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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 12405

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Special Issue Editors

Dr. Alexander Kokhanovsky

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Guest Editor

Max Planck Institute for Chemistry, 55128 Mainz, Germany
Interests: cloud remote sensing; aerosol remote sensing; trace gas remote sensing; snow remote sensing; radiative transfer
Special Issues, Collections and Topics in MDPI journals

Dr. Dmitry Efremenko

E-Mail Website
Co-Guest Editor

Remote Sensing Technology Institute, German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany
Interests: radiative transfer; invariant imbedding; discrete ordinate method; synthetic iterations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims at gathering studies covering modern atmospheric remote sensing techniques. The terrestrial atmosphere is studied in various branches of modern science including chemistry, physics, and climatology. An important source of information on the properties of the atmosphere (temperature and pressure profiles, chemical composition, particulate matter load, and cloud properties) is provided by ground-based, airborne, and satellite atmospheric remote sensing techniques. Both passive and active (LiDAR and radar) remote sensing techniques are used. The data derived are important for the monitoring of air quality, weather, and climate change.

Novel techniques for monitoring clouds, atmospheric aerosols, and trace gases are to be discussed in this Special Issue.

The Special Issue will not only accept papers invited by the Editorial Office and Editorial Board Members, but also regular papers that are focused on the topic. Editorial Board Members are welcome to write or co-write articles and are exempt from the article processing charge for this collection.

Topics may cover anything from the advances in classical cloud, aerosol, and trace gas remote sensing techniques based on spectral reflectance measurements, to more comprehensive approaches based on polarimetric and multiangular observations. Multisource data integration (e.g., LiDAR, multispectral, hyperspectral, polarimetric, multiviewing, and thermal) and multiscale approaches or studies focused on terrestrial atmosphere monitoring are welcome. Topics of interest include but are not limited to:

cloud remote sensing;
aerosol remote sensing;
remote sensing of trace gases;
ground-based remote sensing;
satellite remote sensing;
airborne remote sensing;
ship-borne remote sensing;
fog and rain detection;
inverse problems of radiative transfer theory;
inversion theory;
light scattering and absorption by hydrometeors and aerosol particles.

Dr. Alexander Kokhanovsky
Dr. Dmitry Efremenko
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

clouds
atmospheric aerosol
trace gases
remote sensing
radiative transfer
light scattering
light absorption

Published Papers (7 papers)

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Research

7 pages, 9463 KiB

Open AccessCommunication

A Demonstration of Three-Satellite Stereo Winds

by James L. Carr, Jaime Daniels, Dong L. Wu, Wayne Bresky and Bin Tan

Remote Sens. 2022, 14(21), 5290; https://doi.org/10.3390/rs14215290 - 22 Oct 2022

Cited by 2 | Viewed by 1220

Abstract

Stereo tracking of clouds from multiple satellites permits the simultaneous retrieval of an atmospheric motion vector (“wind”) and its height in the atmosphere. The direct measurement of height is a major advantage of stereo methods over observations made from a single satellite where the height must be inferred from infrared brightness temperatures. A pair of operational geostationary satellites over the Americas provides stereo coverage where their two fields of view intersect. Stereo coverage can be extended to nearly a full hemisphere with a third satellite. We demonstrate this configuration with the operational GOES-R constellation of GOES-16 (east) and GOES-17 (west) augmented by GOES-18 in its central test slot and use the 500-m resolution Advanced Baseline Imager Band 2. We examine the consistency of the pairwise products created from GOES-18 and -16 versus GOES-18 and -17 and create a fused triple-GOES product that spans nearly the full hemisphere seen from GOES-18. We also examine the retrieval of ground points observed under clear skies and compare their retrievals to zero speed and known terrain heights. The results are compatible with a wind accuracy about 0.1 m/s with height assignment uncertainty of 175 m. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Terrestrial Atmosphere)

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20 pages, 2627 KiB

Open AccessArticle

The Approximate Analytical Solution for the Top-of-Atmosphere Spectral Reflectance of Atmosphere—Underlying Snow System over Antarctica

by Alexander Kokhanovsky

Remote Sens. 2022, 14(19), 4778; https://doi.org/10.3390/rs14194778 - 24 Sep 2022

Cited by 2 | Viewed by 1329

Abstract

The analytical solutions of the radiative transfer equation are needed for the solution of various applied atmospheric and snow optics problems. In this paper, we propose a simple analytical equation for the top-of-atmosphere (TOA) spectral reflectance. To simplify the problem under study we consider the case of Antarctica, where both snow and atmosphere are almost free of pollutants. This work is focused on the simulation of the moderate spectral resolution TOA measurements (1 nm or so) and the spectral range 400–1000 nm. The values of the coefficient of variance (CV) between the measured by the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3A and modelled spectra are smaller than 10% for most cases in Antarctica. There are regions in Eastern Antarctica, where the values of CV are smaller than 5%. The areas with larger deviations between measured and retrieved spectra could be due to the presence of clouds or structures on the snow surface not captured by the proposed model. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Terrestrial Atmosphere)

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20 pages, 1362 KiB

Open AccessArticle

Long-Term Variation Study of Fine-Mode Particle Size and Regional Characteristics Using AERONET Data

by Juseon Shin, Juhyeon Sim, Naghmeh Dehkhoda, Sohee Joo, Taegyeong Kim, Gahyeong Kim, Detlef Müller, Matthias Tesche, Sung-Kyun Shin, Dongho Shin and Youngmin Noh

Remote Sens. 2022, 14(18), 4429; https://doi.org/10.3390/rs14184429 - 06 Sep 2022

Cited by 2 | Viewed by 1393

Abstract

To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust (

τ_{D}

) and coarse-(

τ_{PC}

) and fine-pollution particles (

τ_{PF}

) depending on emission sources and size. Ångström exponent [...] Read more.

To identify the long-term trend of particle size variation, we analyzed aerosol optical depth (AOD, τ) separated as dust (

τ_{D}

) and coarse-(

τ_{PC}

) and fine-pollution particles (

τ_{PF}

) depending on emission sources and size. Ångström exponent values are also identified separately as total and fine-mode particles (

α_{T}

and

α_{PF}

). We checked these trends in various ways; (1) first-order linear regression analysis of the annual average values, (2) percent variation using the slope of linear regression method, and (3) a reliability analysis using the Mann–Kendall (MK) test. We selected 17 AERONET sun/sky radiometer sites classified into six regions, i.e., Europe, North Africa, the Middle East, India, Southeast Asia, and Northeast Asia. Although there were regional differences, τ decreased in Europe and Asian regions and increased in the Middle East, India, and North Africa. Values of

τ_{PC}

and

τ_{PF}

, show that aerosol loading caused by non-dust aerosols decreased in Europe and Asia and increased in India. In particular,

τ_{PF}

considerably decreased in Europe and Northeast Asia (95% confidential levels in MK-test), and

τ_{PC}

decreased in Northeast Asia (Z-values for Seoul and Osaka are −2.955 and −2.306, respectively, statistically significant if |z| ≥ 1.96). The decrease in

τ_{PC}

seems to be because of the reduction of primary and anthropogenic emissions from regulation by air quality policies. The meaningful result in this paper is that the particle size became smaller, as seen by values of

α_{T}

that decreased by −3.30 to −30.47% in Europe, North Africa, and the Middle East because

α_{T}

provides information on the particle size. Particle size on average became smaller over India and Asian regions considered in our study due to the decrease in coarse particles. In particular, an increase of

α_{PF}

in most areas shows the probability that the average particle size of fine-mode aerosols became smaller in recent years. We presumed the cause of the increase in

α_{T}

is because relatively large-sized fine-mode particles were eliminated due to air quality policies. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Terrestrial Atmosphere)

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15 pages, 2158 KiB

Open AccessEditor’s ChoiceArticle

An Investigation of the Ice Cloud Detection Sensitivity of Cloud Radars Using the Raman Lidar at the ARM SGP Site

by Mingcheng Wang, Kelly A. Balmes, Tyler J. Thorsen, Dylan Willick and Qiang Fu

Remote Sens. 2022, 14(14), 3466; https://doi.org/10.3390/rs14143466 - 19 Jul 2022

Viewed by 1472

Abstract

The ice cloud detection sensitivity of the millimeter cloud radar (MMCR) and the Ka-band Zenith radar (KAZR) is investigated using a collocated Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains site. Only profiles that are transparent to the RL with ice clouds only are considered in this study. The MMCR underestimates the RL ice cloud optical depth (COD) by 20%. The MMCR detects no ice clouds in 37% of the profiles. These profiles where ice cloud goes undetected by the MMCR typically contain very optically thin clouds, with a mean RL ice COD of 0.03. Higher ice cloud detection sensitivity is found for the KAZR, which underestimates the RL ice COD by 15%. The decrease in the ice COD bias for the KAZR compared to the MMCR is largely due to a decrease in the ice COD bias for the situation where the transparent profiles with ice clouds are detected by both the RL and cloud radar. The climatic net ice cloud radiative effects (CREs) from the RL at the top of the atmosphere (TOA) and the surface are 3.2 W m⁻² and −0.6 W m⁻², respectively. The ice CREs at the TOA and surface are underestimated for the MMCR by 0.7 W m⁻² and 0.16 W m⁻² (21% and 29%) and underestimated for the KAZR by 0.6 W m⁻² and 0.14 W m⁻² (17% and 24%). The ice clouds undetected by the cloud radars led to underestimating the climatic net cloud heating rates below 150 hPa by about 0–0.04 K day⁻¹. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Terrestrial Atmosphere)

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Graphical abstract

15 pages, 4052 KiB

Open AccessArticle

Aerosol Distributions and Sahara Dust Transport in Southern Morocco, from Ground-Based and Satellite Observations

by Hassan Bencherif, Aziza Bounhir, Nelson Bègue, Tristan Millet, Zouhair Benkhaldoun, Kévin Lamy, Thierry Portafaix and Fouad Gadouali

Remote Sens. 2022, 14(10), 2454; https://doi.org/10.3390/rs14102454 - 20 May 2022

Cited by 3 | Viewed by 2339

Abstract

The present study investigates aerosols distributions and a strong Sahara dust-storm event that occurred by early August 2018, in the South of Morocco. We used columnar aerosol optical depth (AOD), Angstrom Exponent (AE) and volume size distributions (VSD) as derived from ground-based observations by 2 AERONET (AErosol RObotic NETwork) sun-photometers at Saada (31.63°N, 8.16°W) and Ouarzazate (30.93°N, 6.91°W) sites, over the periods 2004–2019 and 2012–2015, respectively. The monthly seasonal distributions of AOD, AE, and VSD showed a seasonal trend dominated by the annual cycle, with a maximum aerosol load during summer (July–August) and a minimum in winter (December–January), characterized by a coarse mode near the radius of 2.59 μm and a fine mode at the radius of 0.16 μm, respectively. Indeed, this study showed that aerosol populations in southern Morocco are dominated by Saharan desert dust, especially during the summer season. The latter can sometimes be subject of dust-storm events. The case study presented in this paper reports on one of these events, which happened in early August 2018. The HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model was used to simulate air-mass back-trajectories during the event. In agreement with ground-based (AERONET sun-photometers) and satellite (CALIOP, MODIS and AIRS) observations, HYSPLIT back-trajectories showed that the dust air-mass at the 4-km layer, the average height of the dust plume, has crossed southern Morocco over the Saada site, with a westward direction towards the Atlantic Ocean, before it changed northward up to the Portuguese coasts. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Terrestrial Atmosphere)

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18 pages, 7560 KiB

Open AccessArticle

Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models

by Makiko Nakata, Itaru Sano, Sonoyo Mukai and Alexander Kokhanovsky

Remote Sens. 2022, 14(10), 2344; https://doi.org/10.3390/rs14102344 - 12 May 2022

Cited by 8 | Viewed by 1782

Abstract

The severity of wildfires is increasing globally. In this study, we used data from the Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C/SGLI) to characterize the biomass burning aerosols that are generated by large-scale wildfires. We used data from the September 2020 wildfires in western North America. The target area had a complex topography, comprising a basin among high mountains along a coastal region. The SGLI was essential for dealing with the complex topographical changes in terrain that we encountered, as it contains 19 polarization channels ranging from near ultraviolet (380 nm and 412 nm) to thermal infrared (red at 674 nm and near-infrared at 869 nm) and has a fine spatial resolution (1 km). The SGLI also proved to be efficient in the radiative transfer simulations of severe wildfires through the mutual use of polarization and radiance. We used a regional numerical model SCALE (Scalable Computing for Advanced Library and Environment) to account for variations in meteorological conditions and/or topography. Ground-based aerosol measurements in the target area were sourced from the National Aeronautics and Space Administration-Aerosol Robotic Network; currently, official satellite products typically do not provide the aerosol properties for very optically thick cases of wildfires. This paper used satellite observations, ground-based observations, and a meteorological model to define an algorithm for retrieving the aerosol properties caused by severe wildfire events. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Terrestrial Atmosphere)

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23 pages, 2618 KiB

Open AccessArticle

Atmospheric Conditions within Big Telescope Alt-Azimuthal Region and Possibilities of Astronomical Observations

by Artem Yu. Shikhovtsev, Pavel G. Kovadlo, Vladimir B. Khaikin, Victor V. Nosov, Vladimir P. Lukin, Eugene V. Nosov, Andrey V. Torgaev, Alexander V. Kiselev and Maxim Yu. Shikhovtsev

Remote Sens. 2022, 14(8), 1833; https://doi.org/10.3390/rs14081833 - 11 Apr 2022

Cited by 9 | Viewed by 1929

Abstract

The paper presents the results of analysis of astroclimatic conditions in the Big Telescope Alt-azimuthal (BTA) region (40

°

N–50

°

N; 35

°

E–55

°

E). Using data from the European center for medium-range weather forecast ReAnalysis (ERA-5), we estimated the averaged [...] Read more.

The paper presents the results of analysis of astroclimatic conditions in the Big Telescope Alt-azimuthal (BTA) region (40

°

N–50

°

N; 35

°

E–55

°

E). Using data from the European center for medium-range weather forecast ReAnalysis (ERA-5), we estimated the averaged spatial distributions in total cloud cover, vertical integral of mean kinetic energy, vertical component of wind speed, and wind speed shears, as well as inverse values of Richardson number

1 / R i

. An extensive region with the development of atmospheric flows is formed south and southeast of BTA in winter. High inverse values of the Richardson number, spatial heterogeneities in vertical wind speed, and significant wind speed shears in the lower atmosphere are observed in this region. In terms of turbulence development over BTA, the best time for astronomical observations falls in summer, when vertical shears of wind speed are weakened in the lower atmospheric layers. The situation is opposite in the upper troposphere. In winter, BTA is in the region of moderate vertical wind shears. In summer, a region with increased vertical wind speed shears is formed. Taking into account that the intensity of optical turbulence decreases rapidly with height, better image quality can be expected in summer. Such structure of the atmosphere does not allow one to directly apply atmospheric models in order to describe turbulence based on the turbulence strength as function of its ground values, or to use the classical model describing the turbulence velocity as function of air flow velocity at the height corresponding to the 200 hPa level. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Terrestrial Atmosphere)

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