Characteristics of high-frequency gravity waves generated during pre-monsoon season over a tropical location: A case study

Journal of Atmospheric and Solar-Terrestrial Physics 186 (2019) 61–77

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Characteristics of high-frequency gravity waves generated during premonsoon season over a tropical location: A case study

T

Priyanka Ghosha,∗, Thokuluwa Krishnamurthy Ramkumarb, Viswanadhapalli Yesubabub, Som Sharmaa a b

Physical Research Laboratory, Ahmedabad, 380009, India National Atmospheric Research Laboratory, Gadanki, 517112, India

ARTICLE INFO

ABSTRACT

Keywords: Convection-generated gravity waves MST radar Mid-tropospheric moisture intrusion WRF model simulation

Mesoscale convection weather events, associated with deep cumulonimbus clouds transport moisture, energy and momentum to upper troposphere and lower stratosphere (UTLS), affect the energetics and general circulation of the middle atmosphere. Therefore, it is necessary to understand the atmospheric dynamics during pre–monsoon periods (when strong mesoscale convective events occur) for improving the parameterization of model physics. The present study attempts to investigate the characteristics of high-frequency gravity waves (GWs) generated over Gadanki (13.5° N, 79.2° E), India during one such severe convection event in the pre–monsoon period. For this purpose, the Mesosphere Stratosphere Troposphere (MST) radar at Gadanki was operated continuously for the period of ∼10 h during 27–28 May 2015. A wide spectrum of high frequency GWs with different generation mechanisms are found during this convective event whose vertical propagation characteristics fulfill the non-hydrostatic GWs dispersion relation. The temperature and wind data of ERA (ECMWF Re-Analysis)-interim reanalysis and GPS radiosonde, launched at Gadanki, are also analyzed for ten days around the event day to determine the background atmospheric thermodynamical conditions. Strong upand downdrafts are observed in the altitude range of ∼3.6–20 km (radar limited top height); presence of which even up to ∼20 km height is quite rare. The WRF (Weather Research and Forecasting) model simulated relative humidity on 27–28 May 2015 clearly depicts the mid-tropospheric moisture intrusion. Presence of moisture is also observed at the higher heights ∼17–18 km which could be due to strong low level convergence leading to high divergence value of deep cumulonimbus clouds in UTLS region. Furthermore, this is supported by the Doppler Weather Radar (DWR) and simulated reflectivity of WRF model reaching the tropopause height of ∼18 km. The altitude profiles of phase of some oscillations during convection period depict that the sources of these waves are near ∼20 km which is first of its kind outcome and it is corroborated with high resolution WRF model simulations.

1. Introduction For many decades, numerous studies have been continued for the prediction and better comprehension of the underlying physical mechanisms involved with Indian Summer Monsoon (ISM). The ISM contributes to approximately 80% of the annual rainfall over India (Panchawagh and Vaidya, 2011). Deep convective events occurring during pre-monsoon season are of significant importance as they give direct insight into rainfall patterns and wind velocity of forthcoming monsoon season (Romatschke et al., 2011). On the other hand, convection is one of the major causes of upward-propagating GWs in equatorial region which control the structure and circulation of the

∗

middle and upper atmospheres significantly (Alexander and Vincent, 2000; Dunkerton, 1997; Lindzen and Holton, 1968). Therefore, the characteristics of convective storms generated GWs during pre-monsoon season will be quite different than the storms formed during ISM period which could give a deeper insight into the mass and momentum fluxes transferred during the respective periods. Wave oscillations are generated depending on the intensity and forcing scale of the convective systems with different vertical and horizontal scales. Fritts and Alexander (2003) showed that the convection-generated GWs propagate in the vertical direction and affect the momentum budget of middle atmosphere. Many numerical modeling studies have been done to prove convection as major source of GWs (Alexander

Corresponding author E-mail address: [email protected] (P. Ghosh).

https://doi.org/10.1016/j.jastp.2019.01.018 Received 27 July 2018; Received in revised form 4 January 2019; Accepted 7 January 2019 Available online 23 February 2019 1364-6826/ © 2019 Elsevier Ltd. All rights reserved.

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et al., 1995; Clark et al., 1986; Fovell et al., 1992; Piani, and Durran, 2001). In addition, a non-linear advection and latent heat within a convective system act as primary forcing mechanism for convectively generated high-frequency GWs (Beres et al., 2004, 2002; Lane and Reeder, 2001; Song et al., 2003). Studies of convection generated GWs reveal that vertical profiles associated with them in winds resemble sine wave (positive half) (Bretherton, 1988; Mapes, 1993; Nicholls et al., 1991; Pandya and Alexander, 1999). These studies highlight that leading wave response occurs for the waves having tropospheric vertical wavelengths of about two times the depth of heating. Wavelength of these waves project on vertical heating profile mostly and does not depend on the heating shape (Salby and Garcia, 1987). Since the buoyancy or Brunt Väisälä frequency N is approximately double of its value in the stratosphere than in the troposphere and the vertical wavelength of GWs is inversely proportional to buoyancy or Brunt Väisälä frequency N, the vertical wavelength in stratosphere should be equal to the vertical depth of heating in the troposphere (Beres et al., 2002). Pandya and Alexander (1999) found that the wave amplitudes in a linear model forced by heating only are larger than the ones in nonlinear model whereas the spectral properties like horizontal and vertical wavelengths, frequencies and phase speeds are nearly same in both cases. The observations from Microwave Limb Sounder (MLS) on board Upper Atmosphere Research Satellite (UARS) showed the presence of strong GW variance (in stratospheric region) above thunderstorm with wavelengths in the vertical direction larger than 20 km (Alexander, 1998; McLandress et al., 2000). The high-frequency GWs having wavelengths (in the vertical direction) of 10–30 km contribute significantly to the GW momentum flux in mesosphere (Fritts and Alexander, 2003; Fritts and Vincent, 1987). Many studies (Kirkwood et al., 2010; Valkonen et al., 2010) available in literature report better presentation of Weather Research and Forecasting (WRF) model in capturing the GWs. A study by Zhang et al. (2012) shows that deep convection is one of the most significant GW sources in the stratosphere besides topography. A minimum vertical resolution higher than 1 km along with an adequately high model top (near 1 Pa) is needed to reliably resolve GW activity throughout the middle atmosphere (Alexander et al., 2010). Recently, Ghosh et al. (2016) found that the cloud resolving simulations of WRF are capable to capturing the high-frequency convectively generated GWs during a thunderstorm event. Costantino et al. (2015) simulated WRF idealized experiments [simplified framework with flat orography, constant wind shear) that allows higher model top and higher horizontal (1 km) and vertical grid spacing (less than 1 km below 60 km of altitude)] and WRF real experiments [horizontal resolution of 3 km and a vertical one of less than 1 km below 50 km]. They established that deep convection is a very efficient source of small-scale GWs that propagate from the tropopause up to 60 km. The energy and horizontal momentum fluxes are transported from below to the high stratosphere and lower mesosphere. The purpose of the present work is to study the features of vertically propagating convection-generated GWs during the pre-monsoon period of 27–28 May 2015 by making use of the observations from Mesosphere-Stratosphere-Troposphere (MST) radar, and GPS radiosonde along with the high resolution simulations of WRF. The structure of this study is organized as following where section 2 presents a brief history synoptic meteorological conditions present on 27th May 2015. Section 3 describes the observational data used in the analysis, the model domain and physics configuration employed to generate high resolution model simulation followed by the validation of model with available observations of DWR and gridded rainfall from India Meteorological Department (IMD). Section 4 consists of results and discussions and section 5 highlights the summary and conclusions.

conditions prevailed at many places in coastal Andhra Pradesh. The Southwest Monsoon has advanced into southern parts of south Arabian Sea and Maldives-Comorin areas and some more parts of southwest Bay of Bengal. The western disturbance and cyclonic circulation lies over central Pakistan and adjoining western Rajasthan extending up to 1.5 km Above Sea Level (ASL). The presence of trough extending between 1.5 and 2.1 km ASL from coastal Odisha to Southern Andhra Pradesh is reported in IDWR records. 3. Data analysis and model configuration The MST radar at Gadanki (13.5° N, 79.2° E), India is a highly sensitive, pulse-coded VHF phased array radar (1024 three element Yagi antennas covering an area of 130 m × 130 m) operating at 53 MHz with peak power-aperture product of 3 × 1010 Wm2. Backscattered signals with good signal to noise ratio (SNR) are obtained in the vertical direction (150 m altitude resolution) in the altitude range of 3.75–20 km. More specifications of this radar are given in Rao et al. (1995). In the present study, horizontal and vertical wind velocities are determined with MST radar observations at Gadanki on a thunderstorm day of 27–28 May 2015. The radar is operated continuously from 14:18 UTC (27 May 2015) to 00:30 UTC (28 May 2015) for about ∼10 h in eight-beam mode. The radar beam is titled 10° in the directions of east, west, north and south alongside with two beams in the zenith direction through two orthogonal polarizations, Zx (east-west) and Zy (northsouth). For one scan cycle, the Zx and Zy beams are alternated with the 10-degree tilted beams in the order of East 10 deg., Zx, West 10 deg., Zy, North 10 deg., Zx, South 10 Deg. and Zy. The coded pulse length of the transmitting beam is 16 μs (microsecond) with 1 μs baud length, corresponding to an altitude resolution of 150 m, and the length of the inter-pulse period is 1000 μs Successive 64 pulses are coherently added to get one data point and 512 successive such data points are applied to obtain the power spectra of Doppler [Fast Fourier Transform (FFT)] of the received echoes for each of six beams. Through this set-up, one altitude profile of wind velocities in the horizontal direction is achieved for each 283.32 s and wind velocity in the vertical direction for each 70.92 s as the alternate beams are pointed in the zenith direction. To determine the characteristics of convection generated GWs, the time series of consequent wind velocities are further examined. Height profiles of horizontal wind velocities present in the backdrop (for 10 days with the convective event day in the middle) and temperature during the thunderstorm period, in the present work, ERA-Interim reanalysis data are utilized (Dee et al., 2011). The advanced research version 3.9.1 of Weather Research and Forecasting (WRF) model (Skamarock et al., 2008) is used in the present study. The model was configured with three two-way interactive nested domains [Fig. 1] with the horizontal resolution of 18-km (370 × 308 grids), 6-km (616 × 493 grids) and 2 km (427 × 427 grids) with 60 vertical levels and the model top fixed at 1 hPa. The physics options used in the model include the microphysics scheme (Thompson et al., 2004), Rapid Radiation Transfer Model (RRTMG) for long and short wave radiation scheme (Mlawer et al., 1997), Mellor–Yamada–Nakanishi–Niino (MYNN) non-local scheme for planetary boundary layer (PBL) turbulence (Hong et al., 2006), the Noah scheme for the land surface processes (Chen and Dudhia, 2001) and Kain-Fritisch mass-flux scheme (Kain and Fritsch, 1993) for cumulus convection for the first and second domains, no cumulus scheme is used in the model third domain (2-km). The model physics options are chosen based on the previous studies on simulation of convective over the southern India (Ghosh et al., 2016; Reshmi Mohan et al., 2018; Srinivas et al., 2018, 2013; Yesubabu et al., 2014). The topographic information such as terrain, land use and land cover, and soil types are interpolated from the USGS arc data having resolution of 5 min, 2 min and 30 s for the first, second and third domain of the model, respectively. The model is initialized at 00:00 UTC 27 May 2015 and integrated for 24 h up to 00:00 UTC 28 May 2015 using the 0.75° x 0.75° ECMWF ERA-Interim

2. Synoptic meteorological conditions for the thunderstorm on 27th May 2015 As per the IMD daily weather reports (IDWR), severe heat wave 62

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Fig. 1. WRF model set-up with three domains (resolutions 18, 6 and 2 km) with Gadanki as center.

data and the boundary conditions are updated at 6-h interval. To extract the GW parameters, the perturbation components are calculated from the simulated outputs of calm background model atmosphere. Since we have considered one normal weather day (non-convection day) prior to thunderstorm formation as background, the model is initialized at 00:00 UTC on 03 May 2015 using ECMWF data and it is integrated up to 00:00 UTC on 04 May 2015. GPS radiosonde (launched at NARL, Gadanki) temperature measurements at 09:00 UTC on 27 May 2015 is used to find the cold point tropopause height. GPS radiosonde and ERA-Interim wind measurements are compared to find the background atmospheric condition prevailing during that period. To compare the WRF simulations with the observations latitude vs. longitude contour plots [Fig. 2 (a, b, c)] of (a) India Meteorological Department (IMD) gridded (0.25° × 0.25°) rainfall, (b) Climate Prediction Center (CPC) MORPHing technique (CMORPH) V1 rainfall estimates, (c) the WRF model simulated rainfall (convection parameterization excluded) on 27–28 May 2015 are plotted. Although the IMD gridded rainfall [Fig. 2 (a)] is unable to capture the thunderstorm passage due to coarse resolution of rain

gauges over south east coast, but the CMORPH rainfall estimates [Fig. 2 (b)] and the WRF model simulation [Fig. 2 (c)] captured the passage of a series of thunderstorms, originated in the Indian Ocean, advancing from the south-east direction. Though there are some spatial discrepancies in the simulated rainfall compared to satellite and rain gauge merged product of CMORPH, the hourly rainfall simulated by WRF model matches well with hourly accumulated rainfall of automated weather station (AWS) over Gadanki (Fig. 3). Convection parameterization scheme is used for the two outer domains (Kain, 2004) and for the high-resolution domain (innermost, 2 km), no cumulus scheme is configured. Since the mesoscale instability structure is clearly depicted in the initial model conditions (ERA-Interim Data), no additional assimilations procedures are applied to the model simulations as it could easily capture the observed convection pattern over Gadanki (Ghosh et al., 2016). 4. Results and discussion The time-height section of vertical, meridional and zonal winds and

Fig. 2. Spatial distribution of rainfall (mm day−1 on 27 May 2015) from (a) IMD gridded (0.25° × 0.25°) rainfall, (b) CMORPH V1 rainfall estimates, (c) the WRF model simulated rainfall (convection parameterization excluded). 63

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Fig. 3. Time variation (in UTC) of (a) surface temperature, (b) relative humidity, (c) wind speed, (d) wind direction and (e) accumulated rainfall as observed by an automated weather station (AWS) and simulated by WRF model without convection parameterization.

Fig. 4. Time vs. height (3.6–20 km) contour plots of (a) vertical, (c) meridional and (e) zonal wind velocities (m/s) measured by the MST radar during the period of 14:18–00:30 UTC on 27–28 May 2015 (Left panel). The corresponding vertical shear ((m s−1)/150 m) of them are shown respectively in (b), (d) and (f) (Right panel).

their corresponding vertical shear are shown in Fig. 4. The vertical velocities exhibit strong updrafts and downdrafts ( ± 1 m/s) from the lower heights of 3.6 km to the higher heights of 20 km for nearly 1 h from 14:18–15:30 UTC on 27 May 2015 and also similar velocity pattern is observed during 21:30–00:30 UTC after a normal period

(19:30–21:30 UTC on 28 May 2015) indicating the passage of second cluster clouds of the thunderstorm. From 15:30 UTC on 27 May 2015 to 19:30 UTC on 28 May 2015, the updrafts and downdrafts continue in the height range of ∼7–20 km. An interesting feature is that continuous strong downdraft of ∼1 m/s is observed during 16:00–17:00 UTC at the 64

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Fig. 5. WRF simulated time vs. height (40 m-40 km) contour plots of (a) vertical, (b) meridional, (c) zonal wind velocities in (m/s) (Left panel) and corresponding (d) temperature (ºC), (e) reflectivity (dBz) and (f) relative humidity (%) (Right panel) on 27–28 May 2015.

height region of ∼7–10 km. Generally, the tropopause at ∼18 km over Gadanki (Ghosh et al., 2016) acts as a lid to the convective tower, but in this case the vertical wind velocity indicates the presence of overshooting cloud top (reaching the height of ∼20 km) in these two thunderstorm events. The presence of shear layers [Fig. 4 (b, d, f)] is

detected in zonal and meridional wind velocities (of the magnitude ± 0.005) throughout the height region with enhancement in the height range of ∼12–20 km. Vertical shear (i.e. the change of winds with height) acts as one of the critical factors controlling the occurrence of thunderstorms and its potential severity. Strong vertical shears often 65

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Fig. 6. (a–l). Contour plots of Morlet wavelet power spectrum of vertical wind velocity on 27–28 May 2015.

strength of thunderstorm during pre-monsoon in a positive manner. The relative humidity of 50–60% is noticed even at the height of ∼18 km during 12:00–16:00 UTC which could be due to the formulation of deep convective system which pumps moisture in the UTLS region. The time series of Morlet wavelet power spectrum (Torrence and Compo, 1998) of vertical wind velocity on 27–28 May 2015 for the heights of 4, 7, 9, 11, 13, 15, 16, 16.5, 17, 18, 19 and 20 km respectively shown in Fig. 6 (a–i). The signals inside thick magenta-colored contours are considered to be statistically significant with 95% confidence level. The cone of influence (COI) is shown as red-colored dashed lines (thick). The signals outside the COI are regarded as ambiguous and are not considered for any type of interpretations. Significant oscillations are observed from 14:18 UTC on 27 May 2015 to 00:30 UTC on 28 May 2015 (i.e. at the time of first thunderstorm) with periodicities of ∼15–103 min in almost all the heights varying intermittently with height and time. The wave activities are comparatively less during the normal period (19:30–21:30 UTC) between the two thunderstorm events. Enhancements of oscillations are observed again during 21:30–00:30 UTC on 27–28 May 2015 (i.e. during the passage of the second thunderstorm). The wavelet analysis clearly illustrates that the intensity of wave activities during the first thunderstorm is much higher than the second one with enhancement in the height range of 13–17 km. Significant oscillations are also perceived near the tropopause height of 18 km. GWs with the observed periodic oscillations are regarded to be produced from convection as the wave oscillations befalling time matches with the timing of the thunderstorm event. Similar significant wave oscillations are also detected in the Morlet wavelet power spectrum of zonal (not shown) and meridional (not shown) winds on 27–28 May 2015. The MST radar observed wind (zonal, meridional and vertical) velocities are subjected to detailed power spectral analyses using Fast Fourier transform (FFT) analysis to determine the high-frequency convectively generated GW oscillations (which are above 95% confidence level) during 14:18–19:30 UTC (27 May 2015), 19:30–21:30 UTC (27 May 2015) and 21:30–00:30 UTC on 27–28 May 2015. The oscillations above 95% confidence level in all the wind velocity profiles are considered as the dominant oscillations during that particular period and the height profile of amplitude and phase are plotted accordingly. The

blow the updraft away from the base of the storms and destroy them except for the very strong ones. The simulated vertical, zonal and meridional wind velocities [Fig. 5 (a, b, c)] show a strong correlation with the MST radar derived wind velocities especially in the vertical wind depicting strong updrafts and downdrafts from the lower heights to ∼26 km. In the WRF model, although oscillating vertical wind velocities are present up to ∼40 km, the strength of which decreases gradually from 28 to 40 km. Moreover, there is a mismatch between the observations by MST radar and WRF model in the time of thunderstorm event [13:00 UTC in the WRF simulation and 14:18–15:30 UTC in the MST radar observations] as WRF model has a tendency to simulate the initiation of convection earlier than the observation period. This could be attributed to the tendency of mesoscale model in the early initiation of convection characteristics as reported by Duda (2011). The WRF simulated temperature [Fig. 5 (d)] shows the presence of cold-point tropopause (i.e. the minimum temperature) in the height region of ∼17–18 km. The most striking feature is that the cold-point tropopause shows an anomalous increase of temperature during ∼13:00–17:00 UTC, indicating sudden heating of the atmosphere. Presence of a deep convective tower reaching the height of ∼18 km during 12:00–14:00 UTC is observed in the simulated reflectivity of WRF [Fig. 5 (e)] during 12:00–15:30 UTC. Gettelman et al. (2002) suggested that either convection acts to cool the tropopause or a colder tropopause may reduce the stability of the upper troposphere raising the level of neutral buoyancy of convection. The latent heat release from the deep convective tower at the height of ∼18 km can be one possible reason for the anomalous increase in temperature near the cold-point tropopause height. The presence of a second cluster of cloud is observed in the WRF simulated reflectivity [Fig. 5 (e)] at 21:00 UTC which corresponds to the second thunderstorm event during 21:30–00:30 UTC [Fig. 4]. The WRF simulated relative humidity [Fig. 5 (f)] depicts a rare mid-tropospheric moisture intrusion at the height levels of ∼2–4 km and ∼8–12 km during 00:00–09:00 UTC and it covers the whole height region of ∼2–13 km during 09:00–00:00 UTC indicating the presence of strong convective event. This kind of mid-tropospheric moisture intrusion is quite rare and unique as it is not observed in case of thunderstorm events during monsoon. This can be one of the plausible reasons which can affect the 66

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Fig. 7. Height (3.6–20 km) profiles of amplitude (m s−1) and phase (minutes) (during 14:18–19:30 UTC on 27 May 2015) of ∼28-, ∼31-, ∼44-, ∼62- and ∼103min oscillations in zonal, meridional and vertical wind velocities.

observation period is divided into three different parts: i) 14:18–19:30 UTC (first thunderstorm period), ii) 19:30–21:30 UTC (normal period in between two thunderstorms), iii) 21:30–00:30 UTC (second thunderstorm period) to ascertain the source of the convective GWs generated during particular period. It is well-known that the mechanism for

generation of GWs during convection can be classified as: (1) pure thermal forcing (where the latent heat release within the convective cloud acts as the primary GW forcing mechanism), (2) “obstacle” or “transient mountain” effect (the convective cloud behaves analogous to topography creating GWs), and (3) “mechanical oscillator” effect 67

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Fig. 8. Height (3.6–20 km) profiles of horizontal wavelength (natural logarithm), horizontal group velocity (m s−1) and vertical group velocity (m s−1) (during 14:18–19:30 UTC on 27 May 2015) of ∼28-, ∼31-, ∼44-, ∼62- and ∼103-min oscillations. Table 1 Vertical Wavelength (in km) during 14:18–00:30 UTC on 27–28 May 2015. (a) During 14:18–19:30 UTC on 27 May 2015 Height Range (km)

∼28 min Oscillation

∼31 min Oscillation

∼44 min Oscillation

∼62 min Oscillation

∼103 min Oscillation

3.6–17 (Troposphere) 17-20 (Stratosphere)

∼3.66 ∼1.83

∼6.03 ∼2.64

∼6.73 ∼10.89

∼12.85 ∼1.12

∼8.39 ∼2.04

(b) During 19:30–21:30 UTC on 27 May 2015 Height Range (km)

∼30 min Oscillation

∼40 min Oscillation

∼120 min Oscillation

3.6–17 (Troposphere) 17-20 (Stratosphere)

∼8.12 ∼3.25

∼12.62 ∼6.96

∼6.30 ∼5.82

(c) During 21:30–00:30 UTC on 27–28 May 2015 Height Range (km)

∼15 min Oscillation

∼29 min Oscillation

∼44 min Oscillation

∼59 min Oscillation

∼88 min Oscillation

3.6–17 (Troposphere) 17-20 (Stratosphere)

∼3.35 ∼10.55

∼2.08 ∼10.68

∼45.33 ∼11.39

∼32.03 ∼14.14

∼8.73 ∼101.58

The height (3.6–20 km) profiles shown Fig. 7 of amplitude (m s−1) and phase (in minutes, during 14:18–19:30 UTC on 27 May 2015) of ∼28-, ∼31-, ∼44-, ∼62- and ∼103-min oscillations in vertical, zonal and meridional wind velocities. In case of all the oscillations, the height profile of amplitude in zonal, meridional and vertical wind velocities show oscillating nature with a steady increase in amplitude from the lower to the higher heights of the atmosphere. In the heights of ∼16–19 km, the amplitude of all the oscillations decreases with height and matches with the occurrence of shear layers in the vertical shear of zonal and meridional wind velocities [Fig. 4]. Phase propagation in the upward/downward direction indicates energy proliferation in the downward/upward direction and the source is situated above/below that altitude. The height profile of the phase of vertical wind velocity

(updrafts and downdrafts associated with convective storm produces GWs) (Fritts and Alexander, 2003). While the vertical scale of the convective heating governs the wavelength in vertical direction of the generated GWs, the occurrence of the updrafts and downdrafts regulate the frequency of the GWs during that time (Alexander et al., 1995; Pandya and Alexander, 1999). It can be concluded that when the vertical wavelength is double in troposphere than in stratosphere, the GWs are generated by latent heat release within the convective storm. In case of mechanical oscillator effect, strong updrafts and downdrafts occur which is observed in the vertical wind velocities (with no probable double in vertical wavelength). For obstacle effect, continuous downdraft is observed at the base of stable layer (mainly near to tropopause) which acts as an obstacle to the wind flow (Ghosh et al., 2016). 68

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Fig. 9. Height (3.6–20 km) profiles of amplitude (m s−1) and phase (minutes) (during 19:30–21:30 UTC on 27 May 2015) of ∼30-, ∼40- and ∼120-min oscillations in zonal, meridional and vertical wind velocities.

for ∼28- and ∼31-min oscillation, shows downward phase propagation at the heights of 12–18 km (indicating some kind of source located below 12 km) with a drastic shift at the heights of 10–12 km (which is created by adding the period of the wave for plotting conveniences). The ∼28- and ∼31-min oscillation in the meridional and zonal wind velocities suggests that mechanical oscillator mechanism may be one of the sources of these GWs generated during deep convection. The phase profile of the ∼44 min oscillation shows upward phase propagation above ∼18 km and downward phase propagation in the heights of ∼14–18 km, in the vertical wind velocity. A sudden phase shift is observed in the altitude region of ∼10–12 km and ∼5–8 km (for plotting conveniences). For both ∼62 min and ∼103 min oscillations in the vertical velocity, the phase increases with height at ∼10–19 km but with a sudden shift at ∼13–14 km (due to 2-pi phase shift for plotting accessibilities) for the ∼103 min oscillation. Since the vertical wind velocity [Fig. 4 (a)] shows updrafts and downdrafts in the whole height region of ∼3.6–20 km, the source of the all these oscillations generated during this period can be linked with the mechanical oscillator mechanism. Moreover, the oscillating nature of the phase profile of the zonal and meridional wind velocities of all these oscillations strengthens further this mechanical oscillator mechanism. Using the polarization relation given in Alexander and Holton

(1997), the horizontal wavelength is derived as:

m ˆ w k

û=

(1)

where the corresponding horizontal and vertical wavenumbers are denoted as k and m. Perturbation velocities (zonal and vertical winds), linked with a particular frequency of GWs, are denoted as û and ŵ. Values of u and w are determined from Fourier transform analyses of the Indian MST radar wind velocities. The value of m is determined by noting the phase change (vertical rate) in different height regions. For this analysis, only the areas where phase vary almost linearly with height and smoothly are considered. The principal dispersion relation for the high-frequency GWs (non-hydrostatic e.g. convection) is given by (Alexander and Holton, 1997) as:

{

kU N

}

2

= k 2 + (k 2 + m2 )

(2)

Thus, the zonal and vertical components of the group velocity are:

(Cgx , Cgz ) =

69

k

,

z

=

(m ,

k ) Nm 3

(k2 + m2 ) 2

(3)

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Fig. 10. Height (3.6–20 km) profiles of horizontal wavelength (natural logarithm), horizontal group velocity (m s−1) and vertical group velocity (m s−1) (during 19:30–21:30 UTC on 27 May 2015) of ∼30-, ∼40- and ∼120-min oscillations.

where N is the Brunt-Väisälä (BV) frequency, ω is the observed frequency of waves, U is the background horizontal wind velocity. The horizontal and vertical wave numbers are given as k and m. The height profile (3.6–20 km) of natural logarithm of horizontal wavelength, group velocities (m s−1) in the horizontal and vertical direction (during 14:18–19:30 UTC on 27 May 2015) of the ∼28, ∼31-, ∼44-, ∼62- and ∼103-min oscillations [Fig. 8] shows that horizontal wavelength increases with period of oscillation. The horizontal wavelength is in the range of ∼0–100 km for ∼28 min and ∼44 min oscillation, ∼0–50 km for ∼31 min oscillation, ∼0–330 km for ∼62 min oscillation and ∼0–600 km for ∼103 min oscillation. The horizontal group velocity is in the range of ∼0–7.5 m/s for ∼28 min and ∼31 min oscillation, ∼0–30 m/s for ∼44 min oscillation, ∼0–4 m/s for ∼62 min oscillation and ∼0–12 m/s for ∼103 min oscillation. The vertical group velocity is in the range of ∼0–2 m/s for ∼28 min and ∼62 min oscillation, ∼0–3 m/s for ∼31 min and ∼103 min oscillation, and ∼0–13 m/s for ∼44 min oscillation. An interesting feature is that large horizontal and vertical group velocities are observed for the ∼44 min oscillation whereas the other oscillations have lesser range of values. Table 1 (a) shows the vertical wavelength of ∼28-, ∼31-, ∼44-, ∼62- and ∼103-min oscillations during 14:18–19:30 UTC on 27 May 2015. The vertical wavelength of the ∼28 min and ∼31 min oscillation is double in the troposphere than in the stratosphere. As the BV frequency gets doubled in the stratosphere, the observation of reduced (half) vertical wavelengths in the stratosphere matches with the GWs theory produced by latent heating (Alexander et al., 1995). Thus, it can be said that the ∼28 min and ∼31 min oscillations are considered to be generated from the latent heating during the thunderstorm period and the ∼44-min, ∼62-min and ∼103-min oscillations are considered to be generated from the mechanical oscillator mechanism. The amplitude (m s−1) and phase (minutes starting from 19:30–21:30 UTC on 27 May 2015) profiles, with respect to height (3.6–20 km), of ∼30-, ∼40- and ∼120-min oscillations in the wind

velocities (vertical, zonal and meridional) are shown in Fig. 9. The height profiles of amplitude of ∼30-, ∼40- and ∼120-min oscillations show similar oscillating nature as observed in the case of Fig. 7. The height profile of phase of the ∼30 min oscillation (vertical velocity) shows that source of it is located near ∼15 km and ∼19 km. The vertical velocity phase profile displays mostly standing nature for the ∼40 min oscillation with sudden jerks at ∼13–14 km, ∼10 km and ∼8 km (indicating 2-pi phase shifts manually inserted for plotting accessibility). The height profile of the phase for the ∼120 min oscillation in the vertical velocity shows an increase in phase with height (3.6–20 km) with sudden jerks at the altitudes of ∼4–5 km and ∼13 km (corresponding to phase shift for plotting conveniences). The phase profile of the zonal and meridional wind velocities depicts oscillating nature with height for all the three oscillations. The height (3.6–20 km) profiles of natural logarithm of horizontal wavelength, group velocities (m s−1) in the horizontal and vertical direction (19:30–21:30 UTC on 27 May 2015) of ∼30-, ∼40- and ∼120-min oscillations are shown in Fig. 10. The horizontal wavelength ranges ∼0–150 km for the ∼30 min and ∼120 min oscillation and ∼0–400 km for the ∼40 min oscillation. The horizontal group velocity ranges ∼0–12.5 m/s for the ∼30 min oscillation, ∼0–21 m/s for the ∼40 min oscillation and ∼0–18 km for the ∼120 min oscillation. The vertical group velocity ranges ∼0–3 m/s for the ∼30 min oscillation, ∼0–9.5 m/s for the ∼40 min oscillation and ∼0–6 m/s for the ∼120 min oscillation. Although the horizontal group velocity value of the ∼40 min oscillation is nearly comparable with those of ∼30 min and ∼120 min oscillations, the magnitude of horizontal wavelength and vertical group velocity is much larger than those of ∼30 min and ∼40 min oscillations. This is similar to that of the observation in the case of ∼44 min oscillation (Fig. 8). The vertical wavelength of the oscillations observed during 19:30–21:30 UTC on 27 May 2015 is given in Table 1 (b). The vertical wavelength of ∼30 min and ∼40 min oscillation is nearly double in the troposphere than in the stratosphere which directs that latent heating would be the probable source 70

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Fig. 11. Height (3.6–20 km) profiles of amplitude (m s−1) and phase (minutes) (during 21:30–00:30 UTC on 27–28 May 2015) of ∼15-, ∼29-, ∼44-, ∼58- and ∼88-min oscillations in zonal, meridional and vertical wind velocities.

mechanism for these oscillations. The ∼120 min oscillation would be linked with mechanical oscillator mechanism started during the passage of the first thunderstorm event. The amplitude (m s−1) and phase (minutes starting from 21:30–00:30 UTC on 27–28 May 2015) profiles with respect to altitude

(3.6–20 km) of ∼15-, ∼29-, ∼44-, ∼58- and ∼88-min oscillations in the wind velocities presented in Fig. 11. Since the second thunderstorm was passing over Gadanki during this period, the profiles of phase and amplitude (with respect to height) show similar oscillating nature as observed in Fig. 7. The height profile of phase of the ∼15 min 71

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Fig. 12. Height (3.6–20 km) profiles of horizontal wavelength (natural logarithm), horizontal group velocity (m s−1) and vertical group velocity (m s−1) (during 21:30–00:30 UTC on 27–28 May 2015) of ∼15-, ∼29-, ∼44, ∼59- and ∼88-min oscillations.

Fig. 13. Comparison of WRF simulated reflectivity (dBZ) with the corresponding reflectivity obtained from Doppler Weather Radar (DWR) Chennai at 10:20 UTC on 27 May 2015.

oscillation in vertical wind velocity displays phase propagation (in the upward direction) at altitudes of ∼12–19 km indicating some kind of source is located above that height region. According to the mechanical oscillator effect theory (Fovell et al., 1992), the updrafts and downdrafts are observed propagating up to the tropopause (i.e. the base of a stable layer). In the present study, the oscillating updrafts and downdrafts are observed from the lower height of 3.6 km up to the higher height of 20 km, which indicates that the deep convective cloud

reached up to the lower stratospheric heights justifying the presence of source above 20 km. The disturbed atmospheric condition is depicted clearly in the phase profile of all the observed oscillations. The height (3.6–20 km) profiles of natural logarithm of horizontal wavelength, group velocities (m s−1) in the horizontal and vertical direction (21:30–00:30 UTC on 27–28 May 2015) of ∼15-, ∼29-, ∼44-, ∼59- and ∼88-min oscillations are shown in Fig. 12. The horizontal wavelength ranges ∼0–175 km for the ∼15 min oscillation, 72

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Fig. 14. Height (1–21 km) profiles of (a) GPS radiosonde measured atmospheric temperature (ºC) at 09:00 UTC on 27 May 2015 over Gadanki (13.5° N, 79.2° E), (b) ERA-Interim reanalysis data based Brunt–Väisälä (BV) period (min) (12:00 UTC), (c) BV frequency (rad s−1) (12:00 UTC), (d) Height profiles (1–23 km) background (10-day mean of 12:00 UTC data during 22–31 May 2015) of zonal wind U, and (e) meridional wind V velocities determined by GPS radiosonde and ERA-Interim data.

s−1) (12:00 UTC), (d) Height profiles (1–23 km) background (10-day mean of 12:00 UTC data during 22–31 May 2015) of zonal wind U and (e) meridional wind V velocities calculated from GPS radiosonde and ERA-Interim data. To get the background wind condition over Gadanki during the occurrence of the thunderstorm, height profile of mean zonal and meridional winds (GPS radiosonde and ERA-Interim, averaged for a span of 10 days at 12:00 UTC during 22–31 May 2015) is plotted in Fig. 14 (d, e). The standard errors calculated for 10 days are represented by the horizontal lines present at each of the heights of the mean wind [Fig. 14 (d, e)]. The temperature data acquired from ERAInterim reanalysis (http://apps.ecmwf.int/datasets/data/interim-fulldaily/levtype=pl/) is used for determination of BV frequency as convection was going on at this time, which could give ambiguous temperature information [Fig. 14 (b, c)]. To determine the BV frequency, the formula given by Revathy et al. (1996) is used:

∼0–100 km for the ∼29 min oscillation, ∼0–420 km for the ∼44 min oscillation, ∼0–800 km for the ∼59 min oscillation and ∼0–600 km for the ∼88 min oscillation. The vertical and horizontal group velocities range ∼0–15 m/s, ∼0–10 m/s, ∼0–20 m/s, ∼0–15 m/s, ∼0–65 m/s and ∼0–18 m/s, ∼0–30 m/s, ∼0–40 m/s, ∼0–45 m/s, ∼0–50 m/s respectively for these above-mentioned oscillations. The horizontal wavelength and group velocities (horizontal and vertical) of these oscillations increase with period of oscillation (Ghosh et al., 2016). This observation is quite different between the events occurred during 14:18–19:30 UTC and 19:30–21:30 UTC in the present study (i.e. during the thunderstorms). The vertical wavelength of the oscillations observed during 21:30–00:30 UTC on 27–28 May 2015 is given in Table 1 (c). The mechanical oscillator mechanism can be the probable source of these oscillations since the latent heating and the obstacle effects do not fit in the present scenario described above. In support of the argument that the mechanical oscillator mechanism dominates over the other two mechanisms (latent heating and obstacle or transient mountain effect) for the convection generated GWs, a comparison of the simulated reflectivity obtained from WRF and corresponding picture of Doppler Weather Radar (DWR) at 10:20 UTC 27 May 2015 is plotted (Fig. 13). It is observed that the WRF simulation is able to capture the updrafts and downdrafts inside the thundercloud which is reaching even up to the height of ∼12–13 km whereas the DWR observation shows the cloud to reach the height of ∼18 km (tropopause height over Gadanki). Fig. 14 includes the altitude (1–21 km) profiles of (a) GPS radiosonde measured atmospheric temperature (ºC) at 09:00 UTC on 27 May 2015 over Gadanki (13.5° N, 79.2° E), (b) ERA-Interim reanalysis data based Brunt-Väisälä period (min) (12:00 UTC), (c) BV frequency (rad

N2 =

g T

dT + dz

(4)

where the BV frequency in radians per second is s N, acceleration due to gravity is g (9.8 m s−2), temperature (ºC) as T, height is z and dry adiabatic lapse rate is ϒ (10 °C km−1). The atmospheric temperature data from ERA-Interim (Dee et al., 2011), at mentioned pressure levels, are employed where the pressure levels are altered into altitude levels (using hydrostatic relation),

Height z (km) = H × log

po p

(5)

where the scale height of atmosphere (8 km) is denoted as H, pressure level at surface (1000 hPa) as po and pressure (hPa) as p (matching to 73

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data (where the negative sign indicates a change in wind direction) whereas it is ∼6 to ∼ −25 m/s for the ERA-Interim data. The mean meridional wind ranges ∼ −8 to ∼10 m/s for the GPS radiosonde data and ∼ −7 to ∼6 m/s for the ERA-Interim data. The time-height profiles (40 m-40 km) of WRF model simulated (a) mean temperature (ºC), (b) mean zonal wind U (m/s), and (c) mean meridional wind V velocities (m/s) is shown in Fig. 15. Perturbations are clearly observed in temperature, mean zonal and meridional winds (WRF simulation) from the lower height of ∼40 m up to the higher height of ∼40 km. It is noticed that the GWs generated from the updrafts and downdrafts associated with convection propagate through the tropopause and reach the stratospheric heights. This suggests that the strength of the thunderstorms generated during pre-monsoon period is larger than those generated during the monsoon. Our results are in agreement with Ghosh et al. (2016) who studied thunderstorm event during monsoon. Fig. 16 shows the time vs. height plot of signal-to-noise ratio (SNR in dB) of received echoes by Indian MST radar for the east, zenith Y, north beams [Left Panel, (a, c, e)] and west, zenith X and south beams [Right Panel, (b, d, f)] during 14:18–00:30 UTC on 27–28 May 2015. The presence of enhanced echoes (denoting distinct layers) is clearly observed at the height of ∼18–19 km in the zenith X (Zx) and zenith Y (Zy) beams, which indicates the tropopause height. Tilted layers of enhanced echoes are observed in the height range of ∼11–16 km in both the Zx and Zy beams, which indicates that a portion of the spectrum of GWs propagating upward gets dissipated in this height region. Fig. 17 shows the spectral width (in Hz) corresponding to Fig. 16. It is observed clearly that the spectral width shows enhancement up to the height of ∼10 km during the above-mentioned thunderstorm periods of 14:18–19:30 UTC and 21:30–00:30 UTC. 5. Summary and conclusions In the present work, the characteristics of convectively generated high-frequency GWs from deep convection during the pre-monsoon period of 27–28 May 2015 is investigated for the first time. We used Indian MST radar (which is continuously operated for more than 10 h, during 14:18–00:30 UTC) and GPS radiosonde observations (launched at 09:00 UTC from Gadanki) and the findings are compared with WRF model simulations. For the background wind and temperature information during thunderstorm event, ERA-Interim reanalysis are used. During the observation period, two thunderstorms passed over Gadanki (13.5° N, 79.2° E) at 14:18–19:30 UTC and 21:30–00:30 UTC. Strong updrafts and downdrafts are observed from the lower height of 3.6 km up to 20 km passing through the tropopause. During 14:18–19:30 UTC, the GWs with periodicities of ∼28 min, ∼31 min, ∼44 min, ∼62 min and ∼103 min are generated out of which the ∼28 min and ∼31 min oscillations are generated from the latent heating associated with convection and the ∼44 min, ∼62 min and ∼103 min oscillation are linked with mechanical oscillator mechanism. During normal time period of 19:30–21:30 UTC, ∼30 min, ∼40 min and ∼120 min oscillations are generated out of which the ∼120 min oscillation is linked with mechanical oscillator effect and the other two oscillations are associated with latent heating effect. During the passage of the second thunderstorm (21:30–00:30 UTC), GWs oscillations are generated with the periodicities of ∼15 min, ∼29 min, ∼44 min, ∼58 min and ∼88 min. These oscillations are probably generated from the mechanical oscillator effect as the other two mechanisms are ruled out. The large vertical and horizontal wavelengths of the convection generated GWs observed during the pre-monsoon period indicate that the wave generated in the lower atmosphere could easily propagate up to the stratosphere. ERA-Interim and GPS radiosonde data are used to obtain the background wind and temperature information of the convective events, which are in agreement with high-resolution WRF model simulations over Gadanki. Since the strength of the thunderstorms generated during the pre-monsoon period is much stronger therefore the

Fig. 15. Height profiles (40 m-40 km) of (a) deviation of temperature from mean value (ºC), (b) deviation of zonal wind velocity (U) from mean value [(m/ s)] and (c) deviation of meridional wind velocity (V) from mean value [(m/s)] simulated by WRF model on 27–28 May 2015.

the altitude z in km). The height profile of temperature obtained from GPS radiosonde shows the cold-point tropopause at the height of ∼18 km. The BV frequency shows a sudden jerk in the height regions of ∼2–3 km, ∼8–10 km, ∼15 km and ∼11–12 km, which explains the presence of disturbances for wave propagation in these heights as indicated in the phase profiles [Figs. 7, 9 and 11] and vertical wind velocity [Fig. 4 (a)]. The mean zonal wind ranges ∼3 to ∼ −29 m/s for the GPS radiosonde 74

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Fig. 16. Time (14:18–00:30 UTC on 27–28 May 2015) vs. height (3.6–20 km) contour plots of MST radar signal-to-noise ratio (SNR in dB) for the (a, c, e) east, zenith Y, north beams (Left Panel) and (b, d, f) west, zenith X and south beams (Right Panel).

Fig. 17. Time (14:18–00:30 UTC on 27–28 May 2015) vs. height (3.6–20 km) contour plots of MST radar doppler spectral width (in Hz) for the (a, c, e) east, zenith Y, north beams (Left Panel) and (b, d, f) west, zenith X, south beams (Right Panel).

convective clouds could easily penetrate the tropopause and reach up to the lower stratosphere. The observations from MST radar, GPS radiosonde along with the WRF model simulations show the vertical propagation of GWs from the troposphere to stratosphere in the presence of

deep cumulus clouds near the tropopause, implying stratospheric tropospheric exchange (STE) processes occurred during that event. Thus, the thunderstorms during pre-monsoon period are capable of generating GWs with large energy and momentum fluxes that can be 75

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transported to the higher atmosphere. Hence, they play a very important role in the stratosphere and troposphere exchange processes.

Australia: Observations and a Gravity Wave–Tidal Interaction Model. J. Atmos. Sci. 44, 605–619. https://doi.org/10.1175/1520-0469(1987)044<0605:MMFSAA>2.0. CO;2. Gettelman, A., Salby, M.L., Sassi, F., 2002. Distribution and influence of convection in the tropical tropopause region. J. Geophys. Res. Atmos. 107 ACL 6-1-ACL 6-12. https:// doi.org/10.1029/2001JD001048. Ghosh, P., Ramkumar, T.K., Yesubabu, V., Naidu, C.V., 2016. Convection-generated highfrequency gravity waves as observed by MST radar and simulated by WRF model over the Indian tropical station of Gadanki. Q. J. R. Meteorol. Soc. 142, 3036–3049. https://doi.org/10.1002/qj.2887. Hong, S.-Y., Noh, Y., Dudhia, J., Hong, S.-Y., Noh, Y., Dudhia, J., 2006. A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes. Mon. Weather Rev. 134, 2318–2341. https://doi.org/10.1175/MWR3199.1. Kain, J.S., 2004. The Kain–Fritsch Convective Parameterization: An Update JOHN. J. Appl. Meteorol. 43, 170–181. https://doi.org/10.1175/1520-0450(2004) 043<0170:TKCPAU>2.0.CO;2. Kain, J.S., Fritsch, J.M., 1993. Convective Parameterization for Mesoscale Models: The Kain-Fritsch Scheme. In: The Representation of Cumulus Convection in Numerical Models. American Meteorological Society, Boston, MA, pp. 165–170. https://doi.org/ 10.1007/978-1-935704-13-3_16. Kirkwood, S., Mihalikova, M., Rao, T.N., Satheesan, K., 2010. Turbulence associated with mountain waves over Northern Scandinavia – a case study using the ESRAD VHF radar and the WRF mesoscale model. Atmos. Chem. Phys. 10, 3583–3599. https:// doi.org/10.5194/acp-10-3583-2010. Lane, T.P., Reeder, M.J., 2001. Convectively Generated Gravity Waves and Their Effect on the Cloud Environment. J. Atmos. Sci. 58, 2427–2440. https://doi.org/10.1175/ 1520-0469(2001)058<2427:CGGWAT>2.0.CO;2. Lindzen, R.S., Holton, J.R., 1968. A Theory of the Quasi-Biennial Oscillation. J. Atmos. Sci. 25, 1095–1107. https://doi.org/10.1175/1520-0469(1968) 025<1095:ATOTQB>2.0.CO;2. Mapes, B.E., 1993. Gregarious Tropical Convection. J. Atmos. Sci. 50, 2026–2037. https://doi.org/10.1175/1520-0469(1993)050<2026:GTC>2.0.CO;2. McLandress, C., Alexander, M.J., Wu, D.L., 2000. Microwave Limb Sounder observations of gravity waves in the stratosphere: A climatology and interpretation. J. Geophys. Res. Atmos. 105, 11947–11967. https://doi.org/10.1029/2000JD900097. Mlawer, E.J., Taubman, S.J., Brown, P.D., Iacono, M.J., Clough, S.A., 1997. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res. Atmos. 102, 16663–16682. https://doi.org/10.1029/ 97JD00237. Nicholls, M.E., Pielke, R.A., Cotton, W.R., Nicholls, M.E., Pielke, R.A., Cotton, W.R., 1991. Thermally Forced Gravity Waves in an Atmosphere at Rest. J. Atmos. Sci. 48, 1869–1884. https://doi.org/10.1175/1520-0469(1991)048<1869:TFGWIA>2.0. CO;2. Panchawagh, N.V., Vaidya, S.S., 2011. Link between break/active phases of summer monsoon over India and China. Curr. Sci. 101. Pandya, R.E., Alexander, M.J., 1999. Linear Stratospheric Gravity Waves above Convective Thermal Forcing. J. Atmos. Sci. 56, 2434–2446. https://doi.org/10.1175/ 1520-0469(1999)056<2434:LSGWAC>2.0.CO;2. Piani, C., Durran, D.R., 2001. A Numerical Study of Stratospheric Gravity Waves Triggered by Squall Lines Observed during the TOGA COARE and COPT-81 Experiments. J. Atmos. Sci. 58, 3702–3723. https://doi.org/10.1175/15200469(2001)058<3702:ANSOSG>2.0.CO;2. Rao, P.B., Jain, A.R., Kishore, P., Balamuralidhar, P., Damle, S.H., Viswanathan, G., 1995. Indian MST radar 1. System description and sample vector wind measurements in ST mode. Radio Sci. 30, 1125–1138. https://doi.org/10.1029/95RS00787. Reshmi Mohan, P., Srinivas, C.V., Yesubabu, V., Baskaran, R., Venkatraman, B., 2018. Simulation of a heavy rainfall event over Chennai in Southeast India using WRF: Sensitivity to microphysics parameterization. Atmos. Res. 210, 83–99. https://doi. org/10.1016/j.atmosres.2018.04.005. Revathy, K., Prabhakaran Nair, S.R., Krisha Murthy, B.V., 1996. Deduction of temperature profile from MST radar observations of vertical wind. Geophys. Res. Lett. 23, 285–288. https://doi.org/10.1029/96GL00086. Romatschke, U., Houze, R.A., Romatschke Jr., U., R.A.H, 2011. Characteristics of Precipitating Convective Systems in the Premonsoon Season of South Asia. J. Hydrometeorol. 12, 157–180. https://doi.org/10.1175/2010JHM1311.1. Salby, M.L., Garcia, R.R., 1987. Transient Response to Localized Episodic Heating in the Tropics. Part I: Excitation and Short-Time Near-Field Behavior. J. Atmos. Sci. 44, 458–498. https://doi.org/10.1175/1520-0469(1987)044<0458:TRTLEH>2.0. CO;2. Skamarock, C., Klemp, B., Dudhia, J., Gill, O., Barker, D., Duda, G., Huang, X., Wang, W., Powers, G., 2008. A Description of the Advanced Research WRF Version 3. https:// doi.org/10.5065/D68S4MVH. Song, I.-S., Chun, H.-Y., Lane, T.P., Song, I.-S., Chun, H.-Y., Lane, T.P., 2003. Generation Mechanisms of Convectively Forced Internal Gravity Waves and Their Propagation to the Stratosphere. J. Atmos. Sci. 60, 1960–1980. https://doi.org/10.1175/15200469(2003)060<1960:GMOCFI>2.0.CO;2. Srinivas, C.V., Bhaskar Rao, D.V., Yesubabu, V., Baskaran, R., Venkatraman, B., 2013. Tropical cyclone predictions over the bay of bengal using the high-resolution advanced research weather research and forecasting (ARW) model. Q. J. R. Meteorol. Soc. 139, 1810–1825. https://doi.org/10.1002/qj.2064. Srinivas, C.V., Yesubabu, V., Hari Prasad, D., Hari Prasad, K.B.R.R., Greeshma, M.M., Baskaran, R., Venkatraman, B., 2018. Simulation of an extreme heavy rainfall event over Chennai, India using WRF: Sensitivity to grid resolution and boundary layer physics. Atmos. Res. 210, 66–82. https://doi.org/10.1016/j.atmosres.2018.04.014. Thompson, G., Rasmussen, R.M., Manning, K., Thompson, G., Rasmussen, R.M., Manning, K., 2004. Explicit Forecasts of Winter Precipitation Using an Improved Bulk

Acknowledgements The present research is assisted by Department of Space, Government of India. Authors are grateful to Indian MST Radar group members for their help in observations at NARL, Gadanki. Thanks to Dr. Amit Patra, Dr. Amit P. Kesarkar and Dr. Jyoti Bhate for their valuable suggestions. The data utilized for this work can be accessed upon request. Authors are thankful to the reviewer and Editor for their constructive comments which improved the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jastp.2019.01.018. References Alexander, M.J., 1998. Interpretations of observed climatological patterns in stratospheric gravity wave variance. J. Geophys. Res. Atmos. 103, 8627–8640. https://doi. org/10.1029/97JD03325. Alexander, M.J., Geller, M., McLandress, C., Polavarapu, S., Preusse, P., Sassi, F., Sato, K., Eckermann, S., Ern, M., Hertzog, A., Kawatani, Y., Pulido, M., Shaw, T.A., Sigmond, M., Vincent, R., Watanabe, S., 2010. Recent developments in gravity-wave effects in climate models and the global distribution of gravity-wave momentum flux from observations and models. Q. J. R. Meteorol. Soc. 136, 1103–1124. https://doi.org/ 10.1002/qj.637. Alexander, M.J., Holton, J.R., 1997. A Model Study of Zonal Forcing in the Equatorial Stratosphere by Convectively Induced Gravity Waves. J. Atmos. Sci. 54, 408–419. https://doi.org/10.1175/1520-0469(1997)054<0408:AMSOZF>2.0.CO;2. Alexander, M.J., Holton, J.R., Durran, D.R., 1995. The Gravity Wave Response above Deep Convection in a Squall Line Simulation. J. Atmos. Sci. 52 (12), 2212–2226. https://doi.org/10.1175/1520-0469(1995)052<2212:TGWRAD>2.0.CO;2. Alexander, M.J., Vincent, R.A., 2000. Gravity waves in the tropical lower stratosphere: A model study of seasonal and interannual variability. J. Geophys. Res. Atmos. 105, 17983–17993. https://doi.org/10.1029/2000JD900197. Beres, J.H., Alexander, M.J., Holton, J.R., 2004. A Method of Specifying the Gravity Wave Spectrum above Convection Based on Latent Heating Properties and Background Wind. J. Atmos. Sci. 61, 324–337. https://doi.org/10.1175/1520-0469(2004) 061<0324:AMOSTG>2.0.CO;2. Beres, J.H., Alexander, M.J., Holton, J.R., 2002. Effects of Tropospheric Wind Shear on the Spectrum of Convectively Generated Gravity Waves. J. Atmos. Sci. 59, 1805–1824. https://doi.org/10.1175/1520-0469(2002)059<1805:EOTWSO>2.0. CO;2. Bretherton, C., 1988. Group Velocity and the Linear Response of Stratified Fluids to Internal Heat or Mass Sources. J. Atmos. Sci. 45, 81–94. https://doi.org/10.1175/ 1520-0469(1988)045<0081:GVATLR>2.0.CO;2. Chen, F., Dudhia, J., 2001. Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity. Mon. Weather Rev. 129, 569–585. https://doi.org/10.1175/15200493(2001)129<0569:CAALSH>2.0.CO;2. Clark, T.L., Hauf, T., Kuettner, J.P., 1986. Convectively forced internal gravity waves: Results from two‐dimensional numerical experiments. Q. J. R. Meteorol. Soc. 112, 899–925. https://doi.org/10.1002/qj.49711247402. Costantino, L., Heinrich, P., Mzé, N., Hauchecorne, A., 2015. Convective gravity wave propagation and breaking in the stratosphere: comparison between WRF model simulations and lidar data. Ann. Geophys. 33, 1155–1171. https://doi.org/10.5194/ angeo-33-1155-2015. Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., Vitart, F., 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597. https://doi.org/10.1002/qj.828. Duda, J.D., 2011. WRF simulations of mesoscale convective systems at convection-allowing resolutions. Graduate Theses and Dissertations. pp. 10272. https://lib.dr. iastate.edu/etd/10272. Dunkerton, T.J., 1997. The role of gravity waves in the quasi-biennial oscillation. J. Geophys. Res. 102, 26053–26076. https://doi.org/10.1029/96jd02999. Fovell, Robert G., Durran, Dale, Holton, J.R., 1992. Numerical Simulations of Convectively Generated Stratospheric Gravity Waves. J. Atmos. Sci. 49, 1427–1442. https://doi.org/https://doi.org/10.1175/1520-0469(1992)049<1427:NSOCGS>2. 0.CO;2. Fritts, D.C., Alexander, M.J., 2003. Gravity Wave Dynamics and Effects in the Middle Atmosphere. Rev. Geophys. 41, 1–64. https://doi.org/10.1029/2001RG000106. Fritts, D.C., Vincent, R.A., 1987. Mesospheric Momentum Flux Studies at Adelaide,

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P. Ghosh, et al. Microphysics Scheme. Part I: Description and Sensitivity Analysis. Mon. Weather Rev. 132, 519–542. https://doi.org/10.1175/1520-0493(2004)132<0519:EFOWPU>2. 0.CO;2. Torrence, C., Compo, G.P., 1998. A Practical Guide to Wavelet Analysis. Bull. Am. Meteorol. Soc. 79, 61–78. Valkonen, T., Vihma, T., Kirkwood, S., Johansson, M.M., 2010. Fine-scale model simulation of gravity waves generated by Basen nunatak in Antarctica. Tellus 62, 319–332. https://doi.org/10.1111/j.1600-0870.2010.00443.x.

Yesubabu, V., Srinivas, C.V., Ramakrishna, S.S.V.S., Hari Prasad, K.B.R.R., 2014. Impact of period and timescale of FDDA analysis nudging on the numerical simulation of tropical cyclones in the Bay of Bengal. Nat. Hazards 74, 2109–2128. https://doi.org/ 10.1007/s11069-014-1293-2. Zhang, Y., Xiong, J., Liu, L., Wan, W., 2012. A global morphology of gravity wave activity in the stratosphere revealed by the 8-year SABER/TIMED data. J. Geophys. Res. Atmos. 117 n/a-n/a. https://doi.org/10.1029/2012JD017676.

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