Seasonal and intra-diurnal variability of small-scale gravity waves in OH airglow at two Alpine stations

Abstract. Between December 2013 and August 2017 the instrument FAIM (Fast Airglow IMager) observed the OH airglow emission at two Alpine stations. A year of measurements was performed at Oberpfaffenhofen, Germany (48.09∘ N, 11.28∘ E) and 2 years at Sonnblick, Austria (47.05∘ N, 12.96∘ E). Both stations are part of the network for the detection of mesospheric change (NDMC). The temporal resolution is two frames per second and the field-of-view is 55 km × 60 km and 75 km × 90 km at the OH layer altitude of 87 km with a spatial resolution of 200 and 280 m per pixel, respectively. This resulted in two dense data sets allowing precise derivation of horizontal gravity wave parameters. The analysis is based on a two-dimensional fast Fourier transform with fully automatic peak extraction. By combining the information of consecutive images, time-dependent parameters such as the horizontal phase speed are extracted. The instrument is mainly sensitive to high-frequency small- and medium-scale gravity waves. A clear seasonal dependency concerning the meridional propagation direction is found for these waves in summer in the direction to the summer pole. The zonal direction of propagation is eastwards in summer and westwards in winter. Investigations of the data set revealed an intra-diurnal variability, which may be related to tides. The observed horizontal phase speed and the number of wave events per observation hour are higher in summer than in winter.

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Seasonal and intra-diurnal variability of small-scale gravity waves in OH airglow at two Alpine stations

10.5194/amt-2018-322 ◽

2018 ◽

Author(s):

Patrick Hannawald ◽

Carsten Schmidt ◽

René Sedlak ◽

Sabine Wüst ◽

Michael Bittner

Keyword(s):

Gravity Waves ◽

High Frequency ◽

Phase Speed ◽

Propagation Direction ◽

Field Of View ◽

Small Scale ◽

Data Set ◽

Diurnal Variability ◽

Fully Automatic ◽

One Year

Abstract. Between December 2013 and August 2017 the instrument FAIM (Fast Airglow IMager) observed the OH airglow emission at two Alpine stations. One year of measurements was performed at Oberpfaffenhofen, Germany (48.09° N, 11.28° E) and two years at Sonnblick, Austria (47.05° N, 12.96° E). Both stations are part of the Network for the detection of mesospheric change (NDMC). The temporal resolution is two frames per second and the field of view is 55 km × 60 km and 75 km × 90 km at the OH layer altitude of 87 km with a spatial resolution of 200 m and 280 m per pixel, respectively. This results in two dense datasets allowing precise derivation of horizontal gravity wave parameters. The analysis is based on a two-dimensional Fast Fourier Transform with fully automatic peak extraction. By combining the information of consecutive images time-dependent parameters such as the horizontal phase speed are extracted. The instrument is mainly sensitive to high-frequency small- and medium-scale gravity waves. A clear seasonal dependency concerning the meridional propagation direction is found for these waves in summer in direction to the summer pole. The zonal direction of propagation is eastwards in summer and westwards in winter. Investigations of the data set revealed an intra-diurnal variability, which may be related to tides. The observed horizontal phase speed and the number of wave events per observation hour are higher in summer than in winter.

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Gravity Wave Investigations over Comandante Ferraz Antarctic Station in 2017: General Characteristics, Wind Filtering and Case Study

Atmosphere ◽

10.3390/atmos11080880 ◽

2020 ◽

Vol 11 (8) ◽

pp. 880

Author(s):

Gabriel Augusto Giongo ◽

José Valentin Bageston ◽

Cosme Alexandre Oliveira Barros Figueiredo ◽

Cristiano Max Wrasse ◽

Hosik Kam ◽

...

Keyword(s):

Gravity Wave ◽

Gravity Waves ◽

Phase Speed ◽

Propagation Direction ◽

Small Scale ◽

Wave Source ◽

Medium Scale ◽

Reliable Source ◽

The Fourier Transform

This work presents the characteristics of gravity waves observed over Comandante Ferraz Antarctic Station (EACF: 62.1° S, 58.4° W). A total of 122 gravity waves were observed in 34 nights from March to October 2017, and their parameters were obtained by using the Fourier Transform spectral analysis. The majority of the observed waves presented horizontal wavelength ranging from 15 to 35 km, period from 5 to 20 min, and horizontal phase speed from 10 to 70 ± 2 m·s−1. The propagation direction showed an anisotropic condition, with the slower wave propagating mainly to the west, northwest and southeast directions, while the faster waves propagate to the east, southeast and south. Blocking diagrams for the period of April–July showed a good agreement between the wave propagation direction and the blocking positions, which are eastward oriented while the waves propagate mainly westward. A case study to investigate wave sources was conducted for the night of 20–21 July, wherein eight small-scale and one medium-scale gravity waves were identified. Reverse ray tracing model was used to investigate the gravity wave source, and the results showed that six among eight small-scale gravity waves were generated in the mesosphere. On the other hand, only two small-scale waves and the medium-scale gravity wave had likely tropospheric or stratospheric origin, however, they could not be associated with any reliable source.

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Density Fluctuations in the Lower Thermosphere of Mars Retrieved From the ExoMars Trace Gas Orbiter (TGO) Aerobraking

Atmosphere ◽

10.3390/atmos10100620 ◽

2019 ◽

Vol 10 (10) ◽

pp. 620 ◽

Cited By ~ 2

Author(s):

David Jesch ◽

Alexander S. Medvedev ◽

Francesco Castellini ◽

Erdal Yiğit ◽

Paul Hartogh

Keyword(s):

Gravity Waves ◽

Lower Thermosphere ◽

Wave Activity ◽

Density Fluctuations ◽

Statistical Characteristics ◽

Trace Gas ◽

Small Scale ◽

Data Set ◽

Diurnal Variability ◽

Winter Hemisphere

The upper atmosphere of Mars is constantly perturbed by small-scale gravity waves propagating from below. As gravity waves strongly affect the large-scale dynamics and thermal state, constraining their statistical characteristics is of great importance for modeling the atmospheric circulation. We present a new data set of density perturbation amplitudes derived from accelerometer measurements during aerobraking of the European Space Agency’s Trace Gas Orbiter. The obtained data set presents features found by three previous orbiters: the lower thermosphere polar warming in the winter hemisphere, and the lack of links between gravity wave activity and topography. In addition, the orbits allowed for demonstrating a very weak diurnal variability in wave activity at high latitudes of the southern winter hemisphere for the first time. The estimated vertical damping rates of gravity waves agree well with theoretical predictions. No clear anticorrelation between perturbation amplitudes and the background temperature has been found. This indicates differences in dissipation mechanisms of gravity waves in the lower and upper thermosphere.

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Evidence for tropospheric wind shear excitation of high-phase-speed gravity waves reaching the mesosphere using the ray-tracing technique

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-2709-2015 ◽

2015 ◽

Vol 15 (5) ◽

pp. 2709-2721 ◽

Cited By ~ 24

Author(s):

M. Pramitha ◽

M. Venkat Ratnam ◽

A. Taori ◽

B. V. Krishna Murthy ◽

D. Pallamraju ◽

...

Keyword(s):

Ray Tracing ◽

Gravity Waves ◽

High Frequency ◽

Phase Speed ◽

Horizontal Wind ◽

Climatological Model ◽

Background Temperature ◽

The Waves ◽

High Phase ◽

Mf Radar

Abstract. Sources and propagation characteristics of high-frequency gravity waves observed in the mesosphere using airglow emissions from Gadanki (13.5° N, 79.2° E) and Hyderabad (17.5° N, 78.5° E) are investigated using reverse ray tracing. Wave amplitudes are also traced back, including both radiative and diffusive damping. The ray tracing is performed using background temperature and wind data obtained from the MSISE-90 and HWM-07 models, respectively. For the Gadanki region, the suitability of these models is tested. Further, a climatological model of the background atmosphere for the Gadanki region has been developed using nearly 30 years of observations available from a variety of ground-based (MST radar, radiosondes, MF radar) and rocket- and satellite-borne measurements. ERA-Interim products are utilized for constructing background parameters corresponding to the meteorological conditions of the observations. With the reverse ray-tracing method, the source locations for nine wave events could be identified to be in the upper troposphere, whereas for five other events the waves terminated in the mesosphere itself. Uncertainty in locating the terminal points of wave events in the horizontal direction is estimated to be within 50–100 km and 150–300 km for Gadanki and Hyderabad wave events, respectively. This uncertainty arises mainly due to non-consideration of the day-to-day variability in the tidal amplitudes. Prevailing conditions at the terminal points for each of the 14 events are provided. As no convection in and around the terminal points is noticed, convection is unlikely to be the source. Interestingly, large (~9 m s−1km−1) vertical shears in the horizontal wind are noticed near the ray terminal points (at 10–12 km altitude) and are thus identified to be the source for generating the observed high-phase-speed, high-frequency gravity waves.

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Gravity wave transmission diagram

Annales Geophysicae ◽

10.5194/angeo-33-1479-2015 ◽

2015 ◽

Vol 33 (12) ◽

pp. 1479-1484 ◽

Cited By ~ 5

Author(s):

Y. Tomikawa

Keyword(s):

Gravity Wave ◽

Gravity Waves ◽

Phase Speed ◽

Propagation Direction ◽

Wave Transmission ◽

Vertical Shear ◽

Horizontal Wind ◽

Wave Power ◽

Power Spectral ◽

Horizontal Wavelength

Abstract. A new method of obtaining power spectral distribution of gravity waves as a function of ground-based horizontal phase speed and propagation direction from airglow observations has recently been proposed. To explain gravity wave power spectrum anisotropy, a new gravity wave transmission diagram was developed in this study. Gravity wave transmissivity depends on the existence of critical and turning levels for waves that are determined by background horizontal wind distributions. Gravity wave transmission diagrams for different horizontal wavelengths in simple background horizontal winds with constant vertical shear indicate that the effects of the turning level reflection are significant and strongly dependent on the horizontal wavelength.

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Clusterdv, a simple density-based clustering method that is robust, general and automatic

10.1101/224840 ◽

2017 ◽

Author(s):

João C. Marques ◽

Michael B. Orger

Keyword(s):

Clustering Algorithm ◽

Underlying Structure ◽

Data Sets ◽

Natural Phenomena ◽

Cluster Number ◽

Data Set ◽

Density Peaks ◽

Wide Range ◽

Cluster Shape ◽

Fully Automatic

AbstractHow to partition a data set into a set of distinct clusters is a ubiquitous and challenging problem. The fact that data varies widely in features such as cluster shape, cluster number, density distribution, background noise, outliers and degree of overlap, makes it difficult to find a single algorithm that can be broadly applied. One recent method, clusterdp, based on search of density peaks, can be applied successfully to cluster many kinds of data, but it is not fully automatic, and fails on some simple data distributions. We propose an alternative approach, clusterdv, which estimates density dips between points, and allows robust determination of cluster number and distribution across a wide range of data, without any manual parameter adjustment. We show that this method is able to solve a range of synthetic and experimental data sets, where the underlying structure is known, and identifies consistent and meaningful clusters in new behavioral data.Author summarIt is common that natural phenomena produce groupings, or clusters, in data, that can reveal the underlying processes. However, the form of these clusters can vary arbitrarily, making it challenging to find a single algorithm that identifies their structure correctly, without prior knowledge of the number of groupings or their distribution. We describe a simple clustering algorithm that is fully automatic and is able to correctly identify the number and shape of groupings in data of many types. We expect this algorithm to be useful in finding unknown natural phenomena present in data from a wide range of scientific fields.

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Early results from the Whisper instrument on Cluster: an overview

Annales Geophysicae ◽

10.5194/angeo-19-1241-2001 ◽

2001 ◽

Vol 19 (10/12) ◽

pp. 1241-1258 ◽

Cited By ~ 116

Author(s):

P. M. E. Décréau ◽

P. Fergeau ◽

V. Krasnoselskikh ◽

E. Le Guirriec ◽

M. Lévêque ◽

...

Keyword(s):

Electron Density ◽

Small Scale ◽

Data Sets ◽

Total Density ◽

Total Electron Density ◽

Data Set ◽

Total Electron ◽

Density Data ◽

Early Results ◽

Natural Emissions

Abstract. The Whisper instrument yields two data sets: (i) the electron density determined via the relaxation sounder, and (ii) the spectrum of natural plasma emissions in the frequency band 2–80 kHz. Both data sets allow for the three-dimensional exploration of the magnetosphere by the Cluster mission. The total electron density can be derived unambiguously by the sounder in most magnetospheric regions, provided it is in the range of 0.25 to 80 cm-3 . The natural emissions already observed by earlier spacecraft are fairly well measured by the Whisper instrument, thanks to the digital technology which largely overcomes the limited telemetry allocation. The natural emissions are usually related to the plasma frequency, as identified by the sounder, and the combination of an active sounding operation and a passive survey operation provides a time resolution for the total density determination of 2.2 s in normal telemetry mode and 0.3 s in burst mode telemetry, respectively. Recorded on board the four spacecraft, the Whisper density data set forms a reference for other techniques measuring the electron population. We give examples of Whisper density data used to derive the vector gradient, and estimate the drift velocity of density structures. Wave observations are also of crucial interest for studying small-scale structures, as demonstrated in an example in the fore-shock region. Early results from the Whisper instrument are very encouraging, and demonstrate that the four-point Cluster measurements indeed bring a unique and completely novel view of the regions explored.Key words. Space plasma physics (instruments and techniques; discontinuities, general or miscellaneous)

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Apple Disease Recognition Based on Small-scale Data Sets

Applied Engineering in Agriculture ◽

10.13031/aea.14187 ◽

2021 ◽

Vol 37 (3) ◽

pp. 481-490

Author(s):

Chenyong Song ◽

Dongwei Wang ◽

Haoran Bai ◽

Weihao Sun

Keyword(s):

Identification Accuracy ◽

Model Complexity ◽

Geometric Transformation ◽

Small Scale ◽

Model Parameters ◽

Data Sets ◽

List Type ◽

Data Set ◽

Disease Identification ◽

Scale Data

HighlightsThe proposed data enhancement method can be used for small-scale data sets with rich sample image features.The accuracy of the new model reaches 98.5%, which is better than the traditional CNN method.Abstract: GoogLeNet offers far better performance in identifying apple disease compared to traditional methods. However, the complexity of GoogLeNet is relatively high. For small volumes of data, GoogLeNet does not achieve the same performance as it does with large-scale data. We propose a new apple disease identification model using GoogLeNet’s inception module. The model adopts a variety of methods to optimize its generalization ability. First, geometric transformation and image modification of data enhancement methods (including rotation, scaling, noise interference, random elimination, color space enhancement) and random probability and appropriate combination of strategies are used to amplify the data set. Second, we employ a deep convolution generative adversarial network (DCGAN) to enhance the richness of generated images by increasing the diversity of the noise distribution of the generator. Finally, we optimize the GoogLeNet model structure to reduce model complexity and model parameters, making it more suitable for identifying apple tree diseases. The experimental results show that our approach quickly detects and classifies apple diseases including rust, spotted leaf disease, and anthrax. It outperforms the original GoogLeNet in recognition accuracy and model size, with identification accuracy reaching 98.5%, making it a feasible method for apple disease classification. Keywords: Apple disease identification, Data enhancement, DCGAN, GoogLeNet.

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Parameters of internal gravity waves in the mesosphere-lower thermosphere region derived from meteor radar wind measurements

Annales Geophysicae ◽

10.5194/angeo-23-3431-2005 ◽

2005 ◽

Vol 23 (11) ◽

pp. 3431-3437 ◽

Cited By ~ 6

Author(s):

A. N. Oleynikov ◽

Ch. Jacobi ◽

D. M. Sosnovchik

Keyword(s):

Gravity Waves ◽

High Frequency ◽

Lower Thermosphere ◽

Radar Data ◽

Internal Gravity Waves ◽

Meteor Radar ◽

Energy Propagation ◽

Data Set ◽

Wind Measurements ◽

Phase Progression

Abstract. A procedure of revealing parameters of internal gravity waves from meteor radar wind measurements is presented. The method is based on dividing the measuring volume into different parts and, using wavelet analysis, calculating the phase progression of frequency peaks in the vertical and horizontal direction. Thus, the distribution of vertical and horizontal wavelengths and directions of IGW energy propagation, using meteor radar data, has been obtained. The method was applied to a 4-month data set obtained in July and August, 1998 and 1999. As expected, the majority of waves have been found to propagate upwards, although a considerable number seem to propagate downwards as well. High-frequency (intrinsic periods T* of less than 2 h) waves are dominating. The distribution of waves over the course of an average day is only weakly structured, with weak maxima in the morning and evening.

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Spatial and temporal analysis of high-frequency internal gravity wave signatures in brightness temperature satellite images

10.5194/egusphere-egu21-1609 ◽

2021 ◽

Author(s):

Robert Vicari

Keyword(s):

Water Vapor ◽

Brightness Temperature ◽

Gravity Wave ◽

Gravity Waves ◽

High Frequency ◽

Satellite Images ◽

Internal Gravity Wave ◽

Internal Gravity Waves ◽

Small Scale ◽

Wave Patterns

Highly idealized model studies suggest that convectively generated internal gravity waves in the troposphere with horizontal wavelengths on the order of a few kilometers may affect the lifetime, spacing, and depth of clouds and convection. To answer whether such a convection-wave coupling occurs in the real atmosphere, one needs to find corresponding events in observations. In general, the study of high-frequency internal gravity wave-related phenomena in the troposphere is a challenging task because they are usually small-scale and intermittent. To overcome case-by-case studies, it is desirable to have an automatic method to analyze as much data as possible and provide enough independent and diverse evidence. Here, we focus on brightness temperature satellite images, in particular so-called satellite water vapor channels. These channels measure the radiation at wavelengths corresponding to the energy emitted by water vapor and provide cloud-independent observations of internal gravity waves, in contrast to visible and other infrared satellite channels where one relies on the wave impacts on clouds. In addition, since these water vapor channels are sensitive to certain vertical layers in the troposphere, combining the images also reveals some vertical structure of the observed waves. We propose an algorithm based on local Fourier analyses to extract information about high-frequency wave patterns in given brightness temperature images. This method allows automatic detection and analysis of many wave patterns in a given domain at once, resulting in a climatology that provides an initial observational basis for further research. Using data from the instrument ABI on board the satellite GOES-16 during the field campaign EUREC4A, we demonstrate the capabilities and limitations of the method. Furthermore, we present the respective climatology of the detected waves and discuss approaches based on this to address the initial question.

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