Articles | Volume 18, issue 4
https://doi.org/10.5194/amt-18-981-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-981-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Feb 2025
Research article |
| 27 Feb 2025
| 27 Feb 2025
Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
Steven Platnick
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
G. Thomas Arnold
SSAI, Lanham, Maryland 20706, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
Nandana Amarasinghe
SSAI, Lanham, Maryland 20706, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
Daniel Miller
GESTAR-II, University of Maryland-Baltimore County, Baltimore, Maryland 21250, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
Jennifer Small-Griswold
Department of Atmospheric Sciences, University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA
Mikael Witte
Department of Meteorology, Naval Postgraduate School, Monterey, California 93943, USA
Brian Cairns
NASA Goddard Institute for Space Studies, New York, New York 10025, USA
Siddhant Gupta
Argonne National Laboratory, Lemont, Illinois 60439, USA
Greg McFarquhar
School of Meteorology, University of Oklahoma, Norman, Oklahoma 73072, USA
Joseph O'Brien
Argonne National Laboratory, Lemont, Illinois 60439, USA
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EGUsphere, https://doi.org/10.5194/egusphere-2025-1403, https://doi.org/10.5194/egusphere-2025-1403, 2025
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Aerosols perturb the radiation balance of the Earth-atmosphere system. To reduce the uncertainty in quantifying present-day climate change, we combine two satellite sensors and a model to assess the aerosol effects on radiation in all-sky conditions. Satellite-based and coincident aircraft measurements of aerosol radiative effects agree well over the Southeast Atlantic. This constitutes a crucial first evaluation before we apply our method to more years and regions of the world.
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Abundant aerosols are present above low-level liquid clouds over the southeastern Atlantic during late austral spring. The model simulation differences in the proportion of aerosol residing in the planetary boundary layer and in the free troposphere can greatly affect the regional aerosol radiative effects. This study examines the aerosol loading and fractional aerosol loading in the free troposphere among various models and evaluates them against measurements from the NASA ORACLES campaign.
Qing Yue, Eric J. Fetzer, Likun Wang, Brian H. Kahn, Nadia Smith, John M. Blaisdell, Kerry G. Meyer, Mathias Schreier, Bjorn Lambrigtsen, and Irina Tkatcheva
Atmos. Meas. Tech., 15, 2099–2123, https://doi.org/10.5194/amt-15-2099-2022, https://doi.org/10.5194/amt-15-2099-2022, 2022
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Galina Wind, Arlindo M. da Silva, Kerry G. Meyer, Steven Platnick, and Peter M. Norris
Geosci. Model Dev., 15, 1–14, https://doi.org/10.5194/gmd-15-1-2022, https://doi.org/10.5194/gmd-15-1-2022, 2022
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This is the third paper in series about the Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In this paper we use MCARS to create a set of constraints that might be used to assimilate a new above-cloud aerosol retrieval product developed for the MODIS instrument into a general circulation model. We executed the above-cloud aerosol retrieval over a series of synthetic MODIS granules and found the product to be of excellent quality.
Sarah J. Doherty, Pablo E. Saide, Paquita Zuidema, Yohei Shinozuka, Gonzalo A. Ferrada, Hamish Gordon, Marc Mallet, Kerry Meyer, David Painemal, Steven G. Howell, Steffen Freitag, Amie Dobracki, James R. Podolske, Sharon P. Burton, Richard A. Ferrare, Calvin Howes, Pierre Nabat, Gregory R. Carmichael, Arlindo da Silva, Kristina Pistone, Ian Chang, Lan Gao, Robert Wood, and Jens Redemann
Atmos. Chem. Phys., 22, 1–46, https://doi.org/10.5194/acp-22-1-2022, https://doi.org/10.5194/acp-22-1-2022, 2022
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Between July and October, biomass burning smoke is advected over the southeastern Atlantic Ocean, leading to climate forcing. Model calculations of forcing by this plume vary significantly in both magnitude and sign. This paper compares aerosol and cloud properties observed during three NASA ORACLES field campaigns to the same in four models. It quantifies modeled biases in properties key to aerosol direct radiative forcing and evaluates how these biases propagate to biases in forcing.
Tianle Yuan, Hua Song, Robert Wood, Johannes Mohrmann, Kerry Meyer, Lazaros Oreopoulos, and Steven Platnick
Atmos. Meas. Tech., 13, 6989–6997, https://doi.org/10.5194/amt-13-6989-2020, https://doi.org/10.5194/amt-13-6989-2020, 2020
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We use deep transfer learning techniques to classify satellite cloud images into different morphology types. It achieves the state-of-the-art results and can automatically process a large amount of satellite data. The algorithm will help low-cloud researchers to better understand their mesoscale organizations.
Marc Mallet, Fabien Solmon, Pierre Nabat, Nellie Elguindi, Fabien Waquet, Dominique Bouniol, Andrew Mark Sayer, Kerry Meyer, Romain Roehrig, Martine Michou, Paquita Zuidema, Cyrille Flamant, Jens Redemann, and Paola Formenti
Atmos. Chem. Phys., 20, 13191–13216, https://doi.org/10.5194/acp-20-13191-2020, https://doi.org/10.5194/acp-20-13191-2020, 2020
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This paper presents numerical simulations using two regional climate models to study the impact of biomass fire plumes from central Africa on the radiative balance of this region. The results indicate that biomass fires can either warm the regional climate when they are located above low clouds or cool it when they are located above land. They can also alter sea and land surface temperatures by decreasing solar radiation at the surface. Finally, they can also modify the atmospheric dynamics.
Benjamin Marchant, Steven Platnick, Kerry Meyer, and Galina Wind
Atmos. Meas. Tech., 13, 3263–3275, https://doi.org/10.5194/amt-13-3263-2020, https://doi.org/10.5194/amt-13-3263-2020, 2020
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Multilayer cloud scenes (such as an ice cloud overlapping a liquid cloud) are common in the Earth's atmosphere and are quite difficult to detect from space. The detection of multilayer clouds is important to better understand how they interact with the light and their impact on the climate. So, for the instrument MODIS an algorithm has been developed to detect those clouds, and this paper presents an evaluation of this algorithm by comparing it with
other instruments.
Chenxi Wang, Steven Platnick, Kerry Meyer, Zhibo Zhang, and Yaping Zhou
Atmos. Meas. Tech., 13, 2257–2277, https://doi.org/10.5194/amt-13-2257-2020, https://doi.org/10.5194/amt-13-2257-2020, 2020
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A machine-learning (ML)-based approach that can be used for cloud mask and phase detection is developed. An all-day model that uses infrared (IR) observations and a daytime model that uses shortwave and IR observations from a passive instrument are trained separately for different surface types. The training datasets are selected by using reference pixel types from collocated space lidar. The ML approach is validated carefully and the overall performance is better than traditional methods.
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Marc Mallet, Pierre Nabat, Paquita Zuidema, Jens Redemann, Andrew Mark Sayer, Martin Stengel, Sebastian Schmidt, Sabrina Cochrane, Sharon Burton, Richard Ferrare, Kerry Meyer, Pablo Saide, Hiren Jethva, Omar Torres, Robert Wood, David Saint Martin, Romain Roehrig, Christina Hsu, and Paola Formenti
Atmos. Chem. Phys., 19, 4963–4990, https://doi.org/10.5194/acp-19-4963-2019, https://doi.org/10.5194/acp-19-4963-2019, 2019
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Yuekui Yang, Kerry Meyer, Galina Wind, Yaping Zhou, Alexander Marshak, Steven Platnick, Qilong Min, Anthony B. Davis, Joanna Joiner, Alexander Vasilkov, David Duda, and Wenying Su
Atmos. Meas. Tech., 12, 2019–2031, https://doi.org/10.5194/amt-12-2019-2019, https://doi.org/10.5194/amt-12-2019-2019, 2019
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Thomas Fauchez, Steven Platnick, Kerry Meyer, Céline Cornet, Frédéric Szczap, and Tamás Várnai
Atmos. Chem. Phys., 17, 8489–8508, https://doi.org/10.5194/acp-17-8489-2017, https://doi.org/10.5194/acp-17-8489-2017, 2017
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John Rausch, Kerry Meyer, Ralf Bennartz, and Steven Platnick
Atmos. Meas. Tech., 10, 2105–2116, https://doi.org/10.5194/amt-10-2105-2017, https://doi.org/10.5194/amt-10-2105-2017, 2017
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This paper documents the observed differences in the aggregated (Level-3) cloud droplet effective radius and droplet number concentration estimates inferred from the Aqua–MODIS cloud product collections 5.1 and 6 for warm oceanic cloud scenes over the year 2008. We note significant differences in effective radius and droplet concentration between the two products and discuss the algorithmic and calibration changes which may contribute to observed results.
Kerry Meyer, Yuekui Yang, and Steven Platnick
Atmos. Meas. Tech., 9, 1785–1797, https://doi.org/10.5194/amt-9-1785-2016, https://doi.org/10.5194/amt-9-1785-2016, 2016
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This paper presents the expected uncertainties of a single-channel cloud opacity retrieval technique and a temperature-based cloud phase approach in support of the Deep Space Climate Observatory (DSCOVR) mission; DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations. Results show that, for ice clouds, retrieval errors are minimal (< 2 %), while for liquid clouds the error is limited to within 10 %, although for thin clouds the error can be higher.
Kerry Meyer, Steven Platnick, G. Thomas Arnold, Robert E. Holz, Paolo Veglio, John Yorks, and Chenxi Wang
Atmos. Meas. Tech., 9, 1743–1753, https://doi.org/10.5194/amt-9-1743-2016, https://doi.org/10.5194/amt-9-1743-2016, 2016
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Cirrus cloud optical and microphysical properties are retrieved from remote sensing solar reflectance measurements at two narrow wavelength channels within the broader water vapor absorption band at 1.88 µm. Results from this technique compare well with other solar reflectance, IR, and lidar-based retrievals. This approach is complementary to traditional remote sensing techniques and can extend cloud retrieval capabilities for thin cirrus clouds.
Zhibo Zhang, Kerry Meyer, Hongbin Yu, Steven Platnick, Peter Colarco, Zhaoyan Liu, and Lazaros Oreopoulos
Atmos. Chem. Phys., 16, 2877–2900, https://doi.org/10.5194/acp-16-2877-2016, https://doi.org/10.5194/acp-16-2877-2016, 2016
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The frequency of occurrence and shortwave direct radiative effects (DRE) of above-cloud aerosols (ACAs) over global oceans are investigated using 8 years of collocated CALIOP and MODIS observations. We estimated that ACAs have a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m−2 (range of −0.03 to 0.06 W m−2) at TOA. The DREs at surface and within atmosphere are −0.15 W m−2 (range of −0.09 to −0.21 W m−2), and 0.17 W m−2 (range of 0.11 to 0.24 W m−2), respectively.
T. Fauchez, P. Dubuisson, C. Cornet, F. Szczap, A. Garnier, J. Pelon, and K. Meyer
Atmos. Meas. Tech., 8, 633–647, https://doi.org/10.5194/amt-8-633-2015, https://doi.org/10.5194/amt-8-633-2015, 2015
Meloë S. F. Kacenelenbogen, Ralph Kuehn, Nandana Amarasinghe, Kerry Meyer, Edward Nowottnick, Mark Vaughan, Hong Chen, Sebastian Schmidt, Richard Ferrare, John Hair, Robert Levy, Hongbin Yu, Paquita Zuidema, Robert Holz, and Willem Marais
EGUsphere, https://doi.org/10.5194/egusphere-2025-1403, https://doi.org/10.5194/egusphere-2025-1403, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Aerosols perturb the radiation balance of the Earth-atmosphere system. To reduce the uncertainty in quantifying present-day climate change, we combine two satellite sensors and a model to assess the aerosol effects on radiation in all-sky conditions. Satellite-based and coincident aircraft measurements of aerosol radiative effects agree well over the Southeast Atlantic. This constitutes a crucial first evaluation before we apply our method to more years and regions of the world.
Travis Hahn, Hershel Weiner, Calvin Brooks, Jie Xi Li, Siddhant Gupta, and Dié Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1328, https://doi.org/10.5194/egusphere-2025-1328, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Understanding how clouds evolve is important for improving weather predictions, but existing tools for tracking cloud changes are complex and difficult to compare. To address this, we developed the Community Cloud Model Evaluation Toolkit (CoCoMET) that makes it easier to analyze clouds in both models and observations. By simplifying data processing, standardizing results, and introducing new analysis features, CoCoMET helps researchers better evaluate cloud behavior and improve models.
Scarlet R. Passer, Mikael K. Witte, and Patrick Y. Chuang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-177, https://doi.org/10.5194/amt-2024-177, 2024
Revised manuscript accepted for AMT
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One important property of a cloud is the concentration of cloud drops. This property is relevant to how the cloud interacts with sunlight, and how easily the cloud forms precipitation. Measuring this property from satellite is one important source of data, but it does require making some assumptions. This study evaluates the accuracy of satellite-derived drop concentration by comparing to aircraft measurements.
Florian Tornow, Ann Fridlind, George Tselioudis, Brian Cairns, Andrew Ackerman, Seethala Chellappan, David Painemal, Paquita Zuidema, Christiane Voigt, Simon Kirschler, and Armin Sorooshian
EGUsphere, https://doi.org/10.5194/egusphere-2024-3462, https://doi.org/10.5194/egusphere-2024-3462, 2024
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The recent NASA campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) performed 71 tandem flights in mid-latitude marine cold-air outbreaks off the US Eastern seaboard. We provide meteorological and cloud transition stage context, allowing us to identify days that are most suitable for Lagrangian modeling and analysis. Surveyed cloud properties show signatures of cloud microphysical processes, such as cloud-top entrainment and secondary ice formation.
Jeonggyu Kim, Sungmin Park, Greg M. McFarquhar, Anthony J. Baran, Joo Wan Cha, Kyoungmi Lee, Seoung Soo Lee, Chang Hoon Jung, Kyo-Sun Sunny Lim, and Junshik Um
Atmos. Chem. Phys., 24, 12707–12726, https://doi.org/10.5194/acp-24-12707-2024, https://doi.org/10.5194/acp-24-12707-2024, 2024
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We developed idealized models to represent the shapes of ice particles found in deep convective clouds and calculated their single-scattering properties. By comparing these results with in situ measurements, we discovered that a mixture of shape models matches in situ measurements more closely than single-form models or aggregate models. This finding has important implications for enhancing the simulation of single-scattering properties of ice crystals in deep convective clouds.
Sanja Dmitrovic, Joseph S. Schlosser, Ryan Bennett, Brian Cairns, Gao Chen, Glenn S. Diskin, Richard A. Ferrare, Johnathan W. Hair, Michael A. Jones, Jeffrey S. Reid, Taylor J. Shingler, Michael A. Shook, Armin Sorooshian, Kenneth L. Thornhill, Luke D. Ziemba, and Snorre Stamnes
EGUsphere, https://doi.org/10.5194/egusphere-2024-3088, https://doi.org/10.5194/egusphere-2024-3088, 2024
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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This study focuses on aerosol particles, which critically influence the atmosphere by scattering and absorbing light. To understand these interactions, airborne field campaigns deploy instruments that can measure these particles’ directly or indirectly via remote sensing. We introduce the In Situ Aerosol Retrieval Algorithm (ISARA) to ensure consistency between aerosol measurements and show that the two data sets generally align, with some deviation caused by the presence of larger particles.
Alexei Korolev, Zhipeng Qu, Jason Milbrandt, Ivan Heckman, Mélissa Cholette, Mengistu Wolde, Cuong Nguyen, Greg M. McFarquhar, Paul Lawson, and Ann M. Fridlind
Atmos. Chem. Phys., 24, 11849–11881, https://doi.org/10.5194/acp-24-11849-2024, https://doi.org/10.5194/acp-24-11849-2024, 2024
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The phenomenon of high ice water content (HIWC) occurs in mesoscale convective systems (MCSs) when a large number of small ice particles with typical sizes of a few hundred micrometers is found at high altitudes. It was found that secondary ice production in the vicinity of the melting layer plays a key role in the formation and maintenance of HIWC. This study presents a conceptual model of the formation of HIWC in tropical MCSs based on in situ observations and numerical simulation.
Brent A. McBride, J. Vanderlei Martins, J. Dominik Cieslak, Roberto Fernandez-Borda, Anin Puthukkudy, Xiaoguang Xu, Noah Sienkiewicz, Brian Cairns, and Henrique M. J. Barbosa
Atmos. Meas. Tech., 17, 5709–5729, https://doi.org/10.5194/amt-17-5709-2024, https://doi.org/10.5194/amt-17-5709-2024, 2024
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The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is a new Earth-observing instrument that provides highly accurate measurements of the atmosphere and surface. Using a physics-based calibration technique, we show that AirHARP achieves high measurement accuracy in laboratory and field environments and exceeds a benchmark accuracy requirement for modern aerosol and cloud climate observations. Therefore, the HARP design is highly attractive for upcoming NASA climate missions.
Dié Wang, Roni Kobrosly, Tao Zhang, Tamanna Subba, Susan van den Heever, Siddhant Gupta, and Michael Jensen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2436, https://doi.org/10.5194/egusphere-2024-2436, 2024
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We use a new method to understand how tiny particles in the air, called aerosols, affect rain clouds in the Houston-Galveston area. Aerosols generally do not make these clouds grow much taller, with an average height increase of about 1 km under certain conditions. However, their effects on rainfall strength and cloud expansion are less certain. Clouds influenced by sea breezes show a stronger aerosol impact, possibly due to unaccounted factors like vertical winds in near-surface layers.
Ewan Crosbie, Luke D. Ziemba, Michael A. Shook, Taylor Shingler, Johnathan W. Hair, Armin Sorooshian, Richard A. Ferrare, Brian Cairns, Yonghoon Choi, Joshua DiGangi, Glenn S. Diskin, Chris Hostetler, Simon Kirschler, Richard H. Moore, David Painemal, Claire Robinson, Shane T. Seaman, K. Lee Thornhill, Christiane Voigt, and Edward Winstead
Atmos. Chem. Phys., 24, 6123–6152, https://doi.org/10.5194/acp-24-6123-2024, https://doi.org/10.5194/acp-24-6123-2024, 2024
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Marine clouds are found to clump together in regions or lines, readily discernible from satellite images of the ocean. While clustering is also a feature of deep storm clouds, we focus on smaller cloud systems associated with fair weather and brief localized showers. Two aircraft sampled the region around these shallow systems: one incorporated measurements taken within, adjacent to, and below the clouds, while the other provided a survey from above using remote sensing techniques.
Michie Vianca De Vera, Larry Di Girolamo, Guangyu Zhao, Robert M. Rauber, Stephen W. Nesbitt, and Greg M. McFarquhar
Atmos. Chem. Phys., 24, 5603–5623, https://doi.org/10.5194/acp-24-5603-2024, https://doi.org/10.5194/acp-24-5603-2024, 2024
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Tropical oceanic low clouds remain a dominant source of uncertainty in cloud feedback in climate models due to their macrophysical properties (fraction, size, height, shape, distribution) being misrepresented. High-resolution satellite imagery over the Philippine oceans is used here to characterize cumulus macrophysical properties and their relationship to meteorological variables. Such information can act as a benchmark for cloud models and can improve low-cloud generation in climate models.
Leong Wai Siu, Joseph S. Schlosser, David Painemal, Brian Cairns, Marta A. Fenn, Richard A. Ferrare, Johnathan W. Hair, Chris A. Hostetler, Longlei Li, Mary M. Kleb, Amy Jo Scarino, Taylor J. Shingler, Armin Sorooshian, Snorre A. Stamnes, and Xubin Zeng
Atmos. Meas. Tech., 17, 2739–2759, https://doi.org/10.5194/amt-17-2739-2024, https://doi.org/10.5194/amt-17-2739-2024, 2024
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An unprecedented 3-year aerosol dataset was collected from a recent NASA field campaign over the western North Atlantic Ocean, which offers a special opportunity to evaluate two state-of-the-art remote sensing instruments, one lidar and the other polarimeter, on the same aircraft. Special attention has been paid to validate aerosol optical depth data and their uncertainties when no reference dataset is available. Physical reasons for the disagreement between two instruments are discussed.
Mark A. Smalley, Mikael K. Witte, Jong-Hoon Jeong, and Maria J. Chinita
EGUsphere, https://doi.org/10.5194/egusphere-2024-1098, https://doi.org/10.5194/egusphere-2024-1098, 2024
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Evaporation of rain leads to cooler and sometimes moister surface conditions (cold pools), which can lead to further convection that alters convective, cloud, precipitation, and radiation properties. We introduce a new method of measuring cold pools, which accounts for the seasonal and daily changes in dry air turbulence in which the cold pool signatures are embedded. We then apply it to 8 years of observations in the north midlatitude Atlantic Ocean.
Siddhant Gupta, Dié Wang, Scott E. Giangrande, Thiago S. Biscaro, and Michael P. Jensen
Atmos. Chem. Phys., 24, 4487–4510, https://doi.org/10.5194/acp-24-4487-2024, https://doi.org/10.5194/acp-24-4487-2024, 2024
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We examine the lifecycle of isolated deep convective clouds (DCCs) in the Amazon rainforest. Weather radar echoes from the DCCs are tracked to evaluate their lifecycle. The DCC size and intensity increase, reach a peak, and then decrease over the DCC lifetime. Vertical profiles of air motion and mass transport from different seasons are examined to understand the transport of energy and momentum within DCC cores and to address the deficiencies in simulating DCCs using weather and climate models.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
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This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Neranga K. Hannadige, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, P. Jeremy Werdell, Kirk Knobelspiesse, and Brian Cairns
Atmos. Meas. Tech., 16, 5749–5770, https://doi.org/10.5194/amt-16-5749-2023, https://doi.org/10.5194/amt-16-5749-2023, 2023
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We evaluated the impact of three ocean optical models with different numbers of free parameters on the performance of an aerosol and ocean color remote sensing algorithm using the multi-angle polarimeter (MAP) measurements. It was demonstrated that the three- and seven-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the one-parameter model has smaller retrieval uncertainty over open water.
Matthew D. Lebsock and Mikael Witte
Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, https://doi.org/10.5194/acp-23-14293-2023, 2023
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This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.
Calvin Howes, Pablo E. Saide, Hugh Coe, Amie Dobracki, Steffen Freitag, Jim M. Haywood, Steven G. Howell, Siddhant Gupta, Janek Uin, Mary Kacarab, Chongai Kuang, L. Ruby Leung, Athanasios Nenes, Greg M. McFarquhar, James Podolske, Jens Redemann, Arthur J. Sedlacek, Kenneth L. Thornhill, Jenny P. S. Wong, Robert Wood, Huihui Wu, Yang Zhang, Jianhao Zhang, and Paquita Zuidema
Atmos. Chem. Phys., 23, 13911–13940, https://doi.org/10.5194/acp-23-13911-2023, https://doi.org/10.5194/acp-23-13911-2023, 2023
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To better understand smoke properties and its interactions with clouds, we compare the WRF-CAM5 model with observations from ORACLES, CLARIFY, and LASIC field campaigns in the southeastern Atlantic in August 2017. The model transports and mixes smoke well but does not fully capture some important processes. These include smoke chemical and physical aging over 4–12 days, smoke removal by rain, sulfate particle formation, aerosol activation into cloud droplets, and boundary layer turbulence.
Rose Marie Miller, Robert M. Rauber, Larry Di Girolamo, Matthew Rilloraza, Dongwei Fu, Greg M. McFarquhar, Stephen W. Nesbitt, Luke D. Ziemba, Sarah Woods, and Kenneth Lee Thornhill
Atmos. Chem. Phys., 23, 8959–8977, https://doi.org/10.5194/acp-23-8959-2023, https://doi.org/10.5194/acp-23-8959-2023, 2023
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The influence of human-produced aerosols on clouds remains one of the uncertainties in radiative forcing of Earth’s climate. Measurements of aerosol chemistry from sources around the Philippines illustrate the linkage between aerosol chemical composition and cloud droplet characteristics. Differences in aerosol chemical composition in the marine layer from biomass burning, industrial, ship-produced, and marine aerosols are shown to impact cloud microphysical structure just above cloud base.
Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data, 15, 3419–3472, https://doi.org/10.5194/essd-15-3419-2023, https://doi.org/10.5194/essd-15-3419-2023, 2023
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The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions. HU-25 Falcon and King Air aircraft conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Nikolas Ovaskainen, Pietari Skyttä, Nicklas Nordbäck, and Jon Engström
Solid Earth, 14, 603–624, https://doi.org/10.5194/se-14-603-2023, https://doi.org/10.5194/se-14-603-2023, 2023
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We studied bedrock fracturing at Åland Islands from bedrock outcrops,
digital elevation models and geophysics using multiple scales of observation.
Using the results we can compare properties of the fractures of different sizes
to find similarities and differences; e.g. we found that glacial erosion has a
probable effect on the study of larger bedrock structures. Furthermore, we
collected data from 100 to 500 m long fractures, which have previously
proved to be difficult to sample.
Robert Pincus, Paul A. Hubanks, Steven Platnick, Kerry Meyer, Robert E. Holz, Denis Botambekov, and Casey J. Wall
Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, https://doi.org/10.5194/essd-15-2483-2023, 2023
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This paper describes a new global dataset of cloud properties observed by a specific satellite program created to facilitate comparison with a matching observational proxy used in climate models. Statistics are accumulated over daily and monthly timescales on an equal-angle grid. Statistics include cloud detection, cloud-top pressure, and cloud optical properties. Joint histograms of several variable pairs are also available.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Brian Cairns, Xiaoguang Xu, and J. Vanderlei Martins
Atmos. Meas. Tech., 16, 2067–2087, https://doi.org/10.5194/amt-16-2067-2023, https://doi.org/10.5194/amt-16-2067-2023, 2023
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Multi-angle polarimetric measurements have been shown to greatly improve the remote sensing capability of aerosols and help atmospheric correction for ocean color retrievals. However, the uncertainty correlations among different measurement angles have not been well characterized. In this work, we provided a practical framework to evaluate the impact of the angular uncertainty correlation in retrieval results and a method to directly estimate correlation strength from retrieval residuals.
Emily D. Lenhardt, Lan Gao, Jens Redemann, Feng Xu, Sharon P. Burton, Brian Cairns, Ian Chang, Richard A. Ferrare, Chris A. Hostetler, Pablo E. Saide, Calvin Howes, Yohei Shinozuka, Snorre Stamnes, Mary Kacarab, Amie Dobracki, Jenny Wong, Steffen Freitag, and Athanasios Nenes
Atmos. Meas. Tech., 16, 2037–2054, https://doi.org/10.5194/amt-16-2037-2023, https://doi.org/10.5194/amt-16-2037-2023, 2023
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Small atmospheric particles, such as smoke from wildfires or pollutants from human activities, impact cloud properties, and clouds have a strong influence on climate. To better understand the distributions of these particles, we develop relationships to derive their concentrations from remote sensing measurements from an instrument called a lidar. Our method is reliable for smoke particles, and similar steps can be taken to develop relationships for other particle types.
Ian Chang, Lan Gao, Connor J. Flynn, Yohei Shinozuka, Sarah J. Doherty, Michael S. Diamond, Karla M. Longo, Gonzalo A. Ferrada, Gregory R. Carmichael, Patricia Castellanos, Arlindo M. da Silva, Pablo E. Saide, Calvin Howes, Zhixin Xue, Marc Mallet, Ravi Govindaraju, Qiaoqiao Wang, Yafang Cheng, Yan Feng, Sharon P. Burton, Richard A. Ferrare, Samuel E. LeBlanc, Meloë S. Kacenelenbogen, Kristina Pistone, Michal Segal-Rozenhaimer, Kerry G. Meyer, Ju-Mee Ryoo, Leonhard Pfister, Adeyemi A. Adebiyi, Robert Wood, Paquita Zuidema, Sundar A. Christopher, and Jens Redemann
Atmos. Chem. Phys., 23, 4283–4309, https://doi.org/10.5194/acp-23-4283-2023, https://doi.org/10.5194/acp-23-4283-2023, 2023
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Abundant aerosols are present above low-level liquid clouds over the southeastern Atlantic during late austral spring. The model simulation differences in the proportion of aerosol residing in the planetary boundary layer and in the free troposphere can greatly affect the regional aerosol radiative effects. This study examines the aerosol loading and fractional aerosol loading in the free troposphere among various models and evaluates them against measurements from the NASA ORACLES campaign.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
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Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Ruhi S. Humphries, Melita D. Keywood, Jason P. Ward, James Harnwell, Simon P. Alexander, Andrew R. Klekociuk, Keiichiro Hara, Ian M. McRobert, Alain Protat, Joel Alroe, Luke T. Cravigan, Branka Miljevic, Zoran D. Ristovski, Robyn Schofield, Stephen R. Wilson, Connor J. Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Greg M. McFarquhar, Scott D. Chambers, Alastair G. Williams, and Alan D. Griffiths
Atmos. Chem. Phys., 23, 3749–3777, https://doi.org/10.5194/acp-23-3749-2023, https://doi.org/10.5194/acp-23-3749-2023, 2023
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Observations of aerosols in pristine regions are rare but are vital to constraining the natural baseline from which climate simulations are calculated. Here we present recent seasonal observations of aerosols from the Southern Ocean and contrast them with measurements from Antarctica, Australia and regionally relevant voyages. Strong seasonal cycles persist, but striking differences occur at different latitudes. This study highlights the need for more long-term observations in remote regions.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
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This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba
Atmos. Meas. Tech., 15, 7411–7434, https://doi.org/10.5194/amt-15-7411-2022, https://doi.org/10.5194/amt-15-7411-2022, 2022
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The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.
Paul A. Barrett, Steven J. Abel, Hugh Coe, Ian Crawford, Amie Dobracki, James Haywood, Steve Howell, Anthony Jones, Justin Langridge, Greg M. McFarquhar, Graeme J. Nott, Hannah Price, Jens Redemann, Yohei Shinozuka, Kate Szpek, Jonathan W. Taylor, Robert Wood, Huihui Wu, Paquita Zuidema, Stéphane Bauguitte, Ryan Bennett, Keith Bower, Hong Chen, Sabrina Cochrane, Michael Cotterell, Nicholas Davies, David Delene, Connor Flynn, Andrew Freedman, Steffen Freitag, Siddhant Gupta, David Noone, Timothy B. Onasch, James Podolske, Michael R. Poellot, Sebastian Schmidt, Stephen Springston, Arthur J. Sedlacek III, Jamie Trembath, Alan Vance, Maria A. Zawadowicz, and Jianhao Zhang
Atmos. Meas. Tech., 15, 6329–6371, https://doi.org/10.5194/amt-15-6329-2022, https://doi.org/10.5194/amt-15-6329-2022, 2022
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To better understand weather and climate, it is vital to go into the field and collect observations. Often measurements take place in isolation, but here we compared data from two aircraft and one ground-based site. This was done in order to understand how well measurements made on one platform compared to those made on another. Whilst this is easy to do in a controlled laboratory setting, it is more challenging in the real world, and so these comparisons are as valuable as they are rare.
Siddhant Gupta, Greg M. McFarquhar, Joseph R. O'Brien, Michael R. Poellot, David J. Delene, Ian Chang, Lan Gao, Feng Xu, and Jens Redemann
Atmos. Chem. Phys., 22, 12923–12943, https://doi.org/10.5194/acp-22-12923-2022, https://doi.org/10.5194/acp-22-12923-2022, 2022
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The ability of NASA’s Terra and Aqua satellites to retrieve cloud properties and estimate the changes in cloud properties due to aerosol–cloud interactions (ACI) was examined. There was good agreement between satellite retrievals and in situ measurements over the southeast Atlantic Ocean. This suggests that, combined with information on aerosol properties, satellite retrievals of cloud properties can be used to study ACI over larger domains and longer timescales in the absence of in situ data.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Yongjie Huang, Greg M. McFarquhar, Hugh Morrison, Mengistu Wolde, and Cuong Nguyen
Atmos. Chem. Phys., 22, 12287–12310, https://doi.org/10.5194/acp-22-12287-2022, https://doi.org/10.5194/acp-22-12287-2022, 2022
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Secondary ice production (SIP) is an important physical phenomenon that results in an increase in the cloud ice particle concentration and can have a significant impact on the evolution of clouds. Here, idealized simulations of a tropical convective system were conducted. Agreement between the simulations and observations highlights the impacts of SIP on the maintenance of tropical convection in nature and the importance of including the modelling of SIP in numerical weather prediction models.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
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In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Edward Gryspeerdt, Daniel T. McCoy, Ewan Crosbie, Richard H. Moore, Graeme J. Nott, David Painemal, Jennifer Small-Griswold, Armin Sorooshian, and Luke Ziemba
Atmos. Meas. Tech., 15, 3875–3892, https://doi.org/10.5194/amt-15-3875-2022, https://doi.org/10.5194/amt-15-3875-2022, 2022
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Droplet number concentration is a key property of clouds, influencing a variety of cloud processes. It is also used for estimating the cloud response to aerosols. The satellite retrieval depends on a number of assumptions – different sampling strategies are used to select cases where these assumptions are most likely to hold. Here we investigate the impact of these strategies on the agreement with in situ data, the droplet number climatology and estimates of the indirect radiative forcing.
Dongwei Fu, Larry Di Girolamo, Robert M. Rauber, Greg M. McFarquhar, Stephen W. Nesbitt, Jesse Loveridge, Yulan Hong, Bastiaan van Diedenhoven, Brian Cairns, Mikhail D. Alexandrov, Paul Lawson, Sarah Woods, Simone Tanelli, Sebastian Schmidt, Chris Hostetler, and Amy Jo Scarino
Atmos. Chem. Phys., 22, 8259–8285, https://doi.org/10.5194/acp-22-8259-2022, https://doi.org/10.5194/acp-22-8259-2022, 2022
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Satellite-retrieved cloud microphysics are widely used in climate research because of their central role in water and energy cycles. Here, we provide the first detailed investigation of retrieved cloud drop sizes from in situ and various satellite and airborne remote sensing techniques applied to real cumulus cloud fields. We conclude that the most widely used passive remote sensing method employed in climate research produces high biases of 6–8 µm (60 %–80 %) caused by 3-D radiative effects.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
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We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Qing Yue, Eric J. Fetzer, Likun Wang, Brian H. Kahn, Nadia Smith, John M. Blaisdell, Kerry G. Meyer, Mathias Schreier, Bjorn Lambrigtsen, and Irina Tkatcheva
Atmos. Meas. Tech., 15, 2099–2123, https://doi.org/10.5194/amt-15-2099-2022, https://doi.org/10.5194/amt-15-2099-2022, 2022
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The self-consistency and continuity of cloud retrievals from infrared sounders and imagers aboard Aqua and SNPP (Suomi National Polar-orbiting Partnership) are examined at the pixel scale. Cloud products are found to be consistent with each other. Differences between sounder products are mainly due to cloud clearing and the treatment of clouds in scenes with unsuccessful atmospheric retrievals. The impact of algorithm and instrument differences is clearly seen in the imager cloud retrievals.
Siddhant Gupta, Greg M. McFarquhar, Joseph R. O'Brien, Michael R. Poellot, David J. Delene, Rose M. Miller, and Jennifer D. Small Griswold
Atmos. Chem. Phys., 22, 2769–2793, https://doi.org/10.5194/acp-22-2769-2022, https://doi.org/10.5194/acp-22-2769-2022, 2022
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This study evaluates the impact of biomass burning aerosols on precipitation in marine stratocumulus clouds using observations from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign over the Southeast Atlantic. Instances of contact and separation between aerosol and cloud layers show polluted clouds have a lower precipitation rate and a lower precipitation susceptibility. This information will help improve cloud representation in Earth system models.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Ming Xue, Hugh Morrison, Jason Milbrandt, Alexei V. Korolev, Yachao Hu, Zhipeng Qu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, and Ivan Heckman
Atmos. Chem. Phys., 22, 2365–2384, https://doi.org/10.5194/acp-22-2365-2022, https://doi.org/10.5194/acp-22-2365-2022, 2022
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Numerous small ice crystals in tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. Previous numerical simulations failed to reproduce this phenomenon and hypothesized that key microphysical processes are still lacking in current models to realistically simulate the phenomenon. This study uses numerical experiments to confirm the dominant role of secondary ice production in the formation of these large numbers of small ice crystals.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
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Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Galina Wind, Arlindo M. da Silva, Kerry G. Meyer, Steven Platnick, and Peter M. Norris
Geosci. Model Dev., 15, 1–14, https://doi.org/10.5194/gmd-15-1-2022, https://doi.org/10.5194/gmd-15-1-2022, 2022
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This is the third paper in series about the Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In this paper we use MCARS to create a set of constraints that might be used to assimilate a new above-cloud aerosol retrieval product developed for the MODIS instrument into a general circulation model. We executed the above-cloud aerosol retrieval over a series of synthetic MODIS granules and found the product to be of excellent quality.
Sarah J. Doherty, Pablo E. Saide, Paquita Zuidema, Yohei Shinozuka, Gonzalo A. Ferrada, Hamish Gordon, Marc Mallet, Kerry Meyer, David Painemal, Steven G. Howell, Steffen Freitag, Amie Dobracki, James R. Podolske, Sharon P. Burton, Richard A. Ferrare, Calvin Howes, Pierre Nabat, Gregory R. Carmichael, Arlindo da Silva, Kristina Pistone, Ian Chang, Lan Gao, Robert Wood, and Jens Redemann
Atmos. Chem. Phys., 22, 1–46, https://doi.org/10.5194/acp-22-1-2022, https://doi.org/10.5194/acp-22-1-2022, 2022
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Between July and October, biomass burning smoke is advected over the southeastern Atlantic Ocean, leading to climate forcing. Model calculations of forcing by this plume vary significantly in both magnitude and sign. This paper compares aerosol and cloud properties observed during three NASA ORACLES field campaigns to the same in four models. It quantifies modeled biases in properties key to aerosol direct radiative forcing and evaluates how these biases propagate to biases in forcing.
David Painemal, Douglas Spangenberg, William L. Smith Jr., Patrick Minnis, Brian Cairns, Richard H. Moore, Ewan Crosbie, Claire Robinson, Kenneth L. Thornhill, Edward L. Winstead, and Luke Ziemba
Atmos. Meas. Tech., 14, 6633–6646, https://doi.org/10.5194/amt-14-6633-2021, https://doi.org/10.5194/amt-14-6633-2021, 2021
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Cloud properties derived from satellite sensors are critical for the global monitoring of climate. This study evaluates satellite-based cloud properties over the North Atlantic using airborne data collected during NAAMES. Satellite observations of droplet size and cloud optical depth tend to compare well with NAAMES data. The analysis indicates that the satellite pixel resolution and the specific viewing geometry need to be taken into account in research applications.
Rose M. Miller, Greg M. McFarquhar, Robert M. Rauber, Joseph R. O'Brien, Siddhant Gupta, Michal Segal-Rozenhaimer, Amie N. Dobracki, Arthur J. Sedlacek, Sharon P. Burton, Steven G. Howell, Steffen Freitag, and Caroline Dang
Atmos. Chem. Phys., 21, 14815–14831, https://doi.org/10.5194/acp-21-14815-2021, https://doi.org/10.5194/acp-21-14815-2021, 2021
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A large stratocumulus cloud deck resides off the west coast of central Africa. Biomass burning in Africa produces a large plume of aerosol that is carried by the wind over this stratocumulus cloud deck. This paper shows that particles with sizes from 0.01 to 1 mm reside within this plume. Past studies have shown that biomass burning produces such particles, but this is the first study to show that they can be transported westward, over long distances, to the Atlantic stratocumulus cloud deck.
Ruhi S. Humphries, Melita D. Keywood, Sean Gribben, Ian M. McRobert, Jason P. Ward, Paul Selleck, Sally Taylor, James Harnwell, Connor Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Alain Protat, Simon P. Alexander, and Greg McFarquhar
Atmos. Chem. Phys., 21, 12757–12782, https://doi.org/10.5194/acp-21-12757-2021, https://doi.org/10.5194/acp-21-12757-2021, 2021
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The Southern Ocean region is one of the most pristine in the world and serves as an important proxy for the pre-industrial atmosphere. Improving our understanding of the natural processes in this region is likely to result in the largest reductions in the uncertainty of climate and earth system models. In this paper we present a statistical summary of the latitudinal gradient of aerosol and cloud condensation nuclei concentrations obtained from five voyages spanning the Southern Ocean.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
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Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Xuguang Wang, Hugh Morrison, Alexander Ryzhkov, Yachao Hu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, Jason Milbrandt, Alexei V. Korolev, and Ivan Heckman
Atmos. Chem. Phys., 21, 6919–6944, https://doi.org/10.5194/acp-21-6919-2021, https://doi.org/10.5194/acp-21-6919-2021, 2021
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Numerous small ice crystals in the tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. This study evaluated the numerical models against the airborne observations and investigated the potential cloud processes that could lead to the production of these large numbers of small ice crystals. It is found that key microphysical processes are still lacking or misrepresented in current numerical models to realistically simulate the phenomenon.
Andrew M. Dzambo, Tristan L'Ecuyer, Kenneth Sinclair, Bastiaan van Diedenhoven, Siddhant Gupta, Greg McFarquhar, Joseph R. O'Brien, Brian Cairns, Andrzej P. Wasilewski, and Mikhail Alexandrov
Atmos. Chem. Phys., 21, 5513–5532, https://doi.org/10.5194/acp-21-5513-2021, https://doi.org/10.5194/acp-21-5513-2021, 2021
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This work highlights a new algorithm using data collected from the 2016–2018 NASA ORACLES field campaign. This algorithm synthesizes cloud and rain measurements to attain estimates of cloud and precipitation properties over the southeast Atlantic Ocean. Estimates produced by this algorithm compare well against in situ estimates. Increased rain fractions and rain rates are found in regions of atmospheric instability. This dataset can be used to explore aerosol–cloud–precipitation interactions.
Siddhant Gupta, Greg M. McFarquhar, Joseph R. O'Brien, David J. Delene, Michael R. Poellot, Amie Dobracki, James R. Podolske, Jens Redemann, Samuel E. LeBlanc, Michal Segal-Rozenhaimer, and Kristina Pistone
Atmos. Chem. Phys., 21, 4615–4635, https://doi.org/10.5194/acp-21-4615-2021, https://doi.org/10.5194/acp-21-4615-2021, 2021
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Observations from the 2016 NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign examine how biomass burning aerosols from southern Africa affect marine stratocumulus cloud decks over the Southeast Atlantic. Instances of contact and separation between aerosols and clouds are examined to quantify the impact of aerosol mixing into cloud top on cloud drop numbers and sizes. This information is needed for improving Earth system models and satellite retrievals.
Fanny Peers, Peter Francis, Steven J. Abel, Paul A. Barrett, Keith N. Bower, Michael I. Cotterell, Ian Crawford, Nicholas W. Davies, Cathryn Fox, Stuart Fox, Justin M. Langridge, Kerry G. Meyer, Steven E. Platnick, Kate Szpek, and Jim M. Haywood
Atmos. Chem. Phys., 21, 3235–3254, https://doi.org/10.5194/acp-21-3235-2021, https://doi.org/10.5194/acp-21-3235-2021, 2021
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Satellite observations at high temporal resolution are a valuable asset to monitor the transport of biomass burning plumes and the cloud diurnal cycle in the South Atlantic, but they need to be validated. Cloud and above-cloud aerosol properties retrieved from SEVIRI are compared against MODIS and measurements from the CLARIFY-2017 campaign. While some systematic differences are observed between SEVIRI and MODIS, the overall agreement in the cloud and aerosol properties is very satisfactory.
Zhibo Zhang, Qianqian Song, David B. Mechem, Vincent E. Larson, Jian Wang, Yangang Liu, Mikael K. Witte, Xiquan Dong, and Peng Wu
Atmos. Chem. Phys., 21, 3103–3121, https://doi.org/10.5194/acp-21-3103-2021, https://doi.org/10.5194/acp-21-3103-2021, 2021
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This study investigates the small-scale variations and covariations of cloud microphysical properties, namely, cloud liquid water content and cloud droplet number concentration, in marine boundary layer clouds based on in situ observation from the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign. We discuss the dependence of cloud variations on vertical location in cloud and the implications for warm-rain simulations in the global climate models.
Dillon S. Dodson and Jennifer D. Small Griswold
Atmos. Chem. Phys., 21, 1937–1961, https://doi.org/10.5194/acp-21-1937-2021, https://doi.org/10.5194/acp-21-1937-2021, 2021
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The results here reinforce findings from previous in situ studies of the marine boundary layer. It is found that turbulence is maximized in the middle of the stratocumulus layer from latent heating effects. Precipitation acts to increase turbulence in the sub-cloud layer, while acting to stabilize the entire boundary layer after the evaporation of precipitation in the sub-cloud has stopped. A negative correlation is present between the boundary layer height and turbulence.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
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Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Tianle Yuan, Hua Song, Robert Wood, Johannes Mohrmann, Kerry Meyer, Lazaros Oreopoulos, and Steven Platnick
Atmos. Meas. Tech., 13, 6989–6997, https://doi.org/10.5194/amt-13-6989-2020, https://doi.org/10.5194/amt-13-6989-2020, 2020
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We use deep transfer learning techniques to classify satellite cloud images into different morphology types. It achieves the state-of-the-art results and can automatically process a large amount of satellite data. The algorithm will help low-cloud researchers to better understand their mesoscale organizations.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Marc Mallet, Fabien Solmon, Pierre Nabat, Nellie Elguindi, Fabien Waquet, Dominique Bouniol, Andrew Mark Sayer, Kerry Meyer, Romain Roehrig, Martine Michou, Paquita Zuidema, Cyrille Flamant, Jens Redemann, and Paola Formenti
Atmos. Chem. Phys., 20, 13191–13216, https://doi.org/10.5194/acp-20-13191-2020, https://doi.org/10.5194/acp-20-13191-2020, 2020
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This paper presents numerical simulations using two regional climate models to study the impact of biomass fire plumes from central Africa on the radiative balance of this region. The results indicate that biomass fires can either warm the regional climate when they are located above low clouds or cool it when they are located above land. They can also alter sea and land surface temperatures by decreasing solar radiation at the surface. Finally, they can also modify the atmospheric dynamics.
Adeyemi A. Adebiyi, Paquita Zuidema, Ian Chang, Sharon P. Burton, and Brian Cairns
Atmos. Chem. Phys., 20, 11025–11043, https://doi.org/10.5194/acp-20-11025-2020, https://doi.org/10.5194/acp-20-11025-2020, 2020
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Over the southeast Atlantic, interactions between the low-level clouds and the overlying smoke aerosols have previously been highlighted, but no study has yet focused on the presence of the mid-level clouds that complicate the aerosol–cloud interactions. Here we show that these optically thin super-cooled mid-level clouds are relatively common, and they frequently occur at the top of the smoke layer between August and October with significant radiative impacts on the low-level clouds.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
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The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956, https://doi.org/10.5194/amt-13-3939-2020, https://doi.org/10.5194/amt-13-3939-2020, 2020
Daniel J. Miller, Michal Segal-Rozenhaimer, Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Mikhail Alexandrov, Bastiaan van Diedenhoven, and Andrzej Wasilewski
Atmos. Meas. Tech., 13, 3447–3470, https://doi.org/10.5194/amt-13-3447-2020, https://doi.org/10.5194/amt-13-3447-2020, 2020
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A neural network (NN) is developed and used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. The NN is applied to research scanning polarimeter (RSP) observations obtained during the ORACLES field campaign and compared to other co-located remote sensing retrievals of cloud effective radius and optical thickness. A NN approach can advance more complex iterative search retrieval algorithms by providing a quick initial guess.
Benjamin Marchant, Steven Platnick, Kerry Meyer, and Galina Wind
Atmos. Meas. Tech., 13, 3263–3275, https://doi.org/10.5194/amt-13-3263-2020, https://doi.org/10.5194/amt-13-3263-2020, 2020
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Multilayer cloud scenes (such as an ice cloud overlapping a liquid cloud) are common in the Earth's atmosphere and are quite difficult to detect from space. The detection of multilayer clouds is important to better understand how they interact with the light and their impact on the climate. So, for the instrument MODIS an algorithm has been developed to detect those clouds, and this paper presents an evaluation of this algorithm by comparing it with
other instruments.
Chenxi Wang, Steven Platnick, Kerry Meyer, Zhibo Zhang, and Yaping Zhou
Atmos. Meas. Tech., 13, 2257–2277, https://doi.org/10.5194/amt-13-2257-2020, https://doi.org/10.5194/amt-13-2257-2020, 2020
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A machine-learning (ML)-based approach that can be used for cloud mask and phase detection is developed. An all-day model that uses infrared (IR) observations and a daytime model that uses shortwave and IR observations from a passive instrument are trained separately for different surface types. The training datasets are selected by using reference pixel types from collocated space lidar. The ML approach is validated carefully and the overall performance is better than traditional methods.
Samuel E. LeBlanc, Jens Redemann, Connor Flynn, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal-Rosenheimer, Yohei Shinozuka, Stephen Dunagan, Robert P. Dahlgren, Kerry Meyer, James Podolske, Steven G. Howell, Steffen Freitag, Jennifer Small-Griswold, Brent Holben, Michael Diamond, Robert Wood, Paola Formenti, Stuart Piketh, Gillian Maggs-Kölling, Monja Gerber, and Andreas Namwoonde
Atmos. Chem. Phys., 20, 1565–1590, https://doi.org/10.5194/acp-20-1565-2020, https://doi.org/10.5194/acp-20-1565-2020, 2020
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The southeast Atlantic during August–October experiences layers of smoke from biomass burning over marine stratocumulus clouds. Here we present the light attenuation of the smoke and its dependence in the spatial, vertical, and spectral domain through direct measurements from an airborne platform during September 2016. From our observations of this climatically important smoke, we found an average aerosol optical depth of 0.32 at 500 nm, slightly lower than comparative satellite measurements.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
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In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Steven Platnick, Kerry Meyer, Rich Ferrare, Sharon Burton, Chris Hostetler, Steven Howell, Steffen Freitag, Amie Dobracki, and Sarah Doherty
Atmos. Meas. Tech., 12, 6505–6528, https://doi.org/10.5194/amt-12-6505-2019, https://doi.org/10.5194/amt-12-6505-2019, 2019
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For two cases from the NASA ORACLES experiments, we retrieve aerosol and cloud properties and calculate a direct aerosol radiative effect (DARE). We investigate the relationship between DARE and the cloud albedo by specifying the albedo for which DARE transitions from a cooling to warming radiative effect. Our new aerosol retrieval algorithm is successful despite complexities associated with scenes that contain aerosols above clouds and decreases the uncertainty on retrieved aerosol parameters.
Fanny Peers, Peter Francis, Cathryn Fox, Steven J. Abel, Kate Szpek, Michael I. Cotterell, Nicholas W. Davies, Justin M. Langridge, Kerry G. Meyer, Steven E. Platnick, and Jim M. Haywood
Atmos. Chem. Phys., 19, 9595–9611, https://doi.org/10.5194/acp-19-9595-2019, https://doi.org/10.5194/acp-19-9595-2019, 2019
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The measurements from the geostationary satellite MSG/SEVIRI are used to retrieve the cloud and above-cloud aerosol properties over the South Atlantic. The technique relies on the spectral contrast and the magnitude of the signal in the visible to shortwave infrared region as well as the atmospheric correction based on forecasted water vapour profiles. The sensitivity analysis and the stability of the retrieval over time show great potential of the high-temporal-resolution observations.
Kristina Pistone, Jens Redemann, Sarah Doherty, Paquita Zuidema, Sharon Burton, Brian Cairns, Sabrina Cochrane, Richard Ferrare, Connor Flynn, Steffen Freitag, Steven G. Howell, Meloë Kacenelenbogen, Samuel LeBlanc, Xu Liu, K. Sebastian Schmidt, Arthur J. Sedlacek III, Michal Segal-Rozenhaimer, Yohei Shinozuka, Snorre Stamnes, Bastiaan van Diedenhoven, Gerard Van Harten, and Feng Xu
Atmos. Chem. Phys., 19, 9181–9208, https://doi.org/10.5194/acp-19-9181-2019, https://doi.org/10.5194/acp-19-9181-2019, 2019
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Understanding how smoke particles interact with sunlight is important in calculating their effects on climate, since some smoke is more scattering (cooling) and some is more absorbing (heating). Knowing this proportion is important for both satellite observations and climate models. We measured smoke properties in a recent aircraft-based field campaign off the west coast of Africa and present a comparison of these properties as measured using the six different, independent techniques available.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Yongxiang Hu, Kirk Knobelspiesse, P. Jeremy Werdell, Amir Ibrahim, Brian Cairns, and Alison Chase
Atmos. Meas. Tech., 12, 3921–3941, https://doi.org/10.5194/amt-12-3921-2019, https://doi.org/10.5194/amt-12-3921-2019, 2019
Dillon S. Dodson and Jennifer D. Small Griswold
Atmos. Chem. Phys., 19, 7297–7317, https://doi.org/10.5194/acp-19-7297-2019, https://doi.org/10.5194/acp-19-7297-2019, 2019
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This work looks at how the amount of aerosols contained in cloud affects the spatial orientation of the cloud droplets. Droplet orientation is important because it can lead to changes in the amount of time it takes precipitation to form. The results show that the aerosol amount does not have any effect on the droplet orientation. It is found however that the droplets are spaced closer together (there is increased droplet clustering) at cloud edge and top, as compared to center and bottom.
Marc Mallet, Pierre Nabat, Paquita Zuidema, Jens Redemann, Andrew Mark Sayer, Martin Stengel, Sebastian Schmidt, Sabrina Cochrane, Sharon Burton, Richard Ferrare, Kerry Meyer, Pablo Saide, Hiren Jethva, Omar Torres, Robert Wood, David Saint Martin, Romain Roehrig, Christina Hsu, and Paola Formenti
Atmos. Chem. Phys., 19, 4963–4990, https://doi.org/10.5194/acp-19-4963-2019, https://doi.org/10.5194/acp-19-4963-2019, 2019
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The model is able to represent LWP but not the LCF. AOD is consistent over the continent but also over ocean (ACAOD). Differences are observed in SSA due to the absence of internal mixing in ALADIN-Climate. A significant regional gradient of the forcing at TOA is observed. An intense positive forcing is simulated over Gabon. Results highlight the significant effect of enhanced moisture on BBA extinction. The surface dimming modifies the energy budget.
Yuekui Yang, Kerry Meyer, Galina Wind, Yaping Zhou, Alexander Marshak, Steven Platnick, Qilong Min, Anthony B. Davis, Joanna Joiner, Alexander Vasilkov, David Duda, and Wenying Su
Atmos. Meas. Tech., 12, 2019–2031, https://doi.org/10.5194/amt-12-2019-2019, https://doi.org/10.5194/amt-12-2019-2019, 2019
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The physical basis of the EPIC cloud product algorithms and an initial evaluation of their performance are presented. EPIC cloud products include cloud mask, effective height, and optical depth. Comparison with co-located retrievals from geosynchronous earth orbit (GEO) and low earth orbit (LEO) satellites shows that the algorithms are performing well and are consistent with theoretical expectations. These products are publicly available at the NASA Langley Atmospheric Sciences Data Center.
Joseph A. Finlon, Greg M. McFarquhar, Stephen W. Nesbitt, Robert M. Rauber, Hugh Morrison, Wei Wu, and Pengfei Zhang
Atmos. Chem. Phys., 19, 3621–3643, https://doi.org/10.5194/acp-19-3621-2019, https://doi.org/10.5194/acp-19-3621-2019, 2019
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A new approach describing the relationship between ice crystal mass (m) and dimension (D) is derived, characterizing it as a set of
equally realizableparameters based on the natural variability in cloud conditions observed by aircraft over the Great Plains. Results from this approach address shortcomings of microphysical parameterization schemes and remote sensing retrievals that employ a single m–D relation for a given ice species or environment.
Junshik Um, Greg M. McFarquhar, Jeffrey L. Stith, Chang Hoon Jung, Seoung Soo Lee, Ji Yi Lee, Younghwan Shin, Yun Gon Lee, Yiseok Isaac Yang, Seong Soo Yum, Byung-Gon Kim, Joo Wan Cha, and A-Reum Ko
Atmos. Chem. Phys., 18, 16915–16930, https://doi.org/10.5194/acp-18-16915-2018, https://doi.org/10.5194/acp-18-16915-2018, 2018
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During the 2012 Deep Convective Clouds and Chemistry experiment upper anvils of two storms were sampled. The occurrence of well-defined pristine crystals was low in the anvils, while single frozen droplets and frozen droplet aggregates (FDAs) were the dominant habits. A new algorithm was developed to automatically identify the number, size, and relative position of element frozen droplets within FDAs. The morphological characteristics of FDAs were compared with those of black carbon aggregates.
Emma Järvinen, Olivier Jourdan, David Neubauer, Bin Yao, Chao Liu, Meinrat O. Andreae, Ulrike Lohmann, Manfred Wendisch, Greg M. McFarquhar, Thomas Leisner, and Martin Schnaiter
Atmos. Chem. Phys., 18, 15767–15781, https://doi.org/10.5194/acp-18-15767-2018, https://doi.org/10.5194/acp-18-15767-2018, 2018
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Using light diffraction it is possible to detect microscopic features within ice particles that have not yet been fully characterized. Here, this technique was applied in airborne measurements, where it was found that majority of atmospheric ice particles have features that significantly change the way ice particles interact with solar light. The microscopic features make ice-containing clouds more reflective than previously thought, which could have consequences for predicting our climate.
Michael S. Diamond, Amie Dobracki, Steffen Freitag, Jennifer D. Small Griswold, Ashley Heikkila, Steven G. Howell, Mary E. Kacarab, James R. Podolske, Pablo E. Saide, and Robert Wood
Atmos. Chem. Phys., 18, 14623–14636, https://doi.org/10.5194/acp-18-14623-2018, https://doi.org/10.5194/acp-18-14623-2018, 2018
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Smoke from Africa can mix into clouds over the southeast Atlantic and create new droplets, which brightens the clouds, reflects more sunlight, and thus cools the region. Using aircraft data from a NASA field campaign, we find that cloud properties are correlated with smoke as expected when the smoke is below the clouds but not when smoke is above the clouds because it takes several days for clouds to mix smoke downward. We recommend methods that can track clouds as they move for future studies.
Daniel J. Miller, Zhibo Zhang, Steven Platnick, Andrew S. Ackerman, Frank Werner, Celine Cornet, and Kirk Knobelspiesse
Atmos. Meas. Tech., 11, 3689–3715, https://doi.org/10.5194/amt-11-3689-2018, https://doi.org/10.5194/amt-11-3689-2018, 2018
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Prior satellite comparisons of bispectral and polarimetric cloud droplet size retrievals exhibited systematic biases. However, similar airborne instrument retrievals have been found to be quite similar to one another. This study explains this discrepancy in terms of differing sensitivity to vertical profile, as well as spatial and angular resolution. This is accomplished by using a satellite retrieval simulator – an LES cloud model coupled to radiative transfer and cloud retrieval algorithms.
Antonio Di Noia, Otto P. Hasekamp, Lianghai Wu, Bastiaan van Diedenhoven, Brian Cairns, and John E. Yorks
Atmos. Meas. Tech., 10, 4235–4252, https://doi.org/10.5194/amt-10-4235-2017, https://doi.org/10.5194/amt-10-4235-2017, 2017
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In this paper an algorithm for the retrieval of aerosol properties from NASA Research Scanning Polarimeter (RSP) data is presented. An artificial neural network is used to produce a first estimate of the aerosol properties, which is then improved using an iterative retrieval scheme based on Phillips–Tikhonov regularization. Using the neural network retrievals as a first guess for the Phillips–Tikhonov improved the retrieval convergence, confirming results previously found on ground-based data.
Thomas Fauchez, Steven Platnick, Kerry Meyer, Céline Cornet, Frédéric Szczap, and Tamás Várnai
Atmos. Chem. Phys., 17, 8489–8508, https://doi.org/10.5194/acp-17-8489-2017, https://doi.org/10.5194/acp-17-8489-2017, 2017
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This study presents impact of cirrus cloud horizontal heterogeneity on simulated thermal infrared brightness temperatures at the top of the atmosphere for spatial resolutions ranging from 50 m to 10 km. The cirrus is generated by the 3DCLOUD code and the radiative transfer by the 3DMCPOL code. Brightness temperatures are mostly impacted by the horizontal transport effect and plane-parallel bias at high and coarse spatial resolutions, respectively, with a minimum around 100 m–250 m.
Kenneth Sinclair, Bastiaan van Diedenhoven, Brian Cairns, John Yorks, Andrzej Wasilewski, and Matthew McGill
Atmos. Meas. Tech., 10, 2361–2375, https://doi.org/10.5194/amt-10-2361-2017, https://doi.org/10.5194/amt-10-2361-2017, 2017
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We present a multi-angular contrast approach to retrieve cloud top height (CTH) using photogrammetry. We demonstrate the method’s ability to retrieve heights of multiple cloud layers within single footprints, using the multiple views available for each footprint. This paper provides an in-depth description and performance analysis of the CTH retrieval technique and the retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar.
John Rausch, Kerry Meyer, Ralf Bennartz, and Steven Platnick
Atmos. Meas. Tech., 10, 2105–2116, https://doi.org/10.5194/amt-10-2105-2017, https://doi.org/10.5194/amt-10-2105-2017, 2017
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This paper documents the observed differences in the aggregated (Level-3) cloud droplet effective radius and droplet number concentration estimates inferred from the Aqua–MODIS cloud product collections 5.1 and 6 for warm oceanic cloud scenes over the year 2008. We note significant differences in effective radius and droplet concentration between the two products and discuss the algorithmic and calibration changes which may contribute to observed results.
Ann M. Fridlind, Xiaowen Li, Di Wu, Marcus van Lier-Walqui, Andrew S. Ackerman, Wei-Kuo Tao, Greg M. McFarquhar, Wei Wu, Xiquan Dong, Jingyu Wang, Alexander Ryzhkov, Pengfei Zhang, Michael R. Poellot, Andrea Neumann, and Jason M. Tomlinson
Atmos. Chem. Phys., 17, 5947–5972, https://doi.org/10.5194/acp-17-5947-2017, https://doi.org/10.5194/acp-17-5947-2017, 2017
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Understanding observed storm microphysics via computer simulation requires measurements of aerosol on which most hydrometeors form. We prepare aerosol input data for six storms observed over Oklahoma. We demonstrate their use in simulations of a case with widespread ice outflow well sampled by aircraft. Simulations predict too few ice crystals that are too large. We speculate that microphysics found in tropical storms occurred here, likely associated with poorly understood ice multiplication.
Frank Werner, Galina Wind, Zhibo Zhang, Steven Platnick, Larry Di Girolamo, Guangyu Zhao, Nandana Amarasinghe, and Kerry Meyer
Atmos. Meas. Tech., 9, 5869–5894, https://doi.org/10.5194/amt-9-5869-2016, https://doi.org/10.5194/amt-9-5869-2016, 2016
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A research–level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. This yields reliable estimates of important cloud variables at a horizontal resolution of 30 m. Comparisons of the ASTER retrieval results with the operational cloud products from the Moderate Resolution Imaging Spectroradiometer (MODIS) show a high agreement for 48 example cloud fields.
Ann M. Fridlind, Rachel Atlas, Bastiaan van Diedenhoven, Junshik Um, Greg M. McFarquhar, Andrew S. Ackerman, Elisabeth J. Moyer, and R. Paul Lawson
Atmos. Chem. Phys., 16, 7251–7283, https://doi.org/10.5194/acp-16-7251-2016, https://doi.org/10.5194/acp-16-7251-2016, 2016
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Images of crystals within mid-latitude cirrus clouds are used to derive consistent ice physical and optical properties for a detailed cloud microphysics model, including size-dependent mass, projected area, and fall speed. Based on habits found, properties are derived for bullet rosettes, their aggregates, and crystals with irregular shapes. Derived bullet rosette fall speeds are substantially greater than reported in past studies, owing to differences in mass, area, or diameter representation.
Kerry Meyer, Yuekui Yang, and Steven Platnick
Atmos. Meas. Tech., 9, 1785–1797, https://doi.org/10.5194/amt-9-1785-2016, https://doi.org/10.5194/amt-9-1785-2016, 2016
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This paper presents the expected uncertainties of a single-channel cloud opacity retrieval technique and a temperature-based cloud phase approach in support of the Deep Space Climate Observatory (DSCOVR) mission; DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations. Results show that, for ice clouds, retrieval errors are minimal (< 2 %), while for liquid clouds the error is limited to within 10 %, although for thin clouds the error can be higher.
Robert E. Holz, Steven Platnick, Kerry Meyer, Mark Vaughan, Andrew Heidinger, Ping Yang, Gala Wind, Steven Dutcher, Steven Ackerman, Nandana Amarasinghe, Fredrick Nagle, and Chenxi Wang
Atmos. Chem. Phys., 16, 5075–5090, https://doi.org/10.5194/acp-16-5075-2016, https://doi.org/10.5194/acp-16-5075-2016, 2016
Kerry Meyer, Steven Platnick, G. Thomas Arnold, Robert E. Holz, Paolo Veglio, John Yorks, and Chenxi Wang
Atmos. Meas. Tech., 9, 1743–1753, https://doi.org/10.5194/amt-9-1743-2016, https://doi.org/10.5194/amt-9-1743-2016, 2016
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Cirrus cloud optical and microphysical properties are retrieved from remote sensing solar reflectance measurements at two narrow wavelength channels within the broader water vapor absorption band at 1.88 µm. Results from this technique compare well with other solar reflectance, IR, and lidar-based retrievals. This approach is complementary to traditional remote sensing techniques and can extend cloud retrieval capabilities for thin cirrus clouds.
Joel McCorkel, Brian Cairns, and Andrzej Wasilewski
Atmos. Meas. Tech., 9, 955–962, https://doi.org/10.5194/amt-9-955-2016, https://doi.org/10.5194/amt-9-955-2016, 2016
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The transfer and maintenance of international radiometric standards to satellite remote-sensing instruments is a labor-intensive and costly one. The goal is to provide specific examples for calibration implementation for a potential instrument mission and, with this, advance debate on the roles that the various satellite calibration techniques play in providing the best radiometric standards for Earth-observing sensors.
Zhibo Zhang, Kerry Meyer, Hongbin Yu, Steven Platnick, Peter Colarco, Zhaoyan Liu, and Lazaros Oreopoulos
Atmos. Chem. Phys., 16, 2877–2900, https://doi.org/10.5194/acp-16-2877-2016, https://doi.org/10.5194/acp-16-2877-2016, 2016
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The frequency of occurrence and shortwave direct radiative effects (DRE) of above-cloud aerosols (ACAs) over global oceans are investigated using 8 years of collocated CALIOP and MODIS observations. We estimated that ACAs have a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m−2 (range of −0.03 to 0.06 W m−2) at TOA. The DREs at surface and within atmosphere are −0.15 W m−2 (range of −0.09 to −0.21 W m−2), and 0.17 W m−2 (range of 0.11 to 0.24 W m−2), respectively.
L. M. Zamora, R. A. Kahn, M. J. Cubison, G. S. Diskin, J. L. Jimenez, Y. Kondo, G. M. McFarquhar, A. Nenes, K. L. Thornhill, A. Wisthaler, A. Zelenyuk, and L. D. Ziemba
Atmos. Chem. Phys., 16, 715–738, https://doi.org/10.5194/acp-16-715-2016, https://doi.org/10.5194/acp-16-715-2016, 2016
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Based on extensive aircraft campaigns, we quantify how biomass burning smoke affects subarctic and Arctic liquid cloud microphysical properties. Enhanced cloud albedo may decrease short-wave radiative flux by between 2 and 4 Wm2 or more in some subarctic conditions. Smoke halved average cloud droplet diameter. In one case study, it also appeared to limit droplet formation. Numerous Arctic background Aitken particles can also interact with combustion particles, perhaps affecting their properties.
M. S. Norgren, J. D. Small, H. H. Jonsson, and P. Y. Chuang
Atmos. Chem. Phys., 16, 21–33, https://doi.org/10.5194/acp-16-21-2016, https://doi.org/10.5194/acp-16-21-2016, 2016
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Clouds transport air from near the surface to higher altitudes. However, the amount of air transported in this way is poorly understood. In this study, measurements from aircraft of small clouds over Texas show that the amount is limited to the volume of the visible cloud and not more. This means that these clouds are not very effective at transporting pollution and moisture to upper reaches of the atmosphere, which in turn affects their redistribution and wider impact.
M. Ottaviani, B. van Diedenhoven, and B. Cairns
The Cryosphere, 9, 1933–1942, https://doi.org/10.5194/tc-9-1933-2015, https://doi.org/10.5194/tc-9-1933-2015, 2015
L. Wu, O. Hasekamp, B. van Diedenhoven, and B. Cairns
Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, https://doi.org/10.5194/amt-8-2625-2015, 2015
J. Um, G. M. McFarquhar, Y. P. Hong, S.-S. Lee, C. H. Jung, R. P. Lawson, and Q. Mo
Atmos. Chem. Phys., 15, 3933–3956, https://doi.org/10.5194/acp-15-3933-2015, https://doi.org/10.5194/acp-15-3933-2015, 2015
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Dimensions of ice crystals increased with an increase in temperature and the L-W relationships of crystals with a given L depended heavily on temperature, whereas the aspect ratio depended only weakly on temperature. The relative frequency of occurrence of plates was much larger in anvil clouds compared to that of columnar crystals (i.e., columns and bullet rosettes), whereas the relative occurrence frequency of columnar crystals was much larger in non-anvil clouds.
T. Fauchez, P. Dubuisson, C. Cornet, F. Szczap, A. Garnier, J. Pelon, and K. Meyer
Atmos. Meas. Tech., 8, 633–647, https://doi.org/10.5194/amt-8-633-2015, https://doi.org/10.5194/amt-8-633-2015, 2015
M. K. Witte, P. Y. Chuang, and G. Feingold
Atmos. Chem. Phys., 14, 6729–6738, https://doi.org/10.5194/acp-14-6729-2014, https://doi.org/10.5194/acp-14-6729-2014, 2014
B. van Diedenhoven, B. Cairns, A. M. Fridlind, A. S. Ackerman, and T. J. Garrett
Atmos. Chem. Phys., 13, 3185–3203, https://doi.org/10.5194/acp-13-3185-2013, https://doi.org/10.5194/acp-13-3185-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Attribution of riming and aggregation processes by application of the vertical distribution of particle shape (VDPS) and spectral retrieval techniques to cloud radar observations
Factors limiting contrail detection in satellite imagery
Errors in stereoscopic retrievals of cloud top height for single-layer clouds
A method to retrieve mixed phase cloud vertical structure from airborne lidar
Consideration of the cloud motion for aircraft-based stereographically derived cloud geometry and cloud top heights
Exploring the characteristics of Fengyun-4A Advanced Geostationary Radiation Imager (AGRI) visible reflectance using the China Meteorological Administration Mesoscale (CMA-MESO) forecasts and its implications for data assimilation
Validating global horizontal irradiance retrievals from Meteosat SEVIRI at increased spatial resolution against a dense network of ground-based observations
Effectiveness of Cirrus Detection with MODIS Cloud Mask data
Assessment and application of melting layer simulations for spaceborne radars within the RTTOV-SCATT v13.1 model
Synergistic approach of frozen hydrometeor retrievals: considerations on radiative transfer and model uncertainties in a simulated framework
An evaluation of microphysics in a numerical model using Doppler velocity measured by ground-based radar for application to the EarthCARE satellite
Investigation of cirrus cloud properties in the tropical tropopause layer using high-altitude limb-scanning near-IR spectroscopy during NASA-ATTREX
Comparing FY-2F/CTA products to ground-based manual total cloud cover observations in Xinjiang under complex underlying surfaces and different weather conditions
Model-based evaluation of cloud geometry and droplet size retrievals from two-dimensional polarized measurements of specMACS
Improved RepVGG ground-based cloud image classification with attention convolution
An intercomparison of EarthCARE cloud, aerosol, and precipitation retrieval products
First results of cloud retrieval from the Geostationary Environmental Monitoring Spectrometer
Thundercloud structures detected and analyzed based on coherent Doppler wind lidar
Assessing Arctic low-level clouds and precipitation from above – a radar perspective
What CloudSat cannot see: liquid water content profiles inferred from MODIS and CALIOP observations
Validation of the Cloud_CCI (Cloud Climate Change Initiative) cloud products in the Arctic
The Education and Research 3D Radiative Transfer Toolbox (EaR3T) – towards the mitigation of 3D bias in airborne and spaceborne passive imagery cloud retrievals
Retrieval of microphysical parameters of monsoonal rain using X-band dual-polarization radar: their seasonal dependence and evaluation
Consistency test of precipitating ice cloud retrieval properties obtained from the observations of different instruments operating at Dome C (Antarctica)
Sizing ice hydrometeor populations using the dual-wavelength radar ratio
Impact of the revisit frequency on cloud climatology for CALIPSO, EarthCARE, Aeolus, and ICESat-2 satellite lidar missions
The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data
Horizontal geometry of trade wind cumuli – aircraft observations from a shortwave infrared imager versus a radar profiler
Evaluating the consistency and continuity of pixel-scale cloud property data records from Aqua and SNPP (Suomi National Polar-orbiting Partnership)
Quality assessment of Second-generation Global Imager (SGLI)-observed cloud properties using SKYNET surface observation data
Comparison of scattering ratio profiles retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations and preliminary estimates of cloud fraction profiles
Evaluation of convective cloud microphysics in numerical weather prediction models with dual-wavelength polarimetric radar observations: methods and examples
Synergistic radar and sub-millimeter radiometer retrievals of ice hydrometeors in mid-latitude frontal cloud systems
Evaluation of satellite retrievals of liquid clouds from the GOES-13 imager and MODIS over the midlatitude North Atlantic during the NAAMES campaign
Evaluation of Visible Infrared Imaging Radiometer Suite (VIIRS) neural network cloud detection against current operational cloud masks
The effect of low-level thin arctic clouds on shortwave irradiance: evaluation of estimates from spaceborne passive imagery with aircraft observations
Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O2–O2, MODIS, and Suomi-NPP VIIRS
Dissecting effects of orbital drift of polar-orbiting satellites on accuracy and trends of climate data records of cloud fractional cover
Calibration of global MODIS cloud amount using CALIOP cloud profiles
Evaluation of the MODIS Collection 6 multilayer cloud detection algorithm through comparisons with CloudSat Cloud Profiling Radar and CALIPSO CALIOP products
An extended radar relative calibration adjustment (eRCA) technique for higher-frequency radars and range–height indicator (RHI) scans
Comparing lightning observations of the ground-based European lightning location system EUCLID and the space-based Lightning Imaging Sensor (LIS) on the International Space Station (ISS)
Microwave and submillimeter wave scattering of oriented ice particles
Shallow cumuli cover and its uncertainties from ground-based lidar–radar data and sky images
Using passive and active observations at microwave and sub-millimetre wavelengths to constrain ice particle models
Comparison of the cloud top heights retrieved from MODIS and AHI satellite data with ground-based Ka-band radar
Cross-comparison of cloud liquid water path derived from observations by two space-borne and one ground-based instrument in northern Europe
The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations
Diurnal and nocturnal cloud segmentation of all-sky imager (ASI) images using enhancement fully convolutional networks
Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?
Audrey Teisseire, Anne-Claire Billault-Roux, Teresa Vogl, and Patric Seifert
Atmos. Meas. Tech., 18, 1499–1517, https://doi.org/10.5194/amt-18-1499-2025, https://doi.org/10.5194/amt-18-1499-2025, 2025
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This study demonstrates the ability of a new method delivering the vertical distribution of particle shape to highlight riming and aggregation processes, identifying graupel and aggregates, respectively, as isometric particles. The distinction between these processes can be achieved using lidar or spectral techniques, as demonstrated in the case studies. The capability of the new method to identify rimed particles and aggregates without differentiating them can simplify statistical work.
Oliver G. A. Driver, Marc E. J. Stettler, and Edward Gryspeerdt
Atmos. Meas. Tech., 18, 1115–1134, https://doi.org/10.5194/amt-18-1115-2025, https://doi.org/10.5194/amt-18-1115-2025, 2025
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Contrails (clouds caused by planes) play a large role in the climate warming caused by aviation. Satellites are a good tool to validate modelled impact estimates. Many contrails are either too narrow or too disperse to detect. This work shows that only around half of contrails are observable but that the most climatically important are easier to detect. It supports the use of satellites for contrail observation but highlights the need for observability considerations for specific applications.
Jesse Loveridge and Larry Di Girolamo
EGUsphere, https://doi.org/10.5194/egusphere-2025-20, https://doi.org/10.5194/egusphere-2025-20, 2025
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Stereoscopic techniques are useful for measuring cloud geometry from space. However, clouds are transparent and often have tenuous boundaries. We evaluate the effect of this using numerical simulations. We find that stereoscopy tends to retrieve a cloud boundary that is interior to the true shape by around 100 m and is smoother, depending on the cloud shape and resolution of the instrument. This error is similar across views, highlighting the strength of stereoscopy for change detection.
Ewan Crosbie, Johnathan Hair, Amin Nehrir, Richard Ferrare, Chris Hostetler, Taylor Shingler, David Harper, Marta Fenn, James Collins, Rory Barton-Grimley, Brian Collister, K. Lee Thornhill, Christiane Voigt, Simon Kirschler, and Armin Sorooshian
EGUsphere, https://doi.org/10.5194/egusphere-2024-3844, https://doi.org/10.5194/egusphere-2024-3844, 2024
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A method was developed to extract information from airborne lidar observations about the distribution of ice and liquid water within clouds. The method specifically targets signatures of horizontal and vertical gradients in ice and water that appear in the polarization of the lidar signals. The method was tested against direct measurements of the cloud properties collected by a second aircraft.
Lea Volkmer, Tobias Kölling, Tobias Zinner, and Bernhard Mayer
Atmos. Meas. Tech., 17, 6807–6817, https://doi.org/10.5194/amt-17-6807-2024, https://doi.org/10.5194/amt-17-6807-2024, 2024
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The importance of the consideration of cloud motion for the stereographic determination of cloud top height from aircraft observations is demonstrated using measurements of the airborne spectrometer of the Munich Aerosol Cloud Scanner (specMACS). A method for cloud motion correction using model winds from the European Centre for Medium-Range Weather Forecasts is presented and validated using both real measurements and realistic radiative transfer simulations.
Yongbo Zhou, Yubao Liu, Wei Han, Yuefei Zeng, Haofei Sun, Peilong Yu, and Lijian Zhu
Atmos. Meas. Tech., 17, 6659–6675, https://doi.org/10.5194/amt-17-6659-2024, https://doi.org/10.5194/amt-17-6659-2024, 2024
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The study explored differences between the visible reflectance provided by the Fengyun-4A satellite and its equivalent derived from the China Meteorological Administration Mesoscale model using a forward operator. The observation-minus-simulation biases were able to monitor the performance of the satellite visible instrument. The biases were corrected based on a first-order approximation method, which promotes the data assimilation of satellite visible reflectance in real-world cases.
Job I. Wiltink, Hartwig Deneke, Yves-Marie Saint-Drenan, Chiel C. van Heerwaarden, and Jan Fokke Meirink
Atmos. Meas. Tech., 17, 6003–6024, https://doi.org/10.5194/amt-17-6003-2024, https://doi.org/10.5194/amt-17-6003-2024, 2024
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Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) global horizontal irradiance (GHI) retrievals are validated at standard and increased spatial resolution against a network of 99 pyranometers. GHI accuracy is strongly dependent on the cloud regime. Days with variable cloud conditions show significant accuracy improvements when retrieved at higher resolution. We highlight the benefits of dense network observations and a cloud-regime-resolved approach in validating GHI retrievals.
Żaneta Nguyen Huu, Andrzej Z. Kotarba, and Agnieszka Wypych
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-163, https://doi.org/10.5194/amt-2024-163, 2024
Revised manuscript accepted for AMT
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Clouds affect Earth's energy balance, with high-altitude cirrus clouds contributing to atmospheric warming. While active satellite sensors are the most accurate for detecting cirrus clouds, they are not ideal for long-term studies. This study compares MODIS and CALIOP data, testing six MODIS methods and two ISCCP tests. The ATC test was the most effective, achieving 72.98 % accuracy during daytime and 59.50 % at night, making it suitable for creating a high-level cloud mask.
Rohit Mangla, Mary Borderies, Philippe Chambon, Alan Geer, and James Hocking
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-131, https://doi.org/10.5194/amt-2024-131, 2024
Revised manuscript accepted for AMT
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This study provides a detailed description of the radar simulator available within version 13 of the RTTOV software. It is applied to the Météo-France global numerical weather prediction model, with the objective of simulating Dual-frequency Precipitation Radar reflectivity observations. Additionally, the simulation of the bright-band is addressed, and then successfully applied to model forecasts for the purpose of classifying the model columns between stratiform and convective categories.
Ethel Villeneuve, Philippe Chambon, and Nadia Fourrié
Atmos. Meas. Tech., 17, 3567–3582, https://doi.org/10.5194/amt-17-3567-2024, https://doi.org/10.5194/amt-17-3567-2024, 2024
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In cloudy situations, infrared and microwave observations are complementary, with infrared being sensitive to cloud tops and microwave sensitive to precipitation. However, infrared satellite observations are underused. This study aims to quantify if the inconsistencies in the modelling of clouds prevent the use of cloudy infrared observations in the process of weather forecasting. It shows that the synergistic use of infrared and microwave observations is beneficial, despite inconsistencies.
Woosub Roh, Masaki Satoh, Yuichiro Hagihara, Hiroaki Horie, Yuichi Ohno, and Takuji Kubota
Atmos. Meas. Tech., 17, 3455–3466, https://doi.org/10.5194/amt-17-3455-2024, https://doi.org/10.5194/amt-17-3455-2024, 2024
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The advantage of the use of Doppler velocity in the categorization of the hydrometeors is that Doppler velocities suffer less impact from the attenuation of rain and wet attenuation on an antenna. The ground Cloud Profiling Radar observation of the radar reflectivity for the precipitation case is limited because of wet attenuation on an antenna. We found the main contribution to Doppler velocities is the terminal velocity of hydrometeors by analysis of simulation results.
Santo Fedele Colosimo, Nathaniel Brockway, Vijay Natraj, Robert Spurr, Klaus Pfeilsticker, Lisa Scalone, Max Spolaor, Sarah Woods, and Jochen Stutz
Atmos. Meas. Tech., 17, 2367–2385, https://doi.org/10.5194/amt-17-2367-2024, https://doi.org/10.5194/amt-17-2367-2024, 2024
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Cirrus clouds are poorly understood components of the climate system, in part due to the challenge of observing thin, sub-visible ice clouds. We address this issue with a new observational approach that uses the remote sensing of near-infrared ice water absorption features from a high-altitude aircraft. We describe the underlying principle of this approach and present a new procedure to retrieve ice concentration in cirrus clouds. Our retrievals compare well with in situ observations.
Shuai Li, Hua Zhang, Yonghang Chen, Zhili Wang, Xiangyu Li, Yuan Li, and Yuanyuan Xue
Atmos. Meas. Tech., 17, 2011–2024, https://doi.org/10.5194/amt-17-2011-2024, https://doi.org/10.5194/amt-17-2011-2024, 2024
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In this paper, Xinjiang was the test area, and nine evaluation indexes of FY-2F/CTA, including precision rate, false rate, missing rate, consistency rate, strong rate, weak rate, bias, AE, and RMSE, were calculated and analyzed under complex underlying surface (subsurface types, temperature and altitude conditions) and different weather conditions (dust effects and different cloud cover levels). The precision, consistency, and error indexes of FY-2F/CTA were tested and evaluated.
Lea Volkmer, Veronika Pörtge, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 17, 1703–1719, https://doi.org/10.5194/amt-17-1703-2024, https://doi.org/10.5194/amt-17-1703-2024, 2024
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Three-dimensional radiative transfer simulations are used to evaluate the performance of retrieval algorithms in the derivation of cloud geometry (cloud top heights) and cloud droplet size distributions from two-dimensional polarized radiance measurements of the airborne spectrometer of the Munich Aerosol Cloud Scanner. The cloud droplet size distributions are derived for the effective radius and variance. The simulations are based on cloud data from highly resolved large-eddy simulations.
Chaojun Shi, Leile Han, Ke Zhang, Hongyin Xiang, Xingkuan Li, Zibo Su, and Xian Zheng
Atmos. Meas. Tech., 17, 979–997, https://doi.org/10.5194/amt-17-979-2024, https://doi.org/10.5194/amt-17-979-2024, 2024
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This article mainly studies the problem of ground cloud classification and significantly improves the accuracy of ground cloud classification by applying an improved deep-learning method. The research results show that the method proposed in this article has a significant impact on the classification results of ground cloud images. These conclusions have important implications for providing new insights and future research directions in the field of ground cloud classification.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Bo-Ram Kim, Gyuyeon Kim, Minjeong Cho, Yong-Sang Choi, and Jhoon Kim
Atmos. Meas. Tech., 17, 453–470, https://doi.org/10.5194/amt-17-453-2024, https://doi.org/10.5194/amt-17-453-2024, 2024
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This study introduces the GEMS cloud algorithm and validates its results using data from GEMS and other environmental satellites. The GEMS algorithm is able to detect the lowest cloud heights among the four satellites, and its effective cloud fraction and cloud centroid pressure are well reflected in the retrieval results. The study highlights the algorithm's usefulness in correcting errors in trace gases caused by clouds in the East Asian region.
Kenan Wu, Tianwen Wei, Jinlong Yuan, Haiyun Xia, Xin Huang, Gaopeng Lu, Yunpeng Zhang, Feifan Liu, Baoyou Zhu, and Weidong Ding
Atmos. Meas. Tech., 16, 5811–5825, https://doi.org/10.5194/amt-16-5811-2023, https://doi.org/10.5194/amt-16-5811-2023, 2023
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A compact all-fiber coherent Doppler wind lidar (CDWL) working at the 1.5 µm wavelength is applied to probe the dynamics and microphysics structure of thunderstorms. It was found that thunderclouds below the 0 ℃ isotherm have significant spectrum broadening and an increase in skewness, and that lightning affects the microphysics structure of the thundercloud. It is proven that the precise spectrum of CDWL is a promising indicator for studying the charge structure of thunderstorms.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes
Atmos. Meas. Tech., 16, 3531–3546, https://doi.org/10.5194/amt-16-3531-2023, https://doi.org/10.5194/amt-16-3531-2023, 2023
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In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.
Kameswara S. Vinjamuri, Marco Vountas, Luca Lelli, Martin Stengel, Matthew D. Shupe, Kerstin Ebell, and John P. Burrows
Atmos. Meas. Tech., 16, 2903–2918, https://doi.org/10.5194/amt-16-2903-2023, https://doi.org/10.5194/amt-16-2903-2023, 2023
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Clouds play an important role in Arctic amplification. Cloud data from ground-based sites are valuable but cannot represent the whole Arctic. Therefore the use of satellite products is a measure to cover the entire Arctic. However, the quality of such cloud measurements from space is not well known. The paper discusses the differences and commonalities between satellite and ground-based measurements. We conclude that the satellite dataset, with a few exceptions, can be used in the Arctic.
Hong Chen, K. Sebastian Schmidt, Steven T. Massie, Vikas Nataraja, Matthew S. Norgren, Jake J. Gristey, Graham Feingold, Robert E. Holz, and Hironobu Iwabuchi
Atmos. Meas. Tech., 16, 1971–2000, https://doi.org/10.5194/amt-16-1971-2023, https://doi.org/10.5194/amt-16-1971-2023, 2023
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We introduce the Education and Research 3D Radiative Transfer Toolbox (EaR3T) and propose a radiance self-consistency approach for quantifying and mitigating 3D bias in legacy airborne and spaceborne imagery retrievals due to spatially inhomogeneous clouds and surfaces.
Kumar Abhijeet, Thota Narayana Rao, Nidamanuri Rama Rao, and Kasimahanthi Amar Jyothi
Atmos. Meas. Tech., 16, 871–888, https://doi.org/10.5194/amt-16-871-2023, https://doi.org/10.5194/amt-16-871-2023, 2023
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The present study focuses on retrieving and validating raindrop size distribution (DSD) relations for monsoonal rainfall, which are required for retrieving DSDs with polarimetric radar measurements. The seasonal variation in DSD is quite large and significant, and as a result the coefficients also vary considerably between the seasons and from those existing elsewhere. Among the existing DSD methods, the N-gamma method performs better than the other methods.
Gianluca Di Natale, David D. Turner, Giovanni Bianchini, Massimo Del Guasta, Luca Palchetti, Alessandro Bracci, Luca Baldini, Tiziano Maestri, William Cossich, Michele Martinazzo, and Luca Facheris
Atmos. Meas. Tech., 15, 7235–7258, https://doi.org/10.5194/amt-15-7235-2022, https://doi.org/10.5194/amt-15-7235-2022, 2022
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In this paper, we describe a new approach to test the consistency of the precipitating ice cloud optical and microphysical properties in Antarctica, Dome C, retrieved from hyperspectral measurements in the far-infrared, with the reflectivity detected by a co-located micro rain radar operating at 24 GHz. The retrieved ice crystal sizes were found in accordance with the direct measurements of an optical imager, also installed at Dome C, which can collect the falling ice particles.
Sergey Y. Matrosov, Alexei Korolev, Mengistu Wolde, and Cuong Nguyen
Atmos. Meas. Tech., 15, 6373–6386, https://doi.org/10.5194/amt-15-6373-2022, https://doi.org/10.5194/amt-15-6373-2022, 2022
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A remote sensing method to retrieve sizes of particles in ice clouds and precipitation from radar measurements at two wavelengths is described. This method is based on relating the particle size information to the ratio of radar signals at these two wavelengths. It is demonstrated that this ratio is informative about different characteristic particle sizes. Knowing atmospheric ice particle sizes is important for many applications such as precipitation estimation and climate modeling.
Andrzej Z. Kotarba
Atmos. Meas. Tech., 15, 4307–4322, https://doi.org/10.5194/amt-15-4307-2022, https://doi.org/10.5194/amt-15-4307-2022, 2022
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Space profiling lidars offer a unique insight into cloud properties in Earth’s atmosphere, and are considered the most reliable source of cloud information. However, lidar-based cloud climatologies are infrequently sampled: every 7 to 91 d, and only along the ground track. This study evaluated how accurate are the cloud data from existing (CALIPSO, ICESat-2, Aeolus) and planned (EarthCARE) space lidars, when compared to a cloud climatology obtained with observations taken every day.
Edward Gryspeerdt, Daniel T. McCoy, Ewan Crosbie, Richard H. Moore, Graeme J. Nott, David Painemal, Jennifer Small-Griswold, Armin Sorooshian, and Luke Ziemba
Atmos. Meas. Tech., 15, 3875–3892, https://doi.org/10.5194/amt-15-3875-2022, https://doi.org/10.5194/amt-15-3875-2022, 2022
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Droplet number concentration is a key property of clouds, influencing a variety of cloud processes. It is also used for estimating the cloud response to aerosols. The satellite retrieval depends on a number of assumptions – different sampling strategies are used to select cases where these assumptions are most likely to hold. Here we investigate the impact of these strategies on the agreement with in situ data, the droplet number climatology and estimates of the indirect radiative forcing.
Henning Dorff, Heike Konow, and Felix Ament
Atmos. Meas. Tech., 15, 3641–3661, https://doi.org/10.5194/amt-15-3641-2022, https://doi.org/10.5194/amt-15-3641-2022, 2022
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This study elaborates how aircraft-based horizontal geometries of trade wind cumuli differ whether a one-dimensional profiling radar or a two-dimensional imager is used. Cloud size distributions are examined in terms of sensitivity to sample size, resolution, and instrument field of view. While the radar cannot reproduce the double power law distribution due to coarse resolution and restriction to vertical transects, the imager also reveals the elliptic cloud structure enhancing with wind speed.
Qing Yue, Eric J. Fetzer, Likun Wang, Brian H. Kahn, Nadia Smith, John M. Blaisdell, Kerry G. Meyer, Mathias Schreier, Bjorn Lambrigtsen, and Irina Tkatcheva
Atmos. Meas. Tech., 15, 2099–2123, https://doi.org/10.5194/amt-15-2099-2022, https://doi.org/10.5194/amt-15-2099-2022, 2022
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The self-consistency and continuity of cloud retrievals from infrared sounders and imagers aboard Aqua and SNPP (Suomi National Polar-orbiting Partnership) are examined at the pixel scale. Cloud products are found to be consistent with each other. Differences between sounder products are mainly due to cloud clearing and the treatment of clouds in scenes with unsuccessful atmospheric retrievals. The impact of algorithm and instrument differences is clearly seen in the imager cloud retrievals.
Pradeep Khatri, Tadahiro Hayasaka, Hitoshi Irie, Husi Letu, Takashi Y. Nakajima, Hiroshi Ishimoto, and Tamio Takamura
Atmos. Meas. Tech., 15, 1967–1982, https://doi.org/10.5194/amt-15-1967-2022, https://doi.org/10.5194/amt-15-1967-2022, 2022
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Cloud properties observed by the Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite are evaluated using surface observation data. The study finds that SGLI-observed cloud properties are qualitative enough, although water cloud properties are suggested to be more qualitative, and both water and ice cloud properties can reproduce surface irradiance quite satisfactorily. Thus, SGLI cloud products are very useful for different studies.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, Rodrigo Guzman, Cyprien Gindre, Po-Lun Ma, and Marjolaine Chiriaco
Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, https://doi.org/10.5194/amt-15-1055-2022, 2022
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Space-borne lidars have been providing invaluable information of atmospheric optical properties since 2006, and new lidar missions are on the way to ensure continuous observations. In this work, we compare the clouds estimated from space-borne ALADIN and CALIOP lidar observations. The analysis of collocated data shows that the agreement between the retrieved clouds is good up to 3 km height. Above that, ALADIN detects 40 % less clouds than CALIOP, except for polar stratospheric clouds (PSCs).
Gregor Köcher, Tobias Zinner, Christoph Knote, Eleni Tetoni, Florian Ewald, and Martin Hagen
Atmos. Meas. Tech., 15, 1033–1054, https://doi.org/10.5194/amt-15-1033-2022, https://doi.org/10.5194/amt-15-1033-2022, 2022
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We present a setup for systematic characterization of differences between numerical weather models and radar observations for convective weather situations. Radar observations providing dual-wavelength and polarimetric variables to infer information about hydrometeor shapes and sizes are compared against simulations using microphysics schemes of varying complexity. Differences are found in ice and liquid phase, pointing towards issues of some schemes in reproducing particle size distributions.
Simon Pfreundschuh, Stuart Fox, Patrick Eriksson, David Duncan, Stefan A. Buehler, Manfred Brath, Richard Cotton, and Florian Ewald
Atmos. Meas. Tech., 15, 677–699, https://doi.org/10.5194/amt-15-677-2022, https://doi.org/10.5194/amt-15-677-2022, 2022
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We test a novel method to remotely measure ice particles in clouds. This is important because such measurements are required to improve climate and weather models. The method combines a radar with newly developed sensors measuring microwave radiation at very short wavelengths. We use observations made from aircraft flying above the cloud and compare them to real measurements from inside the cloud. This works well given that one can model the ice particles in the cloud sufficiently well.
David Painemal, Douglas Spangenberg, William L. Smith Jr., Patrick Minnis, Brian Cairns, Richard H. Moore, Ewan Crosbie, Claire Robinson, Kenneth L. Thornhill, Edward L. Winstead, and Luke Ziemba
Atmos. Meas. Tech., 14, 6633–6646, https://doi.org/10.5194/amt-14-6633-2021, https://doi.org/10.5194/amt-14-6633-2021, 2021
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Cloud properties derived from satellite sensors are critical for the global monitoring of climate. This study evaluates satellite-based cloud properties over the North Atlantic using airborne data collected during NAAMES. Satellite observations of droplet size and cloud optical depth tend to compare well with NAAMES data. The analysis indicates that the satellite pixel resolution and the specific viewing geometry need to be taken into account in research applications.
Charles H. White, Andrew K. Heidinger, and Steven A. Ackerman
Atmos. Meas. Tech., 14, 3371–3394, https://doi.org/10.5194/amt-14-3371-2021, https://doi.org/10.5194/amt-14-3371-2021, 2021
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Automated detection of clouds in satellite imagery is an important practice that is useful for predicting and understanding both weather and climate. Cloud detection is often difficult at night and over cold surfaces. In this paper, we discuss how a complex statistical model (a neural network) can more accurately detect clouds compared to currently used approaches. Overall, our results suggest that our approach could result in more reliable assessments of global cloud cover.
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
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In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Jędrzej S. Bojanowski and Jan P. Musiał
Atmos. Meas. Tech., 13, 6771–6788, https://doi.org/10.5194/amt-13-6771-2020, https://doi.org/10.5194/amt-13-6771-2020, 2020
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Satellites such as NOAA's Advanced Very High Resolution Radiometer can uniquely observe changes in cloud cover but are affected by orbital drift that results in shifted image acquisition times, which in turn lead to spurious trends in cloud cover detected during climatological analyses. Providing a detailed quantification of these trends, we show that climate data records must be analysed with caution, as for some periods and regions they do not comply with the requirements for climate data.
Andrzej Z. Kotarba
Atmos. Meas. Tech., 13, 4995–5012, https://doi.org/10.5194/amt-13-4995-2020, https://doi.org/10.5194/amt-13-4995-2020, 2020
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This paper evaluates the operational approach for producing global (Level 3) cloud amount based on MODIS cloud masks (Level 2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 %, and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/local scale. A method of how to correct and calibrate MODIS global data using CALIPSO detections is suggested.
Benjamin Marchant, Steven Platnick, Kerry Meyer, and Galina Wind
Atmos. Meas. Tech., 13, 3263–3275, https://doi.org/10.5194/amt-13-3263-2020, https://doi.org/10.5194/amt-13-3263-2020, 2020
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Multilayer cloud scenes (such as an ice cloud overlapping a liquid cloud) are common in the Earth's atmosphere and are quite difficult to detect from space. The detection of multilayer clouds is important to better understand how they interact with the light and their impact on the climate. So, for the instrument MODIS an algorithm has been developed to detect those clouds, and this paper presents an evaluation of this algorithm by comparing it with
other instruments.
Alexis Hunzinger, Joseph C. Hardin, Nitin Bharadwaj, Adam Varble, and Alyssa Matthews
Atmos. Meas. Tech., 13, 3147–3166, https://doi.org/10.5194/amt-13-3147-2020, https://doi.org/10.5194/amt-13-3147-2020, 2020
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The calibration of weather radars is one of the most dominant sources of errors hindering their use. This work takes a technique for tracking the changes in radar calibration using the radar clutter from the ground and extends it to higher-frequency research radars. It demonstrates that after modifications the technique is successful but that special care needs to be taken in its application at high frequencies. The technique is verified using data from multiple DOE ARM field campaigns.
Dieter R. Poelman and Wolfgang Schulz
Atmos. Meas. Tech., 13, 2965–2977, https://doi.org/10.5194/amt-13-2965-2020, https://doi.org/10.5194/amt-13-2965-2020, 2020
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The objective of this work is to quantify the similarities and contrasts between the lightning observations from the Lightning Imaging Sensor (LIS) on the International Space Station (ISS) and the ground-based European Cooperation for Lightning Detection (EUCLID) network. This work is timely, given that the Meteosat Third Generation (MTG), which has a lightning imager (LI) on board, is going to be launched in 2 years.
Manfred Brath, Robin Ekelund, Patrick Eriksson, Oliver Lemke, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 2309–2333, https://doi.org/10.5194/amt-13-2309-2020, https://doi.org/10.5194/amt-13-2309-2020, 2020
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Microwave dual-polarization observations consistently show that larger atmospheric ice particles tend to have a preferred orientation. We provide a publicly available database of microwave and submillimeter wave scattering properties of oriented ice particles based on discrete dipole approximation scattering calculations. Detailed radiative transfer simulations, recreating observed polarization patterns, are additionally presented in this study.
Erin A. Riley, Jessica M. Kleiss, Laura D. Riihimaki, Charles N. Long, Larry K. Berg, and Evgueni Kassianov
Atmos. Meas. Tech., 13, 2099–2117, https://doi.org/10.5194/amt-13-2099-2020, https://doi.org/10.5194/amt-13-2099-2020, 2020
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Discrepancies in hourly shallow cumuli cover estimates can be substantial. Instrument detection differences contribute to long-term bias in shallow cumuli cover estimates, whereas narrow field-of-view configurations impact measurement uncertainty as averaging time decreases. A new tool is introduced to visually assess both impacts on sub-hourly cloud cover estimates. Accurate shallow cumuli cover estimation is needed for model–observation comparisons and studying cloud-surface interactions.
Robin Ekelund, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 13, 501–520, https://doi.org/10.5194/amt-13-501-2020, https://doi.org/10.5194/amt-13-501-2020, 2020
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Atmospheric ice particles (e.g. snow and ice crystals) are an important part of weather, climate, and the hydrological cycle. This study investigates whether combined satellite measurements by radar and radiometers at microwave wavelengths can be used to find the most likely shape of such ice particles. The method was limited when using only currently operating sensors (CloudSat radar and the GPM Microwave Imager) but shows promise if the upcoming Ice Cloud Imager is also considered.
Juan Huo, Daren Lu, Shu Duan, Yongheng Bi, and Bo Liu
Atmos. Meas. Tech., 13, 1–11, https://doi.org/10.5194/amt-13-1-2020, https://doi.org/10.5194/amt-13-1-2020, 2020
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Cloud top height (CTH) is one of the important cloud parameters providing information about the vertical structure of cloud water content. To better understand the accuracy of CTH derived from passive satellite data, 2 years of ground-based Ka-band radar measurements are compared with CTH inferred from Terra/Aqua MODIS and Himawari AHI. It is found that MODIS and AHI underestimate CTH relative to radar by −1.10 km. Both MODIS and AHI CTH retrieval accuracy depend strongly on cloud depth.
Vladimir S. Kostsov, Anke Kniffka, Martin Stengel, and Dmitry V. Ionov
Atmos. Meas. Tech., 12, 5927–5946, https://doi.org/10.5194/amt-12-5927-2019, https://doi.org/10.5194/amt-12-5927-2019, 2019
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Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms. The LWP data delivered by the satellite instruments SEVIRI and AVHRR together with the data provided by the ground-based radiometer RPG-HATPRO near St. Petersburg, Russia, have been compared. Our study revealed considerable differences between LWP data from SEVIRI and AVHRR in winter over ice-covered relatively small water bodies in this region.
Jonathan K. P. Shonk, Jui-Yuan Christine Chiu, Alexander Marshak, David M. Giles, Chiung-Huei Huang, Gerald G. Mace, Sally Benson, Ilya Slutsker, and Brent N. Holben
Atmos. Meas. Tech., 12, 5087–5099, https://doi.org/10.5194/amt-12-5087-2019, https://doi.org/10.5194/amt-12-5087-2019, 2019
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Retrievals of cloud optical depth made using AERONET radiometers in “cloud mode” rely on the assumption that all cloud is liquid. The presence of ice cloud therefore introduces errors in the retrieved optical depth, which can be over 25 in optically thick ice clouds. However, such clouds are not frequent and the long-term mean optical depth error is about 3 for a sample of real clouds. A correction equation could improve the retrieval further, although this would require extra instrumentation.
Chaojun Shi, Yatong Zhou, Bo Qiu, Jingfei He, Mu Ding, and Shiya Wei
Atmos. Meas. Tech., 12, 4713–4724, https://doi.org/10.5194/amt-12-4713-2019, https://doi.org/10.5194/amt-12-4713-2019, 2019
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Cloud segmentation plays a very important role in astronomical observatory site selection. At present, few researchers segment cloud in nocturnal all-sky imager (ASI) images. We propose a new automatic cloud segmentation algorithm to segment cloud pixels from diurnal and nocturnal ASI images called an enhancement fully convolutional network (EFCN). Experiments showed that the proposed EFCN was much more accurate in cloud segmentation for diurnal and nocturnal ASI images.
Maximilian Maahn, Fabian Hoffmann, Matthew D. Shupe, Gijs de Boer, Sergey Y. Matrosov, and Edward P. Luke
Atmos. Meas. Tech., 12, 3151–3171, https://doi.org/10.5194/amt-12-3151-2019, https://doi.org/10.5194/amt-12-3151-2019, 2019
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Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Here, we present three novel methods for calibrating vertically pointing cloud radars. These calibration methods are based on microphysical processes of liquid clouds, such as the transition of cloud droplets to drizzle drops. We successfully apply the methods to cloud radar data from the North Slope of Alaska (NSA) and Oliktok Point (OLI) ARM sites.
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Short summary
Satellite remote sensing retrievals of cloud droplet size are used to understand clouds and their interactions with aerosols and radiation but require many simplifying assumptions. Evaluation of these retrievals is typically done by comparing against direct measurements of droplets from airborne cloud probes. This paper details an evaluation of proxy airborne remote sensing droplet size retrievals against several cloud probes and explores the impact of key assumptions on retrieval agreement.
Satellite remote sensing retrievals of cloud droplet size are used to understand clouds and...
