Articles | Volume 25, issue 13
https://doi.org/10.5194/acp-25-7403-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-7403-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Analysis of a saline dust storm from the Aralkum Desert – Part 1: Consistency between multisensor satellite aerosol products
Xin Xi
CORRESPONDING AUTHOR
Department of Geological and Mining Engineering and Sciences, Michigan Technological University, Houghton, MI, USA
Department of Chemical and Biochemical Engineering, The University of Iowa, Iowa City, IA, USA
Zhendong Lu
Interdisciplinary Graduate Program in Informatics, The University of Iowa, Iowa City, IA, USA
Andrew M. Sayer
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD, USA
Jaehwa Lee
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
Robert C. Levy
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Yujie Wang
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD, USA
Alexei Lyapustin
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Hongqing Liu
Center for Satellite Applications and Research, National Environmental Satellite, Data, and Information Service, National Oceanic and Atmospheric Administration, College Park, MD, USA
I. M. Systems Group, Inc., College Park, MD, USA
Istvan Laszlo
Center for Satellite Applications and Research, National Environmental Satellite, Data, and Information Service, National Oceanic and Atmospheric Administration, College Park, MD, USA
Department of Atmospheric and Oceanic Sciences, University of Maryland, College Park, MD, USA
Changwoo Ahn
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications Inc., Lanham, MD, USA
Omar Torres
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Sabur Abdullaev
Physical Technical Institute of the Academy of Sciences of Tajikistan, Dushanbe, Tajikistan
James Limbacher
Science and Technology Corporation, Hampton, VA, USA
Ralph A. Kahn
Laboratory for Atmospheric and Space Physics, The University of Colorado Boulder, Boulder, CO, USA
Related authors
Xin Xi
EGUsphere, https://doi.org/10.5194/egusphere-2025-2808, https://doi.org/10.5194/egusphere-2025-2808, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
The atmospheric circulation patterns favoring dust outbreaks from the man-made Aralkum Desert remain poorly understood. This paper reveals that an extreme cold air and dust outbreak in May 2018 was facilitated by recurrent transient Rossby wave packets across the North Atlantic and persistent blocking over Scandinavia. This study underscores the importance of upstream atmospheric blocking for understanding and forecasting cold air and dust outbreaks from Central Asia.
Xinzhu Li, Longlei Li, Yan Feng, and Xin Xi
EGUsphere, https://doi.org/10.5194/egusphere-2025-3013, https://doi.org/10.5194/egusphere-2025-3013, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study evaluates the dust emission variability and relationship with its physical drivers within 21 ESMs, and uncovers new insights about model discrepancies in dust variability and the relative importance of wind and hydroclimate drivers. The study underscores the importance of improving hydroclimate and land surface representations for reducing uncertainties in dust emission responses to climate variability and change.
Xin Xi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-813, https://doi.org/10.5194/acp-2020-813, 2020
Preprint withdrawn
Robert James Duncan Spurr, Matt Christi, Nickolay Anatoly Krotkov, Won-Ei Choi, Simon Carn, Can Li, Natalya Kramarova, David Haffner, Eun-Su Yang, Nick Gorkavyi, Alexander Vasilkov, Krzysztof Wargan, Omar Torres, Diego Loyola, Serena Di Pede, Joris Pepijn Veefkind, and Pawan Kumar Bhartia
EGUsphere, https://doi.org/10.5194/egusphere-2025-2938, https://doi.org/10.5194/egusphere-2025-2938, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
An eruption of the submarine Hunga volcano injected a massive plume of water vapor, sulfur dioxide and aerosols into the Southern tropical stratosphere. The high-altitude Hunga aerosol plume showed up as strongly enhanced solar backscattered ultraviolet (BUV) radiation compromising satellite BUV ozone retrievals. In this paper, we have developed a new technique to retrieve the aerosol amount and height, based on satellite solar BUV radiances from the TROPOMI and OMPS nadir profiler instruments.
Xin Xi
EGUsphere, https://doi.org/10.5194/egusphere-2025-2808, https://doi.org/10.5194/egusphere-2025-2808, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
The atmospheric circulation patterns favoring dust outbreaks from the man-made Aralkum Desert remain poorly understood. This paper reveals that an extreme cold air and dust outbreak in May 2018 was facilitated by recurrent transient Rossby wave packets across the North Atlantic and persistent blocking over Scandinavia. This study underscores the importance of upstream atmospheric blocking for understanding and forecasting cold air and dust outbreaks from Central Asia.
Xinzhu Li, Longlei Li, Yan Feng, and Xin Xi
EGUsphere, https://doi.org/10.5194/egusphere-2025-3013, https://doi.org/10.5194/egusphere-2025-3013, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study evaluates the dust emission variability and relationship with its physical drivers within 21 ESMs, and uncovers new insights about model discrepancies in dust variability and the relative importance of wind and hydroclimate drivers. The study underscores the importance of improving hydroclimate and land surface representations for reducing uncertainties in dust emission responses to climate variability and change.
Xiaohua Pan, Mian Chin, Ralph A. Kahn, Hitoshi Matsui, Toshihiko Takemura, Meiyun Lin, Yuanyu Xie, Dongchul Kim, and Maria Val Martin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2603, https://doi.org/10.5194/egusphere-2025-2603, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Wildfire smoke can travel thousands of kilometers, affecting air quality far from the fire itself. This study looks at how two key factors – how much smoke is emitted & how high it rises – affect how smoke spreads. Using data from a major 2008 Siberian wildfire, four computer models were tested. Results show that models often inject smoke too low & remove it too quickly, missing high-altitude smoke seen by satellites. Better estimates of smoke height are crucial to improve air quality forecasts.
Andrew M. Sayer, Brian Cairns, Kirk D. Knobelspiesse, Luca Lelli, Chamara Rajapakshe, Scott E. Giangrande, Gareth E. Thomas, and Damao Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2005, https://doi.org/10.5194/egusphere-2025-2005, 2025
Short summary
Short summary
Satellites can estimate cloud height in several ways: two include a thermal technique (colder clouds being higher up), and another looking at colours of light that oxygen in the atmosphere absorbs (darker clouds being lower down). It can also be measured (from ground or space) by radar and lidar. We compare satellite data we developed using the oxygen method with other estimates to help us refine our technique.
Jeewoo Lee, Jhoon Kim, Seoyoung Lee, Myungje Choi, Jaehwa Lee, Daniel J. Jacob, Su Keun Kuk, and Young-Je Park
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-281, https://doi.org/10.5194/essd-2025-281, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
Atmospheric aerosols adversely affect human health, with East Asia recognized as one of the most impacted regions. This study presents a long-term (2011–2021), high spatiotemporal resolution aerosol optical depth dataset retrieved from a geostationary satellite over East Asia. The high-resolution data capture subtle aerosol gradients and land-ocean boundaries, providing valuable input for various fields such as aerosol-cloud interaction, climate change, ocean optics, and air quality studies.
Huanxin Zhang, Jun Wang, Nathan Janechek, Cui Ge, Meng Zhou, Lorena Castro García, Tong Sha, Yanyu Wang, Weizhi Deng, Zhixin Xue, Chengzhe Li, Lakhima Chutia, Yi Wang, Sebastian Val, James L. McDuffie, Sina Hasheminassab, Scott E. Gluck, David J. Diner, Peter R. Colarco, and Arlindo M. da Silva
EGUsphere, https://doi.org/10.5194/egusphere-2025-1360, https://doi.org/10.5194/egusphere-2025-1360, 2025
Short summary
Short summary
We present here the development of the Unified Inputs (of initial and boundary conditions) for WRF-Chem (UI-WRF-Chem) framework to support the Multi-Angle Imager for Aerosols (MAIA) satellite mission. Some of the major updates include improving dust size distribution in the chemical boundary conditions, updating land surface properties using timely satellite data and improvement of soil NOx emissions. We demonstrate subsequent model improvement over several of the MAIA target areas.
Zachary Watson, Can Li, Fei Liu, Sean W. Freeman, Huanxin Zhang, Jun Wang, and Shan-Hu Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-1735, https://doi.org/10.5194/egusphere-2025-1735, 2025
Short summary
Short summary
Air pollutants like sulfur dioxide cause direct impacts on human health and the environment. Our work estimated surface concentrations from satellite data using atmospheric models and machine learning compared to an air quality monitoring network. We found that both methods can accurately determine the locations and changes in sulfur dioxide, but the machine learning method had better accuracy. Both methods are useful for monitoring air quality in locations without ground-based measurements.
Meloë S. F. Kacenelenbogen, Ralph Kuehn, Nandana Amarasinghe, Kerry Meyer, Edward Nowottnick, Mark Vaughan, Hong Chen, Sebastian Schmidt, Richard Ferrare, John Hair, Robert Levy, Hongbin Yu, Paquita Zuidema, Robert Holz, and Willem Marais
EGUsphere, https://doi.org/10.5194/egusphere-2025-1403, https://doi.org/10.5194/egusphere-2025-1403, 2025
Short summary
Short summary
Aerosols perturb the radiation balance of the Earth-atmosphere system. To reduce the uncertainty in quantifying present-day climate change, we combine two satellite sensors and a model to assess the aerosol effects on radiation in all-sky conditions. Satellite-based and coincident aircraft measurements of aerosol radiative effects agree well over the Southeast Atlantic. This constitutes a crucial first evaluation before we apply our method to more years and regions of the world.
Katherine T. Junghenn Noyes and Ralph A. Kahn
EGUsphere, https://doi.org/10.5194/egusphere-2025-395, https://doi.org/10.5194/egusphere-2025-395, 2025
Short summary
Short summary
With observations from NASA’s Multi-Angle Imaging Spectroradiometer (MISR) satellite instrument, we can constrain wildfire plume heights, smoke age, and particle size, shape, and light-absorption properties. We study over 3,600 wildfire plumes across Siberia by statistically comparing the MISR results to observations of fire strength, land cover type, and meteorology. We then stratify plumes by land cover type and infer the dominant aerosol aging mechanisms among different plume types.
Mariya Petrenko, Ralph Kahn, Mian Chin, Susanne E. Bauer, Tommi Bergman, Huisheng Bian, Gabriele Curci, Ben Johnson, Johannes W. Kaiser, Zak Kipling, Harri Kokkola, Xiaohong Liu, Keren Mezuman, Tero Mielonen, Gunnar Myhre, Xiaohua Pan, Anna Protonotariou, Samuel Remy, Ragnhild Bieltvedt Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Hailong Wang, Duncan Watson-Parris, and Kai Zhang
Atmos. Chem. Phys., 25, 1545–1567, https://doi.org/10.5194/acp-25-1545-2025, https://doi.org/10.5194/acp-25-1545-2025, 2025
Short summary
Short summary
We compared smoke plume simulations from 11 global models to each other and to satellite smoke amount observations aimed at constraining smoke source strength. In regions where plumes are thick and background aerosol is low, models and satellites compare well. However, the input emission inventory tends to underestimate in many places, and particle property and loss rate assumptions vary enormously among models, causing uncertainties that require systematic in situ measurements to resolve.
Hyerim Kim, Xi Chen, Jun Wang, Zhendong Lu, Meng Zhou, Gregory R. Carmichael, Sang Seo Park, and Jhoon Kim
Atmos. Meas. Tech., 18, 327–349, https://doi.org/10.5194/amt-18-327-2025, https://doi.org/10.5194/amt-18-327-2025, 2025
Short summary
Short summary
We compare passive aerosol layer height (ALH) retrievals from the Earth Polychromatic Imaging Camera (EPIC), TROPOspheric Monitoring Instrument (TROPOMI), and Geostationary Environment Monitoring Spectrometer (GEMS) with lidar. GEMS shows a lower correlation (R = 0.64) than EPIC and TROPOMI (R > 0.7) but with minimal bias (0.1 km vs. overestimated by ~0.8 km). GEMS performance is improved for an ultraviolet aerosol index ≥ 3. EPIC and GEMS ALH diurnal variation differs slightly.
Sarah Smith, Yutian Wu, Rob Levy, and Mingfang Ting
EGUsphere, https://doi.org/10.5194/egusphere-2024-3596, https://doi.org/10.5194/egusphere-2024-3596, 2025
Short summary
Short summary
Satellite data from a laser-based instrument show Arctic particulate matter is highest in winter and spring, and lowest in summer. However, sunlight-based instruments show the highest values in summer and very low values in autumn/spring. We find that a sunlight-based instrument retrieves lower than expected values when the sun is low on the horizon, but only when clouds are also present, likely due to cloud shadows. This causes it to underestimate particulates in winter, even beyond the Arctic.
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
Atmos. Meas. Tech., 17, 7027–7047, https://doi.org/10.5194/amt-17-7027-2024, https://doi.org/10.5194/amt-17-7027-2024, 2024
Short summary
Short summary
Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Tong Sha, Siyu Yang, Qingcai Chen, Liangqing Li, Xiaoyan Ma, Yan-Lin Zhang, Zhaozhong Feng, K. Folkert Boersma, and Jun Wang
Atmos. Chem. Phys., 24, 8441–8455, https://doi.org/10.5194/acp-24-8441-2024, https://doi.org/10.5194/acp-24-8441-2024, 2024
Short summary
Short summary
Using an updated soil reactive nitrogen emission scheme in the Unified Inputs for Weather Research and Forecasting coupled with Chemistry (UI-WRF-Chem) model, we investigate the role of soil NO and HONO (Nr) emissions in air quality and temperature in North China. Contributions of soil Nr emissions to O3 and secondary pollutants are revealed, exceeding effects of soil NOx or HONO emission. Soil Nr emissions play an important role in mitigating O3 pollution and addressing climate change.
Yeseul Cho, Jhoon Kim, Sujung Go, Mijin Kim, Seoyoung Lee, Minseok Kim, Heesung Chong, Won-Jin Lee, Dong-Won Lee, Omar Torres, and Sang Seo Park
Atmos. Meas. Tech., 17, 4369–4390, https://doi.org/10.5194/amt-17-4369-2024, https://doi.org/10.5194/amt-17-4369-2024, 2024
Short summary
Short summary
Aerosol optical properties have been provided by the Geostationary Environment Monitoring Spectrometer (GEMS), the world’s first geostationary-Earth-orbit (GEO) satellite instrument designed for atmospheric environmental monitoring. This study describes improvements made to the GEMS aerosol retrieval algorithm (AERAOD) and presents its validation results. These enhancements aim to provide more accurate and reliable aerosol-monitoring results for Asia.
Zhendong Lu, Jun Wang, Yi Wang, Daven K. Henze, Xi Chen, Tong Sha, and Kang Sun
Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
Short summary
Short summary
In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
Hiren T. Jethva, Omar Torres, Richard A. Ferrare, Sharon P. Burton, Anthony L. Cook, David B. Harper, Chris A. Hostetler, Jens Redemann, Vinay Kayetha, Samuel LeBlanc, Kristina Pistone, Logan Mitchell, and Connor J. Flynn
Atmos. Meas. Tech., 17, 2335–2366, https://doi.org/10.5194/amt-17-2335-2024, https://doi.org/10.5194/amt-17-2335-2024, 2024
Short summary
Short summary
We introduce a novel synergy algorithm applied to ORALCES airborne measurements of above-cloud aerosol optical depth and UV–Vis satellite observations from OMI and MODIS to retrieve spectral aerosol single-scattering albedo of lofted layers of carbonaceous smoke aerosols over clouds. The development of the proposed aerosol–cloud algorithm implies a possible synergy of CALIOP and OMI–MODIS passive sensors to deduce a global product of AOD and SSA of absorbing aerosols above clouds.
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
Short summary
Short summary
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.
Jingting Huang, S. Marcela Loría-Salazar, Min Deng, Jaehwa Lee, and Heather A. Holmes
Atmos. Chem. Phys., 24, 3673–3698, https://doi.org/10.5194/acp-24-3673-2024, https://doi.org/10.5194/acp-24-3673-2024, 2024
Short summary
Short summary
Increased wildfire intensity has resulted in taller wildfire smoke plumes. We investigate the vertical structure of wildfire smoke plumes using aircraft lidar data and establish two effective smoke plume height metrics. Four novel satellite-based plume height products are evaluated for wildfires in the western US. Our results provide guidance on the strengths and limitations of these satellite products and set the stage for improved plume rise estimates by leveraging satellite products.
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
Short summary
Short summary
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.
James A. Limbacher, Ralph A. Kahn, Mariel D. Friberg, Jaehwa Lee, Tyler Summers, and Hai Zhang
Atmos. Meas. Tech., 17, 471–498, https://doi.org/10.5194/amt-17-471-2024, https://doi.org/10.5194/amt-17-471-2024, 2024
Short summary
Short summary
We present the new Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that fuses observations from GOES-16 and GOES-17 to retrieve information about aerosol loading (at 10–15 min cadence) and aerosol particle properties (daily), all at pixel-level resolution. We present MAGARA results for three case studies: the 2018 California Camp Fire, the 2019 Williams Flats Fire, and the 2019 Kincade Fire. We also compare MAGARA aerosol loading and particle properties with AERONET.
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
Short summary
Short summary
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.
Da Lu, Hao Li, Mengke Tian, Guochen Wang, Xiaofei Qin, Na Zhao, Juntao Huo, Fan Yang, Yanfen Lin, Jia Chen, Qingyan Fu, Yusen Duan, Xinyi Dong, Congrui Deng, Sabur F. Abdullaev, and Kan Huang
Atmos. Chem. Phys., 23, 13853–13868, https://doi.org/10.5194/acp-23-13853-2023, https://doi.org/10.5194/acp-23-13853-2023, 2023
Short summary
Short summary
Environmental conditions during dust are usually not favorable for secondary aerosol formation. However in this study, an unusual dust event was captured in a Chinese mega-city and showed “anomalous” meteorology and a special dust backflow transport pathway. The underlying formation mechanisms of secondary aerosols are probed in the context of this special dust event. This study shows significant implications for the varying dust aerosol chemistry in the future changing climate.
Robert R. Nelson, Marcin L. Witek, Michael J. Garay, Michael A. Bull, James A. Limbacher, Ralph A. Kahn, and David J. Diner
Atmos. Meas. Tech., 16, 4947–4960, https://doi.org/10.5194/amt-16-4947-2023, https://doi.org/10.5194/amt-16-4947-2023, 2023
Short summary
Short summary
Shallow and coastal waters are nutrient-rich and turbid due to runoff. They are also located in areas where the atmosphere has more aerosols than open-ocean waters. NASA's Multi-angle Imaging SpectroRadiometer (MISR) has been monitoring aerosols for over 23 years but does not report results over shallow waters. We developed a new algorithm that uses all four of MISR’s bands and considers light leaving water surfaces. This algorithm performs well and increases over-water measurements by over 7 %.
Sebastien Garrigues, Melanie Ades, Samuel Remy, Johannes Flemming, Zak Kipling, Istvan Laszlo, Mark Parrington, Antje Inness, Roberto Ribas, Luke Jones, Richard Engelen, and Vincent-Henri Peuch
Atmos. Chem. Phys., 23, 10473–10487, https://doi.org/10.5194/acp-23-10473-2023, https://doi.org/10.5194/acp-23-10473-2023, 2023
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service (CAMS) provides global monitoring of aerosols using the ECMWF forecast model constrained by the assimilation of satellite aerosol optical depth (AOD). This work aims at evaluating the assimilation of the NOAA VIIRS AOD product in the ECMWF model. It shows that the introduction of VIIRS in the CAMS data assimilation system enhances the accuracy of the aerosol analysis, particularly over Europe and desert and maritime sites.
Qindan Zhu, Bryan Place, Eva Y. Pfannerstill, Sha Tong, Huanxin Zhang, Jun Wang, Clara M. Nussbaumer, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Anthony Bucholtz, John H. Seinfeld, Allen H. Goldstein, and Ronald C. Cohen
Atmos. Chem. Phys., 23, 9669–9683, https://doi.org/10.5194/acp-23-9669-2023, https://doi.org/10.5194/acp-23-9669-2023, 2023
Short summary
Short summary
Nitrogen oxide (NOx) is a hazardous air pollutant, and it is the precursor of short-lived climate forcers like tropospheric ozone and aerosol particles. While NOx emissions from transportation has been strictly regulated, soil NOx emissions are overlooked. We use the airborne flux measurements to observe NOx emissions from highways and urban and cultivated soil land cover types. We show non-negligible soil NOx emissions, which are significantly underestimated in current model simulations.
Ruijun Dang, Daniel J. Jacob, Viral Shah, Sebastian D. Eastham, Thibaud M. Fritz, Loretta J. Mickley, Tianjia Liu, Yi Wang, and Jun Wang
Atmos. Chem. Phys., 23, 6271–6284, https://doi.org/10.5194/acp-23-6271-2023, https://doi.org/10.5194/acp-23-6271-2023, 2023
Short summary
Short summary
We use the GEOS-Chem model to better understand the magnitude and trend in free tropospheric NO2 over the contiguous US. Model underestimate of background NO2 is largely corrected by considering aerosol nitrate photolysis. Increase in aircraft emissions affects satellite retrievals by altering the NO2 shape factor, and this effect is expected to increase in future. We show the importance of properly accounting for the free tropospheric background in interpreting NO2 observations from space.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Michail Mytilinaios, Sara Basart, Sergio Ciamprone, Juan Cuesta, Claudio Dema, Enza Di Tomaso, Paola Formenti, Antonis Gkikas, Oriol Jorba, Ralph Kahn, Carlos Pérez García-Pando, Serena Trippetta, and Lucia Mona
Atmos. Chem. Phys., 23, 5487–5516, https://doi.org/10.5194/acp-23-5487-2023, https://doi.org/10.5194/acp-23-5487-2023, 2023
Short summary
Short summary
Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) dust reanalysis provides a high-resolution 3D reconstruction of past dust conditions, allowing better quantification of climate and socioeconomic dust impacts. We assess the performance of the reanalysis needed to reproduce dust optical depth using dust-related products retrieved from satellite and ground-based observations and show that it reproduces the spatial distribution and seasonal variability of atmospheric dust well.
Athena Augusta Floutsi, Holger Baars, Ronny Engelmann, Dietrich Althausen, Albert Ansmann, Stephanie Bohlmann, Birgit Heese, Julian Hofer, Thomas Kanitz, Moritz Haarig, Kevin Ohneiser, Martin Radenz, Patric Seifert, Annett Skupin, Zhenping Yin, Sabur F. Abdullaev, Mika Komppula, Maria Filioglou, Elina Giannakaki, Iwona S. Stachlewska, Lucja Janicka, Daniele Bortoli, Eleni Marinou, Vassilis Amiridis, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Boris Barja, and Ulla Wandinger
Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, https://doi.org/10.5194/amt-16-2353-2023, 2023
Short summary
Short summary
DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements and currently covers two wavelengths, 355 and 532 nm, for 13 aerosol categories ranging from basic aerosol types to mixtures.
Edward Gryspeerdt, Adam C. Povey, Roy G. Grainger, Otto Hasekamp, N. Christina Hsu, Jane P. Mulcahy, Andrew M. Sayer, and Armin Sorooshian
Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, https://doi.org/10.5194/acp-23-4115-2023, 2023
Short summary
Short summary
The impact of aerosols on clouds is one of the largest uncertainties in the human forcing of the climate. Aerosol can increase the concentrations of droplets in clouds, but observational and model studies produce widely varying estimates of this effect. We show that these estimates can be reconciled if only polluted clouds are studied, but this is insufficient to constrain the climate impact of aerosol. The uncertainty in aerosol impact on clouds is currently driven by cases with little aerosol.
Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, https://doi.org/10.5194/acp-23-3083-2023, 2023
Short summary
Short summary
Plume height is important in wildfire smoke dispersion and affects air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region, but higher pollution in downwind regions, due to the faster spread of the smoke once ejected, affects pollution exceedance forecasts and the early warning of extreme air pollution events.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
Short summary
Short summary
This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023, https://doi.org/10.5194/acp-23-1511-2023, 2023
Short summary
Short summary
This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
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
Short summary
Short summary
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.
James A. Limbacher, Ralph A. Kahn, and Jaehwa Lee
Atmos. Meas. Tech., 15, 6865–6887, https://doi.org/10.5194/amt-15-6865-2022, https://doi.org/10.5194/amt-15-6865-2022, 2022
Short summary
Short summary
Launched in December 1999, NASA’s Multi-angle Imaging SpectroRadiometer (MISR) has given researchers qualitative constraints on aerosol particle properties for the past 22 years. Here, we present a new MISR research aerosol retrieval algorithm (RA) that utilizes over-land surface reflectance data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) to address limitations of the MISR operational aerosol retrieval algorithm and improve retrievals of aerosol particle properties.
Sebastien Garrigues, Samuel Remy, Julien Chimot, Melanie Ades, Antje Inness, Johannes Flemming, Zak Kipling, Istvan Laszlo, Angela Benedetti, Roberto Ribas, Soheila Jafariserajehlou, Bertrand Fougnie, Shobha Kondragunta, Richard Engelen, Vincent-Henri Peuch, Mark Parrington, Nicolas Bousserez, Margarita Vazquez Navarro, and Anna Agusti-Panareda
Atmos. Chem. Phys., 22, 14657–14692, https://doi.org/10.5194/acp-22-14657-2022, https://doi.org/10.5194/acp-22-14657-2022, 2022
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service (CAMS) provides global monitoring of aerosols using the ECMWF forecast model constrained by the assimilation of satellite aerosol optical depth (AOD). This work aims at evaluating two new satellite AODs to enhance the CAMS aerosol global forecast. It highlights the spatial and temporal differences between the satellite AOD products at the model spatial resolution, which is essential information to design multi-satellite AOD data assimilation schemes.
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
Short summary
Short summary
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.
Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney
Atmos. Meas. Tech., 15, 6309–6328, https://doi.org/10.5194/amt-15-6309-2022, https://doi.org/10.5194/amt-15-6309-2022, 2022
Short summary
Short summary
How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.
Lauren M. Zamora, Ralph A. Kahn, Nikolaos Evangeliou, Christine D. Groot Zwaaftink, and Klaus B. Huebert
Atmos. Chem. Phys., 22, 12269–12285, https://doi.org/10.5194/acp-22-12269-2022, https://doi.org/10.5194/acp-22-12269-2022, 2022
Short summary
Short summary
Arctic dust, smoke, and pollution particles can affect clouds and Arctic warming. The distributions of these particles were estimated in three different satellite, reanalysis, and model products. These products showed good agreement overall but indicate that it is important to include local dust in models. We hypothesize that mineral dust effects on ice processes in the Arctic atmosphere might be highest over Siberia, where it is cold, moist, and subject to relatively high dust levels.
Ukkyo Jeong, Si-Chee Tsay, N. Christina Hsu, David M. Giles, John W. Cooper, Jaehwa Lee, Robert J. Swap, Brent N. Holben, James J. Butler, Sheng-Hsiang Wang, Somporn Chantara, Hyunkee Hong, Donghee Kim, and Jhoon Kim
Atmos. Chem. Phys., 22, 11957–11986, https://doi.org/10.5194/acp-22-11957-2022, https://doi.org/10.5194/acp-22-11957-2022, 2022
Short summary
Short summary
Ultraviolet (UV) measurements from satellite and ground are important for deriving information on several atmospheric trace and aerosol characteristics. Simultaneous retrievals of aerosol and trace gases in this study suggest that water uptake by aerosols is one of the important phenomena affecting aerosol properties over northern Thailand, which is important for regional air quality and climate. Obtained aerosol properties covering the UV are also important for various satellite algorithms.
Rachel T. Pinker, Yingtao Ma, Wen Chen, Istvan Laszlo, Hongqing Liu, Hye-Yun Kim, and Jaime Daniels
Atmos. Meas. Tech., 15, 5077–5094, https://doi.org/10.5194/amt-15-5077-2022, https://doi.org/10.5194/amt-15-5077-2022, 2022
Short summary
Short summary
Scene-dependent narrow-to-broadband transformations are developed to facilitate the use of observations from the Advanced Baseline Imager (ABI), the primary instrument on GOES-R, to derive surface shortwave radiative fluxes. This is a first NOAA product at the high resolution of about 5 k over the contiguous United States (CONUS) region. The product is archived and can be downloaded from the NOAA Comprehensive Large Array-data Stewardship System (CLASS).
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
Short summary
Short summary
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.
Xiaoxi Zhao, Kan Huang, Joshua S. Fu, and Sabur F. Abdullaev
Atmos. Chem. Phys., 22, 10389–10407, https://doi.org/10.5194/acp-22-10389-2022, https://doi.org/10.5194/acp-22-10389-2022, 2022
Short summary
Short summary
Long-range transport of Asian dust to the Arctic was considered an important source of Arctic air pollution. Different transport routes to the Arctic had divergent effects on the evolution of aerosol properties. Depositions of long-range-transported dust particles can reduce the Arctic surface albedo considerably. This study implied that the ubiquitous long-transport dust from China exerted considerable aerosol indirect effects on the Arctic and may have potential biogeochemical significance.
Katherine T. Junghenn Noyes, Ralph A. Kahn, James A. Limbacher, and Zhanqing Li
Atmos. Chem. Phys., 22, 10267–10290, https://doi.org/10.5194/acp-22-10267-2022, https://doi.org/10.5194/acp-22-10267-2022, 2022
Short summary
Short summary
We compare retrievals of wildfire smoke particle size, shape, and light absorption from the MISR satellite instrument to modeling and other satellite data on land cover type, drought conditions, meteorology, and estimates of fire intensity (fire radiative power – FRP). We find statistically significant differences in the particle properties based on burning conditions and land cover type, and we interpret how changes in these properties point to specific aerosol aging mechanisms.
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
Short summary
Short summary
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.
Vinay Kayetha, Omar Torres, and Hiren Jethva
Atmos. Meas. Tech., 15, 845–877, https://doi.org/10.5194/amt-15-845-2022, https://doi.org/10.5194/amt-15-845-2022, 2022
Short summary
Short summary
Existing measurements of spectral aerosol absorption are limited, particularly in the UV region. We use the synergy of satellite and ground measurements to derive spectral single scattering albedo of aerosols from the UV–visible spectrum. The resulting spectral SSAs are used to investigate seasonality in absorption for carbonaceous, dust, and urban aerosols. Regional aerosol absorption models that could be used to make reliable assumptions in satellite remote sensing of aerosols are derived.
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
Short summary
Short summary
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.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Nick Gorkavyi, Nickolay Krotkov, Can Li, Leslie Lait, Peter Colarco, Simon Carn, Matthew DeLand, Paul Newman, Mark Schoeberl, Ghassan Taha, Omar Torres, Alexander Vasilkov, and Joanna Joiner
Atmos. Meas. Tech., 14, 7545–7563, https://doi.org/10.5194/amt-14-7545-2021, https://doi.org/10.5194/amt-14-7545-2021, 2021
Short summary
Short summary
The 21 June 2019 eruption of the Raikoke volcano produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. We showed that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of sulfate aerosol lags the initial peak of SO2 by 1.5 months. We also examined the dynamics of an unusual stratospheric coherent circular cloud of SO2 and aerosol observed from 18 July to 22 September 2019.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Sampa Das, Peter R. Colarco, Luke D. Oman, Ghassan Taha, and Omar Torres
Atmos. Chem. Phys., 21, 12069–12090, https://doi.org/10.5194/acp-21-12069-2021, https://doi.org/10.5194/acp-21-12069-2021, 2021
Short summary
Short summary
Interactions of extreme fires with weather systems can produce towering smoke plumes that inject aerosols at very high altitudes (> 10 km). Three such major injections, largest at the time in terms of emitted aerosol mass, took place over British Columbia, Canada, in August 2017. We model the transport and impacts of injected aerosols on the radiation balance of the atmosphere. Our model results match the satellite-observed plume transport and residence time at these high altitudes very closely.
Jing Wei, Zhanqing Li, Rachel T. Pinker, Jun Wang, Lin Sun, Wenhao Xue, Runze Li, and Maureen Cribb
Atmos. Chem. Phys., 21, 7863–7880, https://doi.org/10.5194/acp-21-7863-2021, https://doi.org/10.5194/acp-21-7863-2021, 2021
Short summary
Short summary
This study developed a space-time Light Gradient Boosting Machine (STLG) model to derive the high-temporal-resolution (1 h) and high-quality PM2.5 dataset in China (i.e., ChinaHighPM2.5) at a 5 km spatial resolution from the Himawari-8 Advanced Himawari Imager aerosol products. Our model outperforms most previous related studies with a much lower computation burden in terms of speed and memory, making it most suitable for real-time air pollution monitoring in China.
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
Short summary
Short summary
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.
Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 21, 6895–6917, https://doi.org/10.5194/acp-21-6895-2021, https://doi.org/10.5194/acp-21-6895-2021, 2021
Short summary
Short summary
Absorptive aerosol has a potentially large impact on climate change. We evaluate and intercompare four global satellite datasets of absorptive aerosol optical depth (AAOD) and single-scattering albedo (SSA). We show that these datasets show reasonable correlations with the AErosol RObotic NETwork (AERONET) reference, although significant biases remain. In a follow-up paper we show that these observations nevertheless can be used for model evaluation.
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
Short summary
Short summary
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).
Tianmeng Chen, Zhanqing Li, Ralph A. Kahn, Chuanfeng Zhao, Daniel Rosenfeld, Jianping Guo, Wenchao Han, and Dandan Chen
Atmos. Chem. Phys., 21, 6199–6220, https://doi.org/10.5194/acp-21-6199-2021, https://doi.org/10.5194/acp-21-6199-2021, 2021
Short summary
Short summary
A convective cloud identification process is developed using geostationary satellite data from Himawari-8.
Convective cloud fraction is generally larger before noon and smaller in the afternoon under polluted conditions, but megacities and complex topography can influence the pattern.
A robust relationship between convective cloud and aerosol loading is found. This pattern varies with terrain height and is modulated by varying thermodynamic, dynamical, and humidity conditions during the day.
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
Short summary
Short summary
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.
Omar Torres, Hiren Jethva, Changwoo Ahn, Glen Jaross, and Diego G. Loyola
Atmos. Meas. Tech., 13, 6789–6806, https://doi.org/10.5194/amt-13-6789-2020, https://doi.org/10.5194/amt-13-6789-2020, 2020
Short summary
Short summary
TROPOMI measures the quantity of small suspended particles (aerosols). We describe initial results of aerosol measurements using a NASA algorithm that retrieves the UV aerosol index, aerosol optical depth, and single-scattering albedo. An evaluation of derived products using sun-photometer observations shows close agreement. We also use these results to discuss important biomass burning and wildfire events around the world that got the attention of scientists and news media alike.
Marc Mallet, Fabien Solmon, Pierre Nabat, Nellie Elguindi, Fabien Waquet, Dominique Bouniol, Andrew Mark Sayer, Kerry Meyer, Romain Roehrig, Martine Michou, Paquita Zuidema, Cyrille Flamant, Jens Redemann, and Paola Formenti
Atmos. Chem. Phys., 20, 13191–13216, https://doi.org/10.5194/acp-20-13191-2020, https://doi.org/10.5194/acp-20-13191-2020, 2020
Short summary
Short summary
This paper presents numerical simulations using two regional climate models to study the impact of biomass fire plumes from central Africa on the radiative balance of this region. The results indicate that biomass fires can either warm the regional climate when they are located above low clouds or cool it when they are located above land. They can also alter sea and land surface temperatures by decreasing solar radiation at the surface. Finally, they can also modify the atmospheric dynamics.
Hai Zhang, Shobha Kondragunta, Istvan Laszlo, and Mi Zhou
Atmos. Meas. Tech., 13, 5955–5975, https://doi.org/10.5194/amt-13-5955-2020, https://doi.org/10.5194/amt-13-5955-2020, 2020
Short summary
Short summary
Geostationary Operational Environmental Satellites (GOES) retrieve high temporal resolution aerosol optical depth, which is a measure of the aerosol quantity within the atmospheric column. This work introduces an algorithm that improves the accuracy of the aerosol optical depth retrievals from GOES. The resulting data product can be used in monitoring the air quality and climate change research.
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
Short summary
Short summary
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.
Xin Xi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-813, https://doi.org/10.5194/acp-2020-813, 2020
Preprint withdrawn
Priyanka deSouza, Ralph A. Kahn, James A. Limbacher, Eloise A. Marais, Fábio Duarte, and Carlo Ratti
Atmos. Meas. Tech., 13, 5319–5334, https://doi.org/10.5194/amt-13-5319-2020, https://doi.org/10.5194/amt-13-5319-2020, 2020
Short summary
Short summary
This paper presents a novel method to constrain the size distribution derived from low-cost optical particle counters (OPCs) using satellite data to develop higher-quality particulate matter (PM) estimates. Such estimates can enable cities that do not have access to expensive reference air quality monitors, especially those in the global south, to develop effective air quality management plans.
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
Short summary
Short summary
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.
Xiao Lu, Lin Zhang, Tongwen Wu, Michael S. Long, Jun Wang, Daniel J. Jacob, Fang Zhang, Jie Zhang, Sebastian D. Eastham, Lu Hu, Lei Zhu, Xiong Liu, and Min Wei
Geosci. Model Dev., 13, 3817–3838, https://doi.org/10.5194/gmd-13-3817-2020, https://doi.org/10.5194/gmd-13-3817-2020, 2020
Short summary
Short summary
This study presents the development and evaluation of a new climate chemistry model, BCC-GEOS-Chem v1.0, which couples the GEOS-Chem chemical transport model as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model. A 3-year (2012–2014) simulation of BCC-GEOS-Chem v1.0 shows that the model captures well the spatiotemporal distributions of tropospheric ozone, other gaseous pollutants, and aerosols.
Tong Sha, Xiaoyan Ma, Jun Wang, Rong Tian, Jianqi Zhao, Fang Cao, and Yan-Lin Zhang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-760, https://doi.org/10.5194/acp-2020-760, 2020
Preprint withdrawn
Short summary
Short summary
Most numerical models perform poorly on simulating the inorganic chemical components in PM2.5 (sulfate, nitrate, and ammonium (SNA)), generally underestimate sulfate but overestimate nitrate concentrations in haze events. Our work aims at investigating the role of cloud water in simulating SNA. We find that the uncertainties of cloud water can lead to model bias in simulating SNA, and can be reduced by constraining the modeled cloud water with MODIS satellite observations.
Cited articles
Anstett, M., Limbacher, J. A., and Kahn, R. A.: A global aerosol microphysical property record from the Multi-angle Imaging SpectroRadiometer (MISR) research aerosol retrieval algorithm, in preparation, 2025. a
Argaman, E., Singer, A., and Tsoar, H.: Erodibility of some crust forming soils/sediments from the Southern Aral Sea Basin as determined in a wind tunnel, Earth Surf. Proc. Land., 31, 47–63, https://doi.org/10.1002/esp.1230, 2006. a
ASDC: MISR Level 2 Aerosol parameters V003, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/TERRA/MISR/MIL2ASAE_L2.003, 1999. a
ASDC: DSCOVR EPIC Aerosol Optical Centroid Height Version 1, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/EPIC/DSCOVR/L2_AOCH.001, 2018. a
ASDC: CALIPSO Lidar Level 2 Aerosol Profile, V4-51, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmAPro-Standard-V4-51, 2023. a
Balkanski, Y., Schulz, M., Claquin, T., and Guibert, S.: Reevaluation of Mineral aerosol radiative forcings suggests a better agreement with satellite and AERONET data, Atmos. Chem. Phys., 7, 81–95, https://doi.org/10.5194/acp-7-81-2007, 2007. a
Callewaert, S., Vandenbussche, S., Kumps, N., Kylling, A., Shang, X., Komppula, M., Goloub, P., and De Mazière, M.: The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and evaluation, Atmos. Meas. Tech., 12, 3673–3698, https://doi.org/10.5194/amt-12-3673-2019, 2019. a, b
Capelle, V., Chédin, A., Péquignot, E., Schlüssel, P., Newman, S. M., and Scott, N. A.: Infrared continental surface emissivity spectra and skin temperature retrieved from IASI observations over the tropics, J. Appl. Meteorol. Clim., 51, 1164–1179, https://doi.org/10.1175/JAMC-D-11-0145.1, 2012. a
Capelle, V., Chédin, A., Siméon, M., Tsamalis, C., Pierangelo, C., Pondrom, M., Crevoisier, C., Crepeau, L., and Scott, N. A.: Evaluation of IASI-derived dust aerosol characteristics over the tropical belt, Atmos. Chem. Phys., 14, 9343–9362, https://doi.org/10.5194/acp-14-9343-2014, 2014. a
Capelle, V., Chédin, A., Pondrom, M., Crevoisier, C., Armante, R., Crepeau, L., and Scott, N. A.: Infrared dust aerosol optical depth retrieved daily from IASI and comparison with AERONET over the period 2007–2016, Remote Sens. Environ., 206, 15–32, https://doi.org/10.1016/j.rse.2017.12.008, 2018. a, b, c
Carr, J. L., Wu, D. L., Daniels, J., Friberg, M. D., Bresky, W., and Madani, H.: Geo–geo stereo-tracking of atmospheric motion vectors (AMVS) from the geostationary ring, Remote Sensing, 12, 3779, https://doi.org/10.3390/rs12223779, 2020. a
Clarisse, L., Clerbaux, C., Franco, B., Hadji-Lazaro, J., Whitburn, S., Kopp, A. K., Hurtmans, D., and Coheur, P. F.: A Decadal Data Set of Global Atmospheric Dust Retrieved From IASI Satellite Measurements, J. Geophys. Res.-Atmos., 124, 1618–1647, https://doi.org/10.1029/2018JD029701, 2019. a, b
de Graaf, M., Stammes, P., Torres, O., and Koelemeijer, R. B.: Absorbing Aerosol Index: Sensitivity analysis, application to GOME and comparison with TOMS, J. Geophys. Res.-Atmos., 110, D01201, https://doi.org/10.1029/2004JD005178, 2005. a, b
Diner, D. J., Beckert, J. C., Reilly, T. H., Bruegge, C. J., Conel, J. E., Kahn, R. A., Martonchik, J. V., Ackerman, T. P., Davies, R., Gerstl, S. A., Gordon, H. R., Muller, J. P., Myneni, R. B., Sellers, P. J., Pinty, B., and Verstraete, M. M.: Multi-angle imaging spectroradiometer (MISR) instrument description and experiment overview, IEEE T. Geosci. Remote, 36, 1072–1087, https://doi.org/10.1109/36.700992, 1998. a
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I.: Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations, J. Atmos. Sci., 59, 590–608, https://doi.org/10.1175/1520-0469(2002)059<0590:voaaop>2.0.co;2, 2002. a
Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J. F., Sorokin, M., and Slutsker, I.: Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust, J. Geophys. Res.-Atmos., 111, D11208, https://doi.org/10.1029/2005JD006619, 2006. a
ESA: TROPOMI Level 2 Ultraviolet Aerosol Index products Version 02, ESA [data set], https://doi.org/10.5270/S5P-3dgz66p, 2021. a
Flower, V. J. and Kahn, R. A.: Assessing the altitude and dispersion of volcanic plumes using MISR multi-angle imaging from space: Sixteen years of volcanic activity in the Kamchatka Peninsula, Russia, J. Volcanol. Geoth. Res., 337, 1–15, https://doi.org/10.1016/j.jvolgeores.2017.03.010, 2017. a
Garay, M. J., Witek, M. L., Kahn, R. A., Seidel, F. C., Limbacher, J. A., Bull, M. A., Diner, D. J., Hansen, E. G., Kalashnikova, O. V., Lee, H., Nastan, A. M., and Yu, Y.: Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product, Atmos. Meas. Tech., 13, 593–628, https://doi.org/10.5194/amt-13-593-2020, 2020. a
Groll, M., Opp, C., Issanova, G., Vereshagina, N., and Semenov, O.: Physical and chemical characterization of dust deposited in the Turan Lowland (Central Asia), in: Central Asian DUst Conference (CADUC), 8–12 April 2019, Dushanbe, Tajikistan, vol. 99, ISSN 22671242, https://doi.org/10.1051/e3sconf/20199903005, 2019. a
He, X., Bai, Y., Pan, D., Tang, J., and Wang, D.: Atmospheric correction of satellite ocean color imagery using the ultraviolet wavelength for highly turbid waters, Optics Express, 20, 20754, https://doi.org/10.1364/oe.20.020754, 2012. a
Herman, J. R., Bhartia, P. K., Torres, O., Hsu, C., Seftor, C., and Celarier, E.: Global distribution of UV-absorbing aerosols from Nimbus 7/TOMS data, J. Geophys. Res.-Atmos., 102, 16911–16922, https://doi.org/10.1029/96jd03680, 1997. a, b
Hofer, J., Althausen, D., Abdullaev, S. F., Makhmudov, A. N., Nazarov, B. I., Schettler, G., Engelmann, R., Baars, H., Fomba, K. W., Müller, K., Heinold, B., Kandler, K., and Ansmann, A.: Long-term profiling of mineral dust and pollution aerosol with multiwavelength polarization Raman lidar at the Central Asian site of Dushanbe, Tajikistan: case studies, Atmos. Chem. Phys., 17, 14559–14577, https://doi.org/10.5194/acp-17-14559-2017, 2017. a
Hsu, C.: VIIRS/NOAA20 Deep Blue Aerosol L2 6-Min Swath 6 km, NASA [data set], https://doi.org/10.5067/VIIRS/AERDB_L2_VIIRS_NOAA20.002, 2022. a
Hsu, N. C., Tsay, S. C., King, M. D., and Herman, J. R.: Aerosol properties over bright-reflecting source regions, IEEE T. Geosci. Remote, 42, 557–569, https://doi.org/10.1109/TGRS.2004.824067, 2004. a
Hsu, N. C., Jeong, M. J., Bettenhausen, C., Sayer, A. M., Hansell, R., Seftor, C. S., Huang, J., and Tsay, S. C.: Enhanced Deep Blue aerosol retrieval algorithm: The second generation, J. Geophys. Res.-Atmos., 118, 9296–9315, https://doi.org/10.1002/jgrd.50712, 2013. a
Hsu, N. C., Lee, J., Sayer, A. M., Kim, W., Bettenhausen, C., and Tsay, S. C.: VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long-Term Aerosol Data Records, J. Geophys. Res.-Atmos., 124, 4026–4053, https://doi.org/10.1029/2018JD029688, 2019. a
Jackson, J. M., Liu, H., Laszlo, I., Kondragunta, S., Remer, L. A., Huang, J., and Huang, H. C.: Suomi-NPP VIIRS aerosol algorithms and data products, J. Geophys. Res.-Atmos., 118, 12673–12689, https://doi.org/10.1002/2013JD020449, 2013. a
Jiang, H., Huang, J., Li, L., Huang, L., Manzoor, M., Yang, J., Wu, G., Sun, X., Wang, B., Egamberdieva, D., Panosyan, H., Birkeland, N. K., Zhu, Z., and Li, W.: Onshore soil microbes and endophytes respond differently to geochemical and mineralogical changes in the Aral Sea, Sci. Total Environ., 765, 142675, https://doi.org/10.1016/j.scitotenv.2020.142675, 2021. a
Kahn, R. A., Gaitley, B. J., Garay, M. J., Diner, D. J., Eck, T. F., Smirnov, A., and Holben, B. N.: Multiangle Imaging SpectroRadiometer global aerosol product assessment by comparison with the Aerosol Robotic Network, J. Geophys. Res.-Atmos., 115, D23209, https://doi.org/10.1029/2010JD014601, 2010. a
Kim, M.-H., Omar, A. H., Tackett, J. L., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu, Y., Liu, Z., Poole, L. R., Pitts, M. C., Kar, J., and Magill, B. E.: The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm, Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, 2018. a
Koffi, B., Schulz, M., Bréon, F. M., Griesfeller, J., Winker, D., Balkanski, Y., Bauer, S., Berntsen, T., Chin, M., Collins, W. D., Dentener, F., Diehl, T., Easter, R., Ghan, S., Ginoux, P., Gong, S., Horowitz, L. W., Iversen, T., Kirkevg, A., Koch, D., Krol, M., Myhre, G., Stier, P., and Takemura, T.: Application of the CALIOP layer product to evaluate the vertical distribution of aerosols estimated by global models: AeroCom phase I results, J. Geophys. Res., 117, D10201 https://doi.org/10.1029/2011JD016858, 2012. a
Kondragunta, S., Laszlo, I., and Ma, L.: NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth and Aerosol Particle Size Distribution Environmental Data Record (EDR) from NDE, OAA National Centers for Environmental Information [data set], https://doi.org/10.7289/V5319T4H, 2023. a
Laszlo, I.: Remote Sensing of Tropospheric Aerosol Optical Depth From Multispectral Monodirectional Space-Based Observations, in: Comprehensive Remote Sensing, edited by: Liang, S., Elsevier, Oxford, 137–196, ISBN 978-0-12-803221-3, https://doi.org/10.1016/B978-0-12-409548-9.10389-6, 2018. a
Laszlo, I. and Liu, H.: EPS Aerosol Optical Depth (AOD) Algorithm Theoretical Basis Document Version 3.4, Tech. Rep., NOAA NESDIS Center for Satellite Applications and Research, https://www.star.nesdis.noaa.gov/jpss/documents/ATBD/ATBD_EPS_Aerosol_AOD_v3.4.pdf (last access: 11 October 2024), 2022. a, b, c, d
Lee, J., Hsu, N. C., Sayer, A. M., Bettenhausen, C., and Yang, P.: AERONET-Based Nonspherical Dust Optical Models and Effects on the VIIRS Deep Blue/SOAR Over Water Aerosol Product, J. Geophys. Res.-Atmos., 122, 10384–10401, https://doi.org/10.1002/2017JD027258, 2017. a
Lee, J., Hsu, N. C., Kim, W. V., Sayer, A. M., and Tsay, S.-C.: VIIRS Version 2 Deep Blue Aerosol Products, J. Geophys. Res.-Atmos., 129, e2023JD040082, https://doi.org/10.1029/2023JD040082, 2024. a
Lee, Z., Hu, C., Shang, S., Du, K., Lewis, M., Arnone, R., and Brewin, R.: Penetration of UV-visible solar radiation in the global oceans: Insights from ocean color remote sensing, J. Geophys. Res.-Oceans, 118, 4241–4255, https://doi.org/10.1002/jgrc.20308, 2013. a
Legrand, M., Plana-Fattori, A., and N'Doumé, C.: Satellite detection of dust using the IR imagery of Meteosat 1. Infrared difference dust index, J. Geophys. Res.-Atmos., 106, 18251–18274, https://doi.org/10.1029/2000JD900749, 2001. a
Lensky, I. M. and Rosenfeld, D.: Clouds-Aerosols-Precipitation Satellite Analysis Tool (CAPSAT), Atmos. Chem. Phys., 8, 6739–6753, https://doi.org/10.5194/acp-8-6739-2008, 2008. a
Levy, R. C. and Hsu, N. C.: MODIS Atmosphere L2 Aerosol Product, NASA [data set], https://doi.org/10.5067/MODIS/MYD04_L2.006, 2015a. a, b
Levy, R. C. and Hsu, N. C.: MODIS Atmosphere L2 Aerosol Product, NASA [data set], https://doi.org/10.5067/MODIS/MOD04_3K.061, 2015b. a
Levy, R. C., Mattoo, S., Sawyer, V., and Munchak, L.: VIIRS/NOAA20 Dark Target Aerosol 6-Min L2 Swath 6 km, NASA [data set], https://doi.org/10.5067/VIIRS/AERDT_L2_VIIRS_NOAA20.002, 2023. a
Limbacher, J. A., Kahn, R. A., and Lee, J.: The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water, Atmos. Meas. Tech., 15, 6865–6887, https://doi.org/10.5194/amt-15-6865-2022, 2022. a, b, c
Lu, Z., Wang, J., Xu, X., Chen, X., Kondragunta, S., Torres, O., Wilcox, E. M., and Zeng, J.: Hourly Mapping of the Layer Height of Thick Smoke Plumes Over the Western U.S. in 2020 Severe Fire Season, Frontiers in Remote Sensing, 2, https://doi.org/10.3389/frsen.2021.766628, 2021. a
Lu, Z., Wang, J., Chen, X., Zeng, J., Wang, Y., Xu, X., Christian, K. E., Yorks, J. E., Nowottnick, E. P., Reid, J. S., and Xian, P.: First Mapping of Monthly and Diurnal Climatology of Saharan Dust Layer Height Over the Atlantic Ocean From EPIC/DSCOVR in Deep Space, Geophys. Res. Lett., 50, e2022GL102552, https://doi.org/10.1029/2022GL102552, 2023. a
Lyapustin, A. and Wang, Y.: MODIS/Terra+Aqua Land Aerosol Optical Depth Daily L2G Global 1km SIN Grid V061, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD19A2.061, 2022. a
Lyapustin, A., Wang, Y., Korkin, S., and Huang, D.: MODIS Collection 6 MAIAC algorithm, Atmos. Meas. Tech., 11, 5741–5765, https://doi.org/10.5194/amt-11-5741-2018, 2018. a
Martonchik, J. V., Kahn, R. A., and Diner, D. J.: Retrieval of aerosol properties over land using MISR observations, in: Satellite Aerosol Remote Sensing over Land, edited by: Kokhanovsky, A. and de Leeuw, G., Springer Praxis Books, Springer, Berlin, Heidelberg, 267–293, https://doi.org/10.1007/978-3-540-69397-0_9, 2009. a
Modabberi, A., Noori, R., Madani, K., Ehsani, A. H., Danandeh Mehr, A., Hooshyaripor, F., and Kløve, B.: Caspian Sea is eutrophying: The alarming message of satellite data, Environ. Res. Lett., 15, 124047, https://doi.org/10.1088/1748-9326/abc6d3, 2019. a
Moradi, M.: Interannual and intra-annual cycles of satellite-derived chlorophyll-a concentrations in the Caspian Sea, J. Great Lakes Res., 48, 143–158, https://doi.org/10.1016/j.jglr.2021.10.021, 2022. a
Nelson, D. L., Garay, M. J., Kahn, R. A., and Dunst, B. A.: Stereoscopic height and wind retrievals for aerosol plumes with the MISR INteractive eXplorer (MINX), Remote Sensing, 5, 4593–4628, https://doi.org/10.3390/rs5094593, 2013. a, b
Nobakht, M., Shahgedanova, M., and White, K.: New Inventory of Dust Emission Sources in Central Asia and Northwestern China Derived From MODIS Imagery Using Dust Enhancement Technique, J. Geophys. Res.-Atmos., 126, e2020JD033382, https://doi.org/10.1029/2020JD033382, 2021. a
Offenwanger, T., Samaras, S., and Klüser, L.: Algorithm Theoretical Basis Document Annex D Infrared Mineral Aerosol Retrieval Scheme (IMARS) Algorithm version v7.1, Tech. Rep., Copernicus Climate Change Service, http://dast.data.compute.cci2.ecmwf.int/documents/satellite-aerosol-properties/C3S2_312a_Lot2_FDDP-AER/C3S2_312a_Lot2_D-WP2-FDDP-AER_202311_ATBD_AER_Annex_D_IMARS_v3.3_final2.pdf, last access: 17 October 2024. a, b
Orlovsky, L. and Orlovsky, N.: White sand storms in Central Asia, in: Global Alarm: Dust and Sand Storms from the World’s Dry lands, edited by: Yang, Y., Squires, V., and Lu, Q., Chap. 8, 169–201, United Nations, ISBN 92112011404, 2001. a
Prospero, J. M., Ginoux, P., Torres, O., Nicholson, S. E., and Gill, T. E.: Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product, Rev. Geophys., 40, 2-1–2-31, https://doi.org/10.1029/2000RG000095, 2002. a, b
Remer, L. A., Kaufman, Y. J., Tanré, D., Mattoo, S., Chu, D. A., Martins, J. V., Li, R. R., Ichoku, C., Levy, R. C., Kleidman, R. G., Eck, T. F., Vermote, E., and Holben, B. N.: The MODIS aerosol algorithm, products, and validation, J. Atmos. Sci., 62, 947–973, https://doi.org/10.1175/JAS3385.1, 2005. a
Remer, L. A., Brogniez, C., Cairns, B., Hsu, N. C., Kahn, R., Stammes, P., Tanré, D., and Torres, O.: Recent instruments and algorithms for passive shortwave remote sensing, in: Aerosol Remote Sensing, edited by: Lenoble, J., Remer, L., and Tanre, D., vol. 9783642177, Springer Berlin Heidelberg, Berlin, Heidelberg, 185–222, ISBN 978-3-642-17725-5, https://doi.org/10.1007/978-3-642-17725-5_8, 2013a. a
Remer, L. A., Mattoo, S., Levy, R. C., and Munchak, L. A.: MODIS 3 km aerosol product: algorithm and global perspective, Atmos. Meas. Tech., 6, 1829–1844, https://doi.org/10.5194/amt-6-1829-2013, 2013b. a
Rupakheti, D., Rupakheti, M., Abdullaev, S. F., Yin, X., and Kang, S.: Columnar aerosol properties and radiative effects over Dushanbe, Tajikistan in Central Asia, Environ. Pollut., 265, 114872, https://doi.org/10.1016/j.envpol.2020.114872, 2020. a
Sawyer, V., Levy, R. C., Mattoo, S., Cureton, G., Shi, Y., and Remer, L. A.: Continuing the MODIS dark target aerosol time series with VIIRS, Remote Sensing, 12, 308, https://doi.org/10.3390/rs12020308, 2020. a
Sayer, A. M., Hsu, N. C., Lee, J., Bettenhausen, C., Kim, W. V., and Smirnov, A.: Satellite Ocean Aerosol Retrieval (SOAR) Algorithm Extension to S-NPP VIIRS as Part of the “Deep Blue” Aerosol Project, J. Geophys. Res.-Atmos., 123, 380–400, https://doi.org/10.1002/2017JD027412, 2018. a
Schepanski, K., Tegen, I., and Macke, A.: Comparison of satellite based observations of Saharan dust source areas, Remote Sens. Environ., 123, 90–97, https://doi.org/10.1016/j.rse.2012.03.019, 2012. a
Semenov, V. K., Smirnov, A., Aref'ev, V. N., Sinyakov, V. P., Sorokina, L. I., and Ignatova, N. I.: Aerosol optical depth over the mountainous region in central Asia (Issyk-Kul Lake, Kyrgyzstan), Geophys. Res. Lett., 32, L05807, https://doi.org/10.1029/2004GL021746, 2005. a
Sokolik, I. N. and Toon, O. B.: Incorporation of mineralogical composition into models of the radiative properties of mineral aerosol from UV to IR wavelengths, J. Geophys. Res.-Atmos., 104, 9423–9444, https://doi.org/10.1029/1998JD200048, 1999. a
Stein Zweers, D. C.: TROPOMI ATBD of the UV aerosol index, document number – S5P-KNMI-L2-0008-RP, Tech. Rep. 2.1.0, Royal Netherlands Meteorological Institute, De Bilt, 3731 GA, the Netherlands, https://sentinels.copernicus.eu/documents/247904/2476257 (last access: 8 July 2025), 2022. a
Tanré, D., Kaufman, Y. J., Herman, M., and Mattoo, S.: Remote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiances, J. Geophys. Res.-Atmos., 102, 16971–16988, https://doi.org/10.1029/96jd03437, 1997. a
Torres, O.: OMPS-NPP L2 NM Aerosol Index swath orbital V2, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/40L92G8144IV, 2019a. a, b
Torres, O.: DSCOVR EPIC Level 2 UV Aerosol Version 3, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/EPIC/DSCOVR/L2_AER_03, 2019b. a, b
Torres, O.: TROPOMI/Sentinel-5P Near UV Aerosol Optical Depth and Single Scattering Albedo L2 1-Orbit Snapshot 7.5 km x 3 km, NASA Goddard Space Flight Center, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/MEASURES/AER/DATA204, 2021. a, b
Torres, O., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Gleason, J.: Derivation of aerosol properties from satellite measurements of backscattered ultraviolet radiation: Theoretical basis, J. Geophys. Res.-Atmos., 103, 17099–17110, https://doi.org/10.1029/98JD00900, 1998. a
Torres, O., Ahn, C., and Chen, Z.: Improvements to the OMI near-UV aerosol algorithm using A-train CALIOP and AIRS observations, Atmos. Meas. Tech., 6, 3257–3270, https://doi.org/10.5194/amt-6-3257-2013, 2013. a
Torres, O., Bhartia, P. K., Jethva, H., and Ahn, C.: Impact of the ozone monitoring instrument row anomaly on the long-term record of aerosol products, Atmos. Meas. Tech., 11, 2701–2715, https://doi.org/10.5194/amt-11-2701-2018, 2018. a
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications, Remote Sens. Environ., 120, 70–83, https://doi.org/10.1016/j.rse.2011.09.027, 2012. a
Volz, F. E.: Infrared Optical Constants of Ammonium Sulfate, Sahara Dust, Volcanic Pumice, and Flyash, Applied Optics, 12, 564, https://doi.org/10.1364/ao.12.000564, 1973. a, b, c
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt, W. H., and Young, S. A.: Overview of the CALIPSO mission and CALIOP data processing algorithms, J. Atmos. Ocean. Tech., 26, 2310–2323, https://doi.org/10.1175/2009JTECHA1281.1, 2009. a
Wu, L., Hasekamp, O., van Diedenhoven, B., Cairns, B., Yorks, J. E., and Chowdhary, J.: Passive remote sensing of aerosol layer height using near-UV multiangle polarization measurements, Geophys. Res. Lett., 43, 8783–8790, https://doi.org/10.1002/2016GL069848, 2016. a
Xi, X.: On the Geomorphic, Meteorological, and Hydroclimatic Drivers of the Unusual 2018 Early Summer Salt Dust Storms in Central Asia, J. Geophys. Res.-Atmos., 128, e2022JD038089, https://doi.org/10.1029/2022JD038089, 2023. a, b
Xi, X.: Data from “Analysis of a saline dust storm from the Aralkum Desert – Part 1: Consistency between multisensor satellite aerosol products”, Zenodo [data set], https://doi.org/10.5281/zenodo.13994593, 2025. a
Xi, X. and Sokolik, I. N.: Seasonal dynamics of threshold friction velocity and dust emission in Central Asia, J. Geophys. Res.-Atmos., 120, 1536–1564, https://doi.org/10.1002/2014JD022471, 2015a. a
Xi, X. and Sokolik, I. N.: Dust interannual variability and trend in Central Asia from 2000 to 2014 and their climatic linkages, J. Geophys. Res.-Atmos., 120, 12175–12197, https://doi.org/10.1002/2015JD024092, 2015b. a
Xi, X. and Sokolik, I. N.: Quantifying the anthropogenic dust emission from agricultural land use and desiccation of the Aral Sea in Central Asia, J. Geophys. Res.-Atmos., 121, 12270–12281, https://doi.org/10.1002/2016JD025556, 2016. a
Xu, X., Wang, J., Wang, Y., Zeng, J., Torres, O., Yang, Y., Marshak, A., Reid, J., and Miller, S.: Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: First results from EPIC/DSCOVR at Lagrange-1 point, Geophys. Res. Lett., 44, 7544–7554, https://doi.org/10.1002/2017GL073939, 2017. a, b, c
Xu, X., Wang, J., Wang, Y., Zeng, J., Torres, O., Reid, J. S., Miller, S. D., Martins, J. V., and Remer, L. A.: Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep space, Atmos. Meas. Tech., 12, 3269–3288, https://doi.org/10.5194/amt-12-3269-2019, 2019. a, b, c
Young, S. A., Vaughan, M. A., Garnier, A., Tackett, J. L., Lambeth, J. D., and Powell, K. A.: Extinction and optical depth retrievals for CALIPSO's Version 4 data release, Atmos. Meas. Tech., 11, 5701–5727, https://doi.org/10.5194/amt-11-5701-2018, 2018. a
Zhang, H., Kondragunta, S., Laszlo, I., Liu, H., Remer, L. A., Huang, J., Superczynski, S., and Ciren, P.: An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database, J. Geophys. Res., 121, 10717–10738, https://doi.org/10.1002/2016JD024859, 2016. a
Zhou, D. K., Larar, A. M., Liu, X., Smith, W. L., Strow, L. L., Yang, P., Schlüssel, P., and Calbet, X.: Global land surface emissivity retrieved from satellite ultraspectral IR measurements, IEEE T. Geosci. Remote, 49, 1277–1290, https://doi.org/10.1109/TGRS.2010.2051036, 2011. a, b
Zhou, Y., Levy, R. C., Remer, L. A., Mattoo, S., and Espinosa, W. R.: Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark Target Algorithm: 2. Nonspherical Dust Model, Earth and Space Science, 7, e2020EA001222, https://doi.org/10.1029/2020EA001222, 2020a. a
Zhou, Y., Levy, R. C., Remer, L. A., Mattoo, S., Shi, Y., and Wang, C.: Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark-Target Algorithm: 1. Dust Detection, Earth and Space Science, 7, e2020EA001221, https://doi.org/10.1029/2020EA001221, 2020b. a
Short summary
The Aralkum Desert is challenging for aerosol retrieval due to its bright, heterogeneous, and dynamic surfaces and the lack of in situ constraints on aerosol properties. The performance and consistency of satellite algorithms in observing Aralkum-generated saline dust remain unknown. This study compares multisensor UVAI (ultraviolet aerosol index), AOD (aerosol optical depth), and ALH (aerosol layer height) products and reveals inconsistencies and potential biases over the Aral Sea basin.
The Aralkum Desert is challenging for aerosol retrieval due to its bright, heterogeneous, and...
Altmetrics
Final-revised paper
Preprint