Altitude Variations Research Articles

A deep CNN-LSTM model for predicting interface depth from gravity data over thrust and fold belts of North East India

Geological interface depth modeling from the gravity field data is crucial for the exploration of oil and gas, mapping of sediment-basement interfaces and many other geological modeling studies. Two-dimensional radially averaged power spectrum analyses yield ensemble mean depth from the gravity anomaly which lacks information away from the focus of the depth point modeled. This paper aims to introduce adeep learning techniquecombining a convolutional neural networkand long short-term memory network (CNN-LSTM) with variogram modeling to model interface depths using geospatial coordinates, Bouguer gravity anomaly and altitude variations data over the thrust and fold belts of North-East India. Prior to actual data analysis, the method is tested on a synthetic model. After the optimal network selection with the ‘Relu’ transfer function and ‘Adam’ optimization, the robustness of the CNN-LSTM model is examined and the test results show that the model is robust up to the data assorted with moderate level (∼20%) of correlated noise. The CNN-LSTM model detects important geological structures, subsurface faults, and thrust zones namely, Kohima Synclinorium, Naga and Disang thrust, and Eastern boundary thrust. Comparative results suggest that the CNN-LSTM is skillful based on the mean-squared error (MSE) between the observation and the prediction (MSECNN-LSTM ∼ 0.014) relative to the other machine learning models (Adaptive-Neuro-Fuzzy-Inference System (MSEANFIS ∼ 0.020), Random Forest with Extra Tree(MSERF ∼ 0.075), Support Vector Regression (MSESVR ∼ 0.025), Bayesian Neural Network(MSEBNN ∼ 0.116), Convolutional Neural Network(MSECNN ∼ 0.022), Long Short-Term Memory Network(MSELSTM ∼ 0.023), and Gaussian Process(MSEGP ∼ 0.095)) used in the study. We, therefore, conclude that the proposed approach is robust enough to model the various geological interface depths precisely with appropriate input data of geospatial coordinates, Bouguer gravity anomaly and altitude variation. The approach used here has potential and could be explored further in other complex geological provinces around the world.

Investigation on the pressure and flow characteristics for a high-speed bullet in high-altitude flight

The pressure analysis and flow characteristics during the flight of a high-speed bullet are significant for aerodynamic performance, flight trajectory control, safety and reliability, performance optimization, guidance and navigation. To accurately monitor the pressure variation for a high-speed bullet in the high-altitude flight, a novel local fluid domain method is introduced in current study. This method overcomes the limitations of conventional global fluid domain simulation methods, which often suffer from poor convergence and stability issues. On the basis, the force analysis is conducted and the mathematical model for the theoretical trajectory is established, which is applied to simulate the flight trajectory and construct fluid domain for the high-speed bullet. The findings reveal that monitoring points within the bullet hole are influenced by both cavity flow and the collision of forward airflows during the high-altitude flight. Furthermore, it is observed that the absolute total pressure and reference pressure at these monitoring points within the bullet hole are influenced by altitude variations. Subsequently, the factors affecting the absolute total pressure within the hole are explored, including the hole depth, the hole diameter, the hole position, and the bullet orientation. The results indicate that modifying the bullet structure to incorporate 45° angled hole, as opposed to standard holes, can lead to a 13.6% reduction in absolute total pressure variation. Additionally, mitigating the interaction between the external and internal fluids emerges as a critical factor in reducing absolute total pressure within the hole. This research not only presents a fresh perspective for pressure monitoring within the bullet hole, but also establishes a theoretical foundation for the precise guidance of high-altitude bullets.

Source apportionment study on particulate air pollution in two high-altitude Bolivian cities: La Paz and El Alto

Abstract. La Paz and El Alto are two fast-growing, high-altitude Bolivian cities forming the second-largest metropolitan area in the country. Located between 3200 and 4050 m a.s.l. (above sea level), these cities are home to a burgeoning population of approximately 1.8 million residents. The air quality in this conurbation is heavily influenced by urbanization; however, there are no comprehensive studies evaluating the sources of air pollution and their health impacts. Despite their proximity, the substantial variation in altitude, topography, and socioeconomic activities between La Paz and El Alto result in distinct sources, dynamics, and transport of particulate matter (PM). In this investigation, PM10 samples were collected at two urban background stations located in La Paz and El Alto between April 2016 and June 2017. The samples were later analyzed for a wide range of chemical species including numerous source tracers (OC, EC, water-soluble ions, sugar anhydrides, sugar alcohols, trace metals, and molecular organic species). The United States Environmental Protection Agency (U.S. EPA) Positive Matrix Factorization (PMF v.5.0) receptor model was employed for the source apportionment of PM10. This is one of the first source apportionment studies in South America that incorporates an extensive suite of organic markers, including levoglucosan, polycyclic aromatic hydrocarbons (PAHs), hopanes, and alkanes, alongside inorganic species. The multisite PMF resolved 11 main sources of PM. The largest annual contribution to PM10 came from the following two major sources: the ensemble of the four vehicular emissions sources (exhaust and non-exhaust), accountable for 35 % and 25 % of the measured PM in La Paz and El Alto, respectively; and dust, which contributed 20 % and 32 % to the total PM mass. Secondary aerosols accounted for 22 % (24 %) in La Paz (El Alto). Agricultural smoke resulting from biomass burning in the Bolivian lowlands and neighboring countries contributed to 9 % (8 %) of the total PM10 mass annually, increasing to 17 % (13 %) between August–October. Primary biogenic emissions were responsible for 13 % (7 %) of the measured PM10 mass. Additionally, a profile associated with open waste burning occurring from May to August was identified. Although this source contributed only to 2 % (5 %) of the total PM10 mass, it constitutes the second largest source of PAHs, which are compounds potentially hazardous to human health. Our analysis additionally resolved two different traffic-related factors, a lubricant source (not frequently identified), and a non-exhaust emissions source. Overall, this study demonstrates that PM10 concentrations in La Paz and El Alto region are predominantly influenced by a limited number of local sources. In conclusion, to improve air quality in both cities, efforts should primarily focus on addressing dust, traffic emissions, open waste burning, and biomass burning.

Improved TPH for object detection in aerial images

ABSTRACT Deep learning has greatly enhanced the general object detection capability. However, when directly applied to aerial images, performance drops significantly due to: (1) Most objects in aerial images are dense and small; (2) UAV altitude variations cause diverse object scales. In this paper, we improve TPH algorithm for exceptional aerial object detection performance. Specifically, we introduce the SPD module to replace the strided convolution layers and pooling layers. And we improve the TPH backbone and neck networks so that large and small objects can be detected accurately. Experiments on VisDrone2019 and DOTA datasets validate the effectiveness of our method.

Spatio-Temporal Variation of Critical Relative Humidity Based on Multiple Datasets

Clouds remain an important source of uncertainty in climate simulations, in large part because subgrid processes are not well represented. Critical relative humidity (RHc) is an important metric for subgrid-scale variability in humidity in cloud parameterization. Based on CloudSat and CALIPSO satellite data, we explored the spatial and temporal distribution characteristics of RHc, assessed the ability of ERA-5 and MERRA-2 reanalysis and CMIP-6 climate models to characterise humidity subgrid variability and further explored the influence of meteorological factors and aerosols. The statistical results showed that there was significant variation in the spatial distribution of RHc, with large variations in both latitude and altitude, as well as more pronounced monthly variations, and that there were differences in monthly variations between regions. Both the reanalysis data and the climate models were able to reproduce similar spatial and temporal distribution patterns but differed significantly in their specific values. The temporal correlations with satellite observations were also relatively poor. In addition, aerosols and meteorological conditions affected the distribution of RHc by influencing the cloud fraction at a certain relative humidity level, indicating that their influence needs to be considered in future parameterization schemes.

Provenance and transport of supraglacial debris revealed by variations in debris geochemistry on Khumbu Glacier, Nepal Himalaya

AbstractThe origin of supraglacial debris covers is often conceptualised as the formation of a surface lag by melt‐out of englacial debris from slow‐moving ice, where complexity arises from feedback between debris thickness and sub‐debris ice melt. Here, we examine the origin of a debris cover from the perspective of debris provenance and changing tributary supply in a high‐elevation compound valley glacier. Geochemical analysis of 11 major elements in 21 debris samples from six tributaries of Khumbu Glacier (Nepal) shows unambiguous statistical differentiation of debris sources reflecting lithological differences between tributary catchments. Twenty‐four samples from transects across the ablation area are partitioned according to their source areas using the FR2000 sediment unmixing model. We estimate the age of ice at each transect using a higher order ice flow model. The results show greater proportions of debris from lateral tributaries in downglacier locations that have experienced longer flowline histories. More recently, ice from the Main Himalayan Divide (Western Cwm) has become relatively more important. This suggests a change in the state of the lower glacier's structure depending on the relative ice discharges of lateral and divide sources. Ice flux from lower elevation tributaries was more important probably prior to a weakening of the Indian Summer Monsoon at around 1420 CE. The lower elevation tributaries lie within the range of late Holocene equilibrium line altitude variation and therefore respond most sensitively to climatic drivers of the glacier's flow structure. Negative glacier mass balance since around 1900 CE caused tributary glaciers to detach and high‐elevation catchments to re‐establish as the dominant ice source to Khumbu Glacier.

Traffic perception from aerial images using butterfly fields

Drones are nowadays considered as a valuable solution to monitor urban traffic. Object detectors face numerous challenges when dealing with high-resolution aerial images captured by drones, due to variations in altitude, viewing angle, and weather conditions. To address these challenges, we present an object detector called Butterfly detector that is tailored to detect objects in aerial images. It is an anchor-free method that leverages field-based representations. We introduce Butterfly fields, a type of composite field that describes the spatial information of output features as well as the scale of the detected objects. We employ a voting mechanism between related Butterfly vectors pointing to the object center. We highlight the benefits of our method for urban traffic monitoring by (i) evaluating the recall/precision rate of our detector on two publicly available drone datasets (UAVDT and VisDrone2019), and (ii) measuring the error rate for flow estimations on our newly released EPFL roundabout dataset. We outperform the performance of previous methods while remaining real-time.

Effect of Geographical Location on the Phenolic and Mineral Composition of Chetoui Olive Leaves.

In this study, we investigated the influence of pedological parameters and variation of altitude on the mineral nutrients, phenolic compounds, and antioxidant activities of olive leaves. Samples of the Chetoui cultivar were collected from eight geographical locations with different altitudes. Levels of phenolic compounds varied according to the altitude. Classification of the locations revealed that altitude 1 (>500 m) was characterized by high levels of secoiridoids and simple phenols, while altitude 2 (500-300 m) and altitude 3 (<300 m) were higher in flavonoids. Levels of Mn, Ca and B in the leaves and level of Zn in the soil were significantly correlated with the abundance of oleuropein and luteolin-7-O glucoside, the most important phenols in Chetoui olive leaves. The results suggest that, in addition to pedological criteria, environmental conditions also influence the formation of phenolic compounds.

Altitude Variation on Fruit Development and Quality Attributes of Kiwifruit (Actinidia Deliciosa Chev.) In North-Western Himalaya

Effects of climatic variability at different altitudes on the fruit development and quality attributes of kiwifruit in the North -Western Himalayas of India were investigated. The experiment was carried out at five attitudinal locations (1090, 1275, 1425, 1543, and 1924 m above mean sea level) and with two cultivars viz. Hayward and Allison. It was observed that fruit yield and quality varied according to altitude and cultivars. The Hayward cultivar performed better in terms of yield, graded portion, and fruit quality like titratable acidity and ascorbic acid at higher elevations whereas, the Allison cultivar performed better at lower elevations. Findings revealed that the elevation ranging from 1000 to 1450 m was appropriate for the Allison cultivar and the elevation ranging from 1500 to 1950 m was appropriate for the Hayward cultivation. Bangladesh J. Bot. 52(2): 369-379, 2023 (June)

Baseline Studies on Biochemical Profile of Nellore Sheep in the Hot and Humid Areas of Andhra Pradesh

Nellore breed is the most commonly reared sheep in the state of Andhra Pradesh. The present study was conducted to report the effect of age and physiological status on few blood biochemical parameters of Nellore sheep breed from the hot and humid areas of Andhra Pradesh. The present study was conducted to estimate the blood biochemical parameters and its effect on physiological parameters in Nellore sheep. The results evidenced significantly higher RBC, Hb in pregnant group compared to others. Significantly higher PCV values were recorded in the 0-1 age group of animals. The total protein, creatinine were significantly higher in the lactating group compared to the other two. The albumin levels were found to be significantly higher in pregnant group. The cholesterol, calcium, phosphorus levels were found to be significantly higher in 0-1 year group and decreased in periparturient period. The study established baseline values of Nellore sheep in the hot and humid areas of Andhra Pradesh and therefore can be used as reference values for further studies on these species. Biochemical parameters are important indicators of the health condition and metabolic activity irrespective of the physiological status of the animals. lactating animals. The variations in hematological parameters is multifactorial some of which are altitude, feeding level, age, sex, breed, diurnal and seasonal variation, temperature and physiological status of animals. The baseline values obtained from this study across different physiological status and age groups could be used as a reference for further experimentation on sheep located in these areas..

Earth Gravity Detection System with Altitude Variations Using Phypox Application Integrated with Smartphone Acoustic Sensors

This study aims to examine the effect of altitude on the acceleration of gravity with the help of smartphone acoustic sensors. The altitude varies from the interval 100-1061 MASL (Mean Above Sea Level), located around the Special Region of Yogyakarta. An iron ball is dropped from a certain height, and the time it falls is observed using an acoustic sensor in Phypox, and the results are used to determine the acceleration value due to gravity (g) through the equation g = 2h/t2. Fitting data from measurements of the four altitude variations are shown in the polynomial equation y = 0.000003x2 – 0.0035x +10.718 m/s2 with a regression number R2 = 1,000. This equation shows that the acceleration value due to gravity will decrease quadratically with each increase in the altitude per meter above sea level.

Dayside Vertical Wind Reversal at Transition Altitude From E to F Regions Observed by the ICON Satellite

AbstractThe Michelson Interferometer for Global High‐Resolution Thermospheric Imaging (MIGHTI) onboard the Ionospheric Connection Explorer (ICON) mission measures the neutral winds from about 88 to 310 km altitudes, which provides a good opportunity to investigate the vertical distribution of the neutral winds. In this study we used the green line of MIGHTI to focus on the wind reversal due to large vertical shears at the transition altitude from E to F regions (∼120–220 km). For the limitations of green line filter during night‐time, we therefore present only the results on the dayside from 0600 to 1800 local time (LT). Based on more than 2 years data, there were 206 and 96 orbits identified with clear wind reversal in the meridional and zonal components, respectively. These events almost covered the whole altitude of ∼120–220 km. Interestingly, such wind reversal occurs mostly (about 75%) during magnetic quiet periods with Kp less than 2. Their dependences on LT, geographic latitude (Glat) and longitude (Glon) have been further analyzed. Two different trends for the wind reversals on LT dependence have been found, for example, the mean altitude of meridional (zonal) wind reversal is higher at dawn, and then slowly decreases toward dusk; or the mean altitude of wind reversal is higher at dusk and slowly decreases toward dawn. Such two kinds of altitude trends of wind reversal are also found for the dependence on Glat, but not on Glon. In addition, we find that there are about 90% orbits with wind reversal simultaneously observed at the low E and F regions, but the altitude variations of wind reversal can be the same or opposite in the two regions, even for the same orbit. This result suggests that the wind reversals at the low E and low F regions should be different. The climatology of the wind reversals at low F region observed by ICON provides helpful constrain for the neutral wind simulation based on physical models.

On the Propagation of Traveling Ionospheric Disturbances From the Hunga Tonga‐Hunga Ha'apai Volcano Eruption and Their Possible Connection With Tsunami Waves

AbstractWe report our analysis of ionospheric disturbances from the 15 January 2022 Tonga volcano eruption, using GPS data from the International GNSS Service network and ionosonde data in the Australian sector. Wave fluctuations with amplitudes of ∼1 TECU and altitude variations of ∼100 km were observed in the GPS and ionosonde data, respectively. In near‐field region around Tonga shortly after the eruption, our analysis reveals that the ionospheric disturbances had an azimuthally anisotropic velocity profile, with a peculiar minimum in southwestward direction. Close resemblance is identified between the velocity profile of near‐field ionospheric disturbances and the Tonga tsunami, suggesting a coupling between water and atmospheric waves. In far‐field, the disturbances propagated at ∼300 m/s, circling the globe for at least three days and possibly until 21 January 2022, in agreement with several previous reports of the event. Arrival times of ionospheric disturbances observed by GPS receivers and ionosondes provide consistent picture.

Flying high: Sampling savanna vegetation with UAV‐lidar

Abstract The flexibility of UAV‐lidar remote sensing offers a myriad of new opportunities for savanna ecology, enabling researchers to measure vegetation structure at a variety of temporal and spatial scales. However, this flexibility also increases the number of customizable variables, such as flight altitude, pattern, and sensor parameters, that, when adjusted, can impact data quality as well as the applicability of a dataset to a specific research interest. To better understand the impacts that UAV flight patterns and sensor parameters have on vegetation metrics, we compared 7 lidar point clouds collected with a Riegl VUX − 1LR over a 300 × 300 m area in the Kruger National Park, South Africa. We varied the altitude (60 m above ground, 100 m, 180 m, and 300 m) and sampling pattern (slowing the flight speed, increasing the overlap between flightlines and flying a crosshatch pattern), and compared a variety of vertical vegetation metrics related to height and fractional cover. Comparing vegetation metrics from acquisitions with different flight patterns and sensor parameters, we found that both flight altitude and pattern had significant impacts on derived structure metrics, with variation in altitude causing the largest impacts. Flying higher resulted in lower point cloud heights, leading to a consistent downward trend in percentile height metrics and fractional cover. The magnitude and direction of these trends also varied depending on the vegetation type sampled (trees, shrubs or grasses), showing that the structure and composition of savanna vegetation can interact with the lidar signal and alter derived metrics. While there were statistically significant differences in metrics among acquisitions, the average differences were often on the order of a few centimetres or less, which shows great promise for future comparison studies. We discuss how these results apply in practice, explaining the potential trade‐offs of flying at higher altitudes and with alternate patterns. We highlight how flight and sensor parameters can be geared toward specific ecological applications and vegetation types, and we explore future opportunities for optimizing UAV‐lidar sampling designs in savannas.

On the Ion Line Calibration by Plasma Line in ISR Measurements

The radar constant calibration in incoherent scatter radar ion line processing is essential for the data quality and was not paid enough attention in previous studies. In this investigation, based on several experiments made by the newly built Sanya incoherent scatter radar (SYISR), we made and evaluated the ion line calibration by plasma line both in case study and statistically. The calibration factor had local time and altitude variations, due to the corresponding variations of the transmitted power, the radar gain, and the noise temperature. We obtained a mean calibration factor of 1.35 by the simultaneous measured plasma line and ion line electron density and applied it to a one-month ion line observation calibration. Through a co-located ionosonde measured foF2 evaluation, the calibration decreased the mean deviation from −1.92 MHz (−18%) to −0.33 MHz (−3%), which resulted in much better agreement between the ion line foF2 after calibration and the ionosonde results. The existed deviations between after calibration and ionosonde results were due to the uncertainties either in the used calibration factor or the ionosonde measurements. An empirical Te/Ti usage in raw electron density estimation and ignoring the seasonal and short-term variations of the effecting factors might influence the calibration performance. Using the to-be-completed SYISR Tristatic System, the performance of plasma line calibration technique is expected to be improved in the future.

Chromosome-level genome assembly of Phrynocephalus forsythii using third-generation DNA sequencing and Hi-C analysis.

Phrynocephalus forsythii is a viviparous sand lizard that endemic to the Tarim Basin with a broad altitudinal range of 872 to 3100 m. Such variation in altitude and ecological variables can offer an opportunity to uncover genetic mechanisms of ectothermic adaptation to extreme environments at high- and low-altitude. Furthermore, the evolutionary relationship of karyotype with two different chromosome numbers (2n=46 or 2n=48) in the Chinese Phrynocephalus is unclear. In this study, a chromosome-level reference genome of P. forsythii was assembled. The genome assembly size was 1.82 Gb with a contig N50 length of 46.22Mb, 20,194 protein-coding genes were predicted and 95.50% of these genes were annotated in functional public databases. After cluster contigs into chromosome level using Hi-C paired-end reads, we found that two chromosomes of P. forsythii were originated from one ancestral chromosome of species with 46 chromosomes. Comparative genomic analysis revealed that numerous characteristics associated with high- or low-altitude adaptation, including energy metabolism pathways, hypoxic adaptation and immune, exhibit rapid changes or show signals of positive selection in the P. forsythii genome. This genome provides an excellent genome resource for the study of the karyotypes evolution and ecological genomics of Phrynocephalus.

Topography intensifies variations in the effect of human activities on forest NPP across altitude and slope gradients

The distribution pattern of forest net primary productivity (NPP) is mainly driven by biotic (climate) and abiotic (topography and human activity) factors. However, the influence of these factors on NPP's distribution along the elevation and slope gradient is uncertain. Additionally, it remains uncertain whether the pattern of NPP at the regional scale with significant altitude variations is comparable to that at the mountain scale. This study analyzed the NPP distribution pattern in the Yangtze River Basin, a region with high altitude heterogeneity, and investigated the impact of climate and human activity on the NPP along the elevation and slope gradient. The results revealed that as altitude increased, NPP first rose and then declined, reaching a peak at 2200–2300 m above sea level, This is in line with the distribution of NPP in mountainous areas and suggests that regions with large elevation differences may also experience vertical effects. NPP displayed an “N” shaped distribution along the slope gradient and the effect of climatic factors varied at different altitudes. Precipitation has a greater effect on NPP than the temperature in regions with less than 2300 m altitude, whereas temperature has the opposite effect in high-elevation regions (>2300 m). The study also found that afforestation and the returning farmland to forestland mainly occurred in low- and middle-altitude regions and middle-slope regions, leading to rapid NPP growth. These findings reveal that topography influences climate and human impacts on forest NPP, and future forest management strategies should consider the terrain's impact on tree growth and protect forests in high-altitude and steep-slope areas.

Measurement of supercooled liquid water path in cold clouds based on a 183GHz airborne microwave radiometer

When flying through clouds that co ntain supercooled liquid water, aircraft can accumulate ice at levels that can be dangerous to flight. Similarly, in the field of weather modification, the amount and distribution of a cloud's supercooled water content is an important indicator of artificial precipitation. The G-band water Vapor Radiometer (GVR) is a small instrument that can be mounted on aircraft. Its operating frequency is highly sensitive to low liquid water content, which is particularly suitable for detecting supercooled water in different parts of clouds during changes in flight position. In order to explore supercooled water, we installed such an instrument with four double-sideband receiver channels centered at 183.31 ± 1, ±3, ±7, and ±14GHz, under the right wing of a King Air B-10KL that we used to perform a series of outfield observations and artificial precipitation missions. In this paper, we discuss the feasibility of detecting supercooled liquid water in the clouds over North China with a GVR. A Back Propagation (BP) neural network algorithm that takes into account flight details including aircraft altitude, climate background and geographic location variations was developed to retrieve supercooled liquid water path (SLWP). A numerical simulation test using the radiosonde data as test samples showed that the retrieval results correlate highly with the radiosonde data calculation results, and that the algorithm was applicable for different seasons and different geographical locations. The algorithm was then applied to the aircraft outfield observations of supercooled liquid water and the results were compared with hotwire, another cloud liquid water observation instrument installed on the aircraft. Results here showed agreement in terms of trend. The observation of SLWPs over clouds thought to be of 0-value shows that the root mean square error of retrieval results is as low as 0.2 g m−2. This paper demonstrates that it is feasible to measure supercooled water over North China with GVR using the retrieval algorithm used here, which obtained good results and is able to compensate for the lack of reliable supercooled water detection instruments on the aircraft.

Different Influences on “Wave Turbopause” Exerted by 6.5 DWs and Gravity Waves

“Wave turbopause” is defined as the mesospheric altitude level where the temperature fluctuation field indicates a substantial increase in wave amplitude in the vertical direction. It is similar to turbopause in seasonal and latitudinal variations, providing an almost global analysis of turbopause on the basis of satellite measurements rather than localized detection. Previous studies of “wave turbopause” were based on standard deviation of temperature, which is an integrated measure of wave activity. In this study, we distinguish different atmospheric waves and investigate their influences on “wave turbopause”. By comparing the altitude of “wave turbopause” with peak height of amplitude (PHA) for gravity waves and 6.5 days waves (6.5 DWs), whose period is approximately 6.5 days in the mesosphere and lower thermosphere, we find that the seasonal variation in altitude of “wave turbopause” is higher at the winter pole and lower at the summer pole, correlated with PHA for 6.5 DWs but anti-correlated with PHA for gravity waves. We infer that gravity waves reach saturation and break at lower altitudes in the winter when Brunt–Vaisala frequency is also lower between 80 and 100 km altitudes. Finally, the results may imply that seasonal variations of the “wave turbopause” are driven mainly by 6.5 DWs.

Signatures of gravity wave-induced instabilities in balloon lidar soundings of polar mesospheric clouds

Abstract. The Balloon Lidar Experiment (BOLIDE), which was part of the Polar Mesospheric Cloud Turbulence (PMC Turbo) Balloon Mission has captured vertical profiles of PMCs during a 6 d flight along the Arctic circle in July 2018. The high-resolution soundings (20 m vertical and 10 s temporal resolution) reveal highly structured layers with large gradients in the volume backscatter coefficient. We systematically screen the BOLIDE dataset for small-scale variability by assessing these gradients at high resolution. We find longer tails of the probability density distributions of these gradients compared to a normal distribution, indicating intermittent behaviour. The high occurrence rate of large gradients is assessed in relation to the 15 min averaged layer brightness and the spectral power of short-period (5–62 min) gravity waves based on PMC layer altitude variations. We find that variability on small scales occurs during weak, moderate, and strong gravity wave activity. Layers with below-average brightness are less likely to show small-scale variability in conditions of strong gravity wave activity. We present and discuss the signatures of this small-scale variability, and possibly related dynamical processes, and identify potential cases for future case studies and modelling efforts.