Daytime lidar measurements of the sodium layer in China

Abstract. This paper presents a climatology of the mesospheric sodium layer built from the processing of 7 years of GOMOS data. With respect to preliminary results already published for the year 2003, a more careful analysis was applied to the averaging of occultations inside the climatological bins (10° in latitude-1 month). Also, the slant path absorption lines of the Na doublet around 589 nm shows evidence of partial saturation that was responsible for an underestimation of the Na concentration in our previous results. The sodium climatology has been validated with respect to the Fort Collins lidar measurements and, to a lesser extent, to the OSIRIS 2003–2004 data. Despite the important natural sodium variability, we have shown that the Na vertical column has a marked semi-annual oscillation at low latitudes that merges into an annual oscillation in the polar regions,a spatial distribution pattern that was unreported so far. The sodium layer seems to be clearly influenced by the mesospheric global circulation and the altitude of the layer shows clear signs of subsidence during polar winter. The climatology has been parameterized by time-latitude robust fits to allow for easy use. Taking into account the non-linearity of the transmittance due to partial saturation, an experimental approach is proposed to derive mesospheric temperatures from limb remote sounding measurements.

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A global climatology of the mesospheric sodium layer from GOMOS data during the 2002–2008 period

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-10-6097-2010 ◽

2010 ◽

Vol 10 (3) ◽

pp. 6097-6127 ◽

Cited By ~ 4

Author(s):

D. Fussen ◽

F. Vanhellemont ◽

C. Tétard ◽

N. Mateshvili ◽

E. Dekemper ◽

...

Keyword(s):

Careful Analysis ◽

Polar Regions ◽

Partial Saturation ◽

Vertical Column ◽

Global Circulation ◽

Sodium Layer ◽

Remote Sounding ◽

Lidar Measurements ◽

Low Latitudes ◽

Fort Collins

Abstract. This paper presents a climatology of the mesospheric sodium layer built from the processing of 7 years of GOMOS data. With respect to preliminary results already published for the year 2003, a more careful analysis was applied to the averaging of occultations inside the climatological bins (10° in latitude-1 month). Also, the slant path absorption lines of the Na doublet around 589 nm shows evidence of partial saturation that was responsible for an underestimation of the Na concentration in our previous results. The sodium climatology has been validated with respect to the Fort Collins lidar measurements and, to a lesser extent, to the OSIRIS 2003–2004 data. Despite the important natural sodium variability, we have shown that the Na vertical column has a marked semi-annual oscillation at low latitudes that merges into an annual oscillation in the polar regions, a spatial distribution pattern that was unreported so far. The sodium layer seems to be clearly influenced by the mesospheric global circulation and the altitude of the layer shows clear signs of subsidence during polar winter. The climatology has been parameterized by time-latitude robust fits to allow for easy use. Taking into account the non-linearity of the transmittance due to partial saturation, an experimental approach is proposed to derive mesospheric temperatures from limb remote sounding measurements.

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Simultaneous lidar measurements of the sodium layer at the Air Force Geophysics Laboratory and the University of Illinois

Journal of Geophysical Research Atmospheres ◽

10.1029/ja091ia11p12131 ◽

1986 ◽

Vol 91 (A11) ◽

pp. 12131 ◽

Cited By ~ 7

Author(s):

C. S. Gardner ◽

D. G. Voelz ◽

C. R. Philbrick ◽

D. P. Sipler

Keyword(s):

Air Force ◽

University Of Illinois ◽

Sodium Layer ◽

Lidar Measurements ◽

The University

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Mesospheric fronts in airglow images and the variation of the bottomside sodium layer densities measured by a sodium lidar at Tromsø, Norway

10.5194/egusphere-egu2020-5218 ◽

2020 ◽

Author(s):

Viswanathan Lakshmi Narayanan ◽

Satonori Nozawa ◽

Ingrid Mann ◽

Shin-ichiro Oyama ◽

Kazuo Shiokawa ◽

...

Keyword(s):

Signal Strength ◽

Pass Band ◽

Wave Dynamics ◽

Sodium Layer ◽

Lidar Measurements ◽

Intensity Changes ◽

Frontal Systems ◽

The Relationship ◽

Airglow Intensity ◽

Frontal Boundary

<p>Mesospheric frontal systems are waves extending to hundreds of kilometers along their phase fronts and appear like a boundary. They are observed in the upper mesospheric airglow imaging observations of OH, sodium and OI greenline nightglow emissions. It is believed that the fronts result from gravity wave dynamics associated with favorable background conditions like thermal ducting. Many of the frontal systems are identified as mesospheric bores when they are accompanied with sudden airglow intensity changes across the frontal boundary. Most of the frontal systems propagate with phase locked undulations following the leading front, while some induce turbulence behind the front. Though the existence of the frontal systems in the mesosphere is known for more than two decades, their role and importance is not understood properly. In this work, we use airglow data from an all-sky imager located at Troms&#248; to identify the frontal systems, particularly using OH images. Collocated five-beam sodium lidar measurements are used to identify the structuring in sodium densities around time of passage of the frontal systems. The sodium lidar at Troms&#248; is a versatile system capable of measuring sodium densities, temperatures and winds in the upper mesospshere region. Hence, we obtain the wind and temperature information to study the background conditions during passage of the intense frontal systems. Though, mostly we focus on OH airglow images as they are observed with broad pass band resulting in higher signal strength, we also utilize images from other emissions like OI greenline and sodium whenever they are available and free from auroral features. Interestingly, we find formation of some unusual structuring in the bottomside sodium layer around the passage of the frontal systems. We show different cases during winter months of the years 2013-14 and 2014-15 and investigate the relationship between unusual bottomside structuring in the sodium layer and passage of the frontal systems.</p>

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Large-eddy simulations and lidar measurements of vortex-pair breakup in aircraft wakes

AIAA Journal ◽

10.2514/3.13987 ◽

1998 ◽

Vol 36 ◽

pp. 1439-1445 ◽

Cited By ~ 2

Author(s):

D. C. Lewellen ◽

W. S. Lewellen ◽

L. R. Poole ◽

C. A. Hostetler ◽

R. J. DeCoursey ◽

...

Keyword(s):

Vortex Pair ◽

Large Eddy Simulations ◽

Large Eddy ◽

Lidar Measurements

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Using Machine Learning Methods to Identify Particle Types from Doppler Lidar Measurements in Iceland

Remote Sensing ◽

10.3390/rs13132433 ◽

2021 ◽

Vol 13 (13) ◽

pp. 2433

Author(s):

Shu Yang ◽

Fengchao Peng ◽

Sibylle von Löwis ◽

Guðrún Nína Petersen ◽

David Christian Finger

Keyword(s):

Machine Learning ◽

Weather Conditions ◽

Dust Storms ◽

Machine Learning Algorithms ◽

Lidar Data ◽

Data Sets ◽

Doppler Lidar ◽

Lidar Measurements ◽

Using Data ◽

Filter Noise

Doppler lidars are used worldwide for wind monitoring and recently also for the detection of aerosols. Automatic algorithms that classify the lidar signals retrieved from lidar measurements are very useful for the users. In this study, we explore the value of machine learning to classify backscattered signals from Doppler lidars using data from Iceland. We combined supervised and unsupervised machine learning algorithms with conventional lidar data processing methods and trained two models to filter noise signals and classify Doppler lidar observations into different classes, including clouds, aerosols and rain. The results reveal a high accuracy for noise identification and aerosols and clouds classification. However, precipitation detection is underestimated. The method was tested on data sets from two instruments during different weather conditions, including three dust storms during the summer of 2019. Our results reveal that this method can provide an efficient, accurate and real-time classification of lidar measurements. Accordingly, we conclude that machine learning can open new opportunities for lidar data end-users, such as aviation safety operators, to monitor dust in the vicinity of airports.

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