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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 36101

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Prof. Dr. Gerrit de Leeuw

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Royal Netherlands Meteorological Institute (KNMI), R & D Satellite Observations, 3731 GA De Bilt, The Netherlands
Interests: aerosols; satellite remotes sensing; air quality; climate; aerosol-cloud interaction; sea spray aerosol
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Dear Colleagues,

Atmospheric composition and meteorology play a key role in many different processes that determine, or influence, climate, climate change, air quality, UV index, renewable energy, water balance, nitrogen and carbon cycles, and weather, to name but a few. The observation of variables such as solar radiation, clouds, aerosols, trace gases, greenhouse gases, water vapor, precipitation, meteorological parameters, etc. is therefore essential to understand the underlying atmospheric processes, feedback mechanisms, and effects on the state of the atmosphere, as well as the interaction with the biosphere, cryosphere, land, oceans, socioeconomic aspects, and health.

This Collection offers a platform to present and discuss the development and application of remote sensing techniques toward improving our knowledge and understanding of the atmosphere, atmospheric processes, and their effects on a wide variety of applications.

Prof. Gerrit de Leeuw
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Published Papers (9 papers)

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18 pages, 2227 KiB

Open AccessArticle

A Motion-Correction Method for Turbulence Estimates from Floating Lidars

by Alfredo Peña, Jakob Mann, Nikolas Angelou and Arnhild Jacobsen

Remote Sens. 2022, 14(23), 6065; https://doi.org/10.3390/rs14236065 - 30 Nov 2022

Cited by 4 | Viewed by 1959

Abstract

Estimates of atmospheric turbulence performed by both fixed and floating vertically profiling, conically scanning wind lidars are affected by the measurement volume and turbulence structure, among others. We study this phenomenon by simulating the lidar measurements within synthetic fields of atmospheric turbulence. We use the simulations’ framework to assess the impact of buoy motions on turbulence estimation. Simulation results show that the buoy’s translational motions impact turbulence estimates the most. We also apply the simulation framework to analyze measurements from a floating lidar measuring nearby an offshore meteorological mast for a period of six months. The analysis of measurements is presented both without and with motion compensation. In general, we find from both simulations and measurements that the buoy motions do not impact the mean horizontal wind speed significantly, in agreement with previous studies. However, both simulations and measurements show that the standard deviation of the horizontal velocity is overestimated by the floating lidar. When we correct the measurements based on compensation factors derived from the simulations, the mean bias of the horizontal wind speed standard deviation changes from 18–19% to 5–21%, with large reductions at the first four heights closest to the surface and a slight increase at the highest vertical level. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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22 pages, 5030 KiB

Open AccessArticle

Evaluation of Aerosol Typing with Combination of Remote Sensing Techniques with In Situ Data during the PANACEA Campaigns in Thessaloniki Station, Greece

by Kalliopi Artemis Voudouri, Konstantinos Michailidis, Nikolaos Siomos, Anthi Chatzopoulou, Georgios Kouvarakis, Nikolaos Mihalopoulos, Paraskevi Tzoumaka, Apostolos Kelessis and Dimitrios Balis

Remote Sens. 2022, 14(20), 5076; https://doi.org/10.3390/rs14205076 - 11 Oct 2022

Cited by 2 | Viewed by 1666

Abstract

Two measurement campaigns were conducted at Thessaloniki, an urban station, (40.5°N, 22.9°E; 60 m) in the frame of the PANhellenic infrastructure for Atmospheric Composition and climatEchAnge (PANACEA) project. The first one covers the period from July to August 2019 and the second one from January to February An overview of the aerosol optical properties (columnar and height resolved), acquired with the remote sensing infrastructure of the Laboratory of Atmospheric Physics (LAP) of the Aristotle University of Thessaloniki (AUTH), as well as the additional instrumentation that participated during the PANACEA campaigns is presented. The majority of the detected layers (16 out of 40, ranged between 0.8 and 4.5 km) are classified as biomass burning aerosols, attributed to either city sources or long range transport. Concerning the other aerosol types, the Clean Continental cluster has an occurrence ratio of 23%, while dust layers and mixtures with urban particles transported to Thessaloniki are also identified. Our findings are discussed along with the surface information, i.e., the particulate matter (PM2.5 and PM10) concentrations and the black carbon (BC) concentration, separated into fossil fuel (BC_ff) and biomass/wood burning (BC_wb) fractions. This is the first time that collocated in situ and remote sensing instruments are deployed in Thessaloniki in order to assess the presence of aerosols and the predominant aerosol type both in situ and at elevated heights. Overall, our study showed that the BC_wb contribution to the BC values in Thessaloniki is quite low (11%), whilst the majority of the biomass burning layers identified with the lidar system, are also linked with enhanced BC contribution and high Fine Mode Fraction values. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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24 pages, 14109 KiB

Open AccessArticle

Comparison of S5P/TROPOMI Inferred NO₂ Surface Concentrations with In Situ Measurements over Central Europe

by Andreas Pseftogkas, Maria-Elissavet Koukouli, Arjo Segers, Astrid Manders, Jos van Geffen, Dimitris Balis, Charikleia Meleti, Trissevgeni Stavrakou and Henk Eskes

Remote Sens. 2022, 14(19), 4886; https://doi.org/10.3390/rs14194886 - 30 Sep 2022

Cited by 8 | Viewed by 2672

Abstract

The aim of this paper is to evaluate the surface concentration of nitrogen dioxide (NO₂) inferred from the Sentinel-5 Precursor Tropospheric Monitoring Instrument (S5P/TROPOMI) NO₂ tropospheric column densities over Central Europe for two time periods, summer 2019 and winter 2019–2020. Simulations of the NO₂ tropospheric vertical column densities and surface concentrations from the Long-Term Ozone Simulation–European Operational Smog (LOTOS-EUROS) chemical transport model are also applied in the methodology. More than two hundred in situ air quality monitoring stations, reporting to the European Environment Agency (EEA) air quality database, are used to carry out comparisons with the model simulations and the spaceborne inferred surface concentrations. Stations are separated into seven types (urban traffic, suburban traffic, urban background, suburban background, rural background, suburban industrial and rural industrial) in order to examine the strengths and shortcomings of the different air quality markers, namely the NO₂ vertical column densities and NO₂ surface concentrations. S5P/TROPOMI NO₂ surface concentrations are inferred by multiplying the fraction of the satellite and model NO₂ vertical column densities with the model surface concentrations. The estimated inferred TROPOMI NO₂ surface concentrations are examined further with the altering of three influencing factors: the model vertical leveling scheme, the versions of the TROPOMI NO₂ data and the air mass factors applied to the satellite and model NO₂ vertical column densities. Overall, the inferred TROPOMI NO₂ surface concentrations show a better correlation with the in situ measurements for both time periods and all station types, especially for the industrial stations (R > 0.6) in winter. The calculated correlation for background stations is moderate for both periods (R~0.5 in summer and R > 0.5 in winter), whereas for traffic stations it improves in the winter (from 0.20 to 0.50). After the implementation of the air mass factors from the local model, the bias is significantly reduced for most of the station types, especially in winter for the background stations, ranging from +0.49% for the urban background to +10.37% for the rural background stations. The mean relative bias in winter between the inferred S5P/TROPOMI NO₂ surface concentrations and the ground-based measurements for industrial stations is about −15%, whereas for traffic urban stations it is approximately −25%. In summer, biases are generally higher for all station types, especially for the traffic stations (~−75%), ranging from −54% to −30% for the background and industrial stations. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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14 pages, 2758 KiB

Open AccessArticle

Radiative Transfer Model Simulations for Ground-Based Microwave Radiometers in North China

by Wenying He, Yunchu Cheng, Rongshi Zou, Pucai Wang, Hongbin Chen, Jun Li and Xiangao Xia

Remote Sens. 2021, 13(24), 5161; https://doi.org/10.3390/rs13245161 - 19 Dec 2021

Cited by 3 | Viewed by 2666

Abstract

Ground-based microwave radiometer profilers (MWRPs) are widely used to provide high-temporal resolution atmospheric temperature and humidity profiles. The quality of the observed brightness temperature (TB) from MWRPs is key for retrieving accurate atmospheric profiles. In this study, TB simulations derived from a radiative transfer model (RTM) were used to assess the quality of TB observations. Two types of atmospheric profile data (conventional radiosonde and ERA5 reanalysis) were combined with the RTM to obtain TB simulations, then compared with corresponding observations from three MWRPs located in different places in North China to investigate the influence of input atmospheric profiles on TB simulations and evaluate the quality of TB observations from the three MWRPs. The comparisons of the matching samples under clear-sky conditions showed that TB simulations derived from both radiosonde and ERA5 profiles were very close to the TB observations from most of the MWRP channels; however, the correlation was lower and the bias was obvious at 51.26 GHz and 52.28 GHz, which indicates that the oxygen absorption component in the RTM needs to be improved for lower-frequency temperature channels. The difference in location of the radiosonde and MWRP sites affected the TB simulations for the water vapor channels, but had little impact on temperature channels that are insensitive to humidity. Comparisons of both simulations (ERA5 and Radiosonde) and the corresponding TB observations from the three sites indicated that the water vapor channels observation quality for the MWRP located in southern Beijing needs improvement. For the two types of profile data, ERA5 profiles have a more positive effect on TB simulations in the water vapor channels, such as enhanced consistence, reduced bias and standard deviation between simulations and observations for those MWRPs located away from the radiosonde station. Therefore, hourly ERA5 data are an optimal option in terms of compensating for limited radiosonde measurements and enhancing the monitoring quality of MWRP observations within 24 h. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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26 pages, 7700 KiB

Open AccessArticle

Transport and Variability of Tropospheric Ozone over Oceania and Southern Pacific during the 2019–20 Australian Bushfires

by Nelson Bègue, Hassan Bencherif, Fabrice Jégou, Hélène Vérèmes, Sergey Khaykin, Gisèle Krysztofiak, Thierry Portafaix, Valentin Duflot, Alexandre Baron, Gwenaël Berthet, Corinna Kloss, Guillaume Payen, Philippe Keckhut, Pierre-François Coheur, Cathy Clerbaux, Dan Smale, John Robinson, Richard Querel and Penny Smale

Remote Sens. 2021, 13(16), 3092; https://doi.org/10.3390/rs13163092 - 5 Aug 2021

Cited by 3 | Viewed by 2901

Abstract

The present study contributes to the scientific effort for a better understanding of the potential of the Australian biomass burning events to influence tropospheric trace gas abundances at the regional scale. In order to exclude the influence of the long-range transport of ozone precursors from biomass burning plumes originating from Southern America and Africa, the analysis of the Australian smoke plume has been driven over the period December 2019 to January 2020. This study uses satellite (IASI, MLS, MODIS, CALIOP) and ground-based (sun-photometer, FTIR, ozone radiosondes) observations. The highest values of aerosol optical depth (AOD) and carbon monoxide total columns are observed over Southern and Central Australia. Transport is responsible for the spatial and temporal distributions of aerosols and carbon monoxide over Australia, and also the transport of the smoke plume outside the continent. The dispersion of the tropospheric smoke plume over Oceania and Southern Pacific extends from tropical to extratropical latitudes. Ozone radiosonde measurements performed at Samoa (14.4°S, 170.6°W) and Lauder (45.0°S, 169.4°E) indicate an increase in mid-tropospheric ozone (6–9 km) (from 10% to 43%) linked to the Australian biomass burning plume. This increase in mid-tropospheric ozone induced by the transport of the smoke plume was found to be consistent with MLS observations over the tropical and extratropical latitudes. The smoke plume over the Southern Pacific was organized as a stretchable anticyclonic rolling which impacted the ozone variability in the tropical and subtropical upper-troposphere over Oceania. This is corroborated by the ozone profile measurements at Samoa which exhibit an enhanced ozone layer (29%) in the upper-troposphere. Our results suggest that the transport of Australian biomass burning plumes have significantly impacted the vertical distribution of ozone in the mid-troposphere southern tropical to extratropical latitudes during the 2019–20 extreme Australian bushfires. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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30 pages, 11526 KiB

Open AccessArticle

Detection of Upper and Lower Planetary-Boundary Layer Curves and Estimation of Their Heights from Ceilometer Observations under All-Weather Conditions: Case of Athens, Greece

by Harry D. Kambezidis, Basil E. Psiloglou, Ariadne Gavriil and Kalliopi Petrinoli

Remote Sens. 2021, 13(11), 2175; https://doi.org/10.3390/rs13112175 - 2 Jun 2021

Cited by 5 | Viewed by 3023

Abstract

The planetary-boundary layer (PBL) plays an important role in air-pollution studies over urban/industrial areas. Therefore, numerous experimental/modelling efforts have been conducted to determine the PBL height and provide statistics. Nowadays, remote-sensing techniques such as ceilometers are valuable tools in PBL-height estimation. The National Observatory of Athens operates a Vaisala CL31 ceilometer. This study analyses its records over a 2-year period and provides statistics about the PBL height over Athens. A specifically developed algorithm reads the CL31 records and estimates the PBL height. The algorithm detects an upper and a lower PBL curve. The results show maximum values of about 2500 m above sea level (asl)/3000 m asl in early afternoon hours in all months for upper PBL, and particularly the summer ones, under all-/clear-sky conditions, respectively. On the contrary, the lower PBL does not possess a clear daily pattern. Nevertheless, one morning and another afternoon peak can be identified. The intra-annual variation of the upper PBL height shows a peak in August in all-weather conditions and in September under clear-sky ones. Season-wise, the upper PBL height varies showing an autumn peak for all-weather cases, while the lower PBL height shows a winter maximum due to persistent surface-temperature inversions in this season. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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23 pages, 5000 KiB

Open AccessArticle

The Impact of the Control Measures during the COVID-19 Outbreak on Air Pollution in China

by Cheng Fan, Ying Li, Jie Guang, Zhengqiang Li, Abdelrazek Elnashar, Mona Allam and Gerrit de Leeuw

Remote Sens. 2020, 12(10), 1613; https://doi.org/10.3390/rs12101613 - 18 May 2020

Cited by 129 | Viewed by 10168

Abstract

The outbreak of the COVID-19 virus in Wuhan, China, in January 2020 just before the Spring Festival and subsequent country-wide measures to contain the virus, effectively resulted in the lock-down of the country. Most industries and businesses were closed, traffic was largely reduced, and people were restrained to their homes. This resulted in the reduction of emissions of trace gases and aerosols, the concentrations of which were strongly reduced in many cities around the country. Satellite imagery from the TROPOspheric Monitoring Instrument (TROPOMI) showed an enormous reduction of tropospheric NO₂ concentrations, but aerosol optical depth (AOD), as a measure of the amount of aerosols, was less affected, likely due to the different formation mechanisms and the influence of meteorological factors. In this study, satellite data and ground-based observations were used together to estimate the separate effects of the Spring Festival and the COVID-19 containment measures on atmospheric composition in the winter of 2020. To achieve this, data were analyzed for a period from 30 days before to 60 days after the Spring Festivals in 2017–2020. This extended period of time, including similar periods in previous years, were selected to account for both the decreasing concentrations in response to air pollution control measures, and meteorological effects on concentrations of trace gases and aerosols. Satellite data from TROPOMI provided the spatial distributions over mainland China of the tropospheric vertical column density (VCD) of NO₂, and VCD of SO₂ and CO. The MODerate resolution Imaging Spectroradiometer (MODIS) provided the aerosol optical depth (AOD). The comparison of the satellite data for different periods showed a large reduction of, e.g., NO₂ tropospheric VCDs due to the Spring Festival of up to 80% in some regions, and an additional reduction due to the COVID-19 containment measures of up to 70% in highly populated areas with intensive anthropogenic activities. In other areas, both effects are very small. Ground-based in situ observations from 26 provincial capitals provided concentrations of NO₂, SO₂, CO, O₃, PM_2.5, and PM₁₀. The analysis of these data was focused on the situation in Wuhan, based on daily averaged concentrations. The NO₂ concentrations started to decrease a few days before the Spring Festival and increased after about two weeks, except in 2020 when they continued to be low. SO₂ concentrations behaved in a similar way, whereas CO, PM_2.5, and PM₁₀ also decreased during the Spring Festival but did not trace NO₂ concentrations as SO₂ did. As could be expected from atmospheric chemistry considerations, O₃ concentrations increased. The analysis of the effects of the Spring Festival and the COVID-19 containment measures was complicated due to meteorological influences. Uncertainties contributing to the estimates of the different effects on the trace gas concentrations are discussed. The situation in Wuhan is compared with that in 26 provincial capitals based on 30-day averages for four years, showing different effects across China. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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19 pages, 5611 KiB

Open AccessArticle

A First Case Study of CCN Concentrations from Spaceborne Lidar Observations

by Aristeidis K. Georgoulias, Eleni Marinou, Alexandra Tsekeri, Emmanouil Proestakis, Dimitris Akritidis, Georgia Alexandri, Prodromos Zanis, Dimitris Balis, Franco Marenco, Matthias Tesche and Vassilis Amiridis

Remote Sens. 2020, 12(10), 1557; https://doi.org/10.3390/rs12101557 - 14 May 2020

Cited by 21 | Viewed by 4663

Abstract

We present here the first cloud condensation nuclei (CCN) concentration profiles derived from measurements with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), for different aerosol types at a supersaturation of 0.15%. CCN concentrations, along with the corresponding uncertainties, were inferred for a nighttime CALIPSO overpass on 9 September 2011, with coincident observations with the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft, within the framework of the Evaluation of CALIPSO’s Aerosol Classification scheme over Eastern Mediterranean (ACEMED) research campaign over Thessaloniki, Greece. The CALIPSO aerosol typing is evaluated, based on data from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. Backward trajectories and satellite-based fire counts are used to examine the origin of air masses on that day. Our CCN retrievals are evaluated against particle number concentration retrievals at different height levels, based on the ACEMED airborne measurements and compared against CCN-related retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard Terra and Aqua product over Thessaloniki showing that it is feasible to obtain CCN concentrations from CALIPSO, with an uncertainty of a factor of two to three. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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13 pages, 2592 KiB

Open AccessTechnical Note

Image Collection Simulation Using High-Resolution Atmospheric Modeling

by Andrew Kalukin, Satoshi Endo, Russell Crook, Manoj Mahajan, Robert Fennimore, Alice Cialella, Laurie Gregory, Shinjae Yoo, Wei Xu and Daniel Cisek

Remote Sens. 2020, 12(19), 3214; https://doi.org/10.3390/rs12193214 - 1 Oct 2020

Cited by 1 | Viewed by 3878

Abstract

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes. Full article

(This article belongs to the Special Issue Feature Papers of Section Atmosphere Remote Sensing)

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