region above ~ 50 km. Both the and υ amplitudes of DW1 (Figs. 7b,c) are latitudinally maximized ( ~ 13.8 m s−1; υ ~ 20.2 m s−1) around = 20° in the height region above ~ 60 km. The SW2 amplitude maximum is observed in the middle latitudes and the maximum values increase with height above = 100 km (Figs. 7d–f). Thus, the DW1 and SW2 strongly influence the short-period variations in the low and middle latitudes of the MLT region, respectively. Because both the and υ amplitudes are large for DW1 and SW2, Ri is estimated using the following formula:
eq1
Animation S1 in the online supplemental material for this paper shows the latitude–height section of the occurrence frequency of Ri < 1/4 as a function of local time. Regions with large occurrence frequencies at each local time are observed in the summer middle latitudes and low latitudes of the MLT region. The maximum in the middle latitudes of the summer hemisphere is almost steady. In contrast, the large occurrence frequency region in the low latitudes propagates downward with time over a period of 24 h, suggesting that the large occurrence frequency is caused by DW1. Similar time variations of the region with the occurrence frequency of Ri < 1/4 but with a period of 12 h are seen in the winter MLT. This variation is attributable to SW2, which has large amplitudes in the middle latitudes above = 100 km (Figs. 7d-f). Note that the , , and υ amplitudes of the diurnal tides simulated in the GAIA are in good agreement with those observed by SABER (e.g., Zhu et al. 2008), but the amplitudes of the semidiurnal tides are larger above z = 105 km. Thus, the occurrence frequency of shear instability associated with SW2 would be smaller than in the real atmosphere.
Fig. 7.
Fig. 7.

Latitude–height sections of the amplitudes of the (a) , (b) , and (c) υ components of DW1 and the (d) , (e) , and (f) υ components of SW2 during January as obtained from the GAIA simulation data.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

Figure 8a shows the latitude–height section of the variance of the diurnal variation of the occurrence frequency of Ri < 1/4 during January in the model. The variance is quite small in the summer MLT region. This is consistent with our inference that the shear instability in this area is due to the climatological-mean zonal wind shear caused by the parameterized GW forcing. In contrast, the variance of the local time variation of occurrence frequency of Ri < 1/4 is large in the low latitudes above = 80 km and in the middle latitudes of the winter lower thermosphere. These large variances are attributable to DW1 and SW2, as mentioned before. Figure 8b shows the local time and height section of the occurrence frequency of Ri < 1/4 (contour) and the zonal wind of DW1 (color) at 20.9°S. The regions with maximum occurrence frequencies of Ri < 1/4 propagate downward at a rate of ~−0.6 km h−1. This downward speed accords well with the phase speed of the component of the DW1 in the region above = 90 km. Figure 8c shows the local time and height section of the ratio of the downward energy flux at 20.9°S, where the occurrence frequency of Ri < 1/4 has a secondary maximum in January. It is clear that is large below the height of the maxima of the occurrence frequency of Ri < 1/4 and varies with the local time. This result indicates that large-amplitude DW1 significantly contributes to the formations of shear instability in the low latitudes of the MLT region, which radiates (resolved) GWs. Similarly, SW2 contributes to the shear instability in the winter hemisphere. Figure 8d shows the component of SW2 and the occurrence frequency of Ri < 1/4 at 54.4°N as a function of the local time. The occurrence frequency of Ri < 1/4 varies over a semidiurnal period. The value of is large below the region where the occurrence frequency is maximized depending on the local time. Thus, the shear instability caused by SW2 is a likely mechanism for generating GWs in the middle latitudes of the winter hemisphere in the upper mesosphere and lower thermosphere. Note again that because the amplitudes of the semidiurnal tides simulated in the GAIA are larger than those in the observations above z = 105 km, it is possible that the maximum of the occurrence frequency of Ri < 1/4 above this level is overestimated.

Fig. 8.
Fig. 8.

(a) Variance of the local time variation of the occurrence frequency of Ri < 1/4 during January. (b) Local time and height section of the Ri < 1/4 frequency (contour) and the zonal wind component of DW1 (color) at 20.9°S during January. (c) Local time and height sections of Ri < 1/4 frequency (red contours) and the ratio of < 0 (color shading) at 20.9°S during January. (d) As in (b), but the colors represent the zonal wind component of SW2 at 54.4°N. (e) As in (c), but the red contours represent the Ri < 1/4 frequency at 54.4°N.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

6. Features of resolved GWs in HRGAIA

Structures of GWs resolved in the standard GAIA data may be largely distorted by relatively coarse horizontal model resolutions, although their generation mechanism is likely present in the real atmosphere. Thus, the characteristics of the GWs are also examined using the HRGAIA simulation data, although this simulation period is limited. Figure 9a shows the latitude–height sections of the zonal-mean temperatures and zonal winds in HRGAIA for January. The zonal-mean temperature field of HRGAIA is quite similar to that of the standard GAIA data. A notable difference is seen in the zonal-mean zonal wind field. The eastward jets in the SH stratosphere and mesosphere in HRGAIA are weaker, and their core is located at a higher latitude than that in the GAIA dataset. Moreover, a vertical reversal of the zonal winds near the summer mesopause is clear in HRGAIA, as is consistent with the observations (see Part I, their Fig. 1b).

Fig. 9.
Fig. 9.

Latitude–height sections of the (a) zonal-mean (color shading) and (contours), and (b) EP flux and EPFD (m s−1 day−1) of the resolved GWs during January obtained by the HRGAIA simulation data. Note that the contour intervals are not uniform.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

Next, the EP flux and EPFD associated with the resolved GWs in HRGAIA are examined (Fig. 9b). The EP flux is downward and equatorward, and the EPFD is positive in most regions of the summer mesosphere. The EP flux is upward and poleward, and the EPFD is negative in the winter mesosphere, which is generally consistent with the features seen in the standard GAIA. A difference is observed in the lower thermosphere, where the EP flux is upward (downward) and poleward and the EPFD is negative (positive) in the summer (winter) hemisphere. This difference is probably related to the presence of the clear zero-wind layer in the MLT region in HRGAIA. However, it was confirmed that the total wave forcing due to resolved GWs and parameterized orographic GWs in HRGAIA is comparable to that due to resolved GWs and parameterized orographic and nonorographic GWs in the mesosphere in GAIA (see Fig. 3 in Part I) with an exception at high latitudes causing from the deficiency of the GW parameterization (see Part I).

The possibility of the shear instability is also analyzed as a GW generation mechanism in the MLT region in HRGAIA. Figure 10 shows the latitude–height section of the occurrence frequency of Ri < 1/4 for HRGAIA in January. The distribution of the large occurrence frequency of Ri < 1/4 is quite similar to that in the standard GAIA with a slight difference: the maximum values of the summer middle latitudes and the low latitudes observed in the standard GAIA dataset are located, respectively, in higher and lower latitudes, in HRGAIA. The occurrence frequencies of Ri < 1/4 have maxima at = 56.6°S and = 87 km (~9.5%), and = 0.6°N and = 93 km (~8.1%) in the MLT region. This result suggests that the shear instability and associated in situ generation of the GWs also occurs in HRGAIA.

Fig. 10.
Fig. 10.

Latitude–height section of the occurrence frequency of Ri < 1/4 during January obtained from the HRGAIA simulation data. The contour interval is 1% and the dashed line denotes 0.5%.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

Next, the energy flux of the resolved GWs is examined in the summer MLT region for January using the data from HRGAIA (Fig. 11a). The value of is positive, which is consistent with the features observed in the standard GAIA data. Figure 11b shows the latitude–height section of . Similar to the results for the standard GAIA data analysis, large values are observed below the regions of the large occurrence frequencies of Ri < 1/4. The distribution of is shown separately for the eastward and westward GWs in Figs. 11c and 11d, respectively. The value of is large below the regions of the large occurrence frequencies of Ri < 1/4 in the low and middle latitudes of the summer hemisphere for both components, which is also consistent with the results for the standard GAIA.

Fig. 11.
Fig. 11.

As in Fig. 5, but for the HRGAIA simulation data.

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

Figure 12a shows a cospectrum of the and fluctuations associated with the resolved GWs and zonal-mean zonal winds at = 40.9°S. The vertical profiles in Fig. 12b show the climatologies of , the square of the vertical wind shear, the median of Ri, and the occurrence frequency of Ri < 1/4. While is minimized near = 90 km, the vertical wind shear is maximized near = 77 km. Thus, the median of Ri is minimized and the occurrence frequency of Ri < 1/4 is maximized around = 80 km. The negative cospectrum of and for the eastward-resolved GWs with phase speeds = ~20 m s−1 is observed below = 70 km. This feature of a negative cospectrum of and for eastward-resolved GWs in HRGAIA is similar to that observed in the standard GAIA data, although the phase speeds of the corresponding GWs are slower than those in the standard GAIA. This difference in the phase speed of GWs propagating energy downward between standard GAIA (Fig. 6a) and HRGAIA (Fig. 12a) data is probably related to the difference in the mean zonal wind and the simulated time period as well as the horizontal resolution. The mean zonal wind is about −35 m s−1 at the height of the maximum occurrence frequency of shear instability in the standard GAIA data. In contrast, it is ~0 m s−1 in HRGAIA. If the GWs are generated from the shear instability, the phase speeds of the GWs are expected to be distributed around the background wind speed (e.g., Fritts 1984). The distribution of phase speeds of GWs propagating energy downward is consistent with this expectation both for the standard GAIA and the HRGAIA. Note that the mean zonal wind is around zero at the level with the highest occurrence frequency of the shear instability for HRGAIA. To estimate small phase speed near 0 m s−1, a long time period of simulated data is necessary. However, the time period analyzed for HRGAIA is only a month. These reasons might explain why GWs propagating energy downward are not clearly identified for HRGAIA.

Fig. 12.
Fig. 12.

As in Fig. 6, but for the HRGAIA simulation data at 40.9°S. The dashed lines denote the standard deviation of .

Citation: Journal of the Atmospheric Sciences 75, 10; 10.1175/JAS-D-17-0337.1

The feature of an value that is large in the low latitudes of the MLT region (Fig. 11b) is consistent with the result of standard GAIA. The feature also confirms that the large values are related to the large occurrence frequencies of Ri < 1/4 caused by DW1 (not shown in detail). These results from the HRGAIA data also strongly support the in situ GW generations from the shear instability in the MLT region.

7. Summary and concluding remarks

This study examined the characteristics and generation mechanisms of the resolved GWs in the MLT region using simulation data from GAIA for over approximately 11 years, from August 2004 to June 2015, by separating the GWs into eastward- and westward-propagating components.

According to the analysis of the occurrence frequency of Ri < 1/4, the main mechanism causing the resolved GW generation in the MLT region is likely shear instability. There are two possible causes of the shear instability. In the middle latitudes of the summer hemisphere, a large climatological vertical shear of the zonal wind is observed, satisfying the shear instability. This shear is likely formed by GWFP, more specifically speaking, by nonorographic GW forcing. The dominance of the nonorographic GW forcing is confirmed by the fact that in the summer MLT region the orographic GW forcing is quite weak, and the zonal distribution of the area with high frequency of shear instability does not match that of the orographic GW forcing (not shown). This is related to the existence of the critical level for orographic GWs in the summer lower stratosphere at middle and high latitudes. The large number of GWs propagating energy downward below the strong vertical wind shear supports this inference. The occurrence frequency of the shear instability is also large in the low latitudes of the summer hemisphere and in the middle latitudes of the winter hemisphere. Large-amplitude TWs, in particular, DW1 and SW2, are responsible for the shear instability in these regions. Following the DW1 phase variation, the occurrence frequency of Ri < 1/4 has strong diurnal variability in the low latitudes of the summer hemisphere. In the diurnal variation, is enhanced below the regions with high occurrence frequencies of Ri < 1/4 for each local time. Similar features are observed in the middle latitudes of the winter hemisphere, but the variation is semidiurnal because of the dominant SW2. The in situ GW generations were confirmed by the analyses using simulation data over a limited period from the higher-resolution GAIA (HRGAIA).

The resolved GWs and RWs, including the QTDWs and the 4-day waves in the MLT region, the latter of which were analyzed in detail in Part I, are generated through shear and BT/BC instabilities caused by GWFP, respectively. This means that the climatologies of the mean fields are strongly affected by the GWFP directly and/or indirectly through in situ GW and RW excitations. Thus, it is very important to improve the GW parameterizations. Moreover, these in situ generated GWs in the MLT region may propagate into the thermosphere and contribute to the formation of the thermospheric circulation (e.g., Miyoshi et al. 2014), ionospheric disturbances (e.g., traveling ionospheric disturbances; Kelley 2009), and/or initial disturbances of the equatorial spread F (Huang and Kelley 1996). Further studies are necessary to confirm these viewpoints using whole-atmosphere models.

Acknowledgments

This work was supported by CREST (JPMJCR1663), JST. The figures were prepared using the GFD-DENNOU library. The numerical simulation in this work was performed using the Hitachi SR16000/M1 and the NICT Science Cloud System, Japan.

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Supplementary Materials

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  • Alexander, M. J., J. R. Holton, and D. R. Durran, 1995: The gravity wave response above deep convection in a squall line simulation. J. Atmos. Sci., 52, 22122226, https://doi.org/10.1175/1520-0469(1995)052<2212:TGWRAD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Andrews, D. G., J. R. Holton, and C. B. Leovy, 1987: Middle Atmosphere Dynamics. Academic Press, 489 pp.

  • Becker, E., 2012: Dynamical control of the middle atmosphere. Space Sci. Rev., 168, 283314, https://doi.org/10.1007/s11214-011-9841-5.

  • Becker, E., and S. L. Vadas, 2018: Secondary gravity waves in the winter mesosphere: Results from a high-resolution global circulation model. J. Geophys. Res. Atmos., 123, 26052627, https://doi.org/10.1002/2017JD027460.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bühler, O., and M. E. McIntyre, 1999: On shear-generated gravity waves that reach the mesosphere. Part II: Wave propagation. J. Atmos. Sci., 56, 37643773, https://doi.org/10.1175/1520-0469(1999)056<3764:OSGGWT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bühler, O., M. E. McIntyre, and J. F. Scinocca, 1999: On shear-generated gravity waves that reach the mesosphere. Part I: Wave generation. J. Atmos. Sci., 56, 37493763, https://doi.org/10.1175/1520-0469(1999)056<3749:OSGGWT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • De Wit, R. J., R. E. Hibbins, and P. J. Espy, 2015: The seasonal cycle of gravity wave momentum flux and forcing in the high latitude Northern Hemisphere mesopause region. J. Atmos. Sol.-Terr. Phys., 127, 2129, https://doi.org/10.1016/j.jastp.2014.10.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ern, M., P. Preusse, J. C. Gille, C. L. Hepplewhite, M. G. Mlynczak, J. M. Russell III, and M. Riese, 2011: Implications for atmospheric dynamics derived from global observations of gravity wave momentum flux in stratosphere and mesosphere. J. Geophys. Res., 116, D19107, https://doi.org/10.1029/2011JD015821.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ern, M., P. Preusse, S. Kalisch, M. Kaufmann, and M. Riese, 2013: Role of gravity waves in the forcing of quasi two-day waves in the mesosphere: An observational study. J. Geophys. Res. Atmos., 118, 34673485, https://doi.org/10.1029/2012JD018208.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fritts, D. C., 1984: Shear excitation of atmospheric gravity waves. Part II: Nonlinear radiation from a free shear layer. J. Atmos. Sci., 41, 524537, https://doi.org/10.1175/1520-0469(1984)041<0524:SEOAGW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, C.-S., and M. C. Kelley, 1996: Nonlinear evolution of equatorial spread F: 1. On the role of plasma instabilities and spatial resonance associated with gravity wave seeding. J. Geophys. Res., 101, 283292, https://doi.org/10.1029/95JA02211.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jin, H., and Coauthors, 2011: Vertical connection from the tropospheric activities to the ionospheric longitudinal structure simulated by a new Earth’s whole atmosphere-ionosphere coupled model. J. Geophys. Res., 116, A01316, https://doi.org/10.1029/2010JA015925.

    • Search Google Scholar
    • Export Citation
  • Karlsson, B., and E. Becker, 2016: How does interhemispheric coupling contribute to cool down the summer polar mesosphere? J. Climate, 29, 88078821, https://doi.org/10.1175/JCLI-D-16-0231.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kelley, M. C., 2009: The Earth’s Ionosphere: Plasma Physics and Electrodynamics. 2nd ed. International Geophysics Series, Vol. 96, Academic Press, 576 pp.

  • Lindzen, R. S., 1981: Turbulence and stress owing to gravity wave and tidal breakdown. J. Geophys. Res., 86, 97079714, https://doi.org/10.1029/JC086iC10p09707.

    • Crossref
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  • Fig. 1.

    Latitude–height sections of the zonal-mean temperature (color shading) and zonal wind (contours) climatologies during (a) January and (b) July. The contour interval is 10 m s−1, and the dashed lines denote negative values.

  • Fig. 2.

    Latitude–height sections of the climatologies of the EP flux and its divergence of the resolved GWs propagating eastward during (a) January and (c) July and propagating westward during (b) January and (d) July. Arrows indicate EP flux (m2 s−2). Color shading represents EP flux divergence (m s−1 day−1). Note that the contour intervals are not uniform.

  • Fig. 3.

    Latitude–height sections of the occurrence frequencies of Ri < 1/4 during (a) January and (b) July obtained from the GAIA simulation data. The contour interval is 0.5%.

  • Fig. 4.

    Time–latitude sections of the occurrence frequencies of Ri < 1/4 at = (a) 90–100, (b) 80–90, and (c) 65–75 km, respectively. The variabilities of the occurrence frequencies of Ri < 1/4 data are filtered by a 10-day running mean.

  • Fig. 5.

    (a) Latitude–height section of the climatology of the energy flux for the resolved GWs during January. (b) The latitude–height section of the ratio of < 0 for the resolved GWs, namely, the ratio of the GWs propagating energy downward during January. (c),(d) As in (b), but for the ratio of < 0 of the resolved GWs propagating eastward and westward, respectively. The red lines denote the occurrence frequencies of Ri < 1/4 in Fig. 3a.

  • Fig. 6.

    (a) Cospectrum of and for the resolved gravity waves (color), (solid line), and the standard deviation of (dashed lines) at 40.5°S during January. The horizontal axis denotes the phase speed of GWs or zonal wind speeds. (b) Vertical profiles of (left to right) , the square of the vertical wind shear, the median of Ri, and the occurrence frequencies of Ri < 1/4 at 40.5°S during January.

  • Fig. 7.

    Latitude–height sections of the amplitudes of the (a) , (b) , and (c) υ components of DW1 and the (d) , (e) , and (f) υ components of SW2 during January as obtained from the GAIA simulation data.

  • Fig. 8.

    (a) Variance of the local time variation of the occurrence frequency of Ri < 1/4 during January. (b) Local time and height section of the Ri < 1/4 frequency (contour) and the zonal wind component of DW1 (color) at 20.9°S during January. (c) Local time and height sections of Ri < 1/4 frequency (red contours) and the ratio of < 0 (color shading) at 20.9°S during January. (d) As in (b), but the colors represent the zonal wind component of SW2 at 54.4°N. (e) As in (c), but the red contours represent the Ri < 1/4 frequency at 54.4°N.

  • Fig. 9.

    Latitude–height sections of the (a) zonal-mean (color shading) and (contours), and (b) EP flux and EPFD (m s−1 day−1) of the resolved GWs during January obtained by the HRGAIA simulation data. Note that the contour intervals are not uniform.

  • Fig. 10.

    Latitude–height section of the occurrence frequency of Ri < 1/4 during January obtained from the HRGAIA simulation data. The contour interval is 1% and the dashed line denotes 0.5%.

  • Fig. 11.

    As in Fig. 5, but for the HRGAIA simulation data.

  • Fig. 12.

    As in Fig. 6, but for the HRGAIA simulation data at 40.9°S. The dashed lines denote the standard deviation of .

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