Articles | Volume 14, issue 8
https://doi.org/10.5194/amt-14-5577-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-5577-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Aug 2021
Research article |
| 17 Aug 2021
| 17 Aug 2021
Introducing the MISR level 2 near real-time aerosol product
Marcin L. Witek
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
Michael J. Garay
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
David J. Diner
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
Michael A. Bull
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
Felix C. Seidel
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
Abigail M. Nastan
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
Earl G. Hansen
Jet Propulsion Laboratory, California Institute of Technology, 4800
Oak Grove Drive, Pasadena, CA 91109, USA
Related authors
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 %.
Michael J. Garay, Marcin L. Witek, Ralph A. Kahn, Felix C. Seidel, James A. Limbacher, Michael A. Bull, David J. Diner, Earl G. Hansen, Olga V. Kalashnikova, Huikyo Lee, Abigail M. Nastan, and Yan Yu
Atmos. Meas. Tech., 13, 593–628, https://doi.org/10.5194/amt-13-593-2020, https://doi.org/10.5194/amt-13-593-2020, 2020
Short summary
Short summary
The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version (V23) of the MISR aerosol products, which is reported on a 4.4 km spatial grid and contains retrieved aerosol optical depth and aerosol particle property information derived over both land and water. The changes implemented in V23 have significant impacts on the data product and its interpretation.
Andrew M. Sayer, Yves Govaerts, Pekka Kolmonen, Antti Lipponen, Marta Luffarelli, Tero Mielonen, Falguni Patadia, Thomas Popp, Adam C. Povey, Kerstin Stebel, and Marcin L. Witek
Atmos. Meas. Tech., 13, 373–404, https://doi.org/10.5194/amt-13-373-2020, https://doi.org/10.5194/amt-13-373-2020, 2020
Short summary
Short summary
Satellite measurements of the Earth are routinely processed to estimate useful quantities; one example is the amount of atmospheric aerosols (which are particles such as mineral dust, smoke, volcanic ash, or sea spray). As with all measurements and inferred quantities, there is some degree of uncertainty in this process.
There are various methods to estimate these uncertainties. A related question is the following: how reliable are these estimates? This paper presents a method to assess them.
Marcin L. Witek, Michael J. Garay, David J. Diner, Michael A. Bull, and Felix C. Seidel
Atmos. Meas. Tech., 11, 429–439, https://doi.org/10.5194/amt-11-429-2018, https://doi.org/10.5194/amt-11-429-2018, 2018
Short summary
Short summary
This study outlines a new methodology for assessing air pollution from space using observations from Multi-angle Imaging SpectroRadiometer (MISR). Both air pollution amounts – as well as the uncertainties associated with space observations – are simultaneously and consistently obtained from MISR measurements over oceans. The new products have superior quality to the previous versions and will benefit the air pollution community.
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
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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.
Piyushkumar N. Patel, Jonathan H. Jiang, Ritesh Gautam, Harish Gadhavi, Olga Kalashnikova, Michael J. Garay, Lan Gao, Feng Xu, and Ali Omar
Atmos. Chem. Phys., 24, 2861–2883, https://doi.org/10.5194/acp-24-2861-2024, https://doi.org/10.5194/acp-24-2861-2024, 2024
Short summary
Short summary
Global measurements of cloud condensation nuclei (CCN) are essential for understanding aerosol–cloud interactions and predicting climate change. To address this gap, we introduced a remote sensing algorithm that retrieves vertically resolved CCN number concentrations from airborne and spaceborne lidar systems. This innovation offers a global distribution of CCN concentrations from space, facilitating model evaluation and precise quantification of aerosol climate forcing.
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 %.
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).
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
Short summary
Short summary
Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Yan Yu, Olga V. Kalashnikova, Michael J. Garay, Huikyo Lee, Myungje Choi, Gregory S. Okin, John E. Yorks, James R. Campbell, and Jared Marquis
Atmos. Chem. Phys., 21, 1427–1447, https://doi.org/10.5194/acp-21-1427-2021, https://doi.org/10.5194/acp-21-1427-2021, 2021
Short summary
Short summary
Given the current uncertainties in the simulated diurnal variability of global dust mobilization and concentration, observational characterization of the variations in dust mobilization and concentration will provide a valuable benchmark for evaluating and constraining such model simulations. The current study investigates the diurnal cycle of dust loading across the global tropics, subtropics, and mid-latitudes by analyzing aerosol observations from the International Space Station.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
Short summary
Short summary
The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
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
Short summary
Short summary
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.
Michael J. Garay, Marcin L. Witek, Ralph A. Kahn, Felix C. Seidel, James A. Limbacher, Michael A. Bull, David J. Diner, Earl G. Hansen, Olga V. Kalashnikova, Huikyo Lee, Abigail M. Nastan, and Yan Yu
Atmos. Meas. Tech., 13, 593–628, https://doi.org/10.5194/amt-13-593-2020, https://doi.org/10.5194/amt-13-593-2020, 2020
Short summary
Short summary
The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version (V23) of the MISR aerosol products, which is reported on a 4.4 km spatial grid and contains retrieved aerosol optical depth and aerosol particle property information derived over both land and water. The changes implemented in V23 have significant impacts on the data product and its interpretation.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
Short summary
Short summary
In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Andrew M. Sayer, Yves Govaerts, Pekka Kolmonen, Antti Lipponen, Marta Luffarelli, Tero Mielonen, Falguni Patadia, Thomas Popp, Adam C. Povey, Kerstin Stebel, and Marcin L. Witek
Atmos. Meas. Tech., 13, 373–404, https://doi.org/10.5194/amt-13-373-2020, https://doi.org/10.5194/amt-13-373-2020, 2020
Short summary
Short summary
Satellite measurements of the Earth are routinely processed to estimate useful quantities; one example is the amount of atmospheric aerosols (which are particles such as mineral dust, smoke, volcanic ash, or sea spray). As with all measurements and inferred quantities, there is some degree of uncertainty in this process.
There are various methods to estimate these uncertainties. A related question is the following: how reliable are these estimates? This paper presents a method to assess them.
Yan Yu, Olga V. Kalashnikova, Michael J. Garay, Huikyo Lee, Myungje Choi, Gregory S. Okin, John E. Yorks, and James R. Campbell
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-975, https://doi.org/10.5194/acp-2019-975, 2019
Preprint withdrawn
Short summary
Short summary
Given the current uncertainties in the simulated diurnal variability of global dust mobilization and concentration, observational characterization of the variations in dust mobilization and concentration will provide a valuable benchmark for evaluating and constraining such model simulations. The current study investigates the diurnal cycle of dust loading across the global tropics, sub-tropics, and mid-latitudes by analyzing aerosol observations from the International Space Station.
Myungje Choi, Hyunkwang Lim, Jhoon Kim, Seoyoung Lee, Thomas F. Eck, Brent N. Holben, Michael J. Garay, Edward J. Hyer, Pablo E. Saide, and Hongqing Liu
Atmos. Meas. Tech., 12, 4619–4641, https://doi.org/10.5194/amt-12-4619-2019, https://doi.org/10.5194/amt-12-4619-2019, 2019
Short summary
Short summary
Satellite-based aerosol optical depth (AOD) products have been improved continuously and available from multiple low Earth orbit sensors, such as MODIS, MISR, and VIIRS, and geostationary sensors, such as GOCI and AHI, over East Asia. These multi-satellite AOD products are validated, intercompared, analyzed, and integrated to understand different characteristics, such as quality and spatio-temporal coverage, focused on several aerosol transportation cases during the 2016 KORUS-AQ campaign.
Yan Yu, Olga V. Kalashnikova, Michael J. Garay, and Michael Notaro
Atmos. Chem. Phys., 19, 363–378, https://doi.org/10.5194/acp-19-363-2019, https://doi.org/10.5194/acp-19-363-2019, 2019
Short summary
Short summary
Asian dust has been reported at remote destinations, such as North America. However, the relative contribution of the Taklamakan and Gobi deserts, the major Asian dust sources, remains unaddressed in observation. Here, satellite observations of dust plume characteristics and trajectory modeling suggest latitude-dependent influence of dust from the two deserts, with Taklamakan dust dominantly affecting areas south of 50° N and Gobi dust primarily affecting areas north of 50° N in North America.
Bin Zhao, Jonathan H. Jiang, David J. Diner, Hui Su, Yu Gu, Kuo-Nan Liou, Zhe Jiang, Lei Huang, Yoshi Takano, Xuehua Fan, and Ali H. Omar
Atmos. Chem. Phys., 18, 11247–11260, https://doi.org/10.5194/acp-18-11247-2018, https://doi.org/10.5194/acp-18-11247-2018, 2018
Short summary
Short summary
We combine satellite-borne and ground-based observations to investigate the intra-annual variations of regional aerosol column loading, vertical distribution, and particle types. Column aerosol optical depth (AOD), as well as AOD > 800 m, peaks in summer/spring. However, AOD < 800 m and surface PM2.5 concentrations mostly peak in winter. The aerosol intra-annual variations differ significantly according to aerosol types characterized by different sizes, light absorption, and emission sources.
Brent N. Holben, Jhoon Kim, Itaru Sano, Sonoyo Mukai, Thomas F. Eck, David M. Giles, Joel S. Schafer, Aliaksandr Sinyuk, Ilya Slutsker, Alexander Smirnov, Mikhail Sorokin, Bruce E. Anderson, Huizheng Che, Myungje Choi, James H. Crawford, Richard A. Ferrare, Michael J. Garay, Ukkyo Jeong, Mijin Kim, Woogyung Kim, Nichola Knox, Zhengqiang Li, Hwee S. Lim, Yang Liu, Hal Maring, Makiko Nakata, Kenneth E. Pickering, Stuart Piketh, Jens Redemann, Jeffrey S. Reid, Santo Salinas, Sora Seo, Fuyi Tan, Sachchida N. Tripathi, Owen B. Toon, and Qingyang Xiao
Atmos. Chem. Phys., 18, 655–671, https://doi.org/10.5194/acp-18-655-2018, https://doi.org/10.5194/acp-18-655-2018, 2018
Short summary
Short summary
Aerosol particles, such as smoke, vary over space and time. This paper describes a series of very high-resolution ground-based aerosol measurement networks and associated studies that contributed new understanding of aerosol processes and detailed comparisons to satellite aerosol validation. Significantly, these networks also provide an opportunity to statistically relate grab samples of an aerosol parameter to companion satellite observations, a step toward air quality assessment from space.
Marcin L. Witek, Michael J. Garay, David J. Diner, Michael A. Bull, and Felix C. Seidel
Atmos. Meas. Tech., 11, 429–439, https://doi.org/10.5194/amt-11-429-2018, https://doi.org/10.5194/amt-11-429-2018, 2018
Short summary
Short summary
This study outlines a new methodology for assessing air pollution from space using observations from Multi-angle Imaging SpectroRadiometer (MISR). Both air pollution amounts – as well as the uncertainties associated with space observations – are simultaneously and consistently obtained from MISR measurements over oceans. The new products have superior quality to the previous versions and will benefit the air pollution community.
Longtao Wu, Hui Su, Olga V. Kalashnikova, Jonathan H. Jiang, Chun Zhao, Michael J. Garay, James R. Campbell, and Nanpeng Yu
Atmos. Chem. Phys., 17, 7291–7309, https://doi.org/10.5194/acp-17-7291-2017, https://doi.org/10.5194/acp-17-7291-2017, 2017
Short summary
Short summary
The WRF-Chem simulation successfully captures aerosol variations in the cold season in the San Joaquin Valley (SJV) but has poor performance in the warm season. High-resolution model simulation can better resolve nonhomogeneous distribution of anthropogenic emissions in urban areas, resulting in better simulation of aerosols in the cold season in the SJV. Poor performance of the WRF-Chem model in the warm season in the SJV is mainly due to misrepresentation of dust emission and vertical mixing.
Michael J. Garay, Olga V. Kalashnikova, and Michael A. Bull
Atmos. Chem. Phys., 17, 5095–5106, https://doi.org/10.5194/acp-17-5095-2017, https://doi.org/10.5194/acp-17-5095-2017, 2017
Short summary
Short summary
Satellite data from the MISR instrument were used to produce aerosol optical depth (AOD) retrievals at 4.4 km spatial resolution, a factor of 16 improvement relative to the currently operational 17.6 km product. Retrievals were compared with high-spatial-resolution ground-based observations made by AERONET-DRAGON deployments around the globe. It was found that the 4.4 km MISR retrievals performed significantly better than the 17.6 km retrievals in comparisons made at over 100 individual sites.
Feng Xu, Oleg Dubovik, Peng-Wang Zhai, David J. Diner, Olga V. Kalashnikova, Felix C. Seidel, Pavel Litvinov, Andrii Bovchaliuk, Michael J. Garay, Gerard van Harten, and Anthony B. Davis
Atmos. Meas. Tech., 9, 2877–2907, https://doi.org/10.5194/amt-9-2877-2016, https://doi.org/10.5194/amt-9-2877-2016, 2016
Short summary
Short summary
We developed an algorithm for aerosol and water-leaving radiance retrieval in a simultaneous way.
Felix C. Seidel, Karl Rittger, S. McKenzie Skiles, Noah P. Molotch, and Thomas H. Painter
The Cryosphere, 10, 1229–1244, https://doi.org/10.5194/tc-10-1229-2016, https://doi.org/10.5194/tc-10-1229-2016, 2016
Short summary
Short summary
Quantifying the snow albedo effect is an important step to predict water availability as well as changes in climate and sea level. We use imaging spectroscopy to determine optical properties of mountain snow. We find an inverse relationship between snow albedo and grain size as well as between elevation and grain size. Under strong melt conditions, however, we show that the optical-equivalent snow grain size increases slower than expected at lower elevations and we explain possible reasons.
Huikyo Lee, Olga V. Kalashnikova, Kentaroh Suzuki, Amy Braverman, Michael J. Garay, and Ralph A. Kahn
Atmos. Chem. Phys., 16, 6627–6640, https://doi.org/10.5194/acp-16-6627-2016, https://doi.org/10.5194/acp-16-6627-2016, 2016
Short summary
Short summary
The Multi-angle Imaging SpectroRadiometer (MISR) on NASA's TERRA satellite has provided a global distribution of aerosol amount and type information for each month over 16+ years since March 2000. This study analyzes, for the first time, characteristics of observed and simulated distributions of aerosols for three broad classes of aerosols: spherical nonabsorbing, spherical absorbing, and nonspherical – near or downwind of their major source regions.
S. Li, R. Kahn, M. Chin, M. J. Garay, and Y. Liu
Atmos. Meas. Tech., 8, 1157–1171, https://doi.org/10.5194/amt-8-1157-2015, https://doi.org/10.5194/amt-8-1157-2015, 2015
Short summary
Short summary
We demonstrate a post-processing technique to improve MISR-retrieved aerosol optical properties when information content is low. By filtering the list of aerosol mixtures that pass the MISR retrieval acceptance criteria using pre-defined discrepancy thresholds between MISR and GOCART model simulations, the adjusted MISR Angstrom exponent (ANG) and absorbing AOD (AAOD) agree significantly better with sun-photometer validation data, especially when AOD<0.2 for ANG and AOD<0.5 for AAOD.
O. V. Kalashnikova, M. J. Garay, J. V. Martonchik, and D. J. Diner
Atmos. Meas. Tech., 6, 2131–2154, https://doi.org/10.5194/amt-6-2131-2013, https://doi.org/10.5194/amt-6-2131-2013, 2013
D. J. Diner, F. Xu, M. J. Garay, J. V. Martonchik, B. E. Rheingans, S. Geier, A. Davis, B. R. Hancock, V. M. Jovanovic, M. A. Bull, K. Capraro, R. A. Chipman, and S. C. McClain
Atmos. Meas. Tech., 6, 2007–2025, https://doi.org/10.5194/amt-6-2007-2013, https://doi.org/10.5194/amt-6-2007-2013, 2013
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Retrieval algorithm for aerosol effective height from the Geostationary Environment Monitoring Spectrometer (GEMS)
ACDL/DQ-1 calibration algorithms – Part 1: Nighttime 532 nm polarization and the high-spectral-resolution channel
Aerosol composition retrieval from a combination of three different spaceborne instruments: information content analysis
Compact dual-wavelength depolarization lidar for aerosol characterization over the subtropical North Atlantic
Towards gridded nighttime aerosol optical thickness retrievals using VIIRS day–night band observations over regions with artificial light sources
Multi-layer retrieval of aerosol optical depth in the troposphere using SEVIRI data: a case study of the European continent
Star photometry with all-sky cameras to retrieve aerosol optical depth at night-time
Ground-based contrail observations: comparisons with reanalysis weather data and contrail model simulations
Improvements in aerosol layer height retrievals from TROPOMI oxygen A-band measurements by surface albedo fitting in optimal estimation
Retrieval of stratospheric aerosol extinction coefficients from sun-normalized Ozone Mapper and Profiler Suite Limb Profiler (OMPS-LP) measurements
Total column optical depths retrieved from CALIPSO lidar ocean surface backscatter
ALICENET – an Italian network of automated lidar ceilometers for four-dimensional aerosol monitoring: infrastructure, data processing, and applications
Post-process correction improves the accuracy of satellite PM2.5 retrievals
Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites
Synergy of active and passive airborne observations for heating rates calculation during the AEROCLO-SA field campaign in Namibia
Multi-angle aerosol optical depth retrieval method based on improved surface reflectance
Comparison of diurnal aerosol products retrieved from combinations of micro-pulse lidar and sun photometer observations over the KAUST observation site
First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia
Aerosol optical depth data fusion with Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT-2) instruments GEMS, AMI, and GOCI-II: statistical and deep neural network methods
Stratospheric aerosol characteristics from SCIAMACHY limb observations: two-parameter retrieval
Retrieval and analysis of the composition of an aerosol mixture through Mie–Raman–fluorescence lidar observations
Using neural networks for near-real-time aerosol retrievals from OMPS Limb Profiler measurements
Transport of the Hunga volcanic aerosols inferred from Himawari-8/9 limb measurements
A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure dust
Innovative aerosol hygroscopic growth study from Mie–Raman–fluorescence lidar and microwave radiometer synergy
Evaluation of calibration performance of a low-cost particulate matter sensor using collocated and distant NO2
Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
Multi-wavelength dataset of aerosol extinction profiles retrieved from GOMOS stellar occultation measurements
Deep-Pathfinder: a boundary layer height detection algorithm based on image segmentation
An iterative algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using CALIOP
Cloud detection from multi-angular polarimetric satellite measurements using a neural network ensemble approach
Producing aerosol size distributions consistent with optical particle counters measurements using space-based measurements of aerosol extinction coefficient
Retrieving UV–Vis spectral single-scattering albedo of absorbing aerosols above clouds from synergy of ORACLES airborne and A-train sensors
Characterization of stratospheric particle size distribution uncertainties using SAGE II and SAGE III/ISS extinction spectra
Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
Aerosol and cloud data processing and optical property retrieval algorithms for the spaceborne ACDL/DQ-1
Derivation of depolarization ratios of aerosol fluorescence and water vapor Raman backscatters from lidar measurements
Long-term aerosol particle depolarization ratio measurements with HALO Photonics Doppler lidar
HETEAC-Flex: an optimal estimation method for aerosol typing based on lidar-derived intensive optical properties
MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm
Multi-section reference value for the analysis of horizontally scanning aerosol lidar observations
Retrieval of aerosol optical depth over the Arctic cryosphere during spring and summer using satellite observations
Quantifying particulate matter optical properties and flow rate in industrial stack plumes from the PRISMA hyperspectral imager
Aerosol retrieval over snow using the RemoTAP algorithm
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign
Simultaneous retrieval of aerosol and ocean properties from PACE HARP2 with uncertainty assessment using cascading neural network radiative transfer models
Linear polarization signatures of atmospheric dust with the SolPol direct-sun polarimeter
Retrieval of aerosol properties from zenith sky radiance measurements
An ensemble method for improving the estimation of planetary boundary layer height from radiosonde data
Detection and analysis of Lhù'ààn Mân' (Kluane Lake) dust plumes using passive and active ground-based remote sensing supported by physical surface measurements
Sang Seo Park, Jhoon Kim, Yeseul Cho, Hanlim Lee, Junsung Park, Dong-Won Lee, Won-Jin Lee, and Deok-Rae Kim
Atmos. Meas. Tech., 18, 2241–2259, https://doi.org/10.5194/amt-18-2241-2025, https://doi.org/10.5194/amt-18-2241-2025, 2025
Short summary
Short summary
An operational aerosol effective height (AEH) retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) was developed that solely uses the O2–O2 absorption band considering aerosol and surface properties. AEH retrievals are only performed when aerosol optical depth is larger than 0.3. The retrieval results show significant estimations by comparing the aerosol height from the Cloud–Aerosol Lidar with Orthogonal Polarization and the Tropospheric Monitoring Instrument.
Fanqian Meng, Junwu Tang, Guangyao Dai, Wenrui Long, Kangwen Sun, Zhiyu Zhang, Xiaoquan Song, Jiqiao Liu, Weibiao Chen, and Songhua Wu
Atmos. Meas. Tech., 18, 2021–2039, https://doi.org/10.5194/amt-18-2021-2025, https://doi.org/10.5194/amt-18-2021-2025, 2025
Short summary
Short summary
This paper presents a comprehensive calibration procedure for the first spaceborne high-spectral-resolution lidar with an iodine vapor absorption filter Aerosol and Carbon Detection Lidar (ACDL) on board DQ-1 by utilizing nighttime 532 nm multi-channel data. We analyzed the error sources of the multi-channel calibration coefficients and assessed the results. The results indicate that the uncertainty of the clear-air scattering ratio was within the anticipated range of 7.9 %.
Ulrike Stöffelmair, Thomas Popp, Marco Vountas, and Hartmut Bösch
Atmos. Meas. Tech., 18, 2005–2020, https://doi.org/10.5194/amt-18-2005-2025, https://doi.org/10.5194/amt-18-2005-2025, 2025
Short summary
Short summary
Aerosol composition has a large influence on the climate system. This study uses realistic simulated scenarios to look at the information content of a combination of three satellite-based instruments (SLSTR, IASI and GOME-2). It shows that it is possible to retrieve 6 to 15 different aerosol components in addition to the aerosol optical depth (AOD) and different surface parameters. The results are used for the development of a synergistic multi-sensor retrieval algorithm.
Yenny González, María F. Sánchez-Barrero, Ioana Popovici, África Barreto, Stephane Victori, Ellsworth J. Welton, Rosa D. García, Pablo G. Sicilia, Fernando A. Almansa, Carlos Torres, and Philippe Goloub
Atmos. Meas. Tech., 18, 1885–1908, https://doi.org/10.5194/amt-18-1885-2025, https://doi.org/10.5194/amt-18-1885-2025, 2025
Short summary
Short summary
We characterize the optical properties of various aerosols using a compact dual-wavelength depolarization lidar (CIMEL CE376) at 532 and 808 nm. Through a modified two-wavelength Klett inversion method, we assess the vertical distribution and temporal evolution of Saharan dust, volcanic aerosols and wildfire smoke in the subtropical North Atlantic from August 2021 to August 2023. The study confirms the CE376 lidar's effectiveness in monitoring and characterizing atmospheric aerosols over time.
Jianglong Zhang, Jeffrey S. Reid, Blake T. Sorenson, Steven D. Miller, Miguel O. Román, Zhuosen Wang, Robert J. D. Spurr, Shawn Jaker, Thomas F. Eck, and Juli I. Rubin
Atmos. Meas. Tech., 18, 1787–1810, https://doi.org/10.5194/amt-18-1787-2025, https://doi.org/10.5194/amt-18-1787-2025, 2025
Short summary
Short summary
Using observations from the Visible Infrared Imaging Radiometer Suite day–night band, we developed a method for constructing gridded nighttime aerosol optical thickness (AOT) data based on the spatial derivative of measured top-of-atmosphere attenuated upwelling artificial lights at night. The gridded nighttime AOT retrievals, compared against Aerosol Robotic Network data, show reasonable skill levels for potential data assimilation, air quality, and climate studies of significant events.
Maryam Pashayi, Mehran Satari, and Mehdi Momeni Shahraki
Atmos. Meas. Tech., 18, 1415–1439, https://doi.org/10.5194/amt-18-1415-2025, https://doi.org/10.5194/amt-18-1415-2025, 2025
Short summary
Short summary
Multi-layer aerosol optical depth (AOD) is retrieved using the geostationary Spinning Enhanced Visible and Infrared Imager (SEVIRI) and machine learning, trained on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. The model provides AOD at a 3 km × 3 km spatial and 15 min temporal resolution over Europe. It accurately captured multi-layer AOD dynamics during Saharan dust transport and the Mount Etna eruption, demonstrating consistent physical accuracy.
Roberto Román, Daniel González-Fernández, Juan Carlos Antuña-Sánchez, Celia Herrero del Barrio, Sara Herrero-Anta, África Barreto, Victoria E. Cachorro, Lionel Doppler, Ramiro González, Christoph Ritter, David Mateos, Natalia Kouremeti, Gustavo Copes, Abel Calle, María José Granados-Muñoz, Carlos Toledano, and Ángel M. de Frutos
EGUsphere, https://doi.org/10.5194/egusphere-2025-667, https://doi.org/10.5194/egusphere-2025-667, 2025
Short summary
Short summary
This paper presents a novel technique to extract starlight signals from all-sky images and retrieve aerosol optical depth (AOD). It is validated against lunar photometry, showing a strong correlation between both data series. This innovative approach will expand nocturnal AOD measurements to more locations, as all-sky cameras are a simpler and more cost-effective alternative to stellar and lunar photometers.
Jade Low, Roger Teoh, Joel Ponsonby, Edward Gryspeerdt, Marc Shapiro, and Marc E. J. Stettler
Atmos. Meas. Tech., 18, 37–56, https://doi.org/10.5194/amt-18-37-2025, https://doi.org/10.5194/amt-18-37-2025, 2025
Short summary
Short summary
The radiative forcing due to contrails is of the same order of magnitude as aviation CO2 emissions but has a higher uncertainty. Observations are vital to improve our understanding of the contrail lifecycle, improve models, and measure the effect of mitigation action. Here, we use ground-based cameras combined with flight telemetry to track visible contrails and measure their lifetime and width. We evaluate model predictions and demonstrate the capability of this approach.
Martin de Graaf, Maarten Sneep, Mark ter Linden, L. Gijsbert Tilstra, and J. Pepijn Veefkind
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-198, https://doi.org/10.5194/amt-2024-198, 2025
Revised manuscript accepted for AMT
Short summary
Short summary
The TROPOMI aerosol layer height is constantly being improved since its release in 2019. Over land, the ALH was too low (closer to the surface than expected), especially over bright scenes. This paper describes the latest improvements of the product, especially the treatment of the surface albedo over land. The results are compared with space-based aerosol profiles for a set of situations, ranging from multiple layers of smoke, thick desert dust plumes and low-altitude industrial pollution.
Alexei Rozanov, Christine Pohl, Carlo Arosio, Adam Bourassa, Klaus Bramstedt, Elizaveta Malinina, Landon Rieger, and John P. Burrows
Atmos. Meas. Tech., 17, 6677–6695, https://doi.org/10.5194/amt-17-6677-2024, https://doi.org/10.5194/amt-17-6677-2024, 2024
Short summary
Short summary
We developed a new algorithm to retrieve vertical distributions of aerosol extinction coefficients in the stratosphere. The algorithm is applied to measurements of scattered solar light from the spaceborne OMPS-LP (Ozone Mapper and Profiler Suite Limb Profiler) instrument. The retrieval results are compared to data from other spaceborne instruments and used to investigate the evolution of the aerosol plume following the eruption of the Hunga Tonga–Hunga Ha'apai volcano in January 2022.
Robert A. Ryan, Mark A. Vaughan, Sharon D. Rodier, Jason L. Tackett, John A. Reagan, Richard A. Ferrare, Johnathan W. Hair, John A. Smith, and Brian J. Getzewich
Atmos. Meas. Tech., 17, 6517–6545, https://doi.org/10.5194/amt-17-6517-2024, https://doi.org/10.5194/amt-17-6517-2024, 2024
Short summary
Short summary
We introduce Ocean Derived Column Optical Depth (ODCOD), a new way to estimate column optical depths using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements from the ocean surface. ODCOD estimates include contributions from particulates in the full column, which CALIOP estimates do not, making it a complement measurement to CALIOP’s standard estimates. We find that ODCOD compares well with other established data sets in the daytime but tends to estimate higher at night.
Annachiara Bellini, Henri Diémoz, Luca Di Liberto, Gian Paolo Gobbi, Alessandro Bracci, Ferdinando Pasqualini, and Francesca Barnaba
Atmos. Meas. Tech., 17, 6119–6144, https://doi.org/10.5194/amt-17-6119-2024, https://doi.org/10.5194/amt-17-6119-2024, 2024
Short summary
Short summary
We provide a comprehensive overview of the Italian Automated LIdar-CEilometer network, ALICENET, describing its infrastructure, aerosol retrievals, and main applications. The supplement covers data-processing details. We include examples of output products, comparisons with independent data, and examples of the network capability to provide near-real-time aerosol fields over Italy. ALICENET is expected to benefit the sectors of air quality, radiative budget/solar energy, and aviation safety.
Andrea Porcheddu, Ville Kolehmainen, Timo Lähivaara, and Antti Lipponen
Atmos. Meas. Tech., 17, 5747–5764, https://doi.org/10.5194/amt-17-5747-2024, https://doi.org/10.5194/amt-17-5747-2024, 2024
Short summary
Short summary
This study focuses on improving the accuracy of satellite-based PM2.5 retrieval, crucial for monitoring air quality and its impact on health. It employs machine learning to correct the AOD-to-PM2.5 conversion ratio using various data sources. The approach produces high-resolution PM2.5 estimates with improved accuracy. The method is flexible and can incorporate additional training data from different sources, making it a valuable tool for air quality monitoring and epidemiological 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.
Mégane Ventura, Fabien Waquet, Isabelle Chiapello, Gérard Brogniez, Frédéric Parol, Frédérique Auriol, Rodrigue Loisil, Cyril Delegove, Luc Blarel, Oleg Dubovik, Marc Mallet, Cyrille Flamant, and Paola Formenti
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-121, https://doi.org/10.5194/amt-2024-121, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Biomass burning aerosols (BBA) from Central Africa, are transported above stratocumulus clouds. The absorption of solar energy by aerosols induce warming, altering the clouds dynamics. We developed an approach that combines polarimeter and lidar to quantify it. This methodology is assessed during the AEROCLO-SA campaign. To validate it, we used flux measurements acquired during aircraft loop descents. Major perspective is the generalization of this method to the global level.
Lijuan Chen, Ren Wang, Ying Fei, Peng Fang, Yong Zha, and Haishan Chen
Atmos. Meas. Tech., 17, 4411–4424, https://doi.org/10.5194/amt-17-4411-2024, https://doi.org/10.5194/amt-17-4411-2024, 2024
Short summary
Short summary
This study explores the problems of surface reflectance estimation from previous MISR satellite remote sensing images and develops an error correction model to obtain a higher-precision aerosol optical depth (AOD) product. High-accuracy AOD is important not only for the daily monitoring of air pollution but also for the study of energy exchange between land and atmosphere. This will help further improve the retrieval accuracy of multi-angle AOD on large spatial scales and for long time series.
Anton Lopatin, Oleg Dubovik, Georgiy Stenchikov, Ellsworth J. Welton, Illia Shevchenko, David Fuertes, Marcos Herreras-Giralda, Tatsiana Lapyonok, and Alexander Smirnov
Atmos. Meas. Tech., 17, 4445–4470, https://doi.org/10.5194/amt-17-4445-2024, https://doi.org/10.5194/amt-17-4445-2024, 2024
Short summary
Short summary
We compare aerosol properties over the King Abdullah University of Science and Technology campus using Generalized Retrieval of Aerosol and Surface Properties (GRASP) and the Micro-Pulse Lidar Network (MPLNET). We focus on the impact of different aerosol retrieval assumptions on daytime and nighttime retrievals and analyze seasonal variability in aerosol properties, aiding in understanding aerosol behavior and improving retrieval. Our work has implications for climate and public health.
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.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Yun-Gon Lee, Sujung Go, and Kyunghwa Lee
Atmos. Meas. Tech., 17, 4317–4335, https://doi.org/10.5194/amt-17-4317-2024, https://doi.org/10.5194/amt-17-4317-2024, 2024
Short summary
Short summary
Information about aerosol loading in the atmosphere can be collected from various satellite instruments. Aerosol products from various satellite instruments have their own error characteristics. This study statistically merged aerosol optical depth datasets from multiple instruments aboard geostationary satellites considering uncertainties. Also, a deep neural network technique is adopted for aerosol data merging.
Christine Pohl, Felix Wrana, Alexei Rozanov, Terry Deshler, Elizaveta Malinina, Christian von Savigny, Landon A. Rieger, Adam E. Bourassa, and John P. Burrows
Atmos. Meas. Tech., 17, 4153–4181, https://doi.org/10.5194/amt-17-4153-2024, https://doi.org/10.5194/amt-17-4153-2024, 2024
Short summary
Short summary
Knowledge of stratospheric aerosol characteristics is important for understanding chemical and climate aerosol feedbacks. Two particle size distribution parameters, the aerosol extinction coefficient and the effective radius, are obtained from SCIAMACHY limb observations. The aerosol characteristics show good agreement with independent data sets from balloon-borne and satellite observations. This data set expands the limited knowledge of stratospheric aerosol characteristics.
Igor Veselovskii, Boris Barchunov, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Mikhail Korenskii, Gaël Dubois, William Boissiere, and Nikita Kasianik
Atmos. Meas. Tech., 17, 4137–4152, https://doi.org/10.5194/amt-17-4137-2024, https://doi.org/10.5194/amt-17-4137-2024, 2024
Short summary
Short summary
The paper presents a new method that categorizes atmospheric aerosols by analyzing their optical properties with a Mie–Raman–fluorescence lidar. The research specifically looks into understanding the presence of smoke, urban, and dust aerosols in the mixtures identified by this lidar. The reliability of the results is evaluated using the Monte Carlo technique. The effectiveness of this approach is successfully demonstrated through testing in ATOLL, an observatory influenced by diverse aerosols.
Michael D. Himes, Ghassan Taha, Daniel Kahn, Tong Zhu, and Natalya A. Kramarova
EGUsphere, https://doi.org/10.5194/egusphere-2024-1823, https://doi.org/10.5194/egusphere-2024-1823, 2024
Short summary
Short summary
The Ozone Mapping and Profiler Suite's Limb Profiler (OMPS LP) provides near-global coverage and information about how aerosols from volcanic eruptions and major wildfires are vertically distributed through the atmosphere. We developed a machine learning method to characterize aerosols using OMPS LP measurements about 60 times faster than the current approach. This near-real-time characterization can be used to ensure aviation flight paths avoid dangerous conditions.
Fred Prata
Atmos. Meas. Tech., 17, 3751–3764, https://doi.org/10.5194/amt-17-3751-2024, https://doi.org/10.5194/amt-17-3751-2024, 2024
Short summary
Short summary
Geostationary satellite data have been used to measure the stratospheric aerosols from the explosive Hunga volcanic eruption by using the data in a novel way. The onboard imager views part of the Earth's limb and data from this region were analysed to generate vertical cross-sections of aerosols high in the atmosphere. The analyses show the hemispheric spread of the aerosols and their vertical structure in layers from 22–28 km in the stratosphere.
Emmanouil Proestakis, Antonis Gkikas, Thanasis Georgiou, Anna Kampouri, Eleni Drakaki, Claire L. Ryder, Franco Marenco, Eleni Marinou, and Vassilis Amiridis
Atmos. Meas. Tech., 17, 3625–3667, https://doi.org/10.5194/amt-17-3625-2024, https://doi.org/10.5194/amt-17-3625-2024, 2024
Short summary
Short summary
A new four-dimensional, multiyear, and near-global climate data record of the fine-mode (submicrometer diameter) and coarse-mode (supermicrometer diameter) components of atmospheric pure dust is presented. The dataset is considered unique with respect to a wide range of potential applications, including climatological, time series, and trend analysis over extensive geographical domains and temporal periods, validation of atmospheric dust models and datasets, and air quality.
Robin Miri, Olivier Pujol, Qiaoyun Hu, Philippe Goloub, Igor Veselovskii, Thierry Podvin, and Fabrice Ducos
Atmos. Meas. Tech., 17, 3367–3375, https://doi.org/10.5194/amt-17-3367-2024, https://doi.org/10.5194/amt-17-3367-2024, 2024
Short summary
Short summary
This paper focuses on the use of fluorescence to study aerosols with lidar. An innovative method for aerosol hygroscopic growth study using fluorescence is presented. The paper presents case studies to showcase the effectiveness and potential of the proposed approach. These advancements will contribute to better understanding the interactions between aerosols and water vapor, with future work expected to be dedicated to aerosol–cloud interaction.
Kabseok Ko, Seokheon Cho, and Ramesh R. Rao
Atmos. Meas. Tech., 17, 3303–3322, https://doi.org/10.5194/amt-17-3303-2024, https://doi.org/10.5194/amt-17-3303-2024, 2024
Short summary
Short summary
In our study, we examined how NO2, temperature, and relative humidity influence the calibration of PurpleAir PA-II sensors. We found that incorporating NO2 data from collocated reliable instruments enhances PM2.5 calibration performance. Due to the impracticality of collocating reliable NO2 instruments with sensors, we suggest using distant NO2 data for calibration. We demonstrated that performance improves when distant NO2 correlates highly with collocated NO2 measurements.
Daniel J. V. Robbins, Caroline A. Poulsen, Steven T. Siems, Simon R. Proud, Andrew T. Prata, Roy G. Grainger, and Adam C. Povey
Atmos. Meas. Tech., 17, 3279–3302, https://doi.org/10.5194/amt-17-3279-2024, https://doi.org/10.5194/amt-17-3279-2024, 2024
Short summary
Short summary
Extreme wildfire events are becoming more common with climate change. The smoke plumes associated with these wildfires are not captured by current operational satellite products due to their high optical thickness. We have developed a novel aerosol retrieval for the Advanced Himawari Imager to study these plumes. We find very high values of optical thickness not observed in other operational satellite products, suggesting these plumes have been missed in previous studies.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Didier Fussen, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Alexei Rozanov, and Christine Pohl
Atmos. Meas. Tech., 17, 3085–3101, https://doi.org/10.5194/amt-17-3085-2024, https://doi.org/10.5194/amt-17-3085-2024, 2024
Short summary
Short summary
We have developed the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument aboard Envisat. The retrieved aerosol extinction profiles are provided in the altitude range 10–40 km at 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm for the period 2002–2012. FMI-GOMOSaero aerosol profiles have improved quality; they are in good agreement with other datasets.
Jasper S. Wijnands, Arnoud Apituley, Diego Alves Gouveia, and Jan Willem Noteboom
Atmos. Meas. Tech., 17, 3029–3045, https://doi.org/10.5194/amt-17-3029-2024, https://doi.org/10.5194/amt-17-3029-2024, 2024
Short summary
Short summary
The mixing of air in the lower atmosphere influences the concentration of air pollutants and greenhouse gases. Our study developed a new method, Deep-Pathfinder, to estimate mixing layer height. Deep-Pathfinder analyses imagery with aerosol observations using artificial intelligence techniques for computer vision. Compared to existing methods, it improves temporal consistency and resolution and can be used in real time, which is valuable for aviation, forecasting, and air quality monitoring.
Liang Chang, Jing Li, Jingjing Ren, Changrui Xiong, and Lu Zhang
Atmos. Meas. Tech., 17, 2637–2648, https://doi.org/10.5194/amt-17-2637-2024, https://doi.org/10.5194/amt-17-2637-2024, 2024
Short summary
Short summary
We described a modified lidar inversion algorithm to retrieve aerosol extinction and size distribution simultaneously from two-wavelength elastic lidar measurements. Its major advantage is that the lidar ratio of each layer is determined iteratively by a lidar ratio–Ångström exponent lookup table. The algorithm was applied to the Raman lidar and CALIOP measurements. The retrieved results by our method are in good agreement with those achieved by Raman method.
Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 17, 2595–2610, https://doi.org/10.5194/amt-17-2595-2024, https://doi.org/10.5194/amt-17-2595-2024, 2024
Short summary
Short summary
Currently, aerosol properties from spaceborne multi-angle polarimeter (MAP) instruments can only be retrieved in cloud-free areas or in areas where an aerosol layer is located above a cloud. Therefore, it is important to be able to identify cloud-free pixels for which an aerosol retrieval algorithm can provide meaningful output. The developed neural network cloud screening demonstrates that cloud masking for MAP aerosol retrieval can be based on the MAP measurements themselves.
Nicholas Ernest, Larry W. Thomason, and Terry Deshler
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-62, https://doi.org/10.5194/amt-2024-62, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
We use balloon-borne measurements of aerosol size distribution (ASD) made by the University of Wyoming (UW) to derive distributions which are representative of the ASDs that underlie measurements made by the Stratospheric Aerosol and Gas Experiment II (SAGE II). A simple single mode log-normal distribution has in the past been used to derive ASD from SAGE II data; here we derive bimodal log-normal distributions. Reproducing median aerosol properties, however sometimes with wide variance.
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.
Travis N. Knepp, Mahesh Kovilakam, Larry Thomason, and Stephen J. Miller
Atmos. Meas. Tech., 17, 2025–2054, https://doi.org/10.5194/amt-17-2025-2024, https://doi.org/10.5194/amt-17-2025-2024, 2024
Short summary
Short summary
An algorithm is presented to derive a new SAGE III/ISS (Stratospheric Aerosol and Gas Experiment III on the International Space Station) Level-2 product: the size distribution of stratospheric particles. This is a significant improvement over previous techniques in that we now provide uncertainty estimates for all inferred parameters. We also evaluated the stability of this method in retrieving bimodal distribution parameters. We present a special application to the 2022 eruption of Hunga Tonga.
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.
Guangyao Dai, Songhua Wu, Wenrui Long, Jiqiao Liu, Yuan Xie, Kangwen Sun, Fanqian Meng, Xiaoquan Song, Zhongwei Huang, and Weibiao Chen
Atmos. Meas. Tech., 17, 1879–1890, https://doi.org/10.5194/amt-17-1879-2024, https://doi.org/10.5194/amt-17-1879-2024, 2024
Short summary
Short summary
An overview is given of the main algorithms applied to derive the aerosol and cloud optical property product of the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The paper demonstrates the observational capabilities of ACDL for aerosol and cloud vertical structure and global distribution through two optical property product measurement cases and global aerosol optical depth profile observations.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, William Boissiere, Mikhail Korenskiy, Nikita Kasianik, Sergey Khaykyn, and Robin Miri
Atmos. Meas. Tech., 17, 1023–1036, https://doi.org/10.5194/amt-17-1023-2024, https://doi.org/10.5194/amt-17-1023-2024, 2024
Short summary
Short summary
Measurements of transported smoke layers were performed with a lidar in Lille and a five-channel fluorescence lidar in Moscow. Results show the peak of fluorescence in the boundary layer is at 438 nm, while in the smoke layer it shifts to longer wavelengths. The fluorescence depolarization is 45 % to 55 %. The depolarization ratio of the water vapor channel is low (2 ± 0.5 %) in the absence of fluorescence and can be used to evaluate the contribution of fluorescence to water vapor signal.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
Short summary
Short summary
This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
Athena Augusta Floutsi, Holger Baars, and Ulla Wandinger
Atmos. Meas. Tech., 17, 693–714, https://doi.org/10.5194/amt-17-693-2024, https://doi.org/10.5194/amt-17-693-2024, 2024
Short summary
Short summary
We introduce an aerosol-typing scheme (HETEAC-Flex) based on lidar-derived intensive optical properties and applicable to ground-based and spaceborne lidars. HETEAC-Flex utilizes the optimal estimation method and enables the identification of up to four different aerosol components, as well as the determination of their contribution to the aerosol mixture in terms of relative volume. The aerosol components represent common aerosol types such as dust, sea salt, smoke and pollution.
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.
Juseon Shin, Gahyeong Kim, Dukhyeon Kim, Matthias Tesche, Gahyeon Park, and Youngmin Noh
Atmos. Meas. Tech., 17, 397–406, https://doi.org/10.5194/amt-17-397-2024, https://doi.org/10.5194/amt-17-397-2024, 2024
Short summary
Short summary
We introduce the multi-section method, a novel approach for stable extinction coefficient retrievals in horizontally scanning aerosol lidar measurements, in this study. Our method effectively removes signal–noise-induced irregular peaks and derives a reference extinction coefficient, αref, from multiple scans, resulting in a strong correlation (>0.74) with PM2.5 mass concentrations. Case studies demonstrate its utility in retrieving spatio-temporal aerosol distributions and PM2.5 concentrations.
Basudev Swain, Marco Vountas, Adrien Deroubaix, Luca Lelli, Yanick Ziegler, Soheila Jafariserajehlou, Sachin S. Gunthe, Andreas Herber, Christoph Ritter, Hartmut Bösch, and John P. Burrows
Atmos. Meas. Tech., 17, 359–375, https://doi.org/10.5194/amt-17-359-2024, https://doi.org/10.5194/amt-17-359-2024, 2024
Short summary
Short summary
Aerosols are suspensions of particles dispersed in the air. In this study, we use a novel retrieval of satellite data to investigate an optical property of aerosols, the aerosol optical depth, in the high Arctic to assess their direct and indirect roles in climate change. This study demonstrates that the presented approach shows good quality and very promising potential.
Gabriel Calassou, Pierre-Yves Foucher, and Jean-François Léon
Atmos. Meas. Tech., 17, 57–71, https://doi.org/10.5194/amt-17-57-2024, https://doi.org/10.5194/amt-17-57-2024, 2024
Short summary
Short summary
We propose analyzing the aerosol composition of plumes emitted by different industrial stacks using PRISMA satellite hyperspectral observations. Three industrial sites have been observed: a coal-fired power plant in South Africa, a steel plant in China, and gas flaring at an oil extraction site in Algeria. Aerosol optical thickness and particle radius are retrieved within the plumes. The mass flow rate of particulate matter is estimated in the plume using the integrated mass enhancement method.
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
Short summary
Short summary
In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
Short summary
Short summary
EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
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.
Vasiliki Daskalopoulou, Panagiotis I. Raptis, Alexandra Tsekeri, Vassilis Amiridis, Stelios Kazadzis, Zbigniew Ulanowski, Vassilis Charmandaris, Konstantinos Tassis, and William Martin
Atmos. Meas. Tech., 16, 4529–4550, https://doi.org/10.5194/amt-16-4529-2023, https://doi.org/10.5194/amt-16-4529-2023, 2023
Short summary
Short summary
Atmospheric dust particles may present a preferential alignment due to their shape on long range transport. Since dust is abundant and plays a key role to global climate, the elusive observation of orientation will be a game changer to existing measurement techniques and the representation of particles in climate models. We utilize a specifically designed instrument, SolPol, and target the Sun from the ground for large polarization values under dusty conditions, a clear sign of orientation.
Sara Herrero-Anta, Roberto Román, David Mateos, Ramiro González, Juan Carlos Antuña-Sánchez, Marcos Herreras-Giralda, Antonio Fernando Almansa, Daniel González-Fernández, Celia Herrero del Barrio, Carlos Toledano, Victoria E. Cachorro, and Ángel M. de Frutos
Atmos. Meas. Tech., 16, 4423–4443, https://doi.org/10.5194/amt-16-4423-2023, https://doi.org/10.5194/amt-16-4423-2023, 2023
Short summary
Short summary
This paper shows the potential of a simple radiometer like the ZEN-R52 as a possible alternative for aerosol property retrieval in remote areas. A calibration method based on radiative transfer simulations together with an inversion methodology using the GRASP code is proposed here. The results demonstrate that this methodology is useful for the retrieval of aerosol extensive properties like aerosol optical depth (AOD) and aerosol volume concentration for total, fine and coarse modes.
Xi Chen, Ting Yang, Zifa Wang, Futing Wang, and Haibo Wang
Atmos. Meas. Tech., 16, 4289–4302, https://doi.org/10.5194/amt-16-4289-2023, https://doi.org/10.5194/amt-16-4289-2023, 2023
Short summary
Short summary
Uncertainties remain great in the planetary boundary layer height (PBLH) determination from radiosonde, especially during the transition period of different PBL regimes. We combine seven existing methods along with statistical modification on gradient-based methods. We find that the ensemble method can eliminate the overestimation of PBLH and reduce the inconsistency between individual methods. The ensemble method improves the effectiveness of PBLH determination to 62.6 %.
Seyed Ali Sayedain, Norman T. O'Neill, James King, Patrick L. Hayes, Daniel Bellamy, Richard Washington, Sebastian Engelstaedter, Andy Vicente-Luis, Jill Bachelder, and Malo Bernhard
Atmos. Meas. Tech., 16, 4115–4135, https://doi.org/10.5194/amt-16-4115-2023, https://doi.org/10.5194/amt-16-4115-2023, 2023
Short summary
Short summary
We used (columnar) ground-based remote sensing (RS) tools and surface measurements to characterize local (drainage-basin) dust plumes at a site in the Yukon. Plume height, particle size, and column-to-surface ratios enabled insights into how satellite RS could be used to analyze Arctic-wide dust transport. This helps modelers refine dust impacts in their climate change simulations. It is an important step since local dust is a key source of dust deposition on snow in the sensitive Arctic region.
Cited articles
Ackerman, S., Richard, F., Kathleen, S., Yinghui, L., Liam, G., Bryan, B.,
and Paul, M.: Discriminating clear-sky from cloud with MODIS algorithm
theoretical basis document (MOD35), Univ. Wisconsin – Madison, 6th
Edn. (October), 129, available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.385.4885 (last access: 6 August 2021), 2010.
Benedetti, A., Reid, J. S., and Colarco, P. R.: International cooperative for
aerosol prediction workshop on aerosol forecast verification, B.
Am. Meteorol. Soc., 92, ES48–ES53, https://doi.org/10.1175/BAMS-D-11-00105.1, 2011.
Benedetti, A., Reid, J. S., Knippertz, P., Marsham, J. H., Di Giuseppe, F., Rémy, S., Basart, S., Boucher, O., Brooks, I. M., Menut, L., Mona, L., Laj, P., Pappalardo, G., Wiedensohler, A., Baklanov, A., Brooks, M., Colarco, P. R., Cuevas, E., da Silva, A., Escribano, J., Flemming, J., Huneeus, N., Jorba, O., Kazadzis, S., Kinne, S., Popp, T., Quinn, P. K., Sekiyama, T. T., Tanaka, T., and Terradellas, E.: Status and future of numerical atmospheric aerosol prediction with a focus on data requirements, Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, 2018.
Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., Žabkar, R., Carmichael, G. R., Flemming, J., Inness, A., Pagowski, M., Pérez Camaño, J. L., Saide, P. E., San Jose, R., Sofiev, M., Vira, J., Baklanov, A., Carnevale, C., Grell, G., and Seigneur, C.: Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models, Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, 2015.
Buchard, V., da Silva, A. M., Colarco, P. R., Darmenov, A., Randles, C. A., Govindaraju, R., Torres, O., Campbell, J., and Spurr, R.: Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis, Atmos. Chem. Phys., 15, 5743–5760, https://doi.org/10.5194/acp-15-5743-2015, 2015.
Buchard, V., Randles, C. A., da Silva, A. M., Darmenov, A., Colarco, P. R.,
Govindaraju, R., Ferrare, R., Hair, J., Beyersdorf, A. J., Ziemba, L. D., and
Yu, H.: The MERRA-2 aerosol reanalysis, 1980 onward. Part II: Evaluation and
case studies, J. Climate, 30, 6851–6872, https://doi.org/10.1175/JCLI-D-16-0613.1, 2017.
Butz, A., Hasekamp, O. P., Frankenberg, C., and Aben, U.: Retrievals of
atmospheric CO2 from simulated space-borne measurements of backscattered
near-infrared sunlight: Accounting for aerosol effects, Appl. Optics, 48,
3322–3336, https://doi.org/10.1364/AO.48.003322, 2009.
Choi, M., Lim, H., Kim, J., Lee, S., Eck, T. F., Holben, B. N., Garay, M. J., Hyer, E. J., Saide, P. E., and Liu, H.: Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign, Atmos. Meas. Tech., 12, 4619–4641, https://doi.org/10.5194/amt-12-4619-2019, 2019.
Colarco, P., Da Silva, A., Chin, M., and Diehl, T.: Online simulations of
global aerosol distributions in the NASA GEOS-4 model and comparisons to
satellite and ground-based aerosol optical depth, J. Geophys. Res.-Atmos.,
115, D14207, https://doi.org/10.1029/2009JD012820, 2010.
Di Girolamo, L. and Davies, R.: A Band-Differenced Angular Signature
Technique for Cirrus Cloud Detection, IEEE T. Geosci. Remote,
32, 890–896, https://doi.org/10.1109/36.298017, 1994.
Di Girolamo, L. and Davies, R.: The Image Navigation Cloud Mask for the
Multiangle Imaging Spectroradiometer (MISR), J. Atmos. Ocean. Technol.,
12, 1215–1228, https://doi.org/10.1175/1520-0426(1995)012<1215:tincmf>2.0.co;2, 1995.
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.
W., Gordon, H. R., Muller, J. P., Myneni, R. B., Sellers, P. J., Pinty, B.,
and Verstraete, M. M.: Multiangle Image Spectroradiometer (MISR) instrument
description and experiment overview, IEEE T. Geosci. Remote,
36, 1072–1087, 1998.
Diner, D. J., Di Girolamo, L., and Clothiaux, E. E.: Level 1 Cloud Detection
Algorithm Theoretical Basis, Jet Propuls. Lab. Calif. Inst. Technol.,
D-13397 (Rev. B), available at: https://eospso.gsfc.nasa.gov/sites/default/files/atbd/atbd-misr-06.pdf (last access: 9 August 2021), 1999a.
Diner, D. J., Davies, R., Di Girolamo, L., Horvath, A., Moroney, C., Muller,
J. P., Paradise, S. R., Wenkert, D., and Zong, J.: Level 2 Cloud Detection
and Classification Algorithm Theoretical Basis, Jet Propuls. Lab. Calif.
Inst. Technol., D-11399 (Rev. D), available at: https://eospso.gsfc.nasa.gov/sites/default/files/atbd/atbd-misr-07.pdf (last access: 9 August 2021), 1999b.
Diner, D. J., Abdou, W. A., Ackerman, T. P., Crean, K., Gordon, H. R., Kahn,
R. A., Martonchik, J. V, McMuldroch, S., Paradise, S. R., and Pinty, B.:
Level 2 aerosol retrieval algorithm theoretical basis, Jet Propuls. Lab.
Calif. Inst. Technol., D-11400 (Rev. G), available at: https://eospso.gsfc.nasa.gov/sites/default/files/atbd/atbd-misr-09.pdf (last access: 9 August 2021), 2008.
Di Tomaso, E., Schutgens, N. A. J., Jorba, O., and Pérez García-Pando, C.: Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0, Geosci. Model Dev., 10, 1107–1129, https://doi.org/10.5194/gmd-10-1107-2017, 2017.
Frankenberg, C., Hasekamp, O., O'Dell, C., Sanghavi, S., Butz, A., and Worden, J.: Aerosol information content analysis of multi-angle high spectral resolution measurements and its benefit for high accuracy greenhouse gas retrievals, Atmos. Meas. Tech., 5, 1809–1821, https://doi.org/10.5194/amt-5-1809-2012, 2012.
Frouin, R. J., Franz, B. A., Ibrahim, A., Knobelspiesse, K., Ahmad, Z.,
Cairns, B., Chowdhary, J., Dierssen, H. M., Tan, J., Dubovik, O., Huang, X.,
Davis, A. B., Kalashnikova, O., Thompson, D. R., Remer, L. A., Boss, E.,
Coddington, O., Deschamps, P. Y., Gao, B. C., Gross, L., Hasekamp, O., Omar,
A., Pelletier, B., Ramon, D., Steinmetz, F., and Zhai, P. W.: Atmospheric
Correction of Satellite Ocean-Color Imagery During the PACE Era, Front.
Earth Sci., 7, 145, https://doi.org/10.3389/feart.2019.00145, 2019.
Fu, G., Prata, F., Lin, H. X., Heemink, A., Segers, A., and Lu, S.: Data assimilation for volcanic ash plumes using a satellite observational operator: a case study on the 2010 Eyjafjallajökull volcanic eruption, Atmos. Chem. Phys., 17, 1187–1205, https://doi.org/10.5194/acp-17-1187-2017, 2017.
Gao, B. C., Goetz, A. F. H., and Wiscombe, W. J.: Cirrus cloud detection from
Airborne Imaging Spectrometer data using the 1.38 µm water vapor
band, Geophys. Res. Lett., 20, 301–304, https://doi.org/10.1029/93GL00106, 1993.
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.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan,
K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A.,
da Silva, A. M., Gu, W., Kim, G. K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M.,
Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The modern-era retrospective
analysis for research and applications, version 2 (MERRA-2), J. Climate,
30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Gordon, R.: Atmospheric correction of ocean color imagery in the Earth
Observing System era, J. Geophys. Res.-Atmos., 102, 17081–17106,
https://doi.org/10.1029/96JD02443, 1997.
Houweling, S., Hartmann, W., Aben, I., Schrijver, H., Skidmore, J., Roelofs, G.-J., and Breon, F.-M.: Evidence of systematic errors in SCIAMACHY-observed CO2 due to aerosols, Atmos. Chem. Phys., 5, 3003–3013, https://doi.org/10.5194/acp-5-3003-2005, 2005.
Inness, A., Baier, F., Benedetti, A., Bouarar, I., Chabrillat, S., Clark, H., Clerbaux, C., Coheur, P., Engelen, R. J., Errera, Q., Flemming, J., George, M., Granier, C., Hadji-Lazaro, J., Huijnen, V., Hurtmans, D., Jones, L., Kaiser, J. W., Kapsomenakis, J., Lefever, K., Leitão, J., Razinger, M., Richter, A., Schultz, M. G., Simmons, A. J., Suttie, M., Stein, O., Thépaut, J.-N., Thouret, V., Vrekoussis, M., Zerefos, C., and the MACC team: The MACC reanalysis: an 8 yr data set of atmospheric composition, Atmos. Chem. Phys., 13, 4073–4109, https://doi.org/10.5194/acp-13-4073-2013, 2013.
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019.
IPCC: Climate Change 2013: The Physical Science Basis, Contribution of
Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M. M. B., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA, 2013.
Kahn, R. A. and Gaitley, B. J.: An analysis of global aerosol type as
retrieved by MISR, J. Geophys. Res.-Atmos., 120, 4248–4281,
https://doi.org/10.1002/2015JD023322, 2015.
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.
Kalashnikova, O. V., Garay, M. J., Martonchik, J. V., and Diner, D. J.: MISR Dark Water aerosol retrievals: operational algorithm sensitivity to particle non-sphericity, Atmos. Meas. Tech., 6, 2131–2154, https://doi.org/10.5194/amt-6-2131-2013, 2013.
Lamarque, J.-F., Shindell, D. T., Josse, B., Young, P. J., Cionni, I., Eyring, V., Bergmann, D., Cameron-Smith, P., Collins, W. J., Doherty, R., Dalsoren, S., Faluvegi, G., Folberth, G., Ghan, S. J., Horowitz, L. W., Lee, Y. H., MacKenzie, I. A., Nagashima, T., Naik, V., Plummer, D., Righi, M., Rumbold, S. T., Schulz, M., Skeie, R. B., Stevenson, D. S., Strode, S., Sudo, K., Szopa, S., Voulgarakis, A., and Zeng, G.: The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): overview and description of models, simulations and climate diagnostics, Geosci. Model Dev., 6, 179–206, https://doi.org/10.5194/gmd-6-179-2013, 2013.
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The
contribution of outdoor air pollution sources to premature mortality on a
global scale, Nature, 525, 367–371, https://doi.org/10.1038/nature15371, 2015.
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, M., Westphal, D. L., Walker, A. L., Holt, T. R., Richardson, K. A., and
Miller, S. D.: COAMPS real-time dust storm forecasting during operation
Iraqi freedom, Weather Forecast., 22, 192–206, https://doi.org/10.1175/WAF971.1,
2007.
Lynch, P., Reid, J. S., Westphal, D. L., Zhang, J., Hogan, T. F., Hyer, E. J., Curtis, C. A., Hegg, D. A., Shi, Y., Campbell, J. R., Rubin, J. I., Sessions, W. R., Turk, F. J., and Walker, A. L.: An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences, Geosci. Model Dev., 9, 1489–1522, https://doi.org/10.5194/gmd-9-1489-2016, 2016.
Martonchik, J. V., Diner, D. J., Crean, K. A., and Bull, M. A.: Regional
aerosol retrieval results from MISR, IEEE T. Geosci. Remote,
40, 1520–1531, https://doi.org/10.1109/TGRS.2002.801142, 2002.
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. A. and de Leeuw, G., Springer, Berlin, Heidelberg, pp. 267–293, 2009.
NASA: Multi-angle Imaging SpectroRadiometer, NASA [data set], available at: https://asdc.larc.nasa.gov/project/MISR, last access: 6 August 2021.
Randles, C. A., da Silva, A. M., Buchard, V., Colarco, P. R., Darmenov, A.,
Govindaraju, R., Smirnov, A., Holben, B., Ferrare, R., Hair, J., Shinozuka,
Y., and Flynn, C. J.: The MERRA-2 aerosol reanalysis, 1980 onward. Part I:
System description and data assimilation evaluation, J. Climate, 30,
6823–6850, https://doi.org/10.1175/JCLI-D-16-0609.1, 2017.
Reid, J. S., Benedetti, A., Colarco, P. R., and Hansen, J. A.: International
operational aerosol observability workshop, B. Am.
Meteorol. Soc., 92, ES21–ES24, 2011.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J.,
Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G. K., Bloom,
S., Chen, J., Collins, D., Conaty, A., Da Silva, A., Gu, W., Joiner, J.,
Koster, R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P.,
Redder, C. R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz,
M., and Woollen, J.: MERRA: NASA's modern-era retrospective analysis for
research and applications, J. Climate, 24, 3624–3648,
https://doi.org/10.1175/JCLI-D-11-00015.1, 2011.
Sayer, A. M. and Knobelspiesse, K. D.: How should we aggregate data? Methods accounting for the numerical distributions, with an assessment of aerosol optical depth, Atmos. Chem. Phys., 19, 15023–15048, https://doi.org/10.5194/acp-19-15023-2019, 2019.
Sayer, A. M., Govaerts, Y., Kolmonen, P., Lipponen, A., Luffarelli, M., Mielonen, T., Patadia, F., Popp, T., Povey, A. C., Stebel, K., and Witek, M. L.: A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing, Atmos. Meas. Tech., 13, 373–404, https://doi.org/10.5194/amt-13-373-2020, 2020.
Sekiyama, T. T., Tanaka, T. Y., Shimizu, A., and Miyoshi, T.: Data assimilation of CALIPSO aerosol observations, Atmos. Chem. Phys., 10, 39–49, https://doi.org/10.5194/acp-10-39-2010, 2010.
Shi, Y., Zhang, J., Reid, J. S., Holben, B., Hyer, E. J., and Curtis, C.: An analysis of the collection 5 MODIS over-ocean aerosol optical depth product for its implication in aerosol assimilation, Atmos. Chem. Phys., 11, 557–565, https://doi.org/10.5194/acp-11-557-2011, 2011.
Shi, Y., Zhang, J., Reid, J. S., Hyer, E. J., and Hsu, N. C.: Critical evaluation of the MODIS Deep Blue aerosol optical depth product for data assimilation over North Africa, Atmos. Meas. Tech., 6, 949–969, https://doi.org/10.5194/amt-6-949-2013, 2013.
Shi, Y., Zhang, J., Reid, J. S., Liu, B., and Hyer, E. J.: Critical evaluation of cloud contamination in the MISR aerosol products using MODIS cloud mask products, Atmos. Meas. Tech., 7, 1791–1801, https://doi.org/10.5194/amt-7-1791-2014, 2014.
Shindell, D. T., Lamarque, J.-F., Schulz, M., Flanner, M., Jiao, C., Chin, M., Young, P. J., Lee, Y. H., Rotstayn, L., Mahowald, N., Milly, G., Faluvegi, G., Balkanski, Y., Collins, W. J., Conley, A. J., Dalsoren, S., Easter, R., Ghan, S., Horowitz, L., Liu, X., Myhre, G., Nagashima, T., Naik, V., Rumbold, S. T., Skeie, R., Sudo, K., Szopa, S., Takemura, T., Voulgarakis, A., Yoon, J.-H., and Lo, F.: Radiative forcing in the ACCMIP historical and future climate simulations, Atmos. Chem. Phys., 13, 2939–2974, https://doi.org/10.5194/acp-13-2939-2013, 2013.
Si, Y., Chen, L., Xiong, X., Shi, S., Husi, L., and Cai, K.: Evaluation of
the MISR fine resolution aerosol product using MODIS, MISR, and ground
observations over China, Atmos. Environ., 223, 117229,
https://doi.org/10.1016/j.atmosenv.2019.117229, 2020.
Sogacheva, L., Popp, T., Sayer, A. M., Dubovik, O., Garay, M. J., Heckel, A., Hsu, N. C., Jethva, H., Kahn, R. A., Kolmonen, P., Kosmale, M., de Leeuw, G., Levy, R. C., Litvinov, P., Lyapustin, A., North, P., Torres, O., and Arola, A.: Merging regional and global aerosol optical depth records from major available satellite products, Atmos. Chem. Phys., 20, 2031–2056, https://doi.org/10.5194/acp-20-2031-2020, 2020.
Tao, M., Wang, J., Li, R., Chen, L., Xu, X., Wang, L., Tao, J., Wang, Z., and
Xiang, J.: Characterization of Aerosol Type Over East Asia by 4.4 km MISR
Product: First Insight and General Performance, J. Geophys. Res.-Atmos.,
125, e2019JD031909, https://doi.org/10.1029/2019JD031909, 2020.
Turnock, S. T., Allen, R. J., Andrews, M., Bauer, S. E., Deushi, M., Emmons, L., Good, P., Horowitz, L., John, J. G., Michou, M., Nabat, P., Naik, V., Neubauer, D., O'Connor, F. M., Olivié, D., Oshima, N., Schulz, M., Sellar, A., Shim, S., Takemura, T., Tilmes, S., Tsigaridis, K., Wu, T., and Zhang, J.: Historical and future changes in air pollutants from CMIP6 models, Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, 2020.
Werner, M., Kryza, M., and Guzikowski, J.: Can data assimilation of surface
PM2.5 and Satellite AOD improve WRF-Chem Forecasting? A case study for two
scenarios of particulate air pollution episodes in Poland, Remote Sens.,
11, 2364, https://doi.org/10.3390/rs11202364, 2019.
Witek, M. L., Garay, M. J., Diner, D. J., and Smirnov, A.: Aerosol optical
depths over oceans: A view from MISR retrievals and collocated MAN and
AERONET in situ observations, J. Geophys. Res.-Atmos., 118,
12620–12633, https://doi.org/10.1002/2013JD020393, 2013.
Witek, M. L., Diner, D. J., Garay, M. J., Xu, F., Bull, M. A., and Seidel, F.
C.: Improving MISR AOD Retrievals with Low-Light-Level Corrections for
Veiling Light, IEEE T. Geosci. Remote, 56, 1251–1268,
https://doi.org/10.1109/TGRS.2017.2727342, 2018a.
Witek, M. L., Garay, M. J., Diner, D. J., Bull, M. A., and Seidel, F. C.: New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water, Atmos. Meas. Tech., 11, 429–439, https://doi.org/10.5194/amt-11-429-2018, 2018b.
Witek, M. L., Garay, M. J., Diner, D. J., and Smirnov, A.: Oceanic Aerosol
Loading Derived From MISR's 4.4 km (V23) Aerosol Product, J. Geophys. Res.-Atmos., 124, 10154–10174, https://doi.org/10.1029/2019JD031065, 2019.
Xian, P., Reid, J. S., Hyer, E. J., Sampson, C. R., Rubin, J. I., Ades, M.,
Asencio, N., Basart, S., Benedetti, A., Bhattacharjee, P. S., Brooks, M. E.,
Colarco, P. R., da Silva, A. M., Eck, T. F., Guth, J., Jorba, O.,
Kouznetsov, R., Kipling, Z., Sofiev, M., Perez Garcia-Pando, C., Pradhan,
Y., Tanaka, T., Wang, J., Westphal, D. L., Yumimoto, K., and Zhang, J.:
Current state of the global operational aerosol multi-model ensemble: An
update from the International Cooperative for Aerosol Prediction (ICAP), Q.
J. Roy. Meteor. Soc., 145, 176–209, https://doi.org/10.1002/qj.3497, 2019.
Zhang, J. and Reid, J. S.: An analysis of clear sky and contextual biases
using an operational over ocean MODIS aerosol product, Geophys. Res. Lett.,
36, L15824, https://doi.org/10.1029/2009GL038723, 2009.
Zhang, J. and Reid, J. S.: A decadal regional and global trend analysis of the aerosol optical depth using a data-assimilation grade over-water MODIS and Level 2 MISR aerosol products, Atmos. Chem. Phys., 10, 10949–10963, https://doi.org/10.5194/acp-10-10949-2010, 2010.
Zhang, J., Reid, J. S., Westphal, D. L., Baker, N. L., and Hyer, E. J.: A
system for operational aerosol optical depth data assimilation over global
oceans, J. Geophys. Res.-Atmos., 113, D10208, https://doi.org/10.1029/2007JD009065,
2008.
Short summary
This article documents the development and testing of a new near real-time (NRT) aerosol product from the MISR instrument on NASA’s Terra platform. The NRT product capitalizes on the unique attributes of the MISR retrieval approach, which leads to a high-quality and reliable aerosol data product. Several modifications are described that allow for rapid product generation within a 3 h window following acquisition. Implications for the product quality and consistency are discussed.
This article documents the development and testing of a new near real-time (NRT) aerosol product...
