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ScienceDirect Advances in Space Research 64 (2019) 1926–1939 www.elsevier.com/locate/asr
Allsky airglow imaging observations from Hanle, Leh Ladakh, India: Image analyses and first results S. Mondal a, A. Srivastava a, V. Yadav a, S. Sarkhel a,⇑, M.V. Sunil Krishna a, Yamini K. Rao a,b, Vir Singh a,c a
Department of Physics, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India Department of Physics, Indian Institute of Technology BHU, Varanasi 221005, Uttar Pradesh, India c Guru Nanak Institute of Technology, Kolkata 700114, West Bengal, India
b
Received 21 February 2019; received in revised form 21 May 2019; accepted 27 May 2019 Available online 5 June 2019
Abstract We have installed a multi-wavelength allsky airglow imager over the Indian Himalayan region at Hanle, Leh Ladakh, (32.7°N, 78.9° E; dip lat. 24.1°N). This is the first of its kind that is installed in the Himalayan region at an altitude of around 4200 m above the mean sea level. The high sensitive thermoelectrically cooled CCD based imager is equipped with two interference filters (557.7 nm and 630.0 nm with a bandwidth of 2 nm). The airglow imaging observations have been carried out during moonless nights since June 2018. This paper presents the detailed steps of the image processing techniques to transform the raw images into the geospatially-calibrated images and discusses the process for the estimation of gravity wave parameters (horizontal wavelength, apparent phase velocity and periodicities) from the processed images. In addition, we report a few interesting events like Ripple-type structures, gravity waves and mesospheric bores in the mesopshere and lower thermosphere (MLT) region and the plasma disturbances in the ionospheric F region observed for the first time over Hanle, Leh Ladakh. Ó 2019 COSPAR. Published by Elsevier Ltd. All rights reserved.
Keywords: Allsky imager; Image processing; Gravity waves; Mesospheric bores; Mid-latitude plasma irregularities
1. Introduction For decades, researchers have been carrying out observations of different airglow emissions originating from the Earth’s upper atmosphere in order to understand the dynamics and chemistry of that region. These investigations have revealed that Earth’s atmosphere is a highly coupled system and the coupling occurs mainly through the neutral-dynamical, chemical, and electro-dynamical processes (e.g. Hocking, 1996; Pogoreltsev et al., 2007; Singh et al., 2011; Yig˘it and Medvedev, 2015; Yig˘it et al., 2016). The coupling processes have a crucial role to balance ⇑ Corresponding author.
E-mail address:
[email protected] (S. Sarkhel). https://doi.org/10.1016/j.asr.2019.05.047 0273-1177/Ó 2019 COSPAR. Published by Elsevier Ltd. All rights reserved.
the momentum and energy budget between the different regions of the atmosphere. Atmospheric gravity waves (Hines, 1960) act as a dynamical coupling agent between the mesosphere and thermosphere-ionosphere system. The perturbations in the atmosphere, generated by thermal forcing, lightning, wind flow over mountains, etc. propagate upward and Earth’s gravity acts as a restoring force in the propagation of these waves. These are commonly known as atmospheric gravity waves. The periods of these waves range from as low as 5 min to 3 h. The horizontal wavelengths of the gravity waves can be 50–500 km whereas; the vertical wavelength can range from 5 to 10 km in the mesosphere. They carry energy and momentum through different layers of the atmosphere and breaking and/or saturation of these waves may deposit
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momentum and energy in the upper atmosphere (Hines, 1960, Bretherton, 1969; Fritts and Alexander, 2003; Costantino et al., 2015). The breaking of gravity waves due to neutral instability leads to the small-scale gravity waves in the mesosphere and lower thermosphere (MLT) region. These small-scale gravity waves can be amplified with the interaction of large-scale planetary waves and consequently affect the ionospheric dynamics. Therefore, the characterization of gravity waves is necessary to study the upper atmospheric dynamics comprehensively. The dissipation or breaking of waves alters the density and temperature in the atmospheric layers and consequently modulates the intensity pattern of airglow emissions originating from that region. This intensity variation of airglow emission allows us to investigate the wave dynamics as well as the chemistry of the atmosphere. The altitude integrated airglow intensity fluctuation measured by photometers and the temperature and wind measurements by spectrometers, give useful information about the nature of perturbation but these instruments always look at a small portion of sky in one direction and cannot give spatial information of the perturbation (Batista et al., 2000). Meteor radars are also not suitable to derive the parameters of short period gravity waves because of its low temporal resolution in the MLT region. This shortcoming is fulfilled by developing a highsensitive CCD based allsky imager. A CCD based allsky imager (field of view 180°) can give continuously large spatial as well as temporal information at any airglow emission line during moonless and cloudless nights. The intensity variation due to perturbation at the airglow emission height can be mapped into the image captured by the airglow imager and therefore, consecutive imaging observations can give extra parameters of perturbation like horizontal phase velocity, horizontal scale size, and propagation direction. The MLT region dynamics can be studied from the airglow emission lines whose peak emission height lies at that region. Similarly, thermosphere-ionospheric emission lines can be used to investigate the plasma dynamics and neutral-plasma coupling processes in the ionosphere. The peak emission height of OI 557.7 nm airglow emission is about 97 km (MLT region) and that of OI 630.0 nm emission is about 250 km (ionospheric F region). Therefore, the imaging observations at OI 557.7 nm and OI 630.0 nm are suitable to study the neutral instabilities in the MLT region and the plasma instabilities in the F region respectively. One of the most important ionospheric irregularities are Travelling Ionospheric Disturbances (TIDs) which are known for more than five decades to the research community. TIDs consist of rising and falling sheets of plasma density in the F region, and have been originally attributed to perturbations in the ionized layer modulated by acoustic gravity waves (Hines, 1960). Hunsucker (1982) first categorized TIDs with horizontal wavelengths of 100–500 km and periods of 60 min into medium-scale TIDs (MSTIDs) which are the most persistent and prominent mid-latitude
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nighttime ionospheric irregularities. They have been frequently observed using allsky imagers at various midlatitude locations in northern as well as southern hemispheres. MSTIDs appear in the allsky imagers as periodic dark bands. The occurrence rate of mid-latitude MSTIDs is very high. According to Shiokawa et al. (2005), MSTIDs, having horizontal wavelengths of 100–400 km, were present in allsky images for almost all clear-sky nights, propagating southwestward in Japan and northwestward in Australia. Tsugawa et al. (2006) also observed MSTIDs using total electron content (TEC) maps over Japan. It is reported that seeding in the ionosphere by gravity waves plays an important role in the formation of MSTIDs (Kelley, 2011). However, the exact origin of these MSTIDs is not well understood. Therefore, characterization of both MSTIDs as well as gravity waves is necessary to understand the origin of MSTIDs and the gravity wave seeding mechanism. In this context, the simultaneous imaging study of the MLT region (Filter: 557.7 nm) and F region perturbations (Filter: 630.0 nm) can give insights into the relation between MSTIDs and gravity wave perturbations. Another interesting phenomenon in the F region is spread-F, which appears as ‘‘spread echoes” on ionograms and as dark/bright bands in allsky airglow images of OI 630.0 nm emission band due to plasma irregularities. Mid-latitude spread-F (MSF) is relatively less explored due to its infrequent occurrence as compared to spread-F at low and high latitudes. MSF is reported to exhibit certain different characteristics, like being more frequent during solar minimum and no definite dependence on geomagnetic activity (Benzcze and Bakki, 2002; and references therein). It has been reported that MSF can also be associated with the occurrence of TIDs at mid-latitudes (Bowman, 1981). The breaking of atmospheric gravity waves may instigate plasma instability at the bottom of the F-layer causing formation of MSF (Bowman, 1990). It should be noted that equatorial or low latitude plasma irregularities, when raised to sufficient altitude, could map to mid-latitudes by geomagnetic field lines and appear as MSF. Therefore, studying the morphology and characteristics of MSF is important to understand the coupling between low and mid-latitude electrodynamics. All over the globe, researchers are using high resolution CCD based allsky airglow imagers to capture two dimensional sky at particular airglow layers like OI 557.7 nm, OI 630.0 nm, NaD and OH band emissions, to derive different parameters of atmospheric disturbances in the airglow emission region (e.g. Brown et al., 2004; Seker et al., 2007; Ogawa et al., 2009; Li et al., 2013; Sharma et al., 2014; Nyassor et al., 2018). In the Indian sector, Mukherjee (2003) found the presence of short period gravity waves in the MLT region with periodicity of around 8 min over low latitude station, Panhala (17.0°N, 74.2° E) on 557.7 nm and OH airglow images. Sarkhel et al. (2012, 2019) found the periodicities of 15–30 min of dominant modes of gravity waves using a narrow-band and narrow field-of-view Na airglow photometer measurements
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over Mt. Abu (24.6°N, 72.7°E) and Gadanki (13.5°N, 79.2°E). Recent observations of long lasting Kelvin-Helmholtz (KH) billows in the MLT region have opened up the investigation on the effect of different atmospheric parameters upon KH billows (Sarkhel et al., 2015a, 2015b; Mondal et al., 2019). However, the spatial scale sizes of these long lasting KH billows are not known. In addition, there is no report on the observations of gravity waves in the MLT region over the Indian mid-latitude Himalayan sector. In order to accomplish the proposed research on plasma instabilities, gravity waves and their relationship, we have installed a multi-wavelength allsky airglow imager in the Himalayan region at a very high altitude site near the Indian Astronomical Observatory, Hanle, Leh Ladakh
(32.78°N, 78.96°E; altitude: 4200 m above mean sea level). We got the first light on 12 June 2018 and it is being operated since then in automatic mode during moonless nights. Although several thermospheric airglow imaging observations (e.g. Sinha et al., 2001; Mukherjee et al., 1998; Mukherjee, 2002, 2003; Rajesh et al., 2007; Narayanan, et al., 2009, 2012; Taori et al., 2013; Taori and Sindhya, 2014; and references therein) have been carried out over the Indian region, no imaging observation is reported so far over the northern Himalayan sector. This instrument is the first of its kind installed at a high altitude Indian Himalayan station. In this connection, it is to be noted that the observational site Hanle, Leh Ladakh (dip lat. 24.1°N) (shown in Fig. 1) is the interface between geomagnetic mid and low latitudes over the Himalayan sector and the
Fig. 1. Map of Indian subcontinent indicating the position of the allsky imager at Hanle, Leh Ladakh.
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orographic contribution to the generation of gravity waves over the Himalayan sector is not known. Therefore, the results from this observational site can help us to understand the nature of the gravity waves over this region and the characterization of the ionospheric F region irregularities and MSTIDs over the Indian subcontinent. The results will improve the understanding of the origin of MSTIDs at mid-latitudes, which may also seed the Equatorial Plasma Bubbles (EPB) (Taori et al., 2015; Takahashi et al., 2018). Therefore, the observations will also help to study the possible relationship between EPB and MSTIDs over the Indian sector. Moreover, plasma irregularities observed over Hanle can have equatorial and/or mid-latitude origin. Hence, it is important to understand how this region, which is at the interface of low and mid-latitudes, gets affected by equatorial and mid-latitude processes. This paper brings out the first ever airglow imaging observation from Hanle, Leh Ladakh over the Indian Himalayan region. In addition, it also discusses the detailed steps of new image processing techniques for the estimation of horizontal parameters of the wave-like perturbations in 557.7 nm images and the detection of MSTIDs using OI 630.0 nm airglow imaging observations. 2. Imager details The allsky imaging system procured from Keo Scientific Ltd., Canada consists of mainly two parts: an optical system and a detector. The schematic diagram of the airglow imager is shown in Fig. 2. The optical part contains an f/4 Mamiya fish-eye lens with a focal length 24 mm at the front end of the imager with a maximum field of view 180°. However, we have kept the imager with an effective field of view
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of 140° to remove the mountain area at low elevation angle. The imager also contains a shutter which protects the highly sensitive CCD camera of the imager from daylight. The imager and its data acquisition system are kept inside a weatherproof PUF container for protection against the harsh winter at Hanle, Leh Ladakh. The imager is mounted vertically and looks into the sky through a 10inch hole on the roof of the container. It is covered with a BK7 glass dome which has SiO2 and BBAR anti-reflective coating to protect the primary lens of the imager from UV rays (shown in Fig. 2). It uses a 3-inch tele-centric arrangement (Plano-Convex lens pair) to parallel the image rays to the axis of filter wheel before impinging on a temperature controlled filter wheel which consists of six slots for mounting interference filters. In this imager, only three slots are being utilized. Two slots are mounted with 630.0 and 557.7 nm interference filters with 2 nm bandwidth and another is kept open to observe cloud conditions of the sky. The rear-end optics consists of a highly sensitive thermoelectrically cooled monochromatic CCD (Atik 4000) that has been installed to detect the image. The CCD temperature is to be kept at 16 °C to minimize the dark current and to reduce the occurrence of hot pixels as much as possible during the data acquisition. The CCD has peak quantum efficiency of 65% at wavelength 540 nm and has 0.02e-/s dark current at 10° C ambient temperature. It has large imaging area (16.67 mm 16.05 mm), large pixel size (7.4 mm 7.4 mm) and has high pixel resolution (2047 2047). However, in order to enhance the signalto-noise ratio (SNR), the CCD is binned to 4 4 during the data acquisition. Therefore, the raw image has 511 511 pixel resolution. The optimum exposure time of 180 s has been chosen for both 557.7 and 630.0 nm filters
Fig. 2. The schematic diagram of the allsky imager [left part] over Hanle, Leh Ladakh, India. Instrument and the BK7 glass dome mounted on the roof of the PUF container are shown in the right part of the figure.
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during imaging observations. The imaging system is also capable of taking dark exposure for individual filters at every hour of an observing night. It runs automatically during moonless nights controlled by a customized software and the raw images are systematically stored in the data acquisition system. 3. Imaging processing In order to derive any meaningful scientific information, the raw image needs to be processed. This raw image is also ‘‘warped” so it has to be unwarped to derive the different parameters of any perturbation with a better accuracy. There are several methods available in the literature (Garcia et al., 1997; Narayanan et al., 2009 and references therein) to retrieve useful information from the raw images. The standard method of image processing is discussed below:
where, GðEÞ is the camera mapping function. Under the linear approximation normalized GðEÞ can be considered to be proportional to E and can be written as: GðEÞ ¼ ð90 EÞ=90
ð5Þ
Therefore, with the help of known bright stars’ elevation and azimuth angles over the observation site and time, the standard coordinates of ‘bright stars’ are determined from the Eqs. (3) and (4). After collecting a large number of ‘bright stars’ data points from a standard star catalogue, the calibration constants are obtained by using the Eqs. (1) and (2) and it enables us to find standard coordinate ðf ; gÞ of all the pixel points of the image. Now from the Eqs. (3) and (4), we can find elevation and azimuth of all the image pixel points using the standard coordinates ðf ; gÞ: In order to calculate geographical coordinate ðk; uÞ of a point P of the image at an altitude h, we need EarthCentre-Angle ðECAÞ of that point P. From the geometry of triangular law (shown in Fig. 3), ECA ðWÞ can be found to be:
3.1. Image spatial calibration
W ¼ 90 E sin1 ½R cosðEÞ=ðR þ hÞ
The raw image captured by the fisheye lens is projected onto the CCD image plane. The image becomes compressed and curved toward the horizon due to the curvature effect of the fisheye lens. Therefore, the distance between any two points on the image is not proportional to the distance between two points projected on the CCD. It means that the distance represented by two consecutive pixels near the horizon is different as compared to the distance represented by two consecutive pixels near the zenith. In addition, it is also not possible to know the North direction from the raw image. Hence, the geospatial calibration using known standard stars is needed to find the relation between the pixel coordinate of CCD and the geographical coordinate or distance coordinate ðx; yÞ of the actual image. The transformation from pixel coordinates ði; jÞ to standard coordinates ðf ; gÞ is carried out using two equations:
where R is the radius of the Earth (6371.0 km) and E is the elevation angle of the image point P. Geographical coordinate P ðk; uÞ is to be calculated by the equations:
f ¼ a0 þ a 1 i þ a 2 j
ð1Þ
g ¼ b0 þ b 1 i þ b2 j
ð2Þ
The standard coordinate is defined in such a way that the center of the standard coordinate system coincides with the zenith point of the image (elevation angle 90°) and the coordinate points at circumference of the circle (centered at zenith) indicate an equivalent point of image at the horizon [elevation angle 0°]. The arbitrary constants in the Eqs. (1) and (2), called calibration constants, will be determined with the help of ‘known bright stars’ pixel positions and their actual azimuth (A) and elevation angles (E). The standard coordinates (f ; g) are related to the azimuth and elevation of pixel coordinates by the equations: f ¼ GðEÞ sinðAÞ
ð3Þ
g ¼ GðEÞ cosðAÞ
ð4Þ
k ¼ ksite þ tan1 ðtan W cos AÞ u ¼ usite þ tan
1
ðtan W sin A=cos ksite Þ
ð6Þ
ð7Þ ð8Þ
where, ksite and usite are the latitude and longitude of the installation sites of the imager, respectively. From the geometry, the distance coordinates ðx;yÞ of the point P can be calculated by the equations given below: r ¼ ðR þ hÞ Wðin radianÞ:
ð9Þ
x ¼ r sinðAÞ
ð10Þ
y ¼ r cosðAÞ
ð11Þ
where, the center (0,0) of the distance coordinate is the zenith of the images, x-axis is along EW direction and yaxis is along NS direction (right subplot of Fig. 3). We have chosen 65 bright stars available in the raw image of the OPEN filter for precise geospatial calibration in order to find the azimuth and elevation angle of each pixel. Once the imager is calibrated, there is no need of further calibration for individual images unless the position of imager is altered. Fig. 3 represents the geometry of the geospatial calibration. The equations related to the calibration have been obtained from the Fig. 3. Fig. 4 represents the sequence of image processing of an image observed during the night of 21 June 2018. Fig. 4a is the raw image taken for geospatial calibration and image unwarping. The obtained elevation and azimuth angles corresponding to the CCD pixel point are shown in Fig. 4b and 4c, respectively. Fig. 4b depicts the contour plot of elevation angle of the pixel points superimposed on the raw image and Fig. 4c is the pseudo plot of the azimuthal angle corresponding to pixel points. The azimuthal plot coincides with
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Fig. 3. (Left) Geometry of the geospatial calibration. Pðx;yÞ is the image point. Here, O is the observation point of the imager, h [OZ] represents the altitude of the peak emission layer and r = geographical distance of image the point P from the zenith point Z of the image, A represents azimuth and E is elevation angle. C is the center of the Earth and R [OC] the radius of Earth. (Right) X is the zonal distance coordinate and Y is the meridional distance coordinate. The distances are not to scale.
Fig. 4. Geospatial calibration of image pixel point. (a) The raw image of 557.7 nm filter from Hanle (32.7°N, 78.9°N). (b) The superposition of contour plot of elevation angle corresponding to image pixel point on the raw image. (c) The azimuthal angle of image pixel point. (d) The raw image after removing background noise and bright stars. (e & f) respectively the unwarped images in zonal-meridional distance and latitude-longitude coordinates.
the standard star catalogue image orientation and thus validates our calculation of azimuth for all image pixel points. The elevation angle plot shows that the axis of the imager is
not in exact vertical position but slightly tilted towards the northeast direction. It is also shown that the field of view of the images captured by the imager is 140°.
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3.2. Image unwarping 3.2.1. Star removal After the geospatial calibration of the imager, all the stars (or any planet) have to be removed from the image because they now act as noise during the calculation of gravity waves parameters. A simple algorithm has been developed to remove the stars from images. The algorithm scans all pixel of an image line-by-line and looks for the intensity difference between n and n 3 pixels (n is the pixel’s position along a particular pixel row or column in the image). The intensity of a pixel point in case of stars is quite high as compared to background airglow intensity. Thus, the algorithm can easily detect the position of bright intensity pixel points. Once the pixel points of stars are detected, intensity on those pixel points is replaced by the median values of its surrounding pixel intensities. This process continues in a loop unless it returns to within a preset threshold of the background. Utmost care has been taken to choose the threshold value of intensity difference between the stars and the background during star removal so that the intensities of other pixel points (except bright star positions) remain unchanged. 3.2.2. Subtraction of background noise The raw images from the imager contain sky noise and the CCD dark noise. This needs to be removed in order to get better clarity on the intensity modulation of airglow. The background noise can be removed by subtracting the raw image intensity by an image periodically captured by a background filter providing the same exposure time of raw images. However, the usage of background filter while subtracting the image may cause intensity artifact due to the strong presence of our Milky Way galaxy in the subtracted image as the airglow and background images have not been taken at the same time. Hence, we have not used any background filters in this imager. The CCD generates a dark current due to thermal agitation in the chip. Although the operating temperature of the CCD has been kept as low as possible to reduce the dark current, a ‘hot pixel’ may occur occasionally. As discussed above, the imager is capable of capturing dark frames (during the shutter off condition) at every hour of the observation for an individual filter (matching the exposure time) on a given night. We have chosen an optimum exposure time of 3 min for the 557.7 and 630.0 filters and 10 s for the OPEN filter during data acquisition. The exposure time for dark frames corresponding to a given imaging filter has been kept as the exposure time for that filter. Hence, we subtract the dark frames from the airglow image frame in order to increase the signal to noise ratio. Fig. 4d represents the dark subtracted and star removed image. 3.2.3. Re-gridding The second part of image unwarping consists of a re-gridding process. The image re-gridding is mainly the re-sampling of image intensities into equidistant grid of
distance coordinate by the means of 2D interpolation. The equidistance gridding has to be carried out on the geospatially-calibrated image in (x,y) coordinate. Subsequently, the intensity of each vertex or node point of equidistance gridding can be interpolated. We have used the ‘nearest’ 2D interpolation method for re-gridding. After re-gridding, we have saved the unwarped images into HDF5 file format. Fig. 4e and 4f represents the unwarped image in distance coordinates (zonal and meridional) and geographical coordinate (latitude and longitude), respectively. It is to be noted that small-scale wavelike structure is blurredly visible after removing background noise. In order to enhance these wavelike features and suppress the noise further, two dimensional Fast Fourier Transformation (2D FFT) filtering has been adopted and applied on these unwarped images. 3.3. Image filtering techniques The unfiltered unwarped images are not suitable to calculate the wavelength, apparent periodicity and the apparent phase velocity of the perturbation from the intensity fluctuation, as the wave features are not clearly visible (e.g. Fig. 5a). Therefore, in order to enhance the intensity perturbation by suppressing the noise, the image has been smoothened using the Savitzky–Golay filter in two dimensions. Afterward, the 2D FFT is performed on this image and the power spectrum in two dimensions has been shown in Fig. 5b. In order to select the desired wave number associated with the peak spectral power, a Gaussian filter is applied. Fig. 5c depicts a typical 2D power spectrum of the Gaussian window that has to coincide with the peak-power position of the 2D FFT spectra of the image. In the spatial domain, the filtered image is the convolution of an unfiltered image and the Gaussian filter. However, in the power spectral domain, it is the product of the 2D FFT power spectra of the unfiltered image and the 2D power spectra of the Gaussian filter. The window is then positioned at the peak-power position of the 2D FFT power spectra of the image and then the inverse 2D FFT is performed to get the filtered image. These analyses assure to remove all unwanted fluctuations by suitably choosing the Gaussian filter window size. Fig. 5d represents the 2D FFT filtered image wherein the wavelike features are clearly visible. Thus, the optimum window sizes of the Savitzky–Golay and Gaussian filters can be chosen to enhance wavelike features of different wavelengths. Once the images are filtered, the parameters of the atmospheric gravity waves or any perturbation can be derived from those sequence of filtered images. Intensity fluctuation along the horizontal wave propagation will give the horizontal wavelength and from the phase shift of the intensity peak point from the consecutive images, we can calculate the apparent phase velocities and the periodicities of the waves or any disturbances. The procedure of calculating these parameters of gravity waves is described below.
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Fig.5. 2D FFT of unwarped image. (a) The gridded unwarped image. (b) The 2D FFT power spectrum. (c) The Gaussian filter window. (d) The filtered image enhancing ripple feature.
3.4. Derivation of the parameters of Wave-like perturbation This section is dedicated for the estimation of the gravity wave parameters from the filtered images. A line is overlaid perpendicular to wave-fronts of the gravity waves for all the filtered consecutive images for which atmospheric waves have been detected. The line is rasterized to have equal number of points in the x and y directions. The images, in which the gravity waves are present, are given as an input. The initial and final points of the line, along which the intensity variations are noted, also determine the zonal and meridional distance coordinates. Hence, a line joining the two points is overlaid for the particular number of consecutive images in which the gravity waves have been detected visually. This line represents the direction of propagation of the atmospheric gravity waves. As we input the initial and final points in the direction parallel to the direction of propagation, we get a straight line having unequal number of round off values of zonal and meridional distances. Also, the points are not continuous due to pixel coordinates. Therefore, in order to remove
this problem, the rasterization method is used. Using the end points, we can determine the line of equation y = mx. If m < 1, the number of x values will be greater than the number of y values. If m > 1, the number of x values will be lesser than the number of y values. Thus, the smaller domain is expanded linearly to match the cardinality of the larger one. The values in the expanded domain are also rounded off since they must correspond to index value. The intensity values along the line at the rasterized points are recorded and plotted with the distance where distance is measured by taking initial point as reference point and then the distance of all the points on the line are measured with respect to it. If we take initial points to be xx (1) and yy (1), the distance of nth point defined by xxn and yyn from the initial point will be given as qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi distn ¼ ðxxn xxð1ÞÞ2 þ ðyy n yyð1ÞÞ2 Since, the intensity values are very close to each other, all the plots overlap each other and it becomes difficult to analyze. In order to get rid of this problem, we normalize
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the intensity value and then plot with distance. It is to be noted that the intensity values are shifted from one plot to another to distinguish between two plots and clearly analyze it. The last plot in Fig. 6 is used to show the horizontal intensity fluctuation perpendicular to the wave front. The distance difference between the selected intensity peak points will give the wavelength and the shifting of intensity peak with time (phase propagation) along the propagation direction will enable us to calculate the phase velocity of the wave-like perturbation.
4. Results and discussion The allsky imaging observation has potential to carry out qualitative and quantitative analyses of the mesospheric and ionospheric disturbances. We can characterize the gravity wave parameters in the MLT region as well as the ionospheric F region plasma structures. The image analyses of the OI 557.7 nm will help in studying mesospheric wave dynamics and the OI 630.0 nm can be used to study ionospheric F region plasma dynamics. After rigorous image
Fig. 6. Estimation of average wavelength and phase velocity of the small-scale wave or ‘‘Ripple-type” structure observed in the 557.7 nm airglow images. (a–f) depicts the sequence of six 2D filtered images showing ‘‘Ripple-type” structure. The arrow in each filtered image corresponds to the line of propagation. Lower subplot represents the intensity variation along the line of horizontal propagation.
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analyses of almost six months of moonless and cloudless data, a few interesting events have been observed in both the 557.7 nm and 630.0 nm images. A brief discussion related to the observed events (Figs. 6–8) has been presented below. 4.1. Observation of ‘‘Ripple-Type” structure We have detected a small-scale wave or ripple-type structure in the OI 577.7 nm airglow imaging observation during the night of 21–22 June 2018. Fig. 6(a–f) depict the sequence of filtered images showing the ripple structure. In order to estimate the horizontal wavelength, apparent periodicity and apparent phase velocity, the intensity fluctuations along the line of propagation of the ripple for all the six images have been plotted in the lower part of the Fig. 6. The estimated wavelengths of those ripples are in the range of 13–22 km and apparent phase velocity of 10–22 m/s that lasted for about 45 min. The observed periodicities of ripple are found in the range of 11–16 min. The structure is aligned NW to SE direction. It is clear from the phase progression that there is no specific propagation direction of this structure for a long time. They are very localized and transient. After few minutes, the structure disappeared and the new one appears. These short-time scale structures could have been generated in situ due to local effect of convective or
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dynamical instabilities (Taylor and Hapgood, 1990; Pragati et al., 2010). Breaking of the mountain waves in the MLT region can also generate ripple-type structures. In this regard, topographical condition over Hanle (Himalayan region) may be conducive for the generation of mountain waves. Further analyses will be carried out to ascertain the origin of this ripple-type structure. 4.2. Observation of gravity waves Although both gravity waves and ripples are observed as wave activities by the allsky imager, they differ in characteristics. The key differences between gravity waves and ripples are the duration and scale size of the structures. The ripples are short lived (few minutes) transient phenomenon and are generally confined to a small region, whereas, the gravity waves sustain for much longer duration (up to few hours) covering a major portion in the field of view of the imager as seen in the Fig. 7. In the case of ripples, the wavelength is small as compared to the gravity waves. We have also observed gravity wave activity in the OI 577.7 nm airglow images over Hanle, Leh Ladakh on few occasions. A clear case of gravity wave activity that occurred on 7 November 2018 is shown in Fig. 7(a–f). The duration of the gravity waves was found to be about 2 h, which is much longer than the ripple-type structure
Fig. 7. (a–f) show an example of gravity waves on 7 November 2018 over Hanle, Leh Ladakh on 557.7 nm airglow images. The waves appear from south at the bottom in (a), become prominently visible in (c-d). Overall, the waves lasted for around 2 h.
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Fig. 8. (a–d) depict mesospheric fronts or bore, observed using 557.7 nm filter. Fronts are aligned along East-West direction and propagating southward. (e–d) represent the ionospheric plasma disturbance aligned in the geomagetic NS direction, observed in 630.0 nm filter. Arrow indicates westward drifting of plasma structure.
(shown in Fig. 6). The estimated wavelength of these waves was found to be larger than ripples, which is around 24– 30 km, with an apparent phase velocity found in the range of 8–12 m/s. The estimated apparent periodicities of waves lie in the range of 35–60 min and the waves propagate towards the NE direction.
the front is 46 ± 4 m/s. This mesospheric bore or front is very prominent and lasted for almost 1.3 h. Therefore, a strong inversion layer for a long time during the bore propagation is expected over the Hanle region. The detailed analyses on the relationship between the inversion layer and the characteristics of the bore event in the mesosphere will be carried out in the future.
4.3. Observation of mesospheric bores 4.4. Observation of plasma irregularities Mesospheric bores are unusual type of structures at mesospheric heights, which appear as propagating ‘fronts’ leading to a sudden step jump in the intensity followed by undulated waves (Hozumi et al., 2018). Taylor et al. (1995) first observed this type of structures, during the ALOHA-93 campaign. The characteristics and the possible origin of this type of structure have been studied for a decade (Smith et al., 2003, 2005, 2017; Brown et al., 2004; Fechine et al., 2005, 2009; Nielsen et al., 2006; Li et al., 2013; Medeiros et al., 2001, 2005, 2018). Dewan and Picard (1998, 2001) have carried out theoretical investigation of these type of structures and proposed the gravity wave interaction with the mean flow in the already existing inversion layer is likely the origin of the mesospheric bores. The inversion layer behaves as a channel to propagate the bores. We have also observed a sudden intensity change in the OI 577.7 nm airglow images during the night of 02 Dec 2018 over Hanle, Leh Ladakh. Fig. 8(a–d) represent the sequence of images that depict the propagation of a mesospheric bore along the southward direction and aligned in the East-West. The base of the arrow in the said figure indicates the ‘‘front” of the mesospheric bore. It is to be noted that there is a sudden change in the intensity distribution across the front. The estimated apparent phase velocity of
Thermospheric airglow emissions OI 630.0 nm are extensively used as tracers to investigate the dynamics of the F region. It is an important indicator of thermospheric and ionospheric processes as its intensity at midlatitudes is effectively controlled by the altitude and the density of the ionospheric plasma (Barbier, 1959). Therefore, observations of this emission are useful to unravel the physical process behind several ionospheric phenomena like Traveling Ionospheric Disturbances (TIDs). These TIDs have been detected with various observational techniques and have been attributed to the perturbations of the ionized atmosphere modulated by acoustic-gravity waves (Hines, 1960). MSTIDs are medium horizontal scale TIDs which are the most persistent and prominent of the mid-latitude nighttime ionospheric irregularities. They have horizontal-scale sizes of 50–500 km and phase speeds of 50–170 m/s and have a predominantly northwest-southeast phase surface and propagate towards SW in the northern hemisphere and occasionally move towards NE direction (Shiokawa et al., 2003, 2008; Helmboldt, 2012). Whereas, MSF related plasma irregularity structures will be geomagnetic NS aligned.
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Of late, Sivakandan et al. (2019) reported MSTIDs using allsky imager over a low latitude station, Gadanki in the Indian sector. The allsky imager at Hanle, Leh Ladakh is capable to observe plasma depletions, which are primarily manifestations of mid-latitude ionospheric irregularities. In fact, we have also observed ionospheric disturbances over Hanle, Leh Ladakh on 13 June 2018 in the OI 630.0 nm airglow images as shown in Fig. 8(e–h). The figure depicts the sequence images showing plasma structures. It is to be noted that the dip latitude of Hanle, Leh Ladakh is 24.1°N. It is an interface between low latitude and mid-latitude over Indian sector. Hence, the observation of MSTIDs over this observational site may be expected. It is interesting to note that the structures observed on 13 June 2018 are elongated in nearly northsouth direction similar to field-aligned irregularities and are propagating westward. Therefore, these structures do not seem to be associated with MSTIDs. The plasma structure has a scale size of 234 ± 23 km with drift velocity 60 ± 16 m/s at the western walls. The propagation angle is measured to be 257 ± 4° from the north (clockwise increment). The duration of the event is around 3 h visible in the field of view over Hanle, Leh Ladakh (full sequence of images not shown). The tilting angle of the structure is noticed to be very small and it dissipates within the field of view. Further detailed analyses, using additional instrumental data set, will be carried out in order to find the relationship, if any, with low-latitude ionospheric irregularities over the Indian subcontinent. More such case studies will be helpful in studying Equatorial Spread-F, MSF, and MSTIDs along with their relationships. Therefore, Hanle, Leh Ladakh is potentially a very important station for improving the understanding of the coupling between electrodynamics of equatorial/low and mid-latitudes. 5. Conclusion We are introducing the newly commissioned multiwavelength allsky airglow imager over the Indian Himalayan region at an altitude of 4.2 km above mean sea level. The new CCD based imager system with its unique installation site has a lot of potential for mesospheric and ionospheric research. This paper brings out the detailed steps of instrument operation and the image processing for the estimation of horizontal wavelength, apparent periodicities and phase velocity of gravity waves. A few spectacular events like mesospheric bores, ‘‘Ripple-type” structure, gravity waves and plasma irregularities have also been detected. Further detailed analyses of those events will be carried out in due course. Acknowledgement S. Mondal acknowledges the fellowship from the Ministry of Human Resource Development, Government of India for carrying out this research work. V. Yadav also acknowledges the post doctoral fellowship from Indian
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Institute of Technology Roorkee. We are thankful to P. Sreekumar and G. C. Anupama, Indian Institute of Astrophysics, Bengaluru, India for their support during the initialization of the project for the installation of the multiwavelength airglow imager at Hanle, Leh Ladakh. S. Sarkhel (Principal Investigator) acknowledges the financial support from the Science and Engineering Research Board, Department of Science and Technology, Government of India (SERB/EMR/2016/000247) to procure the multi-wavelength airglow imager. S. Sarkhel also thanks the Dean SRIC, Indian Institute of Technology Roorkee for providing additional financial support for procuring and installation of the imager. We thank Anirban Mitra for his support during the testing of the multiwavelength airglow imager at Department of Physics, IIT Roorkee. We also thank Dorjay Angchuk and other staff members of Indian Astronomical Observatory (IAO) (operated by Indian Institute of Astrophysics), Hanle, Leh Ladakh, India for their support during the installation of the airglow imager. The support from IAO for the day-to-day operation of the imager is duly acknowledged. S. Sarkhel thanks Jorge L. Chau for discussion on the 2D FFT filtering technique of airglow images. S. Sarkhel acknowledges Kazuo Shiokawa and Sivakandan Mani for useful discussion on MSTIDs. We used the StarCalc software for the knowledge of azimuth and elevation angles of standard stars. This work is also supported by the Ministry of Human Resource Development, Government of India. References Barbier, D., 1959. Recherches sur la raie 6300 de la luminescence atmospherique´ nocturne. Ann. Ge´ophys. 15, 179–217. Batista, P.P., Takahashi, H., Gobbi, D., Medeiros, A.F., 2000. First Airglow All Sky Images at 23° S. Adv. Space Res. 26, 925–928. https:// doi.org/10.1016/S0273-1177(00)00031-4. Benzcze, P., Bakki, P., 2002. On the origin of mid-latitude spread-F. Acta Geod. Geoph. Hung. 37 (4), 409–417. https://doi.org/10.1556/ ageod.37.2002.4.4. Brown, L.B., Gerrard, A.J., Meriwether, J.W., Makela, J.J., 2004. All-sky imaging observations of mesospheric fronts in OI 557.7 nm and broadband OH airglow emissions: Analysis of frontal structure, atmospheric background conditions, and potential sourcing mechanisms. J. Geophys. Res. 109, D19104. https://doi.org/10.1029/ 2003JD004223. Bowman, G.G., 1990. A Review of Some Recent Work on Mid-Latitude Spread-F Occurrence as Detected by Ionosondes. J. Geomag. Geoelectr. 42 (2), 109–138. https://doi.org/10.5636/jgg.42.109. Bowman, G., 1981. The nature of ionospheric spread-F irregularities in mid-latitude regions. J. Atmos. Terr. Phys. 43 (1), 65–79. https://doi. org/10.1016/0021-9169(81)90010-6. Bretherton, F.P., 1969. Momentum transport by gravity waves. Q. J. R. Meteorolog. Soc. 95 (404), 213–243. https://doi.org/10.1002/ qj.49709540402. Costantino, L., Heinrich, P., Mze´, N., Hauchecorne, A., 2015. Convective gravity wave propagation and breaking in the stratosphere: comparison between WRF model simulations and lidar data. Annales Geophysicae 33 (9), 1155–1171. https://doi.org/10.5194/angeo-331155-2015. Dewan, E.M., Picard, R.H., 1998. Mesospheric bores. J. Geophys. Res. 103, 6295–6305. https://doi.org/10.1029/97JD02498.
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