Articles | Volume 7, issue 12
https://doi.org/10.5194/amt-7-4353-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-4353-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Dec 2014
Research article |
| 10 Dec 2014
Scientific impact of MODIS C5 calibration degradation and C6+ improvements
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Y. Wang
University of Maryland Baltimore County, Baltimore, Maryland, USA
X. Xiong
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
G. Meister
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
S. Platnick
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
B. Franz
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
S. Korkin
Universities Space Research Association GESTAR, Columbia, Maryland, USA
T. Hilker
Oregon State University, Corvallis, Oregon, USA
J. Tucker
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
F. Hall
University of Maryland Baltimore County, Baltimore, Maryland, USA
P. Sellers
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
A. Wu
Sigma Space Corporation, Lanham, Maryland, USA
A. Angal
Science Systems and Applications Inc., Lanham, Maryland, USA
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Ekaterina Y. Zhdanova, Natalia Y. Chubarova, and Alexei I. Lyapustin
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David M. Giles, Alexander Sinyuk, Mikhail G. Sorokin, Joel S. Schafer, Alexander Smirnov, Ilya Slutsker, Thomas F. Eck, Brent N. Holben, Jasper R. Lewis, James R. Campbell, Ellsworth J. Welton, Sergey V. Korkin, and Alexei I. Lyapustin
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Clouds or instrumental anomalies may perturb ground-based solar measurements used to calculate aerosol optical depth (AOD). This study presents a new algorithm of automated near-real-time (NRT) quality controls with improved cloud screening for AERONET AOD measurements. Results from the new and old algorithms have excellent agreement for the highest-quality AOD level, while the new algorithm provides higher-quality NRT AOD for applications such as data assimilation and satellite evaluation.
Xiaomeng Jin, Arlene M. Fiore, Gabriele Curci, Alexei Lyapustin, Kevin Civerolo, Michael Ku, Aaron van Donkelaar, and Randall V. Martin
Atmos. Chem. Phys., 19, 295–313, https://doi.org/10.5194/acp-19-295-2019, https://doi.org/10.5194/acp-19-295-2019, 2019
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We use a forward geophysical approach to derive surface PM2.5 distribution from satellite AOD over the northeastern US by applying relationships between surface PM2.5 and column AOD from a regional air quality model (CMAQ). We use multi-platform surface, aircraft, and radiosonde measurements to quantify different sources of uncertainties. We highlight model representation of aerosol vertical distribution and speciation as major sources of uncertainties for satellite-derived PM2.5.
Alexei Lyapustin, Yujie Wang, Sergey Korkin, and Dong Huang
Atmos. Meas. Tech., 11, 5741–5765, https://doi.org/10.5194/amt-11-5741-2018, https://doi.org/10.5194/amt-11-5741-2018, 2018
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MAIAC algorithm used for the MODIS C6 processing is described. MAIAC combines time series analysis and pixel/image-based processing to improve the accuracy of cloud detection, aerosol retrievals and atmospheric correction. MAIAC offers an interdisciplinary suite of atmospheric, land surface and snow products. Due to generally high quality, high resolution and high coverage, MAIAC AOD and surface reflectance/BRDF have been widely used for air quality and land research and applications.
Robert C. Levy, Shana Mattoo, Virginia Sawyer, Yingxi Shi, Peter R. Colarco, Alexei I. Lyapustin, Yujie Wang, and Lorraine A. Remer
Atmos. Meas. Tech., 11, 4073–4092, https://doi.org/10.5194/amt-11-4073-2018, https://doi.org/10.5194/amt-11-4073-2018, 2018
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Global aerosol data sets are essential for assessing climate-related questions. When comparing data sets derived from twin satellite sensors, we find consistent global offsets between morning and afternoon observations. Applying satellite-like sampling to a global model derives much weaker morning/afternoon offsets, suggesting that the observational differences are due to calibration. However, applying additional calibration corrections appears to reduce (but not remove) the global offsets.
Matthew J. Cooper, Randall V. Martin, Alexei I. Lyapustin, and Chris A. McLinden
Atmos. Meas. Tech., 11, 2983–2994, https://doi.org/10.5194/amt-11-2983-2018, https://doi.org/10.5194/amt-11-2983-2018, 2018
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To accurately infer air pollutant concentrations from satellite observations, we must first know the reflectivity of the Earth’s surface. Using a model, we show that satellite observations are better able to observe NO2 near the surface if snow is present. However, knowing when snow is present is difficult due to its variability. We test seven existing snow cover data sets to assess their ability to inform future satellite observations and find that the IMS data set is best suited for this task.
I. Veselovskii, D. N Whiteman, M. Korenskiy, A. Suvorina, A. Kolgotin, A. Lyapustin, Y. Wang, M. Chin, H. Bian, T. L. Kucsera, D. Pérez-Ramírez, and B. Holben
Atmos. Chem. Phys., 15, 1647–1660, https://doi.org/10.5194/acp-15-1647-2015, https://doi.org/10.5194/acp-15-1647-2015, 2015
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The multi-wavelength lidar technique was applied to the study of a smoke event near Washington, DC on 26-28 August 2013. Satellite observations combined with transport model predictions imply that the smoke plume originated mainly from Wyoming/Idaho forest fires. The NASA GSFC multi-wavelength Mie-Raman lidar was used to profile the smoke particle parameters such as volume density, effective radius and the real part of the refractive index.
B. Arvani, R. B. Pierce, A. I. Lyapustin, Y. Wang, G. Ghermandi, and S. Teggi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-123-2015, https://doi.org/10.5194/acpd-15-123-2015, 2015
Revised manuscript not accepted
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The manuscript compares 10km Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 and new 1 km Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Optical Depth (AOD) retrievals to small (<10 micron) particulate matter (PM10) surface measurements from monitoring stations within the Po Valley in Northern Italy during 2012. When the depth of the planetary boundary layer (PBL) is used to normalize the AOD, we find PM – AOD correlations of 0.98 for both retrievals.
T. F. Eck, B. N. Holben, J. S. Reid, A. Arola, R. A. Ferrare, C. A. Hostetler, S. N. Crumeyrolle, T. A. Berkoff, E. J. Welton, S. Lolli, A. Lyapustin, Y. Wang, J. S. Schafer, D. M. Giles, B. E. Anderson, K. L. Thornhill, P. Minnis, K. E. Pickering, C. P. Loughner, A. Smirnov, and A. Sinyuk
Atmos. Chem. Phys., 14, 11633–11656, https://doi.org/10.5194/acp-14-11633-2014, https://doi.org/10.5194/acp-14-11633-2014, 2014
J. Strandgren, L. Mei, M. Vountas, J. P. Burrows, A. Lyapustin, and Y. Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-25869-2014, https://doi.org/10.5194/acpd-14-25869-2014, 2014
Revised manuscript not accepted
X. Hu, L. A. Waller, A. Lyapustin, Y. Wang, and Y. Liu
Atmos. Chem. Phys., 14, 6301–6314, https://doi.org/10.5194/acp-14-6301-2014, https://doi.org/10.5194/acp-14-6301-2014, 2014
A. Chudnovsky, C. Tang, A. Lyapustin, Y. Wang, J. Schwartz, and P. Koutrakis
Atmos. Chem. Phys., 13, 10907–10917, https://doi.org/10.5194/acp-13-10907-2013, https://doi.org/10.5194/acp-13-10907-2013, 2013
H. Zhang, R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Lyapustin
Atmos. Meas. Tech., 6, 471–486, https://doi.org/10.5194/amt-6-471-2013, https://doi.org/10.5194/amt-6-471-2013, 2013
Haihui Zhu, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Chi Li, Jun Meng, Christopher R. Oxford, Xuan Liu, Yanshun Li, Dandan Zhang, Inderjeet Singh, and Alexei Lyapustin
Atmos. Chem. Phys., 24, 11565–11584, https://doi.org/10.5194/acp-24-11565-2024, https://doi.org/10.5194/acp-24-11565-2024, 2024
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Ambient fine particulate matter (PM2.5) contributes to 4 million deaths globally each year. Satellite remote sensing of aerosol optical depth (AOD), coupled with a simulated PM2.5–AOD relationship (η), can provide global PM2.5 estimations. This study aims to understand the spatial patterns and driving factors of η to guide future measurement and modeling efforts. We quantified η globally and regionally and found that its spatial variation is strongly influenced by aerosol composition.
Myungje Choi, Alexei Lyapustin, Gregory L. Schuster, Sujung Go, Yujie Wang, Sergey Korkin, Ralph Kahn, Jeffrey S. Reid, Edward J. Hyer, Thomas F. Eck, Mian Chin, David J. Diner, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, and Hans Moosmüller
Atmos. Chem. Phys., 24, 10543–10565, https://doi.org/10.5194/acp-24-10543-2024, https://doi.org/10.5194/acp-24-10543-2024, 2024
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This paper introduces a retrieval algorithm to estimate two key absorbing components in smoke (black carbon and brown carbon) using DSCOVR EPIC measurements. Our analysis reveals distinct smoke properties, including spectral absorption, layer height, and black carbon and brown carbon, over North America and central Africa. The retrieved smoke properties offer valuable observational constraints for modeling radiative forcing and informing health-related studies.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan
Atmos. Meas. Tech., 17, 5455–5476, https://doi.org/10.5194/amt-17-5455-2024, https://doi.org/10.5194/amt-17-5455-2024, 2024
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In this study, for the first time, we combined aerosol data from six satellites using a unified algorithm. The global datasets are generated at a high spatial resolution of about 25 km with an interval of 30 min. The new datasets are compared against ground truth and verified. They will be useful for various applications such as air quality monitoring, climate research, pollution diurnal variability, long-range smoke and dust transport, and evaluation of regional and global models.
Mijin Kim, Robert C. Levy, Lorraine A. Remer, Shana Mattoo, and Pawan Gupta
Atmos. Meas. Tech., 17, 1913–1939, https://doi.org/10.5194/amt-17-1913-2024, https://doi.org/10.5194/amt-17-1913-2024, 2024
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The study focused on evaluating and modifying the surface reflectance parameterization (SRP) of the Dark Target (DT) algorithm for geostationary observation. When using the DT SRP with the ABIs sensor on GOES-R, artificial diurnal signatures were present in AOD retrieval. To overcome this issue, a new SRP was developed, incorporating solar zenith angle and land cover type. The revised SRP resulted in improved AOD retrieval, demonstrating reduced bias around local noon.
Lorraine A. Remer, Robert C. Levy, and J. Vanderlei Martins
Atmos. Chem. Phys., 24, 2113–2127, https://doi.org/10.5194/acp-24-2113-2024, https://doi.org/10.5194/acp-24-2113-2024, 2024
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Aerosols are small liquid or solid particles suspended in the atmosphere, including smoke, particulate pollution, dust, and sea salt. Today, we rely on satellites viewing Earth's atmosphere to learn about these particles. Here, we speculate on the future to imagine how satellite viewing of aerosols will change. We expect more public and private satellites with greater capabilities, better ways to infer information from satellites, and merging of data with models.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
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This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Amanda Gumber, Jeffrey S. Reid, Robert E. Holz, Thomas F. Eck, N. Christina Hsu, Robert C. Levy, Jianglong Zhang, and Paolo Veglio
Atmos. Meas. Tech., 16, 2547–2573, https://doi.org/10.5194/amt-16-2547-2023, https://doi.org/10.5194/amt-16-2547-2023, 2023
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The purpose of this study is to create and evaluate a gridded dataset composed of multiple satellite instruments and algorithms to be used for data assimilation. An important part of aerosol data assimilation is having consistent measurements, especially for severe aerosol events. This study evaluates 4 years of data from MODIS, VIIRS, and AERONET with a focus on aerosol severe event detection from a regional and global perspective.
Xavier Ceamanos, Bruno Six, Suman Moparthy, Dominique Carrer, Adèle Georgeot, Josef Gasteiger, Jérôme Riedi, Jean-Luc Attié, Alexei Lyapustin, and Iosif Katsev
Atmos. Meas. Tech., 16, 2575–2599, https://doi.org/10.5194/amt-16-2575-2023, https://doi.org/10.5194/amt-16-2575-2023, 2023
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A new algorithm to retrieve the diurnal evolution of aerosol optical depth over land and ocean from geostationary meteorological satellites is proposed and successfully evaluated with reference ground-based and satellite data. The high-temporal-resolution aerosol observations that are obtained from the EUMETSAT Meteosat Second Generation mission are unprecedented and open the door to studies that cannot be conducted with the once-a-day observations available from low-Earth-orbit satellites.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Brian Cairns, Xiaoguang Xu, and J. Vanderlei Martins
Atmos. Meas. Tech., 16, 2067–2087, https://doi.org/10.5194/amt-16-2067-2023, https://doi.org/10.5194/amt-16-2067-2023, 2023
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Multi-angle polarimetric measurements have been shown to greatly improve the remote sensing capability of aerosols and help atmospheric correction for ocean color retrievals. However, the uncertainty correlations among different measurement angles have not been well characterized. In this work, we provided a practical framework to evaluate the impact of the angular uncertainty correlation in retrieval results and a method to directly estimate correlation strength from retrieval residuals.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
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The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
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The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Pawan Gupta, Prakash Doraiswamy, Jashwanth Reddy, Palak Balyan, Sagnik Dey, Ryan Chartier, Adeel Khan, Karmann Riter, Brandon Feenstra, Robert C. Levy, Nhu Nguyen Minh Tran, Olga Pikelnaya, Kurinji Selvaraj, Tanushree Ganguly, and Karthik Ganesan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-140, https://doi.org/10.5194/amt-2022-140, 2022
Revised manuscript not accepted
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The use of low-cost sensors in air quality monitoring has been gaining interest across all walks of society. We present the results of evaluations of the PurpleAir against regulatory-grade PM2.5. The results indicate that with proper calibration, we can achieve bias-corrected PM2.5 data using PA sensors. Our study also suggests that pre-deployment calibrations developed at local or regional scales are required for the PA sensors to correct data from the field for scientific data analysis.
Sujung Go, Alexei Lyapustin, Gregory L. Schuster, Myungje Choi, Paul Ginoux, Mian Chin, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, Arlindo da Silva, Brent Holben, and Jeffrey S. Reid
Atmos. Chem. Phys., 22, 1395–1423, https://doi.org/10.5194/acp-22-1395-2022, https://doi.org/10.5194/acp-22-1395-2022, 2022
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This paper presents a retrieval algorithm of iron-oxide species (hematite, goethite) content in the atmosphere from DSCOVR EPIC observations. Our results display variations within the published range of hematite and goethite over the main dust-source regions but show significant seasonal and spatial variability. This implies a single-viewing satellite instrument with UV–visible channels may provide essential information on shortwave dust direct radiative effects for climate modeling.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Hongbin Yu, Qian Tan, Lillian Zhou, Yaping Zhou, Huisheng Bian, Mian Chin, Claire L. Ryder, Robert C. Levy, Yaswant Pradhan, Yingxi Shi, Qianqian Song, Zhibo Zhang, Peter R. Colarco, Dongchul Kim, Lorraine A. Remer, Tianle Yuan, Olga Mayol-Bracero, and Brent N. Holben
Atmos. Chem. Phys., 21, 12359–12383, https://doi.org/10.5194/acp-21-12359-2021, https://doi.org/10.5194/acp-21-12359-2021, 2021
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This study characterizes a historic African dust intrusion into the Caribbean Basin in June 2020 using satellites and NASA GEOS. Dust emissions in West Africa were large albeit not extreme. However, a unique synoptic system accumulated the dust near the coast for about 4 d before it was ventilated. Although GEOS reproduced satellite-observed plume tracks well, it substantially underestimated dust emissions and did not lift up dust high enough for ensuing long-range transport.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Yingxi R. Shi, Robert C. Levy, Leiku Yang, Lorraine A. Remer, Shana Mattoo, and Oleg Dubovik
Atmos. Meas. Tech., 14, 3449–3468, https://doi.org/10.5194/amt-14-3449-2021, https://doi.org/10.5194/amt-14-3449-2021, 2021
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Due to fast industrialization and development, China has been experiencing haze pollution episodes with both high frequencies and severity over the last 3 decades. This study improves the accuracy and data coverage of measured aerosol from satellites, which help quantify, characterize, and understand the impact of the haze phenomena over the entire East Asia region.
Kirk Knobelspiesse, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, Meng Gao, Michael Garay, Samuel Anderson, and Olga Kalashnikova
Atmos. Meas. Tech., 14, 3233–3252, https://doi.org/10.5194/amt-14-3233-2021, https://doi.org/10.5194/amt-14-3233-2021, 2021
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We assessed atmospheric aerosol and ocean surface wind speed remote sensing capability with NASA's Multi-angle Imaging SpectroRadiometer (MISR), using synthetic data and a Bayesian inference technique called generalized nonlinear retrieval analysis (GENRA). We found success using three aerosol parameters plus wind speed. This shows that MISR can perform an atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same spacecraft (Terra).
Cheng Chen, Oleg Dubovik, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Fabrice Ducos, Yevgeny Derimian, Maurice Herman, Didier Tanré, Lorraine A. Remer, Alexei Lyapustin, Andrew M. Sayer, Robert C. Levy, N. Christina Hsu, Jacques Descloitres, Lei Li, Benjamin Torres, Yana Karol, Milagros Herrera, Marcos Herreras, Michael Aspetsberger, Moritz Wanzenboeck, Lukas Bindreiter, Daniel Marth, Andreas Hangler, and Christian Federspiel
Earth Syst. Sci. Data, 12, 3573–3620, https://doi.org/10.5194/essd-12-3573-2020, https://doi.org/10.5194/essd-12-3573-2020, 2020
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Aerosol products obtained from POLDER/PARASOL processed by the GRASP algorithm have been released. The entire archive of PARASOL/GRASP aerosol products is evaluated against AERONET and compared with MODIS (DT, DB and MAIAC), as well as PARASOL/Operational products. PARASOL/GRASP aerosol products provide spectral 443–1020 nm AOD correlating well with AERONET with a maximum bias of 0.02. Finally, GRASP shows capability to derive detailed spectral properties, including aerosol absorption.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
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We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Allan C. Just, Yang Liu, Meytar Sorek-Hamer, Johnathan Rush, Michael Dorman, Robert Chatfield, Yujie Wang, Alexei Lyapustin, and Itai Kloog
Atmos. Meas. Tech., 13, 4669–4681, https://doi.org/10.5194/amt-13-4669-2020, https://doi.org/10.5194/amt-13-4669-2020, 2020
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A flexible machine-learning model was fit to explain the differences between estimates of water vapor from satellites versus ground stations in Northeastern USA. We use nine variables derived from the satellite acquisition and ground characteristics to explain this measurement error. Our results showed overall good agreement, but data from the Terra satellite were drifting too high in recent summers. Our model reduces measurement error and works well in new locations in the northeast.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Sergey Korkin, Joel S. Schafer, Alexander Smirnov, Mikhail Sorokin, and Alexei Lyapustin
Atmos. Meas. Tech., 13, 3375–3411, https://doi.org/10.5194/amt-13-3375-2020, https://doi.org/10.5194/amt-13-3375-2020, 2020
Robert B. Chatfield, Meytar Sorek-Hamer, Robert F. Esswein, and Alexei Lyapustin
Atmos. Chem. Phys., 20, 4379–4397, https://doi.org/10.5194/acp-20-4379-2020, https://doi.org/10.5194/acp-20-4379-2020, 2020
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There is a great need to define health-affecting pollution by small particles as “respirable aerosol”. The wintertime San Joaquin Valley experiences severe episodes that need full maps. A few air pollution monitors are set out by agencies in such regions. Satellite data on haziness and daily calibration using the monitors map out improved pollution estimates for the winter of 2012–2013. These show patterns of valuable empirical information about sources, transport, and cleanout of pollution.
Jing Wei, Zhanqing Li, Maureen Cribb, Wei Huang, Wenhao Xue, Lin Sun, Jianping Guo, Yiran Peng, Jing Li, Alexei Lyapustin, Lei Liu, Hao Wu, and Yimeng Song
Atmos. Chem. Phys., 20, 3273–3289, https://doi.org/10.5194/acp-20-3273-2020, https://doi.org/10.5194/acp-20-3273-2020, 2020
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This study introduced an enhanced space–time extremely randomized trees (STET) approach to improve the 1 km resolution ground-level PM2.5 estimates across China using the remote sensing technology. The STET model shows high accuracy and strong predictive power and appears to outperform most models reported by previous studies. Thus, it is of great importance for future air pollution studies at medium- or small-scale areas and will be applied to generate the historical PM2.5 dataset across China.
Larisa Sogacheva, Thomas Popp, Andrew M. Sayer, Oleg Dubovik, Michael J. Garay, Andreas Heckel, N. Christina Hsu, Hiren Jethva, Ralph A. Kahn, Pekka Kolmonen, Miriam Kosmale, Gerrit de Leeuw, Robert C. Levy, Pavel Litvinov, Alexei Lyapustin, Peter North, Omar Torres, and Antti Arola
Atmos. Chem. Phys., 20, 2031–2056, https://doi.org/10.5194/acp-20-2031-2020, https://doi.org/10.5194/acp-20-2031-2020, 2020
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The typical lifetime of a single satellite platform is on the order of 5–15 years; thus, for climate studies the usage of multiple satellite sensors should be considered.
Here we introduce and evaluate a monthly AOD merged product and AOD global and regional time series for the period 1995–2017 created from 12 individual satellite AOD products, which provide a long-term perspective on AOD changes over different regions of the globe.
Ekaterina Y. Zhdanova, Natalia Y. Chubarova, and Alexei I. Lyapustin
Atmos. Meas. Tech., 13, 877–891, https://doi.org/10.5194/amt-13-877-2020, https://doi.org/10.5194/amt-13-877-2020, 2020
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We estimated the distribution of aerosol optical thickness (AOT) with a spatial resolution of 1 km over the Moscow megacity using the MAIAC satellite aerosol product from May to September over the years 2000–2017. We revealed that the MAIAC product is a reliable instrument for assessing the spatial features of urban aerosol pollution and its temporal dynamics. The local aerosol effect is about 0.02–0.04 in AOT in the visible spectral range over the Moscow megacity.
Hongbin Yu, Yang Yang, Hailong Wang, Qian Tan, Mian Chin, Robert C. Levy, Lorraine A. Remer, Steven J. Smith, Tianle Yuan, and Yingxi Shi
Atmos. Chem. Phys., 20, 139–161, https://doi.org/10.5194/acp-20-139-2020, https://doi.org/10.5194/acp-20-139-2020, 2020
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Emissions and long-range transport of mineral dust and
combustion-related aerosol from burning fossil fuels and biomass vary from year to year, driven by the evolution of the economy and changes in meteorological conditions and environmental regulations. This study offers both satellite and model perspectives on interannual variability and possible trends in combustion aerosol and dust in major continental outflow regions over the past 15 years (2003–2017).
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Robert E. Holz, and Andrew K. Heidinger
Atmos. Meas. Tech., 12, 6557–6577, https://doi.org/10.5194/amt-12-6557-2019, https://doi.org/10.5194/amt-12-6557-2019, 2019
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Aerosol optical depth (AOD) from a geostationary satellite has been retrieved, and validated and diurnal cycles of aerosols are discussed over the eastern hemisphere and a 2-month period of May–June 2016. The new AOD product matches well with AERONET as well as with the standard MODIS product. Future work to make this algorithm operational will need to re-examine masking including snow masks, re-evaluate assumed aerosol models for geosynchronous geometry and address the surface characterization.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Yongxiang Hu, Kirk Knobelspiesse, P. Jeremy Werdell, Amir Ibrahim, Brian Cairns, and Alison Chase
Atmos. Meas. Tech., 12, 3921–3941, https://doi.org/10.5194/amt-12-3921-2019, https://doi.org/10.5194/amt-12-3921-2019, 2019
David M. Giles, Alexander Sinyuk, Mikhail G. Sorokin, Joel S. Schafer, Alexander Smirnov, Ilya Slutsker, Thomas F. Eck, Brent N. Holben, Jasper R. Lewis, James R. Campbell, Ellsworth J. Welton, Sergey V. Korkin, and Alexei I. Lyapustin
Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, https://doi.org/10.5194/amt-12-169-2019, 2019
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Clouds or instrumental anomalies may perturb ground-based solar measurements used to calculate aerosol optical depth (AOD). This study presents a new algorithm of automated near-real-time (NRT) quality controls with improved cloud screening for AERONET AOD measurements. Results from the new and old algorithms have excellent agreement for the highest-quality AOD level, while the new algorithm provides higher-quality NRT AOD for applications such as data assimilation and satellite evaluation.
Xiaomeng Jin, Arlene M. Fiore, Gabriele Curci, Alexei Lyapustin, Kevin Civerolo, Michael Ku, Aaron van Donkelaar, and Randall V. Martin
Atmos. Chem. Phys., 19, 295–313, https://doi.org/10.5194/acp-19-295-2019, https://doi.org/10.5194/acp-19-295-2019, 2019
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We use a forward geophysical approach to derive surface PM2.5 distribution from satellite AOD over the northeastern US by applying relationships between surface PM2.5 and column AOD from a regional air quality model (CMAQ). We use multi-platform surface, aircraft, and radiosonde measurements to quantify different sources of uncertainties. We highlight model representation of aerosol vertical distribution and speciation as major sources of uncertainties for satellite-derived PM2.5.
Yingxi R. Shi, Robert C. Levy, Thomas F. Eck, Brad Fisher, Shana Mattoo, Lorraine A. Remer, Ilya Slutsker, and Jianglong Zhang
Atmos. Chem. Phys., 19, 259–274, https://doi.org/10.5194/acp-19-259-2019, https://doi.org/10.5194/acp-19-259-2019, 2019
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The Indonesian fire and smoke event of 2015 was an extreme episode that affected public health and caused severe economic and environmental damage. We managed to retrieve data over very thick smoke plumes and produce a lot more high aerosol loading data that were previously missed by other satellite products. These results will benefit varieties of downstream research that use the satellite aerosol data and will influence the future development of the global satellite aerosol algorithm.
Alexei Lyapustin, Yujie Wang, Sergey Korkin, and Dong Huang
Atmos. Meas. Tech., 11, 5741–5765, https://doi.org/10.5194/amt-11-5741-2018, https://doi.org/10.5194/amt-11-5741-2018, 2018
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MAIAC algorithm used for the MODIS C6 processing is described. MAIAC combines time series analysis and pixel/image-based processing to improve the accuracy of cloud detection, aerosol retrievals and atmospheric correction. MAIAC offers an interdisciplinary suite of atmospheric, land surface and snow products. Due to generally high quality, high resolution and high coverage, MAIAC AOD and surface reflectance/BRDF have been widely used for air quality and land research and applications.
Robert C. Levy, Shana Mattoo, Virginia Sawyer, Yingxi Shi, Peter R. Colarco, Alexei I. Lyapustin, Yujie Wang, and Lorraine A. Remer
Atmos. Meas. Tech., 11, 4073–4092, https://doi.org/10.5194/amt-11-4073-2018, https://doi.org/10.5194/amt-11-4073-2018, 2018
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Global aerosol data sets are essential for assessing climate-related questions. When comparing data sets derived from twin satellite sensors, we find consistent global offsets between morning and afternoon observations. Applying satellite-like sampling to a global model derives much weaker morning/afternoon offsets, suggesting that the observational differences are due to calibration. However, applying additional calibration corrections appears to reduce (but not remove) the global offsets.
Falguni Patadia, Robert C. Levy, and Shana Mattoo
Atmos. Meas. Tech., 11, 3205–3219, https://doi.org/10.5194/amt-11-3205-2018, https://doi.org/10.5194/amt-11-3205-2018, 2018
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Satellite-measured radiance from an Earth scene comprises light scattered and absorbed by gases, clouds and aerosols in the atmosphere and by the Earth surface. To retrieve aerosol information, the signal from clouds, gases and the surface must be separated from the aerosol signal. This paper highlights the gas absorption correction method used by the MODIS dark-target aerosol retrieval algorithm and demonstrates that aerosol retrieval accuracy depends on accurate gas absorption correction.
Pawan Gupta, Lorraine A. Remer, Robert C. Levy, and Shana Mattoo
Atmos. Meas. Tech., 11, 3145–3159, https://doi.org/10.5194/amt-11-3145-2018, https://doi.org/10.5194/amt-11-3145-2018, 2018
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In this study, we perform global validation of MODIS high-resolution (3 km) AOD over global land by comparing against AERONET measurements. The MODIS–AERONET collocated data sets consist of 161 410 high-confidence AOD pairs from 2000 to 2015 for Terra MODIS and 2003 to 2015 for Aqua MODIS. We find that 62.5 and 68.4 % of AODs retrieved from Terra MODIS and Aqua MODIS, respectively, fall within previously published expected error.
Matthew J. Cooper, Randall V. Martin, Alexei I. Lyapustin, and Chris A. McLinden
Atmos. Meas. Tech., 11, 2983–2994, https://doi.org/10.5194/amt-11-2983-2018, https://doi.org/10.5194/amt-11-2983-2018, 2018
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To accurately infer air pollutant concentrations from satellite observations, we must first know the reflectivity of the Earth’s surface. Using a model, we show that satellite observations are better able to observe NO2 near the surface if snow is present. However, knowing when snow is present is difficult due to its variability. We test seven existing snow cover data sets to assess their ability to inform future satellite observations and find that the IMS data set is best suited for this task.
Antti Lipponen, Tero Mielonen, Mikko R. A. Pitkänen, Robert C. Levy, Virginia R. Sawyer, Sami Romakkaniemi, Ville Kolehmainen, and Antti Arola
Atmos. Meas. Tech., 11, 1529–1547, https://doi.org/10.5194/amt-11-1529-2018, https://doi.org/10.5194/amt-11-1529-2018, 2018
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Atmospheric aerosols are small solid or liquid particles suspended in the atmosphere and they have a significant effect on the climate. Satellite data are used to get global estimates of atmospheric aerosols. In this work, a statistics-based Bayesian aerosol retrieval algorithm was developed to improve the accuracy and quantify the uncertainties related to the aerosol estimates. The algorithm is tested with NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data.
Aristeidis K. Georgoulias, Georgia Alexandri, Konstantinos A. Kourtidis, Jos Lelieveld, Prodromos Zanis, Ulrich Pöschl, Robert Levy, Vassilis Amiridis, Eleni Marinou, and Athanasios Tsikerdekis
Atmos. Chem. Phys., 16, 13853–13884, https://doi.org/10.5194/acp-16-13853-2016, https://doi.org/10.5194/acp-16-13853-2016, 2016
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In this work, single pixel observations from MODIS Terra and Aqua are analyzed together with data from other satellite sensors, reanalysis projects and a chemistry–aerosol-transport model to study the spatiotemporal variability of different aerosol types. The results are in accordance with previous works and are a good reference for future studies in the area focusing on aerosols, clouds, radiation and the effects of particle pollution on human health.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, and Leigh A. Munchak
Atmos. Meas. Tech., 9, 3293–3308, https://doi.org/10.5194/amt-9-3293-2016, https://doi.org/10.5194/amt-9-3293-2016, 2016
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A new surface scheme inside MODIS dark target aerosol retrieval algorithm has been developed to improve the accuracy of aerosol optical depth data over cities. The new scheme integrates the MODIS land surface reflectance and land cover type information into the surface parameterization for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region. The improved aerosols data sets will be useful for air quality applications over cities.
Galina Wind, Arlindo M. da Silva, Peter M. Norris, Steven Platnick, Shana Mattoo, and Robert C. Levy
Geosci. Model Dev., 9, 2377–2389, https://doi.org/10.5194/gmd-9-2377-2016, https://doi.org/10.5194/gmd-9-2377-2016, 2016
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The MCARS code creates sensor radiances using model-generated atmospheric columns and actual sensor and solar geometry. MCARS output looks like real data, so it is usable by any code that reads MODIS data. MCARS output can be used to test remote-sensing retrieval algorithms. Users know what went into creating the radiance: atmosphere, surface, clouds, and aerosols. Models can use MCARS output to create new parameterizations of relations of atmospheric physical quantities and measured radiances.
Souichiro Hioki, Ping Yang, Bryan A. Baum, Steven Platnick, Kerry G. Meyer, Michael D. King, and Jerome Riedi
Atmos. Chem. Phys., 16, 7545–7558, https://doi.org/10.5194/acp-16-7545-2016, https://doi.org/10.5194/acp-16-7545-2016, 2016
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The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multi-directional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed, which provides a more noise-resilient roughness estimate than the conventional approach. A global one-month data sample shows the use and the limit of a severely roughened ice habit to simulate the polarized reflectivity.
Kerry Meyer, Yuekui Yang, and Steven Platnick
Atmos. Meas. Tech., 9, 1785–1797, https://doi.org/10.5194/amt-9-1785-2016, https://doi.org/10.5194/amt-9-1785-2016, 2016
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This paper presents the expected uncertainties of a single-channel cloud opacity retrieval technique and a temperature-based cloud phase approach in support of the Deep Space Climate Observatory (DSCOVR) mission; DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations. Results show that, for ice clouds, retrieval errors are minimal (< 2 %), while for liquid clouds the error is limited to within 10 %, although for thin clouds the error can be higher.
Robert E. Holz, Steven Platnick, Kerry Meyer, Mark Vaughan, Andrew Heidinger, Ping Yang, Gala Wind, Steven Dutcher, Steven Ackerman, Nandana Amarasinghe, Fredrick Nagle, and Chenxi Wang
Atmos. Chem. Phys., 16, 5075–5090, https://doi.org/10.5194/acp-16-5075-2016, https://doi.org/10.5194/acp-16-5075-2016, 2016
Kerry Meyer, Steven Platnick, G. Thomas Arnold, Robert E. Holz, Paolo Veglio, John Yorks, and Chenxi Wang
Atmos. Meas. Tech., 9, 1743–1753, https://doi.org/10.5194/amt-9-1743-2016, https://doi.org/10.5194/amt-9-1743-2016, 2016
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Cirrus cloud optical and microphysical properties are retrieved from remote sensing solar reflectance measurements at two narrow wavelength channels within the broader water vapor absorption band at 1.88 µm. Results from this technique compare well with other solar reflectance, IR, and lidar-based retrievals. This approach is complementary to traditional remote sensing techniques and can extend cloud retrieval capabilities for thin cirrus clouds.
Benjamin Marchant, Steven Platnick, Kerry Meyer, G. Thomas Arnold, and Jérôme Riedi
Atmos. Meas. Tech., 9, 1587–1599, https://doi.org/10.5194/amt-9-1587-2016, https://doi.org/10.5194/amt-9-1587-2016, 2016
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The current paper presents the new MODIS Collection 6 (C6) cloud thermodynamic phase classification algorithm. To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.
Zhibo Zhang, Kerry Meyer, Hongbin Yu, Steven Platnick, Peter Colarco, Zhaoyan Liu, and Lazaros Oreopoulos
Atmos. Chem. Phys., 16, 2877–2900, https://doi.org/10.5194/acp-16-2877-2016, https://doi.org/10.5194/acp-16-2877-2016, 2016
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The frequency of occurrence and shortwave direct radiative effects (DRE) of above-cloud aerosols (ACAs) over global oceans are investigated using 8 years of collocated CALIOP and MODIS observations. We estimated that ACAs have a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m−2 (range of −0.03 to 0.06 W m−2) at TOA. The DREs at surface and within atmosphere are −0.15 W m−2 (range of −0.09 to −0.21 W m−2), and 0.17 W m−2 (range of 0.11 to 0.24 W m−2), respectively.
Q. Xiao, H. Zhang, M. Choi, S. Li, S. Kondragunta, J. Kim, B. Holben, R. C. Levy, and Y. Liu
Atmos. Chem. Phys., 16, 1255–1269, https://doi.org/10.5194/acp-16-1255-2016, https://doi.org/10.5194/acp-16-1255-2016, 2016
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Using ground AOD measurements from AERONET, DRAGON-Asia Campaign, and handheld sunphotometers, we evaluated emerging aerosol products from VIIRS, GOCI, and Terra and Aqua MODIS (Collection 6) in East Asia in 2012–2013. We found that satellite aerosol products performed better in tracking the day-to-day variability than the high-resolution spatial variability. VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.
E. Jäkel, B. Mey, R. Levy, X. Gu, T. Yu, Z. Li, D. Althausen, B. Heese, and M. Wendisch
Atmos. Meas. Tech., 8, 5237–5249, https://doi.org/10.5194/amt-8-5237-2015, https://doi.org/10.5194/amt-8-5237-2015, 2015
R. C. Levy, L. A. Munchak, S. Mattoo, F. Patadia, L. A. Remer, and R. E. Holz
Atmos. Meas. Tech., 8, 4083–4110, https://doi.org/10.5194/amt-8-4083-2015, https://doi.org/10.5194/amt-8-4083-2015, 2015
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Aerosol optical depth (AOD) is an essential climate variable, so we seek to create a long-term AOD record. From MODIS, we have 15+ years, which we want to continue with VIIRS. Accounting for instrumental difference, we have developed a MODIS-like algorithm for VIIRS, and applied it to overlapping 2-year time period. In general, the two data sets are similar, except for VIIRS being high-biased over ocean. We discuss the impacts of calibration, resolution, and sampling on the results.
I. Veselovskii, D. N Whiteman, M. Korenskiy, A. Suvorina, A. Kolgotin, A. Lyapustin, Y. Wang, M. Chin, H. Bian, T. L. Kucsera, D. Pérez-Ramírez, and B. Holben
Atmos. Chem. Phys., 15, 1647–1660, https://doi.org/10.5194/acp-15-1647-2015, https://doi.org/10.5194/acp-15-1647-2015, 2015
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The multi-wavelength lidar technique was applied to the study of a smoke event near Washington, DC on 26-28 August 2013. Satellite observations combined with transport model predictions imply that the smoke plume originated mainly from Wyoming/Idaho forest fires. The NASA GSFC multi-wavelength Mie-Raman lidar was used to profile the smoke particle parameters such as volume density, effective radius and the real part of the refractive index.
B. Arvani, R. B. Pierce, A. I. Lyapustin, Y. Wang, G. Ghermandi, and S. Teggi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-123-2015, https://doi.org/10.5194/acpd-15-123-2015, 2015
Revised manuscript not accepted
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The manuscript compares 10km Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 and new 1 km Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Optical Depth (AOD) retrievals to small (<10 micron) particulate matter (PM10) surface measurements from monitoring stations within the Po Valley in Northern Italy during 2012. When the depth of the planetary boundary layer (PBL) is used to normalize the AOD, we find PM – AOD correlations of 0.98 for both retrievals.
T. F. Eck, B. N. Holben, J. S. Reid, A. Arola, R. A. Ferrare, C. A. Hostetler, S. N. Crumeyrolle, T. A. Berkoff, E. J. Welton, S. Lolli, A. Lyapustin, Y. Wang, J. S. Schafer, D. M. Giles, B. E. Anderson, K. L. Thornhill, P. Minnis, K. E. Pickering, C. P. Loughner, A. Smirnov, and A. Sinyuk
Atmos. Chem. Phys., 14, 11633–11656, https://doi.org/10.5194/acp-14-11633-2014, https://doi.org/10.5194/acp-14-11633-2014, 2014
J. Strandgren, L. Mei, M. Vountas, J. P. Burrows, A. Lyapustin, and Y. Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-25869-2014, https://doi.org/10.5194/acpd-14-25869-2014, 2014
Revised manuscript not accepted
U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. Wind
Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, https://doi.org/10.5194/amt-7-2839-2014, 2014
P. R. Colarco, R. A. Kahn, L. A. Remer, and R. C. Levy
Atmos. Meas. Tech., 7, 2313–2335, https://doi.org/10.5194/amt-7-2313-2014, https://doi.org/10.5194/amt-7-2313-2014, 2014
X. Hu, L. A. Waller, A. Lyapustin, Y. Wang, and Y. Liu
Atmos. Chem. Phys., 14, 6301–6314, https://doi.org/10.5194/acp-14-6301-2014, https://doi.org/10.5194/acp-14-6301-2014, 2014
Z. Zhang, K. Meyer, S. Platnick, L. Oreopoulos, D. Lee, and H. Yu
Atmos. Meas. Tech., 7, 1777–1789, https://doi.org/10.5194/amt-7-1777-2014, https://doi.org/10.5194/amt-7-1777-2014, 2014
M. Chin, T. Diehl, Q. Tan, J. M. Prospero, R. A. Kahn, L. A. Remer, H. Yu, A. M. Sayer, H. Bian, I. V. Geogdzhayev, B. N. Holben, S. G. Howell, B. J. Huebert, N. C. Hsu, D. Kim, T. L. Kucsera, R. C. Levy, M. I. Mishchenko, X. Pan, P. K. Quinn, G. L. Schuster, D. G. Streets, S. A. Strode, O. Torres, and X.-P. Zhao
Atmos. Chem. Phys., 14, 3657–3690, https://doi.org/10.5194/acp-14-3657-2014, https://doi.org/10.5194/acp-14-3657-2014, 2014
J. M. Livingston, J. Redemann, Y. Shinozuka, R. Johnson, P. B. Russell, Q. Zhang, S. Mattoo, L. Remer, R. Levy, L. Munchak, and S. Ramachandran
Atmos. Chem. Phys., 14, 2015–2038, https://doi.org/10.5194/acp-14-2015-2014, https://doi.org/10.5194/acp-14-2015-2014, 2014
G. Wind, A. M. da Silva, P. M. Norris, and S. Platnick
Geosci. Model Dev., 6, 2049–2062, https://doi.org/10.5194/gmd-6-2049-2013, https://doi.org/10.5194/gmd-6-2049-2013, 2013
A. Chudnovsky, C. Tang, A. Lyapustin, Y. Wang, J. Schwartz, and P. Koutrakis
Atmos. Chem. Phys., 13, 10907–10917, https://doi.org/10.5194/acp-13-10907-2013, https://doi.org/10.5194/acp-13-10907-2013, 2013
R. C. Levy, S. Mattoo, L. A. Munchak, L. A. Remer, A. M. Sayer, F. Patadia, and N. C. Hsu
Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, https://doi.org/10.5194/amt-6-2989-2013, 2013
L. A. Remer, S. Mattoo, R. C. Levy, and L. A. Munchak
Atmos. Meas. Tech., 6, 1829–1844, https://doi.org/10.5194/amt-6-1829-2013, https://doi.org/10.5194/amt-6-1829-2013, 2013
L. A. Munchak, R. C. Levy, S. Mattoo, L. A. Remer, B. N. Holben, J. S. Schafer, C. A. Hostetler, and R. A. Ferrare
Atmos. Meas. Tech., 6, 1747–1759, https://doi.org/10.5194/amt-6-1747-2013, https://doi.org/10.5194/amt-6-1747-2013, 2013
H. Zhang, R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Lyapustin
Atmos. Meas. Tech., 6, 471–486, https://doi.org/10.5194/amt-6-471-2013, https://doi.org/10.5194/amt-6-471-2013, 2013
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Instruments and Platforms
The EarthCARE lidar cloud and aerosol profile processor (A-PRO): the A-AER, A-EBD, A-TC, and A-ICE products
Shortwave Array Spectroradiometer-Hemispheric (SAS-He): design and evaluation
Enhancing mobile aerosol monitoring with CE376 dual-wavelength depolarization lidar
Assessment of the spectral misalignment effect (SMILE) on EarthCARE's Multi-Spectral Imager aerosol and cloud property retrievals
The Langley ratio method, a new approach for transferring photometer calibration from direct sun measurements
Multi-star calibration in starphotometry
Continuous observations from horizontally pointing lidar, weather parameters and PM2.5: a pre-deployment assessment for monitoring radioactive dust in Fukushima, Japan
Multiwavelength fluorescence lidar observations of smoke plumes
Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic
Earth observations from the Moon's surface: dependence on lunar libration
Relationship between the sub-micron fraction (SMF) and fine-mode fraction (FMF) in the context of AERONET retrievals
Systematic analysis of virga and its impact on surface particulate matter observations
Spectrometric fluorescence and Raman lidar: absolute calibration of aerosol fluorescence spectra and fluorescence correction of humidity measurements
The polarimetric characteristics of dust with irregular shapes: evaluation of the spheroid model for single particles
The eVe reference polarisation lidar system for the calibration and validation of the Aeolus L2A product
Evaluation of aerosol microphysical, optical and radiative properties measured with a multiwavelength photometer
Polarization lidar for detecting dust orientation: system design and calibration
Accuracy in starphotometry
Rethinking the correction for absorbing aerosols in the OMI- and TROPOMI-like surface UV algorithms
Mie–Raman–fluorescence lidar observations of aerosols during pollen season in the north of France
Satellite imagery and products of the 16–17 February 2020 Saharan Air Layer dust event over the eastern Atlantic: impacts of water vapor on dust detection and morphology
Combined use of Mie–Raman and fluorescence lidar observations for improving aerosol characterization: feasibility experiment
Solar radiometer sensing of multi-year aerosol features over a tropical urban station: direct-Sun and inversion products
An overview of and issues with sky radiometer technology and SKYNET
Scanning polarization lidar LOSA-M3: opportunity for research of crystalline particle orientation in the ice clouds
The polarized Sun and sky radiometer SSARA: design, calibration, and application for ground-based aerosol remote sensing
Nocturnal aerosol optical depth measurements with modified sky radiometer POM-02 using the moon as a light source
Relationship analysis of PM2.5 and boundary layer height using an aerosol and turbulence detection lidar
Monitoring aerosols over Europe: an assessment of the potential benefit of assimilating the VIS04 measurements from the future MTG/FCI geostationary imager
The impact of MISR-derived injection height initialization on wildfire and volcanic plume dispersion in the HYSPLIT model
The instrument constant of sky radiometers (POM-02) – Part 1: Calibration constant
The instrument constant of sky radiometers (POM-02) – Part 2: Solid view angle
Description and applications of a mobile system performing on-road aerosol remote sensing and in situ measurements
Remote sensing of aerosols with small satellites in formation flight
A study of the approaches used to retrieve aerosol extinction, as applied to limb observations made by OSIRIS and SCIAMACHY
Increased aerosol content in the atmosphere over Ukraine during summer 2010
Experimental techniques for the calibration of lidar depolarization channels in EARLINET
Calibration of the DSCOVR EPIC visible and NIR channels using MODIS Terra and Aqua data and EPIC lunar observations
Using paraxial approximation to describe the optical setup of a typical EARLINET lidar system
Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes
Aerosol optical depth determination in the UV using a four-channel precision filter radiometer
A new zenith-looking narrow-band radiometer-based system (ZEN) for dust aerosol optical depth monitoring
Aerosol absorption retrieval at ultraviolet wavelengths in a complex environment
1064 nm rotational Raman lidar for particle extinction and lidar-ratio profiling: cirrus case study
About the effects of polarising optics on lidar signals and the Δ90 calibration
Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers
An empirical method to correct for temperature-dependent variations in the overlap function of CHM15k ceilometers
Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites
The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: the neXT generation
Profiling the PM2.5 mass concentration vertical distribution in the boundary layer
David Patrick Donovan, Gerd-Jan van Zadelhoff, and Ping Wang
Atmos. Meas. Tech., 17, 5301–5340, https://doi.org/10.5194/amt-17-5301-2024, https://doi.org/10.5194/amt-17-5301-2024, 2024
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ATLID (atmospheric lidar) is the lidar to be flown on the Earth Clouds and Radiation Explorer satellite (EarthCARE). EarthCARE is a joint European–Japanese satellite mission that was launched in May 2024. ATLID is an advanced lidar optimized for cloud and aerosol property profile measurements. This paper describes some of the key novel algorithms being applied to this lidar to retrieve cloud and aerosol properties. Example results based on simulated data are presented and discussed.
Evgueni Kassianov, Connor J. Flynn, James C. Barnard, Brian D. Ermold, and Jennifer M. Comstock
Atmos. Meas. Tech., 17, 4997–5013, https://doi.org/10.5194/amt-17-4997-2024, https://doi.org/10.5194/amt-17-4997-2024, 2024
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Conventional ground-based radiometers commonly measure solar radiation at a few wavelengths within a narrow spectral range. These limitations prevent improved retrievals of aerosol, cloud, and surface characteristics. To address these limitations, an advanced ground-based radiometer with expanded spectral coverage and hyperspectral capability is introduced. Its good performance is demonstrated using reference data collected over three coastal regions with diverse types of aerosols and clouds.
Maria Fernanda Sanchez Barrero, Ioana Elisabeta Popovici, Philippe Goloub, Stephane Victori, Qiaoyun Hu, Benjamin Torres, Thierry Podvin, Luc Blarel, Gaël Dubois, Fabrice Ducos, Eric Bourrianne, Aliaksandr Lapionak, Lelia Proniewski, Brent Holben, David Matthew Giles, and Anthony LaRosa
Atmos. Meas. Tech., 17, 3121–3146, https://doi.org/10.5194/amt-17-3121-2024, https://doi.org/10.5194/amt-17-3121-2024, 2024
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This study showcases the use of a compact elastic lidar to monitor aerosols aboard moving platforms. By coupling dual-wavelength and depolarization measurements with photometer data, we studied aerosols during events of Saharan dust and smoke transport. Our research, conducted in various scenarios, not only validated our methods but also offered insights into the atmospheric dynamics near active fires. This study aids future research to fill observational gaps in aerosol monitoring.
Nicole Docter, Anja Hünerbein, David P. Donovan, Rene Preusker, Jürgen Fischer, Jan Fokke Meirink, Piet Stammes, and Michael Eisinger
Atmos. Meas. Tech., 17, 2507–2519, https://doi.org/10.5194/amt-17-2507-2024, https://doi.org/10.5194/amt-17-2507-2024, 2024
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MSI is the imaging spectrometer on board EarthCARE and will provide across-track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
Antonio Fernando Almansa, África Barreto, Natalia Kouremeti, Ramiro González, Akriti Masoom, Carlos Toledano, Julian Gröbner, Rosa Delia García, Yenny González, Stelios Kazadzis, Stéphane Victori, Óscar Álvarez, Fabrice Maupin, Virgilio Carreño, Victoria Eugenia Cachorro, and Emilio Cuevas
Atmos. Meas. Tech., 17, 659–675, https://doi.org/10.5194/amt-17-659-2024, https://doi.org/10.5194/amt-17-659-2024, 2024
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This paper applies sun photometer synergies to improve calibration transference between different sun photometers and also enhance their quality assurance and quality control. We have validated this technique using different instrumentation, the WMO-GAW and NASA-AERONET references, under different aerosol regimes using the standard Langley calibration method as a reference.
Liviu Ivănescu and Norman T. O'Neill
Atmos. Meas. Tech., 16, 6111–6121, https://doi.org/10.5194/amt-16-6111-2023, https://doi.org/10.5194/amt-16-6111-2023, 2023
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The starphotometers' complex infrastructure prohibits calibration campaigns. On-site calibration procedures appear as the only practical solution. A multi-star approach overcomes site-specific sky transparency stability problems. Star selection strategies were proposed for mitigating some sources of errors. Data processing strategies and instrument design improvements appear necessary.
Nofel Lagrosas, Kosuke Okubo, Hitoshi Irie, Yutaka Matsumi, Tomoki Nakayama, Yutaka Sugita, Takashi Okada, and Tatsuo Shiina
Atmos. Meas. Tech., 16, 5937–5951, https://doi.org/10.5194/amt-16-5937-2023, https://doi.org/10.5194/amt-16-5937-2023, 2023
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This work examines the near-ground aerosol–weather relationship from 7-month continuous lidar and weather observations in Chiba, Japan. Optical parameters from lidar data are compared with weather parameters to understand and quantify the aerosol–weather relationship and how these optical parameters are affected by the weather and season. The results provide insights into analyzing optical properties of radioactive aerosols when the lidar system is continuously operated in a radioactive area.
Igor Veselovskii, Nikita Kasianik, Mikhail Korenskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, and Dong Liu
Atmos. Meas. Tech., 16, 2055–2065, https://doi.org/10.5194/amt-16-2055-2023, https://doi.org/10.5194/amt-16-2055-2023, 2023
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A five-channel fluorescence lidar was developed for the study of atmospheric aerosol. The fluorescence spectrum induced by 355 nm laser emission is analyzed in five spectral intervals, namely 438 and 29, 472 and 32, 513 and 29, 560 and 40, and 614 and 54 nm. This lidar system was operated during strong forest fires. Our results demonstrate that, for urban aerosol, the maximal fluorescence backscattering is observed at 472 nm, while for smoke, the spectrum is shifted toward longer wavelengths.
Emily D. Lenhardt, Lan Gao, Jens Redemann, Feng Xu, Sharon P. Burton, Brian Cairns, Ian Chang, Richard A. Ferrare, Chris A. Hostetler, Pablo E. Saide, Calvin Howes, Yohei Shinozuka, Snorre Stamnes, Mary Kacarab, Amie Dobracki, Jenny Wong, Steffen Freitag, and Athanasios Nenes
Atmos. Meas. Tech., 16, 2037–2054, https://doi.org/10.5194/amt-16-2037-2023, https://doi.org/10.5194/amt-16-2037-2023, 2023
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Small atmospheric particles, such as smoke from wildfires or pollutants from human activities, impact cloud properties, and clouds have a strong influence on climate. To better understand the distributions of these particles, we develop relationships to derive their concentrations from remote sensing measurements from an instrument called a lidar. Our method is reliable for smoke particles, and similar steps can be taken to develop relationships for other particle types.
Nick Gorkavyi, Nickolay Krotkov, and Alexander Marshak
Atmos. Meas. Tech., 16, 1527–1537, https://doi.org/10.5194/amt-16-1527-2023, https://doi.org/10.5194/amt-16-1527-2023, 2023
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The article discusses topical issues of the visible (libration) motion of the Earth in the sky of the Moon in a rectangle measuring 13.4° × 15.8°. On the one hand, the librations of the Moon make these observations difficult. On the other hand, they can be used as a natural scanning mechanism for cameras and spectroscopes mounted on a fixed platform on the surface of the Moon.
Norman T. O'Neill, Keyvan Ranjbar, Liviu Ivănescu, Thomas F. Eck, Jeffrey S. Reid, David M. Giles, Daniel Pérez-Ramírez, and Jai Prakash Chaubey
Atmos. Meas. Tech., 16, 1103–1120, https://doi.org/10.5194/amt-16-1103-2023, https://doi.org/10.5194/amt-16-1103-2023, 2023
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Aerosols are atmospheric particles that vary in size (radius) from a fraction of a micrometer (µm) to around 20 µm. They tend to be either smaller than 1 µm (like smoke or pollution) or larger than 1 µm (like dust or sea salt). Their optical effect (scattering and absorbing sunlight) can be divided into FM (fine-mode) and CM (coarse-mode) parts using a cutoff radius around 1 µm or a spectral (color) technique. We present and validate a theoretical link between the types of FM and CM divisions.
Nakul N. Karle, Ricardo K. Sakai, Rosa M. Fitzgerald, Charles Ichoku, Fernando Mercado, and William R. Stockwell
Atmos. Meas. Tech., 16, 1073–1085, https://doi.org/10.5194/amt-16-1073-2023, https://doi.org/10.5194/amt-16-1073-2023, 2023
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Extensive virga research is uncommon, even though it is a common phenomenon. A systematic method was developed to characterize virga using available datasets. In total, 50 virga events were observed, appearing only during a specific time of the year, revealing a seasonal pattern. These virga events were identified and classified, and their impact on surface PM measurements was investigated. A more detailed examination of the selected events reveals that virga impacts regional air quality.
Jens Reichardt, Oliver Behrendt, and Felix Lauermann
Atmos. Meas. Tech., 16, 1–13, https://doi.org/10.5194/amt-16-1-2023, https://doi.org/10.5194/amt-16-1-2023, 2023
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The UVA spectrometer is the latest instrumental addition to the spectrometric fluorescence and Raman lidar RAMSES. The redesigned receiver and the data analysis of the fluorescence measurement are described. Furthermore, the effect of aerosol fluorescence on humidity measurements is studied. It turns out that Raman lidars equipped with a spectrometer show superior performance over those with one discrete fluorescence detection channel only. The cause is variability in the fluorescence spectrum.
Jie Luo, Zhengqiang Li, Cheng Fan, Hua Xu, Ying Zhang, Weizhen Hou, Lili Qie, Haoran Gu, Mengyao Zhu, Yinna Li, and Kaitao Li
Atmos. Meas. Tech., 15, 2767–2789, https://doi.org/10.5194/amt-15-2767-2022, https://doi.org/10.5194/amt-15-2767-2022, 2022
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A single model is difficult to represent various shapes of dust. We proposed a tunable model to represent dust with various shapes. Two tunable parameters were used to represent the effects of the erosion degree and binding forces from the mass center. Thus, the model can represent various dust shapes by adjusting the tunable parameters. Besides, the applicability of the spheroid model in calculating the optical properties and polarimetric characteristics is evaluated.
Peristera Paschou, Nikolaos Siomos, Alexandra Tsekeri, Alexandros Louridas, George Georgoussis, Volker Freudenthaler, Ioannis Binietoglou, George Tsaknakis, Alexandros Tavernarakis, Christos Evangelatos, Jonas von Bismarck, Thomas Kanitz, Charikleia Meleti, Eleni Marinou, and Vassilis Amiridis
Atmos. Meas. Tech., 15, 2299–2323, https://doi.org/10.5194/amt-15-2299-2022, https://doi.org/10.5194/amt-15-2299-2022, 2022
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The eVe lidar delivers quality-assured aerosol and cloud optical properties according to the standards of ACTRIS. It is a mobile reference system for the validation of the ESA's Aeolus satellite mission (L2 aerosol and cloud products). eVe provides linear and circular polarisation measurements with Raman capabilities. Here, we describe the system design, the polarisation calibration techniques, and the software for the retrieval of the optical products.
Yu Zheng, Huizheng Che, Yupeng Wang, Xiangao Xia, Xiuqing Hu, Xiaochun Zhang, Jun Zhu, Jibiao Zhu, Hujia Zhao, Lei Li, Ke Gui, and Xiaoye Zhang
Atmos. Meas. Tech., 15, 2139–2158, https://doi.org/10.5194/amt-15-2139-2022, https://doi.org/10.5194/amt-15-2139-2022, 2022
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Ground-based observations of aerosols and aerosol data verification is important for satellite and climate model modification. Here we present an evaluation of aerosol microphysical, optical and radiative properties measured using a multiwavelength photometer with a highly integrated design and smart control performance. The validation of this product is discussed in detail using AERONET as a reference. This work contributes to reducing AOD uncertainties in China and combating climate change.
Alexandra Tsekeri, Vassilis Amiridis, Alexandros Louridas, George Georgoussis, Volker Freudenthaler, Spiros Metallinos, George Doxastakis, Josef Gasteiger, Nikolaos Siomos, Peristera Paschou, Thanasis Georgiou, George Tsaknakis, Christos Evangelatos, and Ioannis Binietoglou
Atmos. Meas. Tech., 14, 7453–7474, https://doi.org/10.5194/amt-14-7453-2021, https://doi.org/10.5194/amt-14-7453-2021, 2021
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Dust orientation in the Earth's atmosphere has been an ongoing investigation in recent years, and its potential proof will be a paradigm shift for dust remote sensing. We have designed and developed a polarization lidar that provides direct measurements of dust orientation, as well as more detailed information of the particle microphysics. We provide a description of its design as well as its first measurements.
Liviu Ivănescu, Konstantin Baibakov, Norman T. O'Neill, Jean-Pierre Blanchet, and Karl-Heinz Schulz
Atmos. Meas. Tech., 14, 6561–6599, https://doi.org/10.5194/amt-14-6561-2021, https://doi.org/10.5194/amt-14-6561-2021, 2021
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Starphotometry seeks to provide accurate measures of nocturnal optical depth (OD). It is driven by a need to characterize aerosols and their radiative forcing effects during a very data-sparse period. A sub-0.01 OD error is required to adequately characterize key aerosol parameters. We found approaches for sufficiently mitigating errors to achieve the 0.01 standard. This renders starphotometry the equal of daytime techniques and opens the door to exploiting its distinct star-pointing advantages.
Antti Arola, William Wandji Nyamsi, Antti Lipponen, Stelios Kazadzis, Nickolay A. Krotkov, and Johanna Tamminen
Atmos. Meas. Tech., 14, 4947–4957, https://doi.org/10.5194/amt-14-4947-2021, https://doi.org/10.5194/amt-14-4947-2021, 2021
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Methods to estimate surface UV radiation from satellite measurements offer the only means to obtain global coverage, and the development of satellite-based UV algorithms has been ongoing since the early 1990s. One of the main challenges in this development has been how to account for the overall effect of absorption by atmospheric aerosols. One such method was suggested roughly a decade ago, and in this study we propose further improvements for this kind of approach.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Marie Choël, Nicolas Visez, and Mikhail Korenskiy
Atmos. Meas. Tech., 14, 4773–4786, https://doi.org/10.5194/amt-14-4773-2021, https://doi.org/10.5194/amt-14-4773-2021, 2021
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The multiwavelength Mie–Raman–fluorescence lidar of the University of Lille was used to characterize aerosols during the pollen season in the north of France for the period March–June 2020. The results of observations demonstrate that the presence of pollen grains in aerosol mixtures leads to an increase in the depolarization ratio and to the enhancement of the fluorescence backscattering.
Lewis Grasso, Daniel Bikos, Jorel Torres, John F. Dostalek, Ting-Chi Wu, John Forsythe, Heather Q. Cronk, Curtis J. Seaman, Steven D. Miller, Emily Berndt, Harry G. Weinman, and Kennard B. Kasper
Atmos. Meas. Tech., 14, 1615–1634, https://doi.org/10.5194/amt-14-1615-2021, https://doi.org/10.5194/amt-14-1615-2021, 2021
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This study uses geostationary imagery to detect dust. This research was done to demonstrate the ability of dust detection over ocean surfaces in a dry atmosphere.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Mikhail Korenskiy, Olivier Pujol, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 13, 6691–6701, https://doi.org/10.5194/amt-13-6691-2020, https://doi.org/10.5194/amt-13-6691-2020, 2020
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To study the feasibility of a fluorescence lidar for aerosol characterization, the fluorescence channel is added to the multiwavelength Mie-Raman lidar of Lille University. A part of the fluorescence spectrum is selected by the interference filter of 44 nm bandwidth centered at 466 nm. Such an approach has demonstrated high sensitivity, allowing fluorescence signals from weak aerosol layers to be detected. The technique can also be used for monitoring the aerosol inside the cloud layers.
Katta Vijayakumar, Panuganti C. S. Devara, Sunil M. Sonbawne, David M. Giles, Brent N. Holben, Sarangam Vijaya Bhaskara Rao, and Chalicheemalapalli K. Jayasankar
Atmos. Meas. Tech., 13, 5569–5593, https://doi.org/10.5194/amt-13-5569-2020, https://doi.org/10.5194/amt-13-5569-2020, 2020
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The direct-Sun and inversion products of urban atmospheric aerosols, obtained from a Cimel Sun–sky radiometer in Pune, India, under the AERONET program since October 2004, have been reported in this paper. The mean seasonal variations in AOD from cloud-free days indicated greater values during the monsoon season, revealing dominance of hygroscopic aerosols over the station. Such results are sparse in India and are important for estimating aerosol radiative forcing and validating climate models.
Teruyuki Nakajima, Monica Campanelli, Huizheng Che, Victor Estellés, Hitoshi Irie, Sang-Woo Kim, Jhoon Kim, Dong Liu, Tomoaki Nishizawa, Govindan Pandithurai, Vijay Kumar Soni, Boossarasiri Thana, Nas-Urt Tugjsurn, Kazuma Aoki, Sujung Go, Makiko Hashimoto, Akiko Higurashi, Stelios Kazadzis, Pradeep Khatri, Natalia Kouremeti, Rei Kudo, Franco Marenco, Masahiro Momoi, Shantikumar S. Ningombam, Claire L. Ryder, Akihiro Uchiyama, and Akihiro Yamazaki
Atmos. Meas. Tech., 13, 4195–4218, https://doi.org/10.5194/amt-13-4195-2020, https://doi.org/10.5194/amt-13-4195-2020, 2020
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This paper overviews the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. The paper also discusses current issues of SKYNET to provide better information for the community.
Grigorii P. Kokhanenko, Yurii S. Balin, Marina G. Klemasheva, Sergei V. Nasonov, Mikhail M. Novoselov, Iogannes E. Penner, and Svetlana V. Samoilova
Atmos. Meas. Tech., 13, 1113–1127, https://doi.org/10.5194/amt-13-1113-2020, https://doi.org/10.5194/amt-13-1113-2020, 2020
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Cirrus clouds consist of crystals (plates, needles) that can orient themselves in space as a result of free fall. This leads to the appearance of various types of optical halo and to specular reflection of solar radiation. The presence of such particles significantly affects the passage of thermal radiation through the mid- and high-level ice clouds. Using the properties of polarization, a scanning lidar makes it possible to identify cloud areas with oriented crystals.
Hans Grob, Claudia Emde, Matthias Wiegner, Meinhard Seefeldner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 13, 239–258, https://doi.org/10.5194/amt-13-239-2020, https://doi.org/10.5194/amt-13-239-2020, 2020
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Polarimetry has been established as an enhancement to classical photometry in aerosol remote sensing over the past years. We propose a fast and exact radiometric and polarimetric calibration method for polarized photometers. Additionally, a technique for correcting an alt-azimuthal mount is introduced.
These methods are applied to measurements obtained with our SSARA instrument during the A-LIFE field campaign. For 2 d, the data are subjected to an inversion of aerosol optical properties.
Akihiro Uchiyama, Masataka Shiobara, Hiroshi Kobayashi, Tsuneo Matsunaga, Akihiro Yamazaki, Kazunori Inei, Kazuhiro Kawai, and Yoshiaki Watanabe
Atmos. Meas. Tech., 12, 6465–6488, https://doi.org/10.5194/amt-12-6465-2019, https://doi.org/10.5194/amt-12-6465-2019, 2019
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The majority of aerosol data are obtained from daytime measurements using the Sun as a light source, and there are few datasets available for studying nighttime aerosol characteristics. To estimate the aerosol optical depth (AOD) during the nighttime using the moon as a light source, a radiometer for the daytime was modified, and a new calibration method was developed. As a result, the estimations of the nighttime AOD were made with the same degree of precision and accuracy during the daytime.
Chong Wang, Mingjiao Jia, Haiyun Xia, Yunbin Wu, Tianwen Wei, Xiang Shang, Chengyun Yang, Xianghui Xue, and Xiankang Dou
Atmos. Meas. Tech., 12, 3303–3315, https://doi.org/10.5194/amt-12-3303-2019, https://doi.org/10.5194/amt-12-3303-2019, 2019
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To investigate the relationship between BLH and air pollution under different conditions, a compact micro-pulse lidar integrating both direct-detection lidar and coherent Doppler wind lidar is built. Evolution of atmospheric boundary layer height (BLH), aerosol layer and fine structure in cloud base are well retrieved. Negative correlation exists between BLH and PM2.5. Different trends show that the relationship between PM2.5 and BLH should be considered in different boundary layer categories.
Maxence Descheemaecker, Matthieu Plu, Virginie Marécal, Marine Claeyman, Francis Olivier, Youva Aoun, Philippe Blanc, Lucien Wald, Jonathan Guth, Bojan Sič, Jérôme Vidot, Andrea Piacentini, and Béatrice Josse
Atmos. Meas. Tech., 12, 1251–1275, https://doi.org/10.5194/amt-12-1251-2019, https://doi.org/10.5194/amt-12-1251-2019, 2019
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The future Flexible Combined Imager (FCI) on board MeteoSat Third Generation is expected to improve the detection and the quantification of aerosols. The study assesses the potential of FCI/VIS04 channel for monitoring air pollution in Europe. An observing system simulation experiment in MOCAGE is developed, and they show a large positive impact of the assimilation over a 4-month period and particularly during a severe pollution episode. The added value of geostationary data is also assessed.
Charles J. Vernon, Ryan Bolt, Timothy Canty, and Ralph A. Kahn
Atmos. Meas. Tech., 11, 6289–6307, https://doi.org/10.5194/amt-11-6289-2018, https://doi.org/10.5194/amt-11-6289-2018, 2018
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The height that aerosols are injected into the atmosphere can significantly impact the dispersion of aerosol plumes. We use direct observations from the MISR instrument to determine aerosol injection height and constrain the HYSPLIT Dispersion model with these data. We have shown that the nominal plume-rise calculation within HYSPLIT tends to underestimate injection heights of wildfires and that simulations constrained with MISR injection height can show better agreement with MODIS observations.
Akihiro Uchiyama, Tsuneo Matsunaga, and Akihiro Yamazaki
Atmos. Meas. Tech., 11, 5363–5388, https://doi.org/10.5194/amt-11-5363-2018, https://doi.org/10.5194/amt-11-5363-2018, 2018
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Atmospheric aerosols are an important constituent of the atmosphere. Measurement networks using radiometers such as SKYNET have been developed. There are two constants that we must determine to make accurate measurements. One of them is the calibration constant. The accuracy of the current method to determine this was investigated and the new method for water vapor and near-infrared channels was developed. Utilizing the results of this paper, SKYNET measurement data will become more reliable.
Akihiro Uchiyama, Tsuneo Matsunaga, and Akihiro Yamazaki
Atmos. Meas. Tech., 11, 5389–5402, https://doi.org/10.5194/amt-11-5389-2018, https://doi.org/10.5194/amt-11-5389-2018, 2018
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Atmospheric aerosols are an important constituent of the atmosphere. Measurement networks using radiometers such as SKYNET have been developed. There are two constants that we must determine. One of them is the solid view angle (SVA) of the radiometer. The problems related to SVA were investigated. It was shown that the conventional method can cause a systematic underestimation, and an improved method was proposed. Utilizing the results of this paper, SKYNET data will become more reliable.
Ioana Elisabeta Popovici, Philippe Goloub, Thierry Podvin, Luc Blarel, Rodrigue Loisil, Florin Unga, Augustin Mortier, Christine Deroo, Stéphane Victori, Fabrice Ducos, Benjamin Torres, Cyril Delegove, Marie Choël, Nathalie Pujol-Söhne, and Christophe Pietras
Atmos. Meas. Tech., 11, 4671–4691, https://doi.org/10.5194/amt-11-4671-2018, https://doi.org/10.5194/amt-11-4671-2018, 2018
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This paper aims to show the potential of an instrumented mobile platform, performing on-road remote sensing and in situ measurements, to derive aerosol properties. It is distinguished from other transportable platforms through its ability to perform measurements during movement. Its reduced size, versatility and great flexibility makes it suitable for following sudden aerosol events and for validating satellite measurements and model simulations.
Kirk Knobelspiesse and Sreeja Nag
Atmos. Meas. Tech., 11, 3935–3954, https://doi.org/10.5194/amt-11-3935-2018, https://doi.org/10.5194/amt-11-3935-2018, 2018
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We test if small satellites flying in formation can be used for multi-angle aerosol remote sensing. So far, this has only been done with multiple views on one satellite. Single-view angle satellites flying in formation are a technically feasible alternative, although with different geometries. Using Bayesian information content analysis, we find such satellites equally capable. For aerosol remote sensing, the number of viewing angles is the most important.
Landon A. Rieger, Elizaveta P. Malinina, Alexei V. Rozanov, John P. Burrows, Adam E. Bourassa, and Doug A. Degenstein
Atmos. Meas. Tech., 11, 3433–3445, https://doi.org/10.5194/amt-11-3433-2018, https://doi.org/10.5194/amt-11-3433-2018, 2018
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This paper compares aerosol extinction records from two limb scattering instruments, OSIRIS and SCIAMACHY, to that from the occultation instrument SAGE II. Differences are investigated through modelling and retrieval studies and important sources of systematic errors are quantified. It is found that the largest biases come from uncertainties in the aerosol size distribution and the aerosol particle concentration at altitudes above 30 km.
Evgenia Galytska, Vassyl Danylevsky, René Hommel, and John P. Burrows
Atmos. Meas. Tech., 11, 2101–2118, https://doi.org/10.5194/amt-11-2101-2018, https://doi.org/10.5194/amt-11-2101-2018, 2018
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This research assesses the influence of biomass burning during forest fires throughout summer 2010 on aerosol load over Ukraine, the European territory of Russia (ETR) and Eastern Europe. We apply and compare ground-based and satellite measurements to determine aerosol content, dynamics, and properties. With the application of modeling techniques (HYSPLIT), we show that the maximum AOD in August 2010 over Ukraine was caused by particle transport from the forest fires in the ETR.
Livio Belegante, Juan Antonio Bravo-Aranda, Volker Freudenthaler, Doina Nicolae, Anca Nemuc, Dragos Ene, Lucas Alados-Arboledas, Aldo Amodeo, Gelsomina Pappalardo, Giuseppe D'Amico, Francesco Amato, Ronny Engelmann, Holger Baars, Ulla Wandinger, Alexandros Papayannis, Panos Kokkalis, and Sérgio N. Pereira
Atmos. Meas. Tech., 11, 1119–1141, https://doi.org/10.5194/amt-11-1119-2018, https://doi.org/10.5194/amt-11-1119-2018, 2018
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This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected EARLINET lidar instruments. The calibrated volume and particle depolarization profiles at 532 nm show values that fall within a range that is accepted in the literature. The depolarization accuracy estimate at 532 nm is better than ±0.03 for all cases.
Igor V. Geogdzhayev and Alexander Marshak
Atmos. Meas. Tech., 11, 359–368, https://doi.org/10.5194/amt-11-359-2018, https://doi.org/10.5194/amt-11-359-2018, 2018
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The unique Earth view of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) orbiting at the point of equal attraction from the Earth and the Sun can significantly augment the low-orbit remote sensing of aerosols, clouds and gases. We derive the relationship between the digital counts and the reflected sunlight intensity for some EPIC channels using collocated Earth views from EPIC and Moderate Resolution Imaging Spectroradiometer (MODIS) and EPIC moon views.
Panagiotis Kokkalis
Atmos. Meas. Tech., 10, 3103–3115, https://doi.org/10.5194/amt-10-3103-2017, https://doi.org/10.5194/amt-10-3103-2017, 2017
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The mathematical formulation for the optical setup of a typical EARLINET lidar system is given here. The equations describing a lidar system from the emitted laser beam to the projection of the telescope aperture on the final receiving unit (i.e., photomultiplier or photodiode) are presented, based on paraxial approximation and a geometric optics approach. The evaluation of the formulation is performed with ray-tracing simulations on a real system.
Andrew M. Sayer, N. Christina Hsu, Corey Bettenhausen, Robert E. Holz, Jaehwa Lee, Greg Quinn, and Paolo Veglio
Atmos. Meas. Tech., 10, 1425–1444, https://doi.org/10.5194/amt-10-1425-2017, https://doi.org/10.5194/amt-10-1425-2017, 2017
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The satellite instrument VIIRS is being used to carry on observations of the Earth made by older satellites like MODIS. Data sets created from these satellite observations depend on the quality of the satellite instruments' calibration. This paper describes a comparison between the calibration of these two sensors. MODIS is believed to be more reliable and so VIIRS is corrected to bring it in line with MODIS. These corrections are shown to improve the quality of VIIRS aerosol data.
Thomas Carlund, Natalia Kouremeti, Stelios Kazadzis, and Julian Gröbner
Atmos. Meas. Tech., 10, 905–923, https://doi.org/10.5194/amt-10-905-2017, https://doi.org/10.5194/amt-10-905-2017, 2017
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Aerosols play an important role in atmospheric processes. Aerosol optical depth is the most common measure of columnar aerosol load. We present a sunphotometer called UVPFR that is able to measure aerosol optical depth in the ultraviolet range, including the calibration, characterization and validation of the instrument/measurements. The instrument will serve as a reference on the intercalibration of Brewer spectrophotometers that are also able to measure aerosol optical depth in the UV region.
A. Fernando Almansa, Emilio Cuevas, Benjamín Torres, África Barreto, Rosa D. García, Victoria E. Cachorro, Ángel M. de Frutos, César López, and Ramón Ramos
Atmos. Meas. Tech., 10, 565–579, https://doi.org/10.5194/amt-10-565-2017, https://doi.org/10.5194/amt-10-565-2017, 2017
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This study presents a new zenith-looking narrow-band radiometer-based system (ZEN), conceived for dust aerosol optical depth (AOD) monitoring. The ZEN system comprises a robust and automated radiometer (ZEN-R41), and a lookup table methodology for AOD retrieval (ZEN-LUT). Our results suggest that ZEN is a suitable system to fill the current observational gaps and to complement observations performed by sun-photometer networks in order to improve mineral dust monitoring in remote locations.
Stelios Kazadzis, Panagiotis Raptis, Natalia Kouremeti, Vassilis Amiridis, Antti Arola, Evangelos Gerasopoulos, and Gregory L. Schuster
Atmos. Meas. Tech., 9, 5997–6011, https://doi.org/10.5194/amt-9-5997-2016, https://doi.org/10.5194/amt-9-5997-2016, 2016
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Aerosols play an important role in the Earth's climate. One of the main aerosol properties is the single scattering albedo which is a measure of the aerosol absorption. In this work we have presented a method to retrieve this aerosol property in the ultraviolet and we presented the results for measurements at the urban environment of Athens, Greece. We show that the spectral dependence of the aerosol absorption in the VIS–IR and the UV range depends on the aerosol composition and type.
Moritz Haarig, Ronny Engelmann, Albert Ansmann, Igor Veselovskii, David N. Whiteman, and Dietrich Althausen
Atmos. Meas. Tech., 9, 4269–4278, https://doi.org/10.5194/amt-9-4269-2016, https://doi.org/10.5194/amt-9-4269-2016, 2016
Volker Freudenthaler
Atmos. Meas. Tech., 9, 4181–4255, https://doi.org/10.5194/amt-9-4181-2016, https://doi.org/10.5194/amt-9-4181-2016, 2016
Simone Kotthaus, Ewan O'Connor, Christoph Münkel, Cristina Charlton-Perez, Martial Haeffelin, Andrew M. Gabey, and C. Sue B. Grimmond
Atmos. Meas. Tech., 9, 3769–3791, https://doi.org/10.5194/amt-9-3769-2016, https://doi.org/10.5194/amt-9-3769-2016, 2016
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Ceilometers lidars are useful to study clouds, aerosol layers and atmospheric boundary layer structures. As sensor optics and acquisition algorithms can strongly influence the observations, sensor specifics need to be incorporated into the physical interpretation. Here, recommendations are made for the operation and processing of profile observations from the widely deployed Vaisala CL31 ceilometer. Proposed corrections are shown to increase data quality and even data availability at times.
Maxime Hervo, Yann Poltera, and Alexander Haefele
Atmos. Meas. Tech., 9, 2947–2959, https://doi.org/10.5194/amt-9-2947-2016, https://doi.org/10.5194/amt-9-2947-2016, 2016
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Imperfections in a lidar's overlap function lead to artefacts in the lidar (Light Detection and Ranging) signals. These artefacts can erroneously be interpreted as an aerosol gradient or, in extreme cases, as a cloud base leading to false cloud detection. In this study an algorithm is presented to correct such artefacts.
The algorithm is completely automatic and does not require any intervention on site. It is therefore suited for use in large automatic lidar networks.
Aaron R. Naeger, Pawan Gupta, Bradley T. Zavodsky, and Kevin M. McGrath
Atmos. Meas. Tech., 9, 2463–2482, https://doi.org/10.5194/amt-9-2463-2016, https://doi.org/10.5194/amt-9-2463-2016, 2016
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In this study, we merge aerosol information from multiple satellite sensors on board low-earth orbiting (LEO) and geostationary (GEO) platforms in order to provide a more comprehensive understanding of the spatial distribution of aerosols compared to when only using single sensors as is commonly done. Our results show that merging aerosol information from LEO and GEO platforms can be very useful, which paves the way for applications to the more advanced next-generation of satellites.
Ronny Engelmann, Thomas Kanitz, Holger Baars, Birgit Heese, Dietrich Althausen, Annett Skupin, Ulla Wandinger, Mika Komppula, Iwona S. Stachlewska, Vassilis Amiridis, Eleni Marinou, Ina Mattis, Holger Linné, and Albert Ansmann
Atmos. Meas. Tech., 9, 1767–1784, https://doi.org/10.5194/amt-9-1767-2016, https://doi.org/10.5194/amt-9-1767-2016, 2016
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The atmospheric science community demands for autonomous and quality-assured vertically resolved measurements of aerosol and cloud properties. For this purpose, a portable lidar called Polly
was developed at TROPOS in 2003. This lidar type was continuously improved with gained experience from EARLINET, worldwide field campaigns, and institute collaborations within the last 10 years. We present recent changes to the setup of our portable multiwavelength Raman and polarization lidar PollyXT.
Zongming Tao, Zhenzhu Wang, Shijun Yang, Huihui Shan, Xiaomin Ma, Hui Zhang, Sugui Zhao, Dong Liu, Chenbo Xie, and Yingjian Wang
Atmos. Meas. Tech., 9, 1369–1376, https://doi.org/10.5194/amt-9-1369-2016, https://doi.org/10.5194/amt-9-1369-2016, 2016
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A new measurement technology of PM2.5 mass concentration profile near ground is addressed using a CCD side-scatter lidar and a PM2.5 detector.
The PM2.5 mass concentration profile can be built upon the vertical distribution of the extinction coefficient for aerosol. The PM2.5 is always loading in the planet boundary layer with a complex muti-layer structure. The new method for PM2.5 mass concentration profile is useful for improving our understanding of air quality and atmospheric environment.
Cited articles
Franz, B. A., Kwiatkowska, E. J., Meister, G., and McClain, C. R.: Moderate Resolution Imaging Spectroradiometer on Terra: limitations for ocean color applications, J. Appl. Remote Sens., 2, 023525, https://doi.org/10.1117/1.2957964, 2008.
Gordon, H. R., Du, T., and Zhang, T.: Atmospheric correction of ocean color sensors: analysis of the effects of residual instrument polarization sensitivity, Appl. Optics, 36, 6938–6948, 1997.
Hilker, T., Lyapustin, A. I., Tucker, C. J., Sellers, P. J., Hall, F. G., and Wang, Y.: Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter, Remote Sens. Environ., 127, 370–384, https://doi.org/10.1016/j.rse.2012.08.035, 2012.
Hilker, T., Lyapustin, A. I., Tucker, C. J., Hall, F. G., Myneni, R. B., Wang, Y., Bi, J., de Moura, Y. M., Sellers, P. J.: Vegetation dynamics and rainfall sensitivity of the Amazon, P. Natl. Acad. Sci., 111, 16041–16046, https://doi.org/10.1073/pnas.1404870111, 2014.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F., Jankowiak, I., and Smirnov, A.: AERONET-A Federated Instrument Network and Data Archive for Aerosol Characterization, Remote Sens. Environ., 66, 1–16, 1998.
Hubanks, P., King, M. D., Platnick, S., and Pincus, R.: MODIS Algorithm Theoretical Basis Document No. ATBD-MOD-30 for Level-3 Global Gridded Atmosphere Products (08_D3, 08_E3, 08_M3, available at: http://modis-atmos.gsfc.nasa.gov/_docs/L3_ATBD_2008_12_04.pdf (last access: 8 December 2014), 2008.
Jeong, M.-J., Hsu, N. C., Kwiatkowska, E. J., Franz, B. A., and Meister, G.: Impacts of cross-platform vicarious calibration on the Deep Blue aerosol retrievals for MODIS aboard Terra, IEEE T. Geosci. Remote Sens., 49, 4877–4888, https://doi.org/10.1109/TGRS.2011.2153205, 2011.
Kahn, R. A., Gaitley, B. J., Garay, M. J., Diner, D. J., Eck, T., Smirnov, A., and Holben, B. N.: MISR global aerosol product assessment by comparison with Aerosol Robotic Network, J. Geophys. Res., 115, D23209, https://doi.org/10.1029/2010JD014601, 2010.
King, M. D., Platnick, S., Menzel, W. P., Ackerman, S. A., and Hubanks, P. A.: Spatial and Temporal Distribution of Clouds Observed by MODIS onboard the Terra and Aqua Satellites, IEEE Trans. Geosci. Remote Sens., 51, 3826–3852, https://doi.org/10.1109/TGRS.2012.2227333, 2013.
Korkin S., Lyapustin, A., and Rozanov, V.: APC: A new code for atmospheric polarization computations, J. Quant. Spectrosc. Ra., 127, 1–11, 2013.
Kwiatkowska, E. J., Franz, B. A., Meister, G., McClain, C. R., and Xiong, X.: Cross calibration of ocean-color bands from Moderate Resolution Imaging Spectroradiometer on Terra platform, Appl. Optics, 47, 6796–6810, 2008.
Levy, R. C., Remer, L., Mattoo, S., Vermote, E., and Kaufman, Y. J.: Second-generation algorithm for retrieving aerosol properties over land from MODIS spectral reflectance, J. Geophys. Res., 112, D13211, https://doi.org/10.1029/2006JD007811, 2007a.
Levy, R. C., Remer, L. A., and Dubovik, O.: Global aerosol optical properties and application to MODIS aerosol retrieval over land, J. Geophys. Res., 112, D13210, https://doi.org/10.1029/2006JD007815, 2007b.
Levy, R., Leptoukh, G., Kahn, R., Zubko, V., Gopalan, A., and Remer, L.: A critical look at deriving monthly aerosol optical depth from satellite data, IEEE T. Geosci. Remote Sens., 9, 2942–2956, https://doi.org/10.1109/TGRS.2009.2013842, 2009.
Levy, R. C., Remer, L. A., Kleidman, R. G., Mattoo, S., Ichoku, C., Kahn, R., and Eck, T. F.: Global evaluation of the Collection 5 MODIS dark-target aerosol products over land, Atmos. Chem. Phys., 10, 10399–10420, https://doi.org/10.5194/acp-10-10399-2010, 2010.
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, 2013.
Liu, H. Q. and Huete, A.: A Feedback Based Modification of the NDVI to Minimize Canopy Background and Atmospheric Noise, IEEE Geosci. Remote Sens., 33, 457–465, 1985.
Lyapustin, A., Wang, Y., and Frey, R.: An Automatic Cloud Mask Algorithm Based on Time Series of MODIS Measurements, J. Geophys. Res., 113, D16207, https://doi.org/10.1029/2007JD009641, 2008.
Lyapustin, A., Martonchik, J., Wang, Y., Laszlo, I., and Korkin, S.: Multi-Angle Implementation of Atmospheric Correction (MAIAC): 1. Radiative Transfer Basis and Look-Up Tables, J. Geophys. Res., 116, D03210, https://doi.org/10.1029/2010JD014985, 2011a.
Lyapustin, A., Wang, Y., Laszlo, I., Kahn, R., Korkin, S., Remer, L., Levy, R., and Reid, J. S.: Multi-Angle Implementation of Atmospheric Correction (MAIAC): 2. Aerosol Algorithm, J. Geophys. Res., 116, D03211, https://doi.org/10.1029/2010JD014986, 2011b.
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