1.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China 2.Institute of Atmosphere Physics, Chinese Academy Sciences, Beijing 100029, China Manuscript received: 2018-03-01 Manuscript revised: 2018-08-07 Manuscript accepted: 2018-08-20 Abstract:A three-dimensional transformed Eulerian-mean (3D TEM) equation under a non-hydrostatic and non-geostrophic assumption is deduced in this study. The vertical component of the 3D wave activity flux deduced here is the primary difference from previous studies, which is suitable to mesoscale systems. Using the 3D TEM equation, the energy propagation of the inertia-gravity waves and how the generation and dissipation of the inertia-gravity waves drive the mean flow can be examined. During the mature stage of a heavy precipitation event, the maximum of the Eliassen-Palm (EP) flux divergence is primarily concentrated at the height of 10-14 km, where the energy of the inertia-gravity waves propagates forward (eastward) and upward. Examining the contribution of each term of the 3D TEM equation shows that the EP flux divergence is the primary contributor to the mean flow tendency. The EP flux divergence decelerates the zonal wind above and below the high-level jet at the height of 10 km and 15 km, and accelerates the high-level jet at the height of 12-14 km. This structure enhances the vertical wind shear of the environment and promotes the development of the rainstorm. Keywords: three-dimensional EP flux, heavy precipitation, inertia-gravity waves 摘要:在非地转非静力平衡条件下, 我们成功推导出适用于中小尺度的三维EP通量方程. 其中, 与前人工作的最大区别是在于推导得到的三维EP通量的垂直分量. 利用三维EP通量方程, 我们研究了惯性重力波的能量传播问题以及惯性重力波对背景流场的影响. 我们选取四川地区一次暴雨过程为例. 分析发现在暴雨的成熟阶段, 最大的EP通量散度位于高空10-14km的位置, 此处有惯性重力波向前向上传播. 将EP通量进一步分解后分析发现, EP通量散度是对背景流场的主要贡献项. EP通量散度能够使得高空急流的上下两侧U风速减速, 并且加速高空急流, 从而增强高空急流上下两侧的垂直风切, 进一步促进了暴雨发展. 关键词:三维EP通量, 暴雨, 惯性重力波
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4.1. Numerical model description
The numerical experiment is performed using the Weather Research and Forecasting model to simulate the rainstorm. The initial and lateral boundary conditions of the model are based on the Global Forecast System (GFS) analysis dataset from the National Centers for Environmental Prediction, with horizontal grid spacing of 0.5°× 0.5°. The numerical experiment is one-way nested with two domains (Fig. 1a). The two domains both have 303× 303 horizontal grids, with horizontal grid spacings of 3 km and 1 km. Also, the domains have 51 vertical layers, with the model top set at 50 hPa. The model is integrated for 36 h, starting at 0000 UTC 17 August 2014, with output every 10 min. The physical parameterization schemes include the New Thompson microphysics scheme (Thompson et al., 2008), the RRTM longwave radiation transfer scheme (Mlawer et al., 1997), the Goddard shortwave radiation transfer scheme, and the Mellor-Yamada-Janjic scheme of the planetary boundary layer (Janji?, 1994). Figures 1b and c show the 6-h accumulated precipitation from the observations and the simulation in domain 1. The observed precipitation data are an hourly precipitation gridded dataset, which is from China automatic station and CMORPH precipitation data (http://data.cma.cn/data/detail/dataCode/SEVP_CLI_CHN_MERGE_CMP_PRE_HOUR_GRID_0.10/keywords/cmorph.html ). The heavy rainfall occurred predominantly in Sichuan, along the border of the Sichuan Basin and the Tibetan Plateau. The rainband moved from the northwest to the southeast. Compared to the observations, the simulated precipitation is slightly stronger, possibly because the observational data are from meteorological stations, but the terrain is complex in northern Sichuan and in the Tibetan Plateau; thus, there are fewer meteorological stations and the observational data have a lower resolution. However, the simulation can accommodate changes in the rainfall location, variation and duration. Next, the simulation data are used to study the 3D wave activity flux during the precipitation event.
2 4.2. Inertia-gravity waves -->
4.2. Inertia-gravity waves
Lu et al. (2005a,b) and (Gao et al., 2015) discussed that the polarization——meaning that the directions of wave propagation and wave oscillation are perpendicular——is a representative characteristic of inertia-gravity waves. The phase difference between the perturbation divergence and vorticity of π/2 is an important characteristic of inertia-gravity waves. This polarization feature is crucial for extracting the inertia-gravity waves simply from simulations and observational data. Figures 2a and b show the vertical distribution of vertical vorticity and horizontal divergence at 1030 UTC and 1400 UTC. There are clearly positive and negative changes in the vertical vorticity and horizontal divergence at the height of 12 km in the rainstorm system. Also, it can be seen that the divergence region is one-quarter of a wavelength ahead of the vorticity, which is a typical characteristic of inertia-gravity waves. A detailed analysis of the characteristics of inertia-gravity waves during the heavy precipitation event can be found in (Liu et al., 2018). Notably, when inertia-gravity waves gradually enhance, the corresponding surface precipitation is also increasing. At 1400 UTC (Fig. 2b), the strength of the inertia-gravity waves and the accumulated precipitation peak almost simultaneously. It can be seen that the precipitation has a close relationship with the inertia-gravity waves. Therefore, in the next section, the 3D EP flux is introduced to analyze the influence of inertia-gravity waves on the development of precipitation. Figure2. Vertical profile of vertical vorticity (shaded; units: 10-3 s-2) and horizontal divergence (contours; units: 10-3 s-2) along 31.1°N at (a) 1030 UTC and (b) 1400 UTC. The grey region denotes the topography. The red line represents the 30-min accumulated precipitation (units: mm).
2 4.3. 3D EP flux analysis -->
4.3. 3D EP flux analysis
In this section, to demonstrate the application of the divergence of the 3D EP flux, a simple case of a heavy precipitation event that occurred in the Sichuan area is analyzed. The time-mean field is obtained by a moving average with a period of 100 min, which is approximately the period of the inertia-gravity waves during the precipitation (Liu et al., 2018). The disturbance field is defined as the deviation from the time-mean field. Figure 3 is a vertical profile of area-average $\bar u_t$ (the averaged area is the domain 2 region). The red line represents the $\bar u_t$ resulting from the time partial derivative of the simulated u-wind, and the green line represents the $\bar u_t$ resulting from the left-hand side of the TEM equation [Eq. (15)]. Although the red line is slightly stronger than the green line, the two lines have the same variation tendency with height: positive in the lower and higher level, indicating that the u-wind tends to increase, and negative in the middle level, meaning that the u-wind tends to decrease. Thus, the TEM equation is valid and can be used in the following. Figure3. Vertical profile of area-average $\bar{u}_t$ at 0900 UTC (the red line represents the time partial derivative from simulated data; the green line is calculated from the TEM equation; units: m s-2).
The EP flux is proportional to the group velocity deduced above. Figure 4 shows the longitude-pressure cross section of the EP flux F1 and the EP flux divergence ?· F1 during the mature stages of the rainstorm. The contour is the 30-min accumulated precipitation, denoting the rainstorm location. The maximum of the EP flux divergence is primarily concentrated at the height of 10-14 km, which is consistent with the above-mentioned location of the inertia-gravity waves. In terms of the TEM equation, the EP flux divergence corresponds to the wave forcing to the mean flow. The positive EP flux divergence could weaken the mean flow, and the negative EP flux divergence could enhance the mean flow. There were two parts of the EP flux divergence in the rainstorm. One part is in the region of 103°-104°E, with negative EP flux divergence, indicating that the EP flux divergence accelerates the westerly wind at the height of 12 km. The other is in the region of 104°-105°E, where the EP flux divergence alternates between positive and negative. This means that there is almost no acceleration or deceleration. The EP flux (vector) is proportional to the group velocity, representing the propagation of the inertia-gravity wave energy. The EP flux vector in Fig. 4, with a maximum value in the region of 103°-104°E, points forward (eastward) and upward in the rainstorm, indicating that the wave energy propagates forward (eastward) and upward. The reason for the forward and upward propagation of the wave energy can be explained insofar as the strong westerly airflow runs over the mountain, causing powerful ascending velocity due to the mountain lift. The powerful upward motion transports the wave energy upward and the strong westerly airflow transports the wave energy forward. Whereas, in the decaying stage, the EP flux and the EP flux divergence almost vanish (figure omitted). Figure4. Cross sections of EP flux (vectors) and EP flux divergence (shaded; units: 10-3 m s-2) along 31.1°N at 1030 UTC. The red line denotes the 30-min accumulated precipitation (units: mm).
To examine the contribution of each term of the TEM equation to the mean flow, the longitude-pressure cross sections of $\overline{V}\cdot\nabla\bar{u}$, $\overline{v^{\ast}}f$ and ?· F1 are shown in Fig. 5. The EP flux divergence ?· F1 is strongest (Fig. 5c) and plays a key role in the environmental flow variation. The EP flux divergence is negative in the region of 103°-104°E, indicating an acceleration of westerly wind. There is a high-level jet at the height of 12-14 km during the rainstorm, and therefore the negative EP flux divergence is maintained and enhances the high-level jet, which is conducive to enhancing the vertical wind shear. In (Liu et al., 2018), it was shown that intensified high-level vertical wind shear favors inertia-gravity wave development and enhances convection, thus promoting rainstorm development. Many researchers (e.g., Uccelini, 1975; Li, 1978; Koch and Siedlarz, 1999; Lane and Zhang, 2011) have examined the interaction between inertia-gravity waves and deep convection and proposed that mesoscale gravity waves are capable of causing convective instability and initiating thunderstorm development; in turn, the latent heat release feeds back to the background waves, triggering or amplifying the gravity waves. In addition, there are positive and negative changes in the EP flux divergence in the region of 104°-105°E, indicatingthe westerly wind accelerates and decelerates alternately. The acceleration and deceleration cancel each other out, meaning there is almost no acceleration of the westerly wind. Therefore, strong convergence of EP flux occurs near the region of 103.5°-104°E, providing beneficial conditions for heavy precipitation development. The wind advection term $\overline{V}\cdot\nabla\bar{u}$ is the second major contributor to the mean flow (Fig. 5a). The wind advection term is positive at the height of 12-14 km and negative at the height of 14-16 km, indicating deceleration of the westerly wind at relatively low levels and acceleration at relatively high levels. The residual mean circulation term $\overline{v^{\ast}}f$ (Fig. 5b) is much weaker, with a distribution at height of 12-14 km. Figure5. Cross sections of terms of the 3D TEM equation at 1030 UTC along 31.1°N: (a) $\bar{v}\cdot\nabla\bar{u}$; (b) $\overline{v^{\ast}}f$; (c) ?· F1 (units: 10-3 m s-2). The black line denotes the 30-min accumulated precipitation (units: mm).
Figure 6 shows the vertical profile of the regional average of $\overline{V}\cdot\nabla\bar{u}$, $\overline{v^{\ast}}f$, ?· F1 and $\bar{u}_t$. The selected region is where the 6-h accumulated precipitation is greater than 10 mm. During the developing stage of the rainstorm (Fig. 6a), the EP flux divergence is negative at the height of 12-14 km, which is advantageous to enhancing the westerly wind and the high-level jet. Also, the EP flux divergence is positive at approximately the height of 10 km and 15 km, which is conducive to weakening the westerly wind above and below the high-level jet, thus enhancing the vertical wind shear of the environment. The non-geostrophic balance and vertical wind shear near the high-level jet is conducive to inertia-gravity wave enhancement; in turn, the developing inertia-gravity waves enhance the perturbation of the atmosphere, and thus the EP flux markedly strengthens. The residual mean circulation term $\overline{v^{\ast}}f$ is weaker and almost opposite to the distribution of the wind advection term $\overline{V}\cdot\nabla\bar{u}$, but their effects are the same with the deceleration of westerly wind. In the declining stage (Fig. 6b), each term is much weaker than before. The distribution of the EP flux is unchanged, but its intensity is obviously reduced. The wind advection terms contributes the most to the wind tendency $\bar{u}_t$, causing the reduction of the westerly wind. Figure6. Vertical profile of area-average terms from the 3D TEM equation (a) at 1030 UTC and (b) at 1500 UTC. The red line denotes the EP flux divergence ? · F1; the green line denotes the advection terms $\bar{v}\cdot\nabla\bar{u}$; the blue line denotes the residual mean circulation $\overline{v^{\ast}}f$; and the yellow line denotes the local variation $\bar{u}_t$ (units: 10-3 m s-2).
To study the causes of the EP flux divergence variation, we disassemble the 3D EP flux divergence into three parts. Figure 7 shows the longitude-pressure cross sections of ? F1,1/? x, ? F1,2/? y and ? F1,3/? z, where F1,1 denotes the zonal transport of the zonal momentum, F1,2 denotes meridional transport of zonal momentum, and F1,3 denotes the vertical transport of zonal momentum and the meridional transport of the heat flux. It can be seen that ? F1,1/? x and ? F1,3/? z are much stronger than ? F1,2/? y. Comparison between ? F1,1/? x, ? F1,3/? z and ? · F1 shows that ? F1,1/? x makes the greatest contribution to ? · F1, and their distributions are similar. F1,1 consists of the zonal transport of horizontal momentum $\overline{u'u'}$ and the difference between the perturbation kinetic energy and perturbation potential energy S, which are shown in Figs. 8a and b. The two terms with the same magnitude are both important to F1,1. $\overline{u'u'}$ is primarily located over the peak of the precipitation, possibly due to the high-level jet. S is positive to the east of the maximal precipitation and negative to the west, meaning the perturbation kinetic energy is stronger to the east of the maximal precipitation and the perturbation potential energy is stronger at the west. F1,3 consists of the vertical transport of horizontal momentum $\overline{u'w'}$ and the meridional transport of the heat flux $f(\overline{v'\theta'}/N^2)(g/\bar{\theta})$, which are shown in Figs. 8c and d. $\overline{u'w'}$ is much stronger than $f(\overline{v'\theta'}/N^2)(g/\bar{\theta})$, so the vertical transport of horizontal momentum $\overline{u'w'}$ is the primary contributor to the F1,3 variation. This is because there is strong upward motion over the peak of the precipitation due to the mountain uplift. Previous studies have shown that the vertical transportation of horizontal momentum flux is very important to convective activity (e.g., Houze, 2004; Chong et al., 1987; Chong, 2010). This study provides another explanation for the importance of $\overline{u'w'}$. Figure7. Cross sections of (a) ? F1,1/? x, (b) ? F1,2/? y and (c) ? F1,3/? z (units: m-2 s-2) at 1030 UTC along 31.1°N. The red line denotes the 30-min accumulated precipitation (units: mm).
Figure8. Cross sections of (a) $\overline{u'u'}$, (b) S, (c) $\overline{u'w'}$ and (d) $f(\overline{v'\theta'}/N^2)(g/\bar{\theta})$ (units: m-2 s-2) at 1030 UTC along 31.1°N. The red line denotes the 30-min accumulated precipitation (units: mm).
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APPENDIX A
From the governing equations, it is assumed that the basic flow is still, and the linear disturbance equations for 3D inertia-gravity waves are \begin{eqnarray} \frac{\partial{u}'}{\partial t}-f{v}'+\frac{1}{\bar {\rho}}\frac{\partial{p}'}{\partial x}=0 ,\ \ (A1)\\ \frac{\partial{v}'}{\partial t}+f{u}'+\frac{1}{\bar {\rho}}\frac{\partial{p}'}{\partial y}=0 , \ \ (A2)\end{eqnarray} \begin{eqnarray} \frac{\partial{w}'}{\partial t}+\frac{1}{\bar {\rho}}\frac{\partial{p}'}{\partial z} -g\frac{{\theta}'}{\bar {\theta}}=0 , \ \ (A3)\\ \frac{\partial{u}'}{\partial x}+\frac{\partial{v}'}{\partial y}+\frac{\partial{w}'}{\partial z}=0 , \ \ (A4)\\ \frac{\partial{\theta}'}{\partial t}+N^2\frac{\bar {\theta}}{g}{w}'=0 . \ \ (A5)\end{eqnarray} According to multi-scale methods of waves, the slow spatial and temporal scale is defined as X=ε x, Y=ε y, Z=ε z, T=ε t, where x, y, and t are the physical quantities of the quick spatial and temporal scale, and parameter |ε|? 1. It is assumed that a form of a plane wave is considered, \begin{equation} {A}'=A_0(X,Y,Z,T){\rm e}^{i\phi} , \ \ (A6)\end{equation} where φ=kx+ly+mz-ω t is the wave phase; k, l and m are the wave numbers in the x, y, and z directions; $\tilde\omega=\omega-k\bar{u}$ is the intrinsic frequency; and ω is the local frequency. Because the basic flow is still $(\bar{u}\approx0)$,the intrinsic frequency is thus equal to the local frequency. The phase of φ satisfies the relationships \begin{equation} \frac{\partial\phi}{\partial t}=-\omega ,\quad \frac{\partial\phi}{\partial x}=k ,\quad \frac{\partial\phi}{\partial y}=l ,\quad \frac{\partial\phi}{\partial z}=n . \ \ (A7)\end{equation} Then, it can be proved that the wave numbers satisfy the following relationships: \begin{eqnarray} \frac{\partial\omega}{\partial X}&=&-\frac{\partial k}{\partial T} ,\quad \frac{\partial\omega}{\partial Y}=-\frac{\partial l}{\partial T} ,\quad \frac{\partial\omega}{\partial Z}=-\frac{\partial m}{\partial T} ,\nonumber\\ \frac{\partial k}{\partial Y}&=&\frac{\partial l}{\partial X} ,\quad \frac{\partial k}{\partial Z}=\frac{\partial m}{\partial X} ,\quad \frac{\partial l}{\partial Z}=\frac{\partial m}{\partial Y} . \ \ (A8)\end{eqnarray} The amplitude of waves is expressed by the method of small parameters: \begin{equation} A_0(X,Y,Z,T)=\sum_{n=0}^\infty\varepsilon_nA_{0,n}(X,Y,Z,T) . \ \ (A9)\end{equation} Substitution of Eq. (A9) into Eqs. (A1)-(A5) yields the ε0 approximate equations: \begin{eqnarray} -i\omega u_{0,0}-fv_{0,0}+ik\frac{p_{0,0}}{\bar {\rho}}=0 ,\ \ (A10)\\ -i\omega v_{0,0}+fu_{0,0}+il\frac{p_{0,0}}{\bar{\rho}}=0 ,\ \ (A11)\\ -i\omega w_{0,0}+in\frac{p_{0,0}}{\bar {\rho}}-g\frac{\theta_{0,0}}{\bar{\theta}}=0 ,\ \ (A12)\\ ku_{0,0}+lv_{0,0}+mw_{0,0}=0 ,\ \ (A13)\\ -i\omega\theta_{0,0}+N^2\frac{\bar {\theta}}{g}w_{0,0}=0 , \ \ (A14)\end{eqnarray} and the ε1 approximate equations: \begin{eqnarray} -i\omega u_{1,0}-fv_{1,0}+ik\frac{p_{1,0}}{\bar {\rho}}=-\left(\frac{\partial u_{0,0}}{\partial T}+ \frac{1}{\bar {\rho}}\frac{\partial p_{0,0}}{\partial X}\right)&\!=\!&-A ,\ \ (A15)\qquad\ \ \\ -i\omega v_{1,0}+fu_{1,0}+il\frac{p_{1,0}}{\bar {\rho}}=-\left(\frac{\partial v_{1,0}}{\partial T}+ \frac{1}{\bar {\rho}}\frac{\partial p_{0,0}}{\partial Y}\right)&\!=\!&-B ,\ \ (A16)\\ -i\omega w_{1,0}+in\frac{p_{1,0}}{\bar {\rho}}-g\frac{\theta_{1,0}}{\bar {\theta}} =-\left(\frac{\partial w_{0,0}}{\partial T}+\frac{1}{\bar {\rho}}\frac{\partial p_{0,0}}{\partial Z}\right)&\!=\!&-C , \ \ (A17)\end{eqnarray} \begin{eqnarray} ku_{1,0}+lv_{1,0}+mw_{1,0}=i\frac{\partial u_{0,0}}{\partial X}+i\frac{\partial v_{0,0}}{\partial Y}+i\frac{\partial w_{0,0}}{\partial Z}&\!=\!&-D ,\ \ (A18)\qquad\quad\\ -i\omega\theta_{1,0}+N^2\frac{\bar {\theta}}{g}w_{1,0}=-\frac{\partial\theta_{0,0}}{\partial T}&\!=\!&-E .\ \ (A19) \end{eqnarray} Eliminating the zero-order disturbance in the ε1 approximate equations produces \begin{eqnarray} &&(i\omega k+fl)mA+(i\omega l-fk)mB-i\omega(k^2+l^2)C-\qquad\nonumber\\ &&(\omega^2-f^2)mD+(k^2+l^2)\frac{g}{\bar {\theta}}E=0 . \ \ (A20)\end{eqnarray} Substituting Eqs. (A15)-(A19) of A, B, C, D and E into Eq. (A20), the 3D wave activity equations for inertia-gravity waves are obtained: \begin{equation} \frac{\partial H}{\partial T}+\frac{\partial}{\partial X}(C_{{g},x}H)+ \frac{\partial}{\partial Y}(C_{{g},y}H)+\frac{\partial}{\partial Z}(C_{{g},z}H)=0 , \ \ (A21)\end{equation} where H=(k2+l2+m2)ω02 is the wave activity density and Cg=(Cg,x,Cg,y,Cg,z) are the group velocities of the 3D inertia-gravity waves: \begin{eqnarray} C_{{g},x}&=&\frac{(\omega^2-f^2)n^2k}{\omega(k^2+l^2+n^2)(k^2+l^2)} ,\ \ (A22)\\ C_{{g},y}&=&\frac{(\omega^2-f^2)n^2l}{\omega(k^2+l^2+n^2)(k^2+l^2)} ,\ \ (A23)\\ C_{{g},z}&=&\frac{(\omega^2-f^2)n}{\omega(k^2+l^2+n^2)} , \ \ (A24)\end{eqnarray} H satisfies the wave activity density conservation equation as follows: \begin{equation} \frac{\partial A}{\partial t}+\nabla\cdot({C}_{g}A)=0 . \ \ (A25)\end{equation} Based on the dispersion relation for inertia-gravity waves [Eq. (32)] and the local wave number [Eq. (A8)], the wave parameter tendency equations are given in the following: \begin{eqnarray} \frac{\partial\omega}{\partial T}+C_{{g},x}\frac{\partial\omega}{\partial X}+ C_{{g},y}\frac{\partial\omega}{\partial Y}+C_{{g},z}\frac{\partial\omega}{\partial Z}&=&0 ,\ \ (A26)\\ \frac{\partial k}{\partial T}+C_{{g},x}\frac{\partial k}{\partial X}+C_{{g},y}\frac{\partial k}{\partial Y}+C_{{g},z}\frac{\partial k}{\partial Z}&=&0 ,\ \ (A27)\\ \frac{\partial l}{\partial T}+C_{{g},x}\frac{\partial l}{\partial X}+C_{{g},y}\frac{\partial l}{\partial Y}+C_{{g},z}\frac{\partial l}{\partial Z}&=&0 ,\ \ (A28)\\ \frac{\partial m}{\partial T}+C_{{g},x}\frac{\partial m}{\partial X}+C_{{g},y}\frac{\partial m}{\partial Y}+C_{{g},z}\frac{\partial m}{\partial Z}&=&0 . \ \ (A29)\end{eqnarray}
3 APPENDIX B -->
APPENDIX B
Andrews and McIntyre (1976, 1978) noted that the residual mean circulation has to satisfy the relationship between the Eulerian-mean flow and the Stokes drift. Kinoshita and Sato (2013a,b studied and demonstrated that their 3D residual mean circulation is the sum of the Eulerian-mean flow and the Stokes drift under different assumptions at large scales. In this section, considering disturbances with small amplitudes in the basic state, we demonstrate that the residual mean circulation satisfies the relationship between the Eulerian-mean flow and the Stokes drift under non-hydrostatic equilibrium in mesoscale systems. The Stokes drift describes the difference between the Lagrangian and Eulerian averages of flow fields: \begin{equation} \bar {u}_{\rm S}=\bar {u}_{\rm L}-\bar {u} , \ \ (B1)\end{equation} where $\bar{u}_L$ is the Lagrangian average and $\bar{u}$ is the Eulerian average. The generic expression for Stokes drift by Taylor-expansion is \begin{equation} \bar {u}_{\rm S}=\overline{\xi'u'_x}+\overline{\eta'v'_y}+\overline{\varsigma'u'_z}+o(a^2) , \ \ (B2)\end{equation} where $\xi'(x,y,z,t)$, η'(x,y,z,t) and ζ'(x,y,z,t) are the zonal, meridional and vertical displacement of the air parcel, respectively. Ignoring the third and higher order, the 3D Stokes drift can be written as \begin{eqnarray} \bar {u}_{\rm S}&=&(\overline{\xi'u'})_x+(\overline{\eta'u'})_y+(\overline{\zeta'u'})_z ,\ \ (B3)\\ \bar{v}_{\rm S}&=&(\overline{\xi'v'})_x+(\overline{\eta'v'})_y+(\overline{\zeta'v'})_z ,\ \ (B4)\\ \bar {w}_{\rm S}&=&(\overline{\xi'w'})_x+(\overline{\eta'w'})_y+(\overline{\zeta'w'})_z , \ \ (B5)\end{eqnarray} where $\xi'$, η' and ζ' satisfy the Lagrangian constraint relationships \begin{eqnarray} &&{\xi}'_x+{\eta}'_y+{\zeta}'_z=0 ,\ \ (B6)\\ &&\overline{{\xi}'}=\overline{{\eta}'}=\overline{{\zeta}'}=0 ,\ \ (B7)\\ &&\overline{D}{\xi}'={u}' ,\quad \overline{D}{\eta}'={v}' ,\quad \overline{D}{\zeta}'={w}' , \ \ (B8)\end{eqnarray} and \begin{equation} \overline{D}=\frac{\partial}{\partial t}+\bar {u}\frac{\partial}{\partial x}+ \bar {v}\frac{\partial}{\partial y}+\bar {w}\frac{\partial}{\partial z} \ \ (B9)\end{equation} Ignoring basic flow, Eq. (B8) is expressed as follows \begin{equation} \frac{\partial{\xi}'}{\partial t}={u}' ,\quad \frac{\partial{\eta}'}{\partial t}={v}' ,\quad \frac{\partial{\zeta}'}{\partial t}={w}' . \ \ (B10)\end{equation} It is assumed that the particle disturbance displacement has the form of a plane sinusoidal wave $(\xi',\eta',\zeta')=(\xi_0,\eta_0,\zeta_0)\rm e^i\phi$, which is substituted into Eq. (B10). The particle displacement amplitude is obtained as \begin{eqnarray} \xi_0&=&\frac{i}{\omega}u_0=i\frac{k\omega p_{{\rm 0r}}-lfp_{{\rm 0i}}}{\omega(\omega^2-f^2)\rho_0}-\frac{k\omega p_{{\rm 0i}}+lfp_{{\rm 0r}}}{\omega(\omega^2-f^2)\rho_0} ,\ \ (B11)\\ \eta_0&=&\frac{iv_0}{\omega}=i\frac{kfp_{{\rm 0i}}-l\omega p_{{\rm 0r}}}{\omega(\omega^2-f^2)\rho_0}-\frac{l\omega p_{{\rm 0i}}-kfp_{{\rm 0r}}}{\omega(\omega^2-f^2)\rho_0} ,\ \ (B12)\\ \zeta_0&=&\frac{iw_0}{\omega}=-i\frac{(k^2+l^2)\omega p_{0{\rm r}}}{\omega n(\omega^2-f^2)\rho_0}+\frac{(k^2+l^2)\omega p_{{\rm 0i}}}{\omega n(\omega^2-f^2)\rho_0} .\ \ (B13)\quad \end{eqnarray} By using the particle displacement amplitudes, Eqs. (B11)-(B13), and the disturbance amplitudes, Eqs. (25)-(27), along with the Reynolds average relationship, it can be proved that the products of $\overline{\xi'u'}$, $\overline{\eta'v'}$ and $\overline{\zeta'w'}$ are zero because two quantities of the respective products are out of phase by 90°: $\overline{\xi'u'}= (1/2)\rm R(\xi_0^\otimes u_0)=0$, $\overline{\eta'v'}=(1/2)\rm R(\eta_0^\otimes v_0)=0$, $\overline{\zeta'w'}=(1/2)\rm R(\zeta_0^\otimes w_0)=0$. From Eqs. (B3)-(B5), the 3D Stokes drift is obtained: \begin{eqnarray} \bar {u}_{\rm S}&=&(\overline{\eta'u'})_y+(\overline{\zeta'u'})_z ,\ \ (B14)\\ \bar {v}_{\rm S}&=&(\overline{\xi'v'})_x+(\overline{\zeta'v'})_z ,\ \ (B15)\\ \bar {w}_{\rm S}&=&(\overline{\xi'w'})_x+(\overline{\eta'w'})_y . \ \ (B16)\end{eqnarray} By using the particle displacement amplitudes, Eqs. (B11)-(B13) and the Reynolds average relationship, the following relation is obtained: \begin{eqnarray} \overline{\eta'u'}&=&\frac{f(k^2+l^2)}{(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B17)\\ \overline{\xi'v'}&=&-\frac{f(k^2+l^2)}{(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B18)\\ \overline{\varsigma'u'}&=&-\frac{lf(k^2+l^2)}{n(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B19)\\ \overline{\xi'w'}&=&\frac{lf(k^2+l^2)}{n(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B20)\\ \overline{\eta'w'}&=&-\frac{kf(k^2+l^2)}{n(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B21)\\ \overline{\varsigma'v'}&=&\frac{kf(k^2+l^2)}{n(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B22)\\ \overline{u'\frac{\theta'}{N^2}\frac{g}{\bar {\theta}}}&=&\frac{fl(k^2+l^2)}{n(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B23)\\ \overline{v'\frac{\theta'}{N^2}\frac{g}{\bar {\theta}}}&=&-\frac{kf(k^2+l^2)}{n(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} ,\ \ (B24)\\ \overline{S}&=&\frac{f^2(k^2+l^2)}{(f^2-\omega^2)^2}\frac{\overline{p'^2}}{\bar {\rho}^2} . \ \ (B25)\end{eqnarray} Substituting Eqs. (B17)-(B22) into the expression of Stokes drift, Eqs. (b14)-(b16), yields \begin{eqnarray} \bar {u}_{\rm S}&=&\frac{(\overline{S})_y}{f}-\left(\frac{\overline{u'\theta'}}{N^2}\frac{g}{\bar {\theta}}\right)_z ,\ \ (B26)\\ \bar {v}_{\rm S}&=&-\frac{(\overline{S})_x}{f}-\left(\frac{\overline{v'\theta'}}{N^2}\frac{g}{\bar {\theta}}\right)_z ,\ \ (B27)\\ \bar {w}_{\rm S}&=&\left(\frac{\overline{u'\theta'}}{N^2}\frac{g}{\bar {\theta}}\right)_x+\left(\frac{\overline{v'\theta'}}{N^2}\frac{g}{\bar {\theta}}\right)_y . \ \ (B28)\end{eqnarray} Comparing the expressions of Stokes drift, Eqs. (B26)-(B28), with the expressions of the residual mean circulation, Eqs. (12)-(14), the following relation is obtained: \begin{eqnarray} \overline{u^\ast}&=&\bar {u}+\bar {u}_{\rm S} ,\ \ (B29)\\ \overline{v^\ast}&=&\bar {v}+\bar {v}_{\rm S} ,\ \ (B30)\\ \overline{w^\ast}&=&\bar {w}+\bar {w}_{\rm S} . \ \ (B31)\end{eqnarray} Thus, it is verified that the obtained 3D residual mean circulation is equal to the sum of the Eulerian time-mean flow and the Stokes drift, which satisfies the relationship between the Stokes drift and the residual mean circulation. The TEM equations derived above under non-hydrostatic equilibrium are useful in examining how the generation and dissipation of atmospheric waves drives the mean circulation, and in exploring the energy propagation of inertia-gravity waves in mesoscale systems.
Ya-nan Deng, Hamdy Kashtoh, Quan Wang, Guang-xiao Zhen, Qi-yu Li, Ling-hui Tang,Hai-long Gao, Chun-rui Zhang, Li Qin, Min Su, Fei Li, Xia-he Huang, Yi ...