Articles | Volume 12, issue 11
https://doi.org/10.5194/amt-12-6173-2019
© Author(s) 2019. 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-12-6173-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
CALIPSO level 3 stratospheric aerosol profile product: version 1.00 algorithm description and initial assessment
Science Systems and Applications Inc., Hampton, VA, USA
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Kam-Pui Lee
Science Systems and Applications Inc., Hampton, VA, USA
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Mark A. Vaughan
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Jason L. Tackett
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Charles R. Trepte
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
David M. Winker
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Patricia L. Lucker
Science Systems and Applications Inc., Hampton, VA, USA
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Brian J. Getzewich
Science Systems and Applications Inc., Hampton, VA, USA
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Related authors
Jason L. Tackett, Jayanta Kar, Mark A. Vaughan, Brian J. Getzewich, Man-Hae Kim, Jean-Paul Vernier, Ali H. Omar, Brian E. Magill, Michael C. Pitts, and David M. Winker
Atmos. Meas. Tech., 16, 745–768, https://doi.org/10.5194/amt-16-745-2023, https://doi.org/10.5194/amt-16-745-2023, 2023
Short summary
Short summary
The accurate identification of aerosol types in the stratosphere is important to characterize their impacts on the Earth climate system. The space-borne lidar on board CALIPSO is well-posed to identify aerosols in the stratosphere from volcanic eruptions and major wildfire events. This paper describes improvements implemented in the version 4.5 CALIPSO data release to more accurately discriminate between volcanic ash, sulfate, and smoke within the stratosphere.
Travis N. Knepp, Larry Thomason, Mahesh Kovilakam, Jason Tackett, Jayanta Kar, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 15, 5235–5260, https://doi.org/10.5194/amt-15-5235-2022, https://doi.org/10.5194/amt-15-5235-2022, 2022
Short summary
Short summary
We used aerosol profiles from the SAGE III/ISS instrument to develop an aerosol classification method that was tested on four case-study events (two volcanic, two fire) and supported with CALIOP aerosol products. The method worked well in identifying smoke and volcanic aerosol in the stratosphere for these events. Raikoke is presented as a demonstration of the limitations of this method.
Zhujun Li, David Painemal, Gregory Schuster, Marian Clayton, Richard Ferrare, Mark Vaughan, Damien Josset, Jayanta Kar, and Charles Trepte
Atmos. Meas. Tech., 15, 2745–2766, https://doi.org/10.5194/amt-15-2745-2022, https://doi.org/10.5194/amt-15-2745-2022, 2022
Short summary
Short summary
For more than 15 years, CALIPSO has revolutionized our understanding of the role of aerosols in climate. Here we evaluate CALIPSO aerosol typing over the ocean using an independent CALIPSO–CloudSat product. The analysis suggests that CALIPSO correctly categorizes clean marine aerosol over the open ocean, elevated smoke over the SE Atlantic, and dust over the tropical Atlantic. Similarities between clean and dusty marine over the open ocean implies that algorithm modifications are warranted.
Luca Bugliaro, Dennis Piontek, Stephan Kox, Marius Schmidl, Bernhard Mayer, Richard Müller, Margarita Vázquez-Navarro, Daniel M. Peters, Roy G. Grainger, Josef Gasteiger, and Jayanta Kar
Nat. Hazards Earth Syst. Sci., 22, 1029–1054, https://doi.org/10.5194/nhess-22-1029-2022, https://doi.org/10.5194/nhess-22-1029-2022, 2022
Short summary
Short summary
The monitoring of ash dispersion in the atmosphere is an important task for satellite remote sensing since ash represents a threat to air traffic. We present an AI-based method that retrieves the spatial extension and properties of volcanic ash clouds with high temporal resolution during day and night by means of geostationary satellite measurements. This algorithm, trained on realistic observations simulated with a radiative transfer model, runs operationally at the German Weather Service.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036, https://doi.org/10.5194/amt-14-1015-2021, https://doi.org/10.5194/amt-14-1015-2021, 2021
Short summary
Short summary
This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Shan Zeng, Mark Vaughan, Zhaoyan Liu, Charles Trepte, Jayanta Kar, Ali Omar, David Winker, Patricia Lucker, Yongxiang Hu, Brian Getzewich, and Melody Avery
Atmos. Meas. Tech., 12, 2261–2285, https://doi.org/10.5194/amt-12-2261-2019, https://doi.org/10.5194/amt-12-2261-2019, 2019
Short summary
Short summary
We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol discrimination (CAD) algorithm to correctly distinguish between clouds and aerosols detected in the CALIPSO lidar backscatter signals. FKM is an unsupervised learning algorithm, so the classifications it derives are wholly independent from those reported by the CAD scheme. For a full month of measurements, the two techniques agree in ~ 95 % of all cases, providing strong evidence for CAD correctness.
Zhaoyan Liu, Jayanta Kar, Shan Zeng, Jason Tackett, Mark Vaughan, Melody Avery, Jacques Pelon, Brian Getzewich, Kam-Pui Lee, Brian Magill, Ali Omar, Patricia Lucker, Charles Trepte, and David Winker
Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, https://doi.org/10.5194/amt-12-703-2019, 2019
Short summary
Short summary
We describe the enhancements made to the cloud–aerosol discrimination (CAD) algorithms used to produce the CALIPSO version 4 (V4) data products. Revisions to the CAD probability distribution functions have greatly improved the recognition of aerosol layers lofted into the upper troposphere, and CAD is now applied to all layers detected in the stratosphere and all layers detected at single-shot resolution. Detailed comparisons show significant improvements relative to previous versions.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
Short summary
Short summary
The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
Brian J. Getzewich, Mark A. Vaughan, William H. Hunt, Melody A. Avery, Kathleen A. Powell, Jason L. Tackett, David M. Winker, Jayanta Kar, Kam-Pui Lee, and Travis D. Toth
Atmos. Meas. Tech., 11, 6309–6326, https://doi.org/10.5194/amt-11-6309-2018, https://doi.org/10.5194/amt-11-6309-2018, 2018
Short summary
Short summary
We describe the new architecture of the version 4 (V4) CALIOP 532 nm daytime calibration procedures. Critical differences from the versions include moving the night-to-day calibration transfer region into the lower stratosphere coupled to a multi-dimensional data averaging scheme. Comparisons to collocated high spectral resolution lidar (HSRL) measurements shows that the V4 532 nm daytime attenuated backscatter coefficients replicate the HSRL data to within 1.0 % ± 3.5 %.
Man-Hae Kim, Ali H. Omar, Jason L. Tackett, Mark A. Vaughan, David M. Winker, Charles R. Trepte, Yongxiang Hu, Zhaoyan Liu, Lamont R. Poole, Michael C. Pitts, Jayanta Kar, and Brian E. Magill
Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, https://doi.org/10.5194/amt-11-6107-2018, 2018
Short summary
Short summary
This paper discusses recent advances made in distinguishing among different aerosols species detected in the CALIPSO lidar measurements. A new classification algorithm now classifies four different aerosol types in the stratosphere, and the number of aerosol types recognized in the troposphere has increased from six to seven. The lidar ratios characterizing each type have been updated and the effects of these changes on CALIPSO retrievals of aerosol optical depth are examined in detail.
Jason L. Tackett, David M. Winker, Brian J. Getzewich, Mark A. Vaughan, Stuart A. Young, and Jayanta Kar
Atmos. Meas. Tech., 11, 4129–4152, https://doi.org/10.5194/amt-11-4129-2018, https://doi.org/10.5194/amt-11-4129-2018, 2018
Short summary
Short summary
The CALIPSO level 3 aerosol profile product reports globally gridded, quality-screened monthly mean aerosol extinction profiles retrieved by the spaceborne lidar, CALIOP. This paper describes the quality screening and averaging methods used to generate the product. Impacts of quality screening on reported quantities are evaluated, in particular the change in aerosol extinction profiles and aerosol optical depth. The paper thereby provides guidance on the use of CALIOP aerosol data.
Jayanta Kar, Mark A. Vaughan, Kam-Pui Lee, Jason L. Tackett, Melody A. Avery, Anne Garnier, Brian J. Getzewich, William H. Hunt, Damien Josset, Zhaoyan Liu, Patricia L. Lucker, Brian Magill, Ali H. Omar, Jacques Pelon, Raymond R. Rogers, Travis D. Toth, Charles R. Trepte, Jean-Paul Vernier, David M. Winker, and Stuart A. Young
Atmos. Meas. Tech., 11, 1459–1479, https://doi.org/10.5194/amt-11-1459-2018, https://doi.org/10.5194/amt-11-1459-2018, 2018
Short summary
Short summary
We present the motivation for and the implementation of the version 4.1 nighttime 532 nm parallel-channel calibration of the CALIOP lidar. The accuracy of calibration is significantly improved by raising the molecular normalization altitude from 30–34 km to 36–39 km to substantially reduce stratospheric aerosol contamination. The new calibration procedure eliminates biases in earlier versions and leads to an improved representation of stratospheric aerosols.
Z. Liu, D. Winker, A. Omar, M. Vaughan, J. Kar, C. Trepte, Y. Hu, and G. Schuster
Atmos. Chem. Phys., 15, 1265–1288, https://doi.org/10.5194/acp-15-1265-2015, https://doi.org/10.5194/acp-15-1265-2015, 2015
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.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
Short summary
Short summary
Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
David Winker, Xia Cai, Mark Vaughan, Anne Garnier, Brian Magill, Melody Avery, and Brian Getzewich
Earth Syst. Sci. Data, 16, 2831–2855, https://doi.org/10.5194/essd-16-2831-2024, https://doi.org/10.5194/essd-16-2831-2024, 2024
Short summary
Short summary
Clouds play important roles in both weather and climate. In this paper we describe version 1.0 of a unique global ice cloud data product derived from over 12 years of global spaceborne lidar measurements. This monthly gridded product provides a unique vertically resolved characterization of the occurrence and properties, optical and physical, of thin ice clouds and the tops of deep convective clouds. It should provide significant value for cloud research and model evaluation.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Jason L. Tackett, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1127, https://doi.org/10.5194/egusphere-2024-1127, 2024
Short summary
Short summary
We use the GEOS-Chem model to simulate aerosols over the western North Atlantic Ocean (WNAO) during the winter and summer campaigns of ACTIVATE 2020. Model results are evaluated against in situ and remote sensing measurements from two aircraft as well as ground-based and satellite observations. The improved understanding of the aerosol life cycle, composition, transport pathways, and distribution has important implications for characterizing aerosol-cloud-meteorology interactions over the WNAO.
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
Geosci. Model Dev., 16, 1359–1377, https://doi.org/10.5194/gmd-16-1359-2023, https://doi.org/10.5194/gmd-16-1359-2023, 2023
Short summary
Short summary
Aerosol has a large impact on climate. Using a lidar aerosol simulator ensures consistent comparisons between modeled and observed aerosol. We present a lidar aerosol simulator that applies a cloud masking and an aerosol detection threshold. We estimate the lidar signals that would be observed at 532 nm by the Cloud-Aerosol Lidar with Orthogonal Polarization overflying the atmosphere predicted by a climate model. Our comparison at the seasonal timescale shows a discrepancy in the Southern Ocean.
Jason L. Tackett, Jayanta Kar, Mark A. Vaughan, Brian J. Getzewich, Man-Hae Kim, Jean-Paul Vernier, Ali H. Omar, Brian E. Magill, Michael C. Pitts, and David M. Winker
Atmos. Meas. Tech., 16, 745–768, https://doi.org/10.5194/amt-16-745-2023, https://doi.org/10.5194/amt-16-745-2023, 2023
Short summary
Short summary
The accurate identification of aerosol types in the stratosphere is important to characterize their impacts on the Earth climate system. The space-borne lidar on board CALIPSO is well-posed to identify aerosols in the stratosphere from volcanic eruptions and major wildfire events. This paper describes improvements implemented in the version 4.5 CALIPSO data release to more accurately discriminate between volcanic ash, sulfate, and smoke within the stratosphere.
Travis N. Knepp, Larry Thomason, Mahesh Kovilakam, Jason Tackett, Jayanta Kar, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 15, 5235–5260, https://doi.org/10.5194/amt-15-5235-2022, https://doi.org/10.5194/amt-15-5235-2022, 2022
Short summary
Short summary
We used aerosol profiles from the SAGE III/ISS instrument to develop an aerosol classification method that was tested on four case-study events (two volcanic, two fire) and supported with CALIOP aerosol products. The method worked well in identifying smoke and volcanic aerosol in the stratosphere for these events. Raikoke is presented as a demonstration of the limitations of this method.
Zhujun Li, David Painemal, Gregory Schuster, Marian Clayton, Richard Ferrare, Mark Vaughan, Damien Josset, Jayanta Kar, and Charles Trepte
Atmos. Meas. Tech., 15, 2745–2766, https://doi.org/10.5194/amt-15-2745-2022, https://doi.org/10.5194/amt-15-2745-2022, 2022
Short summary
Short summary
For more than 15 years, CALIPSO has revolutionized our understanding of the role of aerosols in climate. Here we evaluate CALIPSO aerosol typing over the ocean using an independent CALIPSO–CloudSat product. The analysis suggests that CALIPSO correctly categorizes clean marine aerosol over the open ocean, elevated smoke over the SE Atlantic, and dust over the tropical Atlantic. Similarities between clean and dusty marine over the open ocean implies that algorithm modifications are warranted.
Luca Bugliaro, Dennis Piontek, Stephan Kox, Marius Schmidl, Bernhard Mayer, Richard Müller, Margarita Vázquez-Navarro, Daniel M. Peters, Roy G. Grainger, Josef Gasteiger, and Jayanta Kar
Nat. Hazards Earth Syst. Sci., 22, 1029–1054, https://doi.org/10.5194/nhess-22-1029-2022, https://doi.org/10.5194/nhess-22-1029-2022, 2022
Short summary
Short summary
The monitoring of ash dispersion in the atmosphere is an important task for satellite remote sensing since ash represents a threat to air traffic. We present an AI-based method that retrieves the spatial extension and properties of volcanic ash clouds with high temporal resolution during day and night by means of geostationary satellite measurements. This algorithm, trained on realistic observations simulated with a radiative transfer model, runs operationally at the German Weather Service.
Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
Atmos. Meas. Tech., 15, 1931–1956, https://doi.org/10.5194/amt-15-1931-2022, https://doi.org/10.5194/amt-15-1931-2022, 2022
Short summary
Short summary
A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of
not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, https://doi.org/10.5194/amt-14-3253-2021, 2021
Short summary
Short summary
The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results are presented in a companion paper (Part II).
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, https://doi.org/10.5194/amt-14-3277-2021, 2021
Short summary
Short summary
The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
Thibault Vaillant de Guélis, Mark A. Vaughan, David M. Winker, and Zhaoyan Liu
Atmos. Meas. Tech., 14, 1593–1613, https://doi.org/10.5194/amt-14-1593-2021, https://doi.org/10.5194/amt-14-1593-2021, 2021
Short summary
Short summary
We introduce a new lidar feature detection algorithm that dramatically improves the fine details of layers identified in the CALIOP data. By applying our two-dimensional scanning technique to the measurements in all three channels, we minimize false positives while accurately identifying previously undetected features such as subvisible cirrus and the full vertical extent of dense smoke plumes. Multiple comparisons to version 4.2 CALIOP retrievals illustrate the scope of the improvements made.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036, https://doi.org/10.5194/amt-14-1015-2021, https://doi.org/10.5194/amt-14-1015-2021, 2021
Short summary
Short summary
This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Melody A. Avery, Robert A. Ryan, Brian J. Getzewich, Mark A. Vaughan, David M. Winker, Yongxiang Hu, Anne Garnier, Jacques Pelon, and Carolus A. Verhappen
Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, https://doi.org/10.5194/amt-13-4539-2020, 2020
Short summary
Short summary
CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6 %–9 % for high-confidence cloud phases and 1 %–2 % for all cloudy bins, including cloud fringes and unknown cloud phases. In V4 there are many fewer cloud layers identified as horizontally oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
Rebecca M. Pauly, John E. Yorks, Dennis L. Hlavka, Matthew J. McGill, Vassilis Amiridis, Stephen P. Palm, Sharon D. Rodier, Mark A. Vaughan, Patrick A. Selmer, Andrew W. Kupchock, Holger Baars, and Anna Gialitaki
Atmos. Meas. Tech., 12, 6241–6258, https://doi.org/10.5194/amt-12-6241-2019, https://doi.org/10.5194/amt-12-6241-2019, 2019
Short summary
Short summary
The Cloud Aerosol Transport System (CATS) demonstrated that direct calibration of 1064 nm lidar data from a spaceborne platform is possible. By normalizing the CATS signal to a modeled molecular backscatter profile the CATS data were calibrated, enabling the derivation of optical properties of clouds and aerosols. Comparisons of the calibrated signal with airborne lidar, ground-based lidar, and spaceborne lidar all show agreement within the estimated error bars of the respective instruments.
Jeffrey S. Reid, Derek J. Posselt, Kathleen Kaku, Robert A. Holz, Gao Chen, Edwin W. Eloranta, Ralph E. Kuehn, Sarah Woods, Jianglong Zhang, Bruce Anderson, T. Paul Bui, Glenn S. Diskin, Patrick Minnis, Michael J. Newchurch, Simone Tanelli, Charles R. Trepte, K. Lee Thornhill, and Luke D. Ziemba
Atmos. Chem. Phys., 19, 11413–11442, https://doi.org/10.5194/acp-19-11413-2019, https://doi.org/10.5194/acp-19-11413-2019, 2019
Short summary
Short summary
The scientific community often focuses on the vertical transport of pollutants by clouds for those with bases at the planetary boundary layer (such as typical fair-weather cumulus) and the outflow from thunderstorms at their tops. We demonstrate complex aerosol and cloud features formed in mid-level thunderstorm outflow. These layers have strong relationships to mid-level tropospheric clouds, an important but difficult to model or monitor cloud regime for climate studies.
Shan Zeng, Mark Vaughan, Zhaoyan Liu, Charles Trepte, Jayanta Kar, Ali Omar, David Winker, Patricia Lucker, Yongxiang Hu, Brian Getzewich, and Melody Avery
Atmos. Meas. Tech., 12, 2261–2285, https://doi.org/10.5194/amt-12-2261-2019, https://doi.org/10.5194/amt-12-2261-2019, 2019
Short summary
Short summary
We use a fuzzy k-means (FKM) classifier to assess the ability of the CALIPSO cloud–aerosol discrimination (CAD) algorithm to correctly distinguish between clouds and aerosols detected in the CALIPSO lidar backscatter signals. FKM is an unsupervised learning algorithm, so the classifications it derives are wholly independent from those reported by the CAD scheme. For a full month of measurements, the two techniques agree in ~ 95 % of all cases, providing strong evidence for CAD correctness.
Meloë S. Kacenelenbogen, Mark A. Vaughan, Jens Redemann, Stuart A. Young, Zhaoyan Liu, Yongxiang Hu, Ali H. Omar, Samuel LeBlanc, Yohei Shinozuka, John Livingston, Qin Zhang, and Kathleen A. Powell
Atmos. Chem. Phys., 19, 4933–4962, https://doi.org/10.5194/acp-19-4933-2019, https://doi.org/10.5194/acp-19-4933-2019, 2019
Short summary
Short summary
Significant efforts are required to estimate the direct radiative effects of aerosols above clouds (DAREcloudy). We have used a combination of passive and active A-Train satellite sensors and derive mainly positive global and regional DAREcloudy values (e.g., global seasonal values between 0.13 and 0.26 W m-2). Despite differences in methods and sensors, the DAREcloudy values in this study are generally higher than previously reported. We discuss the primary reasons for these higher estimates.
David Painemal, Marian Clayton, Richard Ferrare, Sharon Burton, Damien Josset, and Mark Vaughan
Atmos. Meas. Tech., 12, 2201–2217, https://doi.org/10.5194/amt-12-2201-2019, https://doi.org/10.5194/amt-12-2201-2019, 2019
Short summary
Short summary
We present 1 year of a new CALIOP-based aerosol extinction coefficient and lidar ratio over the ocean, with the goal of providing a flexible dataset for climate research as well as independent retrievals that can be helpful for refining CALIPSO Science Team algorithms. The retrievals are derived by constraining the lidar equation with an aerosol optical depth estimated from cross-calibrated CALIOP and CloudSat surface echos.
Travis D. Toth, Jianglong Zhang, Jeffrey S. Reid, and Mark A. Vaughan
Atmos. Meas. Tech., 12, 1739–1754, https://doi.org/10.5194/amt-12-1739-2019, https://doi.org/10.5194/amt-12-1739-2019, 2019
Short summary
Short summary
An innovative method is presented for deriving particulate matter (PM) concentrations using CALIOP measurements. Deviating from conventional approaches of relying on passive satellite column-integrated aerosol measurements, PM concentrations are derived from near-surface CALIOP measurements through a bulk-mass-modeling method. This proof-of-concept study shows that, while limited in spatial and temporal coverage, CALIOP exhibits reasonable skill for PM applications.
Zhaoyan Liu, Jayanta Kar, Shan Zeng, Jason Tackett, Mark Vaughan, Melody Avery, Jacques Pelon, Brian Getzewich, Kam-Pui Lee, Brian Magill, Ali Omar, Patricia Lucker, Charles Trepte, and David Winker
Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, https://doi.org/10.5194/amt-12-703-2019, 2019
Short summary
Short summary
We describe the enhancements made to the cloud–aerosol discrimination (CAD) algorithms used to produce the CALIPSO version 4 (V4) data products. Revisions to the CAD probability distribution functions have greatly improved the recognition of aerosol layers lofted into the upper troposphere, and CAD is now applied to all layers detected in the stratosphere and all layers detected at single-shot resolution. Detailed comparisons show significant improvements relative to previous versions.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
Short summary
Short summary
The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
Brian J. Getzewich, Mark A. Vaughan, William H. Hunt, Melody A. Avery, Kathleen A. Powell, Jason L. Tackett, David M. Winker, Jayanta Kar, Kam-Pui Lee, and Travis D. Toth
Atmos. Meas. Tech., 11, 6309–6326, https://doi.org/10.5194/amt-11-6309-2018, https://doi.org/10.5194/amt-11-6309-2018, 2018
Short summary
Short summary
We describe the new architecture of the version 4 (V4) CALIOP 532 nm daytime calibration procedures. Critical differences from the versions include moving the night-to-day calibration transfer region into the lower stratosphere coupled to a multi-dimensional data averaging scheme. Comparisons to collocated high spectral resolution lidar (HSRL) measurements shows that the V4 532 nm daytime attenuated backscatter coefficients replicate the HSRL data to within 1.0 % ± 3.5 %.
Man-Hae Kim, Ali H. Omar, Jason L. Tackett, Mark A. Vaughan, David M. Winker, Charles R. Trepte, Yongxiang Hu, Zhaoyan Liu, Lamont R. Poole, Michael C. Pitts, Jayanta Kar, and Brian E. Magill
Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, https://doi.org/10.5194/amt-11-6107-2018, 2018
Short summary
Short summary
This paper discusses recent advances made in distinguishing among different aerosols species detected in the CALIPSO lidar measurements. A new classification algorithm now classifies four different aerosol types in the stratosphere, and the number of aerosol types recognized in the troposphere has increased from six to seven. The lidar ratios characterizing each type have been updated and the effects of these changes on CALIPSO retrievals of aerosol optical depth are examined in detail.
Stuart A. Young, Mark A. Vaughan, Anne Garnier, Jason L. Tackett, James D. Lambeth, and Kathleen A. Powell
Atmos. Meas. Tech., 11, 5701–5727, https://doi.org/10.5194/amt-11-5701-2018, https://doi.org/10.5194/amt-11-5701-2018, 2018
Short summary
Short summary
This paper describes comprehensive upgrades to the algorithms used to retrieve altitude-resolved profiles of cloud and aerosol extinction coefficients from the elastic backscatter measurements made by the space-based CALIPSO lidar. The CALIPSO version 4 data products generated by these new algorithms are explored in detail, and the many areas of improvement are highlighted using extensive comparisons both to previous versions and to collocated measurements made by space-based passive sensors.
Jason L. Tackett, David M. Winker, Brian J. Getzewich, Mark A. Vaughan, Stuart A. Young, and Jayanta Kar
Atmos. Meas. Tech., 11, 4129–4152, https://doi.org/10.5194/amt-11-4129-2018, https://doi.org/10.5194/amt-11-4129-2018, 2018
Short summary
Short summary
The CALIPSO level 3 aerosol profile product reports globally gridded, quality-screened monthly mean aerosol extinction profiles retrieved by the spaceborne lidar, CALIOP. This paper describes the quality screening and averaging methods used to generate the product. Impacts of quality screening on reported quantities are evaluated, in particular the change in aerosol extinction profiles and aerosol optical depth. The paper thereby provides guidance on the use of CALIOP aerosol data.
Xiaomei Lu, Yongxiang Hu, Yuekui Yang, Mark Vaughan, Zhaoyan Liu, Sharon Rodier, William Hunt, Kathy Powell, Patricia Lucker, and Charles Trepte
Atmos. Meas. Tech., 11, 3281–3296, https://doi.org/10.5194/amt-11-3281-2018, https://doi.org/10.5194/amt-11-3281-2018, 2018
Short summary
Short summary
This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. The surface bidirectional reflectances retrieved from CALIOP measurements contribute complementary data for existing MODIS standard data products and could be used to detect and monitor seasonal surface reflectance changes in high latitude regions where passive MODIS measurements are limited.
Quentin Bourgeois, Annica M. L. Ekman, Jean-Baptiste Renard, Radovan Krejci, Abhay Devasthale, Frida A.-M. Bender, Ilona Riipinen, Gwenaël Berthet, and Jason L. Tackett
Atmos. Chem. Phys., 18, 7709–7720, https://doi.org/10.5194/acp-18-7709-2018, https://doi.org/10.5194/acp-18-7709-2018, 2018
Short summary
Short summary
The altitude of aerosols is crucial as they can impact cloud formation and radiation. In this study, satellite observations have been used to characterize the global aerosol optical depth (AOD) in the boundary layer and the free troposphere. The free troposphere contributes 39 % to the global AOD during daytime. Overall, the results have implications for the description of budgets, sources, sinks and transport of aerosol particles as presently described in the atmospheric model.
Anne Garnier, Thierry Trémas, Jacques Pelon, Kam-Pui Lee, Delphine Nobileau, Lydwine Gross-Colzy, Nicolas Pascal, Pascale Ferrage, and Noëlle A. Scott
Atmos. Meas. Tech., 11, 2485–2500, https://doi.org/10.5194/amt-11-2485-2018, https://doi.org/10.5194/amt-11-2485-2018, 2018
Short summary
Short summary
Residual calibration biases affecting CALIPSO IIR Version 1 calibrated radiances in the Northern Hemisphere are analyzed and reduced through in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels.
Jayanta Kar, Mark A. Vaughan, Kam-Pui Lee, Jason L. Tackett, Melody A. Avery, Anne Garnier, Brian J. Getzewich, William H. Hunt, Damien Josset, Zhaoyan Liu, Patricia L. Lucker, Brian Magill, Ali H. Omar, Jacques Pelon, Raymond R. Rogers, Travis D. Toth, Charles R. Trepte, Jean-Paul Vernier, David M. Winker, and Stuart A. Young
Atmos. Meas. Tech., 11, 1459–1479, https://doi.org/10.5194/amt-11-1459-2018, https://doi.org/10.5194/amt-11-1459-2018, 2018
Short summary
Short summary
We present the motivation for and the implementation of the version 4.1 nighttime 532 nm parallel-channel calibration of the CALIOP lidar. The accuracy of calibration is significantly improved by raising the molecular normalization altitude from 30–34 km to 36–39 km to substantially reduce stratospheric aerosol contamination. The new calibration procedure eliminates biases in earlier versions and leads to an improved representation of stratospheric aerosols.
Travis D. Toth, James R. Campbell, Jeffrey S. Reid, Jason L. Tackett, Mark A. Vaughan, Jianglong Zhang, and Jared W. Marquis
Atmos. Meas. Tech., 11, 499–514, https://doi.org/10.5194/amt-11-499-2018, https://doi.org/10.5194/amt-11-499-2018, 2018
Thibault Vaillant de Guélis, Hélène Chepfer, Vincent Noel, Rodrigo Guzman, Philippe Dubuisson, David M. Winker, and Seiji Kato
Atmos. Meas. Tech., 10, 4659–4685, https://doi.org/10.5194/amt-10-4659-2017, https://doi.org/10.5194/amt-10-4659-2017, 2017
Robert E. Holz, Steven Platnick, Kerry Meyer, Mark Vaughan, Andrew Heidinger, Ping Yang, Gala Wind, Steven Dutcher, Steven Ackerman, Nandana Amarasinghe, Fredrick Nagle, and Chenxi Wang
Atmos. Chem. Phys., 16, 5075–5090, https://doi.org/10.5194/acp-16-5075-2016, https://doi.org/10.5194/acp-16-5075-2016, 2016
A. Garnier, J. Pelon, M. A. Vaughan, D. M. Winker, C. R. Trepte, and P. Dubuisson
Atmos. Meas. Tech., 8, 2759–2774, https://doi.org/10.5194/amt-8-2759-2015, https://doi.org/10.5194/amt-8-2759-2015, 2015
Short summary
Short summary
Cloud absorption optical depths retrieved at 12.05 microns are compared to extinction optical depths retrieved at 0.532 microns from perfectly co-located observations of single-layered semi-transparent cirrus over oceans made by the space-borne CALIPSO IIR infrared radiometer and CALIOP lidar. A new relationship describing the temperature-dependent effect of multiple scattering in the CALIOP retrievals is derived and discussed.
Z. Liu, D. Winker, A. Omar, M. Vaughan, J. Kar, C. Trepte, Y. Hu, and G. Schuster
Atmos. Chem. Phys., 15, 1265–1288, https://doi.org/10.5194/acp-15-1265-2015, https://doi.org/10.5194/acp-15-1265-2015, 2015
J. R. Campbell, M. A. Vaughan, M. Oo, R. E. Holz, J. R. Lewis, and E. J. Welton
Atmos. Meas. Tech., 8, 435–449, https://doi.org/10.5194/amt-8-435-2015, https://doi.org/10.5194/amt-8-435-2015, 2015
Short summary
Short summary
Digital thresholds based on 2012 CALIOP satellite lidar measurements are investigated for distinguishing cirrus cloud presence, including cloud top temperatures and heights combined with layer depolarization and phase and optical depths. A cloud top temperature of -37 C is found to exhibit the most stable performance, owing to it being the point of homogeneous liquid-water freezing. Depolarization and phase help but are mostly ambiguous at warmer temperatures where mixed-phase clouds propagate.
R. R. Rogers, M. A. Vaughan, C. A. Hostetler, S. P. Burton, R. A. Ferrare, S. A. Young, J. W. Hair, M. D. Obland, D. B. Harper, A. L. Cook, and D. M. Winker
Atmos. Meas. Tech., 7, 4317–4340, https://doi.org/10.5194/amt-7-4317-2014, https://doi.org/10.5194/amt-7-4317-2014, 2014
S. Zeng, J. Riedi, C. R. Trepte, D. M. Winker, and Y.-X. Hu
Atmos. Chem. Phys., 14, 7125–7134, https://doi.org/10.5194/acp-14-7125-2014, https://doi.org/10.5194/acp-14-7125-2014, 2014
S. P. Burton, M. A. Vaughan, R. A. Ferrare, and C. A. Hostetler
Atmos. Meas. Tech., 7, 419–436, https://doi.org/10.5194/amt-7-419-2014, https://doi.org/10.5194/amt-7-419-2014, 2014
F. J. S. Lopes, E. Landulfo, and M. A. Vaughan
Atmos. Meas. Tech., 6, 3281–3299, https://doi.org/10.5194/amt-6-3281-2013, https://doi.org/10.5194/amt-6-3281-2013, 2013
S. Rodier, Y. Hu, and M. Vaughan
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4681-2013, https://doi.org/10.5194/tcd-7-4681-2013, 2013
Revised manuscript has not been submitted
S. P. Burton, R. A. Ferrare, M. A. Vaughan, A. H. Omar, R. R. Rogers, C. A. Hostetler, and J. W. Hair
Atmos. Meas. Tech., 6, 1397–1412, https://doi.org/10.5194/amt-6-1397-2013, https://doi.org/10.5194/amt-6-1397-2013, 2013
D. M. Winker, J. L. Tackett, B. J. Getzewich, Z. Liu, M. A. Vaughan, and R. R. Rogers
Atmos. Chem. Phys., 13, 3345–3361, https://doi.org/10.5194/acp-13-3345-2013, https://doi.org/10.5194/acp-13-3345-2013, 2013
P. J. Sheridan, E. Andrews, J. A. Ogren, J. L. Tackett, and D. M. Winker
Atmos. Chem. Phys., 12, 11695–11721, https://doi.org/10.5194/acp-12-11695-2012, https://doi.org/10.5194/acp-12-11695-2012, 2012
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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
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
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
Ground-based contrail observations: comparisons with flight telemetry and contrail model estimates
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
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
Retrieval of stratospheric aerosol extinction coefficients from OMPS-LP 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
Cloud top heights and aerosol layer properties from EarthCARE lidar observations: the A-CTH and A-ALD products
Influence of electromagnetic interference on the evaluation of lidar-derived aerosol properties from Ny-Ålesund, Svalbard
Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations
Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product
Evaluating the effects of columnar NO2 on the accuracy of aerosol optical properties retrievals
An explicit formulation for the retrieval of the overlap function in an elastic and Raman aerosol lidar
The classification of atmospheric hydrometeors and aerosols from the EarthCARE radar and lidar: the A-TC, C-TC and AC-TC products
SAGE III/ISS aerosol/cloud categorization and its impact on GloSSAC
Exploring geometrical stereoscopic aerosol top height retrieval from geostationary satellite imagery in East Asia
Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals
Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data
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.
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.
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.
Jade Low, Roger Teoh, Joel Ponsonby, Edward Gryspeerdt, Marc Shapiro, and Marc Stettler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1458, https://doi.org/10.5194/egusphere-2024-1458, 2024
Short summary
Short summary
The radiative forcing due to contrails is the same order of magnitude as aviation CO2 emissions yet has a higher uncertainty. Observations are vital to improve understanding of the contrail lifecycle, to improve model and to 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.
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.
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.
Alexei Rozanov, Christine Pohl, Carlo Arosio, Adam Bourassa, Klaus Bramstedt, Elizaveta Malinina, Landon Rieger, and John P. Burrows
EGUsphere, https://doi.org/10.5194/egusphere-2024-358, https://doi.org/10.5194/egusphere-2024-358, 2024
Short summary
Short summary
We developed a new algorithm to retrieve vertical distributions of the aerosol extinction coefficient in the stratosphere. The algorithm is applied to measurements of the scattered solar light form the space borne OMPS-LP (Ozone Mapping and Profiler Suite-Limb Profiler) instrument. The retrieval results are compared to the data from other space borne instruments and used to investigate the evolution of the aerosol plume after the eruption of the Hunga Tonga-Hunga Ha'apai volcano in January 2022.
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.
Ulla Wandinger, Moritz Haarig, Holger Baars, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 4031–4052, https://doi.org/10.5194/amt-16-4031-2023, https://doi.org/10.5194/amt-16-4031-2023, 2023
Short summary
Short summary
We introduce the algorithms that have been developed to derive cloud top height and aerosol layer products from observations with the Atmospheric Lidar (ATLID) onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE). The products provide information on the uppermost cloud and geometrical and optical properties of aerosol layers in an atmospheric column. They can be used individually but also serve as input for algorithms that combine observations with EarthCARE’s lidar and imager.
Tim Poguntke and Christoph Ritter
Atmos. Meas. Tech., 16, 4009–4014, https://doi.org/10.5194/amt-16-4009-2023, https://doi.org/10.5194/amt-16-4009-2023, 2023
Short summary
Short summary
In this work we analyze the impact of electromagnetic interference on an aerosol lidar. We found that aging transient recorders may produce a noise with fixed frequency that can be removed a posteriori.
Rei Kudo, Akiko Higurashi, Eiji Oikawa, Masahiro Fujikawa, Hiroshi Ishimoto, and Tomoaki Nishizawa
Atmos. Meas. Tech., 16, 3835–3863, https://doi.org/10.5194/amt-16-3835-2023, https://doi.org/10.5194/amt-16-3835-2023, 2023
Short summary
Short summary
A synergistic retrieval method of aerosol components (water-soluble, light-absorbing, dust, and sea salt particles) from CALIOP and MODIS observations was developed. The total global 3-D distributions and those for each component showed good consistency with the CALIOP and MODIS official products and previous studies. The shortwave direct radiative effects of each component at the top and bottom of the atmosphere and for the heating rate were also consistent with previous studies.
Nicole Docter, Rene Preusker, Florian Filipitsch, Lena Kritten, Franziska Schmidt, and Jürgen Fischer
Atmos. Meas. Tech., 16, 3437–3457, https://doi.org/10.5194/amt-16-3437-2023, https://doi.org/10.5194/amt-16-3437-2023, 2023
Short summary
Short summary
We describe the stand-alone retrieval algorithm used to derive aerosol properties relying on measurements of the Multi-Spectral Imager (MSI) aboard the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite. This aerosol data product will be available as M-AOT after the launch of EarthCARE. Additionally, we applied the algorithm to simulated EarthCARE MSI and Moderate Resolution Imaging Spectroradiometer (MODIS) data for prelaunch algorithm verification.
Theano Drosoglou, Ioannis-Panagiotis Raptis, Massimo Valeri, Stefano Casadio, Francesca Barnaba, Marcos Herreras-Giralda, Anton Lopatin, Oleg Dubovik, Gabriele Brizzi, Fabrizio Niro, Monica Campanelli, and Stelios Kazadzis
Atmos. Meas. Tech., 16, 2989–3014, https://doi.org/10.5194/amt-16-2989-2023, https://doi.org/10.5194/amt-16-2989-2023, 2023
Short summary
Short summary
Aerosol optical properties derived from sun photometers depend on the optical depth of trace gases absorbing solar radiation at specific spectral ranges. Various networks use satellite-based climatologies to account for this or neglect their effect. In this work, we evaluate the effect of NO2 absorption in aerosol retrievals from AERONET and SKYNET over two stations in Rome, Italy, with relatively high NO2 spatiotemporal variations, using NO2 data from the Pandora network and the TROPOMI sensor.
Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Michaël Sicard, Federico Dios, Cristina Gil-Díaz, Daniel Camilo Fortunato dos Santos Oliveira, and Francesc Rocadenbosch
Atmos. Meas. Tech., 16, 3015–3025, https://doi.org/10.5194/amt-16-3015-2023, https://doi.org/10.5194/amt-16-3015-2023, 2023
Short summary
Short summary
We derive an explicit (i.e., non-iterative) formula for the retrieval of the overlap function in an aerosol lidar with both elastic and Raman N2 and/or O2 channels used for independent measurements of aerosol backscatter and extinction coefficients. The formula requires only the measured, range-corrected elastic and the corresponding Raman signals, plus an assumed lidar ratio. We assess the influence of the lidar ratio error in the overlap function retrieval and present retrieval examples.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
Short summary
Short summary
The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Mahesh Kovilakam, Larry Thomason, and Travis Knepp
Atmos. Meas. Tech., 16, 2709–2731, https://doi.org/10.5194/amt-16-2709-2023, https://doi.org/10.5194/amt-16-2709-2023, 2023
Short summary
Short summary
The paper describes SAGE III/ISS aerosol/cloud categorization and its implications on Global Space-based Stratospheric Aerosol Climatology (GloSSAC). The presence of data from the SAGE type of multi-wavelength measurements is important in GloSSAC. The new aerosol/cloud categorization method described in this paper will help retain more measurements, particularly in the lower stratosphere during and following a volcanic event and other processes.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Huidong Yeo, and Sang-Woo Kim
Atmos. Meas. Tech., 16, 2673–2690, https://doi.org/10.5194/amt-16-2673-2023, https://doi.org/10.5194/amt-16-2673-2023, 2023
Short summary
Short summary
Aerosol height information is important when seeking an understanding of the vertical structure of the aerosol layer and long-range transport. In this study, a geometrical aerosol top height (ATH) retrieval using a parallax of two geostationary satellites is investigated. With sufficient longitudinal separation between the two satellites, a decent ATH product could be retrieved.
Jianglong Zhang, Jeffrey S. Reid, Steven D. Miller, Miguel Román, Zhuosen Wang, Robert J. D. Spurr, and Shawn Jaker
Atmos. Meas. Tech., 16, 2531–2546, https://doi.org/10.5194/amt-16-2531-2023, https://doi.org/10.5194/amt-16-2531-2023, 2023
Short summary
Short summary
We adapted the spherical harmonics discrete ordinate method 3-dimentional radiative transfer model (3-D RTM) and developed a nighttime 3-D RTM capability for simulating top-of-atmosphere radiances from artificial light sources for aerosol retrievals. Our study suggests that both aerosol optical depth and aerosol plume height can be effectively retrieved using nighttime observations over artificial light sources, through the newly developed radiative transfer modeling capability.
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.
Cited articles
Ansmann, A., Baars, H., Chudnovsky, A., Mattis, I., Veselovskii, I., Haarig, M., Seifert, P., Engelmann, R., and Wandinger, U.: Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21–22 August 2017, Atmos. Chem. Phys., 18, 11831–11845, https://doi.org/10.5194/acp-18-11831-2018, 2018.
Beyerle, G., Neuber, R., Schrems, O., Wittrock, F., and Knudsen, B.:
Multiwavelength lidar measurements of stratospheric aerosols above
Spitsbergen during winter 1992/93, Geophys. Res. Lett., 21, 57–60,
https://doi.org/10.1029/93GL02846, 1994.
Brock, C. A., Jonsson, H. H., Wilson, J. C., Dye, J. E., Baumgardner, D.,
Borrmann, S., Pitts, M. C., Osborn, M. T., Decoursey, R. J., and Woods, D.
C.: Relations between optical extinction, backscatter and aerosol surface
and volume in the stratosphere following the eruption of Mt. Pinatubo,
Geophys. Res. Lett., 20, 2555–2558 https://doi.org/10.1029/93GL01691, 1993.
Bourassa, A. E., Rieger, L. A., Lloyd, N. D., and Degenstein, D. A.: Odin-OSIRIS stratospheric aerosol data product and SAGE III intercomparison, Atmos. Chem. Phys., 12, 605–614, https://doi.org/10.5194/acp-12-605-2012, 2012.
Chazette, P., David, C., Lefrere, J., Godin, S., Pelon, J., and Megie, G.:
Comparative lidar study of the optical, geometrical and dynamical properties of stratospheric post-volcanic aerosols, following the eruptions of El Chichon and Mount Pinatubo, J. Geophys. Res., 100, 23195–23207,
https://doi.org/10.1029/95JD02268, 1995.
Chen, Z., Bhartia, P. K., Loughman, R., Colarco, P., and DeLand, M.: Improvement of stratospheric aerosol extinction retrieval from OMPS/LP using a new aerosol model, Atmos. Meas. Tech., 11, 6495–6509, https://doi.org/10.5194/amt-11-6495-2018, 2018.
Chu, W. P. and McCormick, M. P.: Inversion of stratospheric aerosol and
gaseous constituents from spacecraft solar extinction data in the 0.38–1.0 µm wavelength region, Appl. Optics, 18, 1404–1413, 1979.
Chu, W. P., McCormick, M. P., Lenoble, J., Brogniez, C., and Pruvost, P.:
SAGE II inversion algorithm, J. Geophys. Res., 94, 8339–8351,
https://doi.org/10.1029/JD094iD06p08339, 1989.
Cisewski, M., Zawodny, J., Gasbarre, J., Eckman, R., Topiwala, N.,
Rodriguez-Alverez, O., Cheek, D., and Hall, S.: The Stratospheric Aerosol and Gas Experiment (SAGE III) on the International Space Station (ISS) Mission, Proc. SPIE 9241, Sensors, Systems, and Next-Generation Satellites XVIII, 924107 (11 November 2014), Amsterdam, Netherlands, https://doi.org/10.1117/12.2073131, 2014.
Damadeo, R. P., Zawodny, J. M., Thomason, L. W., and Iyer, N.: SAGE version 7.0 algorithm: application to SAGE II, Atmos. Meas. Tech., 6, 3539–3561, https://doi.org/10.5194/amt-6-3539-2013, 2013.
de Laat, A. T. J., Stein Zweers, D. C., Boers, R.. and Tuinder, O. N. E.: A
solar escalator: Observational evidence of the self-lifting of smoke and
aerosols by absorption of solar radiation in the February 2009 Australian
Black Saturday plume, J. Geophys. Res., 117, D04204,
https://doi.org/10.1029/2011JD017016, 2012.
Deshler, T.: A review of global stratospheric aerosol: Measurements,
importance, life cycle, and local stratospheric aerosol, Atmos. Res., 90, 223–232, https://doi.org/10.1016/j.atmosres.2008.03.016, 2008.
Friberg, J., Martinsson, B. G., Andersson, S. M., and Sandvik, O. S.: Volcanic impact on the climate – the stratospheric aerosol load in the period 2006–2015, Atmos. Chem. Phys., 18, 11149–11169, https://doi.org/10.5194/acp-18-11149-2018, 2018.
Fromm, M., Lindsey, D. T., Servranckx, R., Yue, G., Trickl, T., Sica, R.,
Doucet, P., and Godin-Beekmann, S.: The untold story of pyrocumulonimbus,
B. Am. Meteorol. Soc., 91, 1193–1209, https://doi.org/10.1175/2010BAMS3004.1, 2010.
Gelaro, R., McCarty, W., Suarez, 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., Markova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M.,
Schubert, S. C., 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.
Glaccum, W., Lucke, R. L., Bevilacqua, R. M., Shettle, E. P., Hornstein, J.
S., Chen, D. T., Lumpe, J. D., Hrigman, S. S., Debrestian, J. J., Fromm, M.
D., Dalaudier, F., Chassefiere, F., Deniel, C., Randall, C. E., Rusch, D.
W., Olivero, J. J., Brogniez, C., Lenoble, J., and Kremer, R.: The polar
ozone and aerosol measurement instrument, J. Geophys. Res., 101,
14479–14487, 1996.
Glatthor, N., Höpfner, M., Semeniuk, K., Lupu, A., Palmer, P. I., McConnell, J. C., Kaminski, J. W., von Clarmann, T., Stiller, G. P., Funke, B., Kellmann, S., Linden, A., and Wiegele, A.: The Australian bushfires of February 2009: MIPAS observations and GEM-AQ model results, Atmos. Chem. Phys., 13, 1637–1658, https://doi.org/10.5194/acp-13-1637-2013, 2013.
Grams, G. and Fiocco, G.: Stratospheric aerosol layer during 1964 and 1965,
J. Geophys. Res., 72, 3523–3542, https://doi.org/10.1029/JZ072i014p03523, 1967.
Haarig, M., Ansmann, A., Baars, H., Jimenez, C., Veselovskii, I., Engelmann, R., and Althausen, D.: Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke, Atmos. Chem. Phys., 18, 11847–11861, https://doi.org/10.5194/acp-18-11847-2018, 2018.
Hofmann, D. J., Rosen, J. M., Pepin, T. J., and Pinninck, R. G.: Stratospheric aerosol measurements I: Time variations at northern midlatitudes, J. Atmos. Sci., 32, 1446–1456, 1975.
Hofmann, D., Barnes, J., O'Neill, M., Trudeau, M., and Neely, R.: Increase
in background stratospheric aerosol observed with lidar at Mauna Loa
observatory and Boulder, Colorado, Geophys. Res. Lett., 36, L15808,
https://doi.org/10.1029/2009GL039008, 2009.
Hoffmann, A., Ritter, C., Stock, M., Maturilli, M., Eckhardt, S., Herber, A., and Neuber, R.: Lidar measurements of the Kasatochi aerosol plume in August and September 2008 in Ny‐Ålesund, Spitsbergen, J. Geophys. Res., 115, D00L12, https://doi.org/10.1029/2009JD013039, 2010.
Hunt, W. H., Winker, D. M., Vaughan, M. A., Powell, K. A., Lucker, P. L., and Weimer, C.: CALIPSO Lidar description and performance assessment, J. Atmos. Ocean. Tech., 26, 1214–1228, https://doi.org/10.1175/2009JTECHA1223.1, 2009.
Jaeger, H. and Deshler, T.: Lidar backscatter to extinction, mass and area
conversions for stratos- pheric aerosols based on midlatitude balloonborne
size distribution measurements, Geophys. Res. Lett., 29, 1929,
https://doi.org/10.1029/2002GL015609, 2002.
Junge, C. E. and Manson, J. E.: Stratospheric aerosol studies, J. Geophys.
Res., 66, 2163–2182, https://doi.org/10.1029/JZ066i007p02163, 1961.
Kar, J., Bremer, H., Drummond, J. R., Rochon, Y. J., Jones, D. B. A.,
Nichitiu, F., Zou, J., Liu, J., Gille, J. C., Edwards, D. P., Deeter, M. N.,
Francis, G., Ziskin, D., and Warner, J.: Evidence of vertical transport of
carbon monoxide from Measurements of Pollution in the Troposphere, Geophys.
Res. Lett., 31, L23105, https://doi.org/10.1029/2004GL021128, 2004.
Kar, J., Vaughan, M. A., Lee, K.-P., Tackett, J. L., Avery, M. A., Garnier, A., Getzewich, B. J., Hunt, W. H., Josset, D., Liu, Z., Lucker, P. L., Magill, B., Omar, A. H., Pelon, J., Rogers, R. R., Toth, T. D., Trepte, C. R., Vernier, J.-P., Winker, D. M., and Young, S. A.: CALIPSO lidar calibration at 532 nm: version 4 nighttime algorithm, Atmos. Meas. Tech., 11, 1459–1479, https://doi.org/10.5194/amt-11-1459-2018, 2018a.
Kar, J., Vaughan, M. A., Tackett, J., Omar, A., Trepte, C. R. ,and Lucker, P.
L.: Constrained lidar ratios for volcanic ash and sulfate layers in the
stratosphere from CALIOP version 4.10 data, American Geophysical Union Fall Meeting, Washington, DC, 10–14 December 2018b.
Kent, G. S. and McCormick, M. P.: SAGE and SAM II measurements of global
stratospheric aerosol optical depth and mass loading, J. Geophys. Res., 89,
5303–5314, 1984.
Khaykin, S. M., Godin-Beekmann, S., Keckhut, P., Hauchecorne, A., Jumelet, J., Vernier, J.-P., Bourassa, A., Degenstein, D. A., Rieger, L. A., Bingen, C., Vanhellemont, F., Robert, C., DeLand, M., and Bhartia, P. K.: Variability and evolution of the midlatitude stratospheric aerosol budget from 22 years of ground-based lidar and satellite observations, Atmos. Chem. Phys., 17, 1829–1845, https://doi.org/10.5194/acp-17-1829-2017, 2017.
Khaykin, S. M., Godin-Beekmann, S., Hauchecorne, A., Pelon, J., Ravetta, F.,
and Keckhut, P.: Stratospheric smoke with unprecedentedly high backscatter
observed by lidars above southern France, Geophys. Res. Lett., 45, 1639–1646, https://doi.org/10.1002/2017GL076763, 2018.
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.
Kravitz, B., Robock, A., Bourassa, A., Deshler, T., Wu, D., Mattis, I., Finger, F., Hoffmann, A., Ritter, C., Bitar, L., Duck, T. J., and Barnes, J. E.: Simulation and observations of stratospheric aerosols from the 2009 Sarychev volcanic eruption, J. Geophys. Res., 116, D18211, https://doi.org/10.1029/2010JD015501, 2011.
Kremser, S., Thomason, L. W., von Hobe, M., Hermann, M., Deshler, T.,
Timmreck, C., Toohey, M., Stenke, A., Schwarz, J. P., Weigel, R.,
Fueglistaler, S., Prata, F. J., Vernier, J.-P., Schlager, H., Barnes, J. E.,
Antuna-Marrero, J.-C., Fairlie, D., Palm, M., Mahieu, E., Notholt, J., Rex,
M., Bingen, C., Vanhellemont, F., Bourassa, A., Plane, J. M. C., Kolcke, D.,
Carn, S. A., Clarisse, L., Trickl, T., Neely, R., James, A. D., Rieger, L.,
Wilson, J. C., and Meland, B.: Stratospheric aerosol-Observations, processes
and impact on climate, Rev. Geophys., 54, 278–335,
https://doi.org/10.1002/2015RG000511, 2016.
Liu, Z., Liu, D., Huang, J., Vaughan, M., Uno, I., Sugimoto, N., Kittaka, C., Trepte, C., Wang, Z., Hostetler, C., and Winker, D.: Airborne dust distributions over the Tibetan Plateau and surrounding areas derived from the first year of CALIPSO lidar observations, Atmos. Chem. Phys., 8, 5045–5060, https://doi.org/10.5194/acp-8-5045-2008, 2008.
Liu, Z., Vaughan, M., Winker, D., Kittaka, C., Getzewich, B., Kuehn, R.,
Omar, A., Powell, K., Trepte, C., and Hostetler, C.: The CALIPSO lidar cloud
and aerosol discrimination: Version 2 Algorithm and initial assessment of
performance, J. Atmos. Ocean. Tech., 26, 1198–1212,
https://doi.org/10.1175/2009JTECHA1229.1, 2009.
Liu, Z., Kar, J., Zeng, S., Tackett, J., Vaughan, M., Avery, M., Pelon, J., Getzewich, B., Lee, K.-P., Magill, B., Omar, A., Lucker, P., Trepte, C., and Winker, D.: Discriminating between clouds and aerosols in the CALIOP version 4.1 data products, Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, 2019.
Lopes, F. J. S., Silva, J. J., Antuña Marrero, J. C., Taha, G. and
Landulfo, E.: Synergetic Aerosol Layer Observation After the 2015 Calbuco
Volcanic Eruption Event, Remote Sensing, 11, 195,
https://doi.org/10.3390/rs11020195, 2019.
Lucke, R. L., Korwan, D. R., Bevilacqua, R. M., Hornstein, J. S., Shettle, E. P., Chen, D. T., Daehler, M., Lumpe, J. D., Fromm, M. D., Debrestian, D., Neff, B., Squire, M., König‐Langlo, G., and Davies, J.: The Polar Ozone and Aerosol Measurement (POAM III) instrument and early validation results, J. Geophys. Res., 104, 18785–18799, 1999.
Mauldin III, L. E., Zaun, N. H., McCormick, M. P., Guy, J. H., and Vaughan,
W. R.: Stratospheric aerosol and Gas Experiment II instruments: A functional description, Opt. Eng., 24, 307–312, https://doi.org/10.1117/12.7973473, 1985.
McCormick, M. P., Swissler, T. J., Fuller, W. H., Hunt, W. H., and Osborn, M. T.: Airborne and Ground-Based lidar measurements of the El Chichón
stratospheric aerosol from 90∘ N to 56∘ S, Geofis. Int., 23, 187–221, 1984.
McElroy, C. T., Nowlan, C. R., Drummond, J. R., Bernath, P. F., Barton, D.
V., Dufour, D. G., Midwinter, C., Hall, R. B., Ogyu, A., Ullberg, A.,
Wardle, D. I., Kar, J., Zou, J., Nichitiu, F., Boone, C. D., Walker, K. A.,
and Rowlands, N.: The ACE-MAESTRO instrument on SCISAT: Description,
performance, and preliminary results, Appl. Optics, 46, 4341–4356, 2007.
McGill, M. J., Vaughan, M. A., Trepte, C. R., Hart, W. D., Hlavka, D. L.,
Winker, D. M., and Kuehn, R.: Airborne validation of spatial properties
measured by the CALIPSO lidar, J. Geophys. Res., 112, D20201,
https://doi.org/10.1029/2007JD008768, 2007.
Noel, V., Chepfer, H., Hoareau, C., Reverdy, M., and Cesana, G.: Effects of
solar activity on noise in CALIOP profiles above the South Atlantic Anomaly,
Atmos. Meas. Tech., 7, 1597-1603, https://doi.org/10.5194/amt-7-1597-2014,
2014.
Northam, G. B., Rosen, J. M., Melfi, S. H., Pepin, T. J., McCormick, M. P.,
Hofmann, D. J., and Fuller, W. H.: Dustsonde and Lidar Measurements of
Stratospheric Aerosols: a Comparison, Appl. Optics, 13, 2416–2421, https://doi.org/10.1364/AO.13.002416, 1974.
Omar, A. H., Winker, D. M., Vaughan, M. A., Hu, Y., Trepte, C. R., Ferrare, R. A., Lee, K. P., Hostetler, C. A., Kittaka, C., Rogers, R. R., and Kuehn, R. E.: The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm, J. Atmos. Ocean. Tech., 26, 1994–2014, https://doi.org/10.1175/2009JTECHA1231.1, 2009.
O'Neill, N. T., Perro, C., Saha, A., Lesins G., Duck, T. J., Eloranta, E.
W., Nott, G. J., Hoffman, A., Karumudi, M. L., Ritter, C., Bourassa, A.,
Abboud, I., Carn, S. A., and Savastiouk, V.: Properties of Sarychev sulphate
aerosols over the Arctic, J. Geophys. Res., 117, D04203,
https://doi.org/10.1029/2011JD016838, 2012.
Penning de Vries, M. J. M., Dörner, S., Puḳīte, J., Hörmann, C., Fromm, M. D., and Wagner, T.: Characterisation of a stratospheric sulfate plume from the Nabro volcano using a combination of passive satellite measurements in nadir and limb geometry, Atmos. Chem. Phys., 14, 8149–8163, https://doi.org/10.5194/acp-14-8149-2014, 2014.
Peterson, D. A., Campbell, J. R., Hyer, E. J., Fromm, M. D., Kablick III, G.
P., Cossuth, J. H., and DeLand, M. T.: Wildfire-driven thunderstorms cause a
volcano-like stratospheric injection of smoke, npj Climate and Atmospheric
Science, 1, 30, https://doi.org/10.1038/s41612-018-0039-3, 2018.
Pitts, M. C., Thomason, L. W., Poole, L. R., and Winker, D. M.: Characterization of Polar Stratospheric Clouds with spaceborne lidar: CALIPSO and the 2006 Antarctic season, Atmos. Chem. Phys., 7, 5207–5228, https://doi.org/10.5194/acp-7-5207-2007, 2007.
Pitts, M. C., Poole, L. R., and Thomason, L. W.: CALIPSO polar stratospheric cloud observations: second-generation detection algorithm and composition discrimination, Atmos. Chem. Phys., 9, 7577–7589, https://doi.org/10.5194/acp-9-7577-2009, 2009.
Powell, K. A.: Development of the CALIPSO Lidar Simulator, M.Sc. thesis,
Department of Applied Science, The College of William and Mary, 228 pp.,
2005.
Powell, K. A., Hostetler, C. A., Liu, Z., Vaughan, M. A., Kuehn, R. A.,
Hunt, W. H., Lee, K.-P., Trepte, C. R., Rogers, R. R., Young, S. A., and
Winker, D. M.: CALIPSO Lidar calibration algorithms. Part I: Nighttime 532 nm parallel channel and 532 nm perpendicular channel, J. Atmos. Ocean.
Tech., 26, 2015–2033, https://doi.org/10.1175/2009JTECHA1242.1, 2009.
Prata, A. T., Young, S. A., Siems, S. T., and Manton, M. J.: Lidar ratios of stratospheric volcanic ash and sulfate aerosols retrieved from CALIOP measurements, Atmos. Chem. Phys., 17, 8599–8618, https://doi.org/10.5194/acp-17-8599-2017, 2017.
Ridley, D. A., Solomon, S., Barnes, J. E., Burlakov, V. D., Deshler, T.,
Dolgii, S. I., Herber, A. B., Nagai, T., Neely, R. R., Nevzorov, A. V.,
Ritter, C., Sakai, T., Santer, B. D., Sato, M., Schmidt, A., Uchino, O., and
Vernier, J. P.: Total volcanic stratospheric aerosol optical depths and
implications for global climate change, Geophys. Res. Lett., 41, 7763–7769,
https://doi.org/10.1002/2014GL061541, 2014.
Robock, A.: Volcanic eruptions and climate, Rev. Geophys., 38, 191–219,
https://doi.org/10.1029/1998RG000054, 2000.
SAGE III Science Team: SAGE III Level 2 Data, NASA Atmospheric Science Data Center (ASDC), Hampton, VA, USA, https://doi.org/10.5067/ISS/SAGEIII/SOLAR_HDF4_L2-V5.1, 2013.
Sakai, T., Uchino, O., Nagai, N., Liley, B., Morino, I., and Fujimoto, T.:
Long-term variation of stratospheric aerosols observed with lidars over
Tsukuba, Japan, from 1982 and Lauder, New Zealand, from 1992 to 2015, J.
Geophys. Res.-Atmos., 121, 10283–10293, https://doi.org/10.1002/2016JD025132, 2016.
Sassen, K., Wang, Z., and Liu, D.: Cirrus clouds and deep convection in the
tropics: Insighs from CALIPSO and CloudSat, J. Geophys. Res., 114, D00H06,
https://doi.org/10.1029/2009JD011916, 2009.
Solomon, S., Daniel, J. S., Neely III, R. R., Vernier, J. P., Dutton, E. G.,
and Thomason, L. W.: The persistently variable “background”
stratospheric aerosol layer and global climate change, Science, 333, 866–870, https://doi.org/10.1126/science.1206027, 2011.
Thomason, L. W. and Peter, T.: Assessment of stratospheric aerosol
properties (ASAP), SPARC report no 4, WCRP-124,WMO/TD-No. 1295, 2006.
Thomason, L. W. and Vernier, J.-P.: Improved SAGE II cloud/aerosol categorization and observations of the Asian tropopause aerosol layer: 1989–2005, Atmos. Chem. Phys., 13, 4605–4616, https://doi.org/10.5194/acp-13-4605-2013, 2013.
Thomason, L. W., Pitts, M. C., and Winker, D. M.: CALIPSO observations of stratospheric aerosols: a preliminary assessment, Atmos. Chem. Phys., 7, 5283–5290, https://doi.org/10.5194/acp-7-5283-2007, 2007.
Thomason, L. W., Burton, S. P., Luo, B.-P., and Peter, T.: SAGE II measurements of stratospheric aerosol properties at non-volcanic levels, Atmos. Chem. Phys., 8, 983–995, https://doi.org/10.5194/acp-8-983-2008, 2008.
Thomason, L. W., Moore, J. R., Pitts, M. C., Zawodny, J. M., and Chiou, E. W.: An evaluation of the SAGE III version 4 aerosol extinction coefficient and water vapor data products, Atmos. Chem. Phys., 10, 2159–2173, https://doi.org/10.5194/acp-10-2159-2010, 2010.
Thomason, L. W., Ernest, N., Millán, L., Rieger, L., Bourassa, A., Vernier, J.-P., Manney, G., Luo, B., Arfeuille, F., and Peter, T.: A global space-based stratospheric aerosol climatology: 1979–2016, Earth Syst. Sci. Data, 10, 469–492, https://doi.org/10.5194/essd-10-469-2018,
2018.
Trepte, C. R. and Hitchman, M. H.: Tropical stratospheric circulation deduced from satellite aerosol data, Nature, 355, 626–628, https://doi.org/10.1038/355626a0, 1992.
Trickl, T., Giehl, H., Jäger, H., and Vogelmann, H.: 35 yr of stratospheric aerosol measurements at Garmisch-Partenkirchen: from Fuego to Eyjafjallajökull, and beyond, Atmos. Chem. Phys., 13, 5205–5225, https://doi.org/10.5194/acp-13-5205-2013, 2013.
Turco, R. P., Whitten, R. C., Toon, O. B., Pollack, J. B., and Hamill, P.:
OCS, stratospheric aerosols and climate, Nature, 283, 283–285,
https://doi.org/10.1038/283283a0, 1980.
Vaughan, M. A., Powell, K. A., Kuehn, R. E., Young, S. A., Winker, D. M.,
Hostetler, C. A., Hunt, W. H., Liu, Z., McGill, M. J., and Getzewitch, B.
J.: Fully automated detection of cloud and aerosol layers in the CALIPSO
lidar measurements, J. Atmos. Ocean. Tech., 26, 2034–2050,
https://doi.org/10.1175/2009JTECHA1228.1, 2009.
Vaughan, M. A., Pitts, M., Trepte, C., Winker, D., Detweiler, P., Garnier,
A., Getzewich, B., Hunt, W., Lambeth, J., Lee, K.-P., Lucker, P., Murray,
T., Rodier, S., Tremas, T., Bazureau, A., and Pelon, J.: Cloud-Aerosol LIDAR
Infrared Pathfinder Satellite Observations (CALIPSO) data management system
data products catalog, Release 4.10, NASA Langley Research Center Document
PC-SCI-503, Hampton, Va, USA, 2016.
Vernier, J. P., Pommereau, J. P., Garnier, A., Pelon, J., Larsen, N.,
Nielsen, J., Christiansen, T., Cairo, F., Thomason, L. W., Leblanc, T., and
McDermid, I. S.: Tropical stratospheric aerosol layer from CALIPSO lidar
observations, J. Geophys. Res., 114, D00H10, https://doi.org/10.1029/2009JD011946, 2009.
Vernier, J.-P., Fairlie, T. D., Murray, J. J., Tupper, A., Trepte, C.,
Winker, D., Pelon, J., Garnier, A., Jumelet, J., Pavolonis, M., Omar, A. H.,
and Powell, K. A.: An advanced system to monitor the 3D structure of diffuse
volcanic ash clouds, J. Appl. Meteorol. Clim., 52, 2125–2138, https://doi.org/10.1175/JAMC-D-12-0279.1, 2013.
Vernier, J.-P., Fairlie, T. D., Deshler, T., Natarajan, M., Knepp, T.,
Foster, K., Weinhold, F. G., Bedka, K. M., Thomason, L., and Trepte, C.: In
situ and space based observations of the Kelud volcanic plume: The
persistence of ash in the lower stratosphere, J. Geophys. Res., 121,
11104–11118, https://doi.org/10.1002/2016JD025344, 2016.
Winker, D. M., Pelon, J., Coakley, Jr., J. A., Ackerman, S. A., Charlson, R. J., Colarco, P. R., Flamant, P., Fu, Q., Hoff, R., Kittaka, C., Kubar, T. L., Le Treut, H., McCormick, M. P., Mégie, G., Poole, L., Powell, K., Trepte, C., Vaughan, M. A., and Wielicki, B. A.: The CALIPSO Mission: A Global 3D View Of Aerosols And Clouds, B. Am. Meteorol. Soc., 91, 1211–1229,
https://doi.org/10.1175/2010BAMS3009.1, 2010.
Winker, D. M., Liu, Z., Omar, A., Tackett, J., and Fairlie, D.: CALIOP
observations of the transport of ash from the Eyjafjallajökull volcano
in April 2010, J. Geophys. Res., 117, D00U15,
https://doi.org/10.1029/2011JD016499, 2012.
Winker, D. M., Tackett, J. L., Getzewich, B. J., Liu, Z., Vaughan, M. A., and Rogers, R. R.: The global 3-D distribution of tropospheric aerosols as characterized by CALIOP, Atmos. Chem. Phys., 13, 3345–3361, https://doi.org/10.5194/acp-13-3345-2013, 2013.
Young, S. A. and Vaughan, M. A.: The retrieval of profiles of particulate
extinction from Cloud Aerosol Lidar Infrared Pathfinder Satellite
Observations (CALIPSO) data: Algorithm description, J. Atmos. Ocean. Tech.,
26, 1105–1119, https://doi.org/10.1175/2008JTECHA1221.1, 2009.
Young, S. A., Vaughan, M. A., Kuehn, R. E., and Winker, D. M.: The retrieval
of profiles of particulate extinction from Cloud–Aerosol Lidar Infrared
Pathfinder Satellite Observations (CALIPSO) data: Uncertainty and error
sensitivity analyses. J. Atmos. Ocean. Tech., 30, 395–428,
https://doi.org/10.1175/JTECH-D-12-00046.1, 2013.
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, 2016.
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.
Short summary
This work describes the science algorithm for the recently released CALIPSO level 3 stratospheric aerosol product. It is shown that the retrieved extinction profiles capture the major stratospheric perturbations over the last decade resulting from volcanic eruptions, pyroCb smoke events, and signatures of stratospheric dynamics. An initial assessment is also provided by intercomparison with the latest aerosol retrievals from the SAGE III instrument aboard the International Space Station.
This work describes the science algorithm for the recently released CALIPSO level 3...