Articles | Volume 11, issue 7
Atmos. Meas. Tech., 11, 4273–4289, 2018
https://doi.org/10.5194/amt-11-4273-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 11, 4273–4289, 2018
https://doi.org/10.5194/amt-11-4273-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 20 Jul 2018
Research article | 20 Jul 2018
Parameterizing cloud top effective radii from satellite retrieved values, accounting for vertical photon transport: quantification and correction of the resulting bias in droplet concentration and liquid water path retrievals
Daniel P. Grosvenor et al.
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Matthew Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel McCoy, Daniel 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. Discuss., https://doi.org/10.5194/acp-2021-559, https://doi.org/10.5194/acp-2021-559, 2021
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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.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Daniel P. Grosvenor and Kenneth S. Carslaw
Atmos. Chem. Phys., 20, 15681–15724, https://doi.org/10.5194/acp-20-15681-2020, https://doi.org/10.5194/acp-20-15681-2020, 2020
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Particles arising from human activity interact with clouds and affect how much of the Sun's energy is reflected away. Lack of understanding about how to represent this in models leads to large uncertainties in climate predictions. We quantify cloud responses to particles in the latest UK Met Office climate model over the North Atlantic Ocean, showing that, in contrast to suggestions elsewhere, increases in cloud coverage and thickness are important over large areas.
Hamish Gordon, Paul R. Field, Steven J. Abel, Paul Barrett, Keith Bower, Ian Crawford, Zhiqiang Cui, Daniel P. Grosvenor, Adrian A. Hill, Jonathan Taylor, Jonathan Wilkinson, Huihui Wu, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10997–11024, https://doi.org/10.5194/acp-20-10997-2020, https://doi.org/10.5194/acp-20-10997-2020, 2020
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The Met Office's Unified Model is widely used both for weather forecasting and climate prediction. We present the first version of the model in which both aerosol and cloud particle mass and number concentrations are allowed to evolve separately and independently, which is important for studying how aerosols affect weather and climate. We test the model against aircraft observations near Ascension Island in the Atlantic, focusing on how aerosols can "activate" to become cloud droplets.
Leighton A. Regayre, Julia Schmale, Jill S. Johnson, Christian Tatzelt, Andrea Baccarini, Silvia Henning, Masaru Yoshioka, Frank Stratmann, Martin Gysel-Beer, Daniel P. Grosvenor, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10063–10072, https://doi.org/10.5194/acp-20-10063-2020, https://doi.org/10.5194/acp-20-10063-2020, 2020
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The amount of energy reflected back into space because of man-made particles is highly uncertain. Processes related to naturally occurring particles cause most of the uncertainty, but these processes are poorly constrained by present-day measurements. We show that measurements over the Southern Ocean, far from pollution sources, efficiently reduce climate model uncertainties. Our results pave the way to designing experiments and measurement campaigns that reduce this uncertainty even further.
Daniel T. McCoy, Paul Field, Hamish Gordon, Gregory S. Elsaesser, and Daniel P. Grosvenor
Atmos. Chem. Phys., 20, 4085–4103, https://doi.org/10.5194/acp-20-4085-2020, https://doi.org/10.5194/acp-20-4085-2020, 2020
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Incomplete understanding of how aerosol affects clouds degrades our ability to predict future climate. In particular, it is unclear how aerosol affects the lifetime of clouds. Does it increase or decrease it? This confusion is partially because causality flows from aerosol to clouds and clouds to aerosol, and it is hard to tell what is happening in observations. Here, we use simulations to tell us about how clouds affect aerosol and use this to interpret observations, showing increased lifetime.
Hamish Gordon, Paul R. Field, Steven J. Abel, Mohit Dalvi, Daniel P. Grosvenor, Adrian A. Hill, Ben T. Johnson, Annette K. Miltenberger, Masaru Yoshioka, and Ken S. Carslaw
Atmos. Chem. Phys., 18, 15261–15289, https://doi.org/10.5194/acp-18-15261-2018, https://doi.org/10.5194/acp-18-15261-2018, 2018
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Smoke from African fires is frequently transported across the Atlantic Ocean, where it interacts with clouds. We simulate the interaction of the smoke with the clouds, and the consequences of this for the solar radiation the clouds reflect. The simulations use a new regional configuration of the UK Met Office climate model. Our simulations indicate that the properties of the clouds, in particular their height and reflectivity, and the fractional cloud cover, are strongly affected by the smoke.
Daniel T. McCoy, Paul R. Field, Anja Schmidt, Daniel P. Grosvenor, Frida A.-M. Bender, Ben J. Shipway, Adrian A. Hill, Jonathan M. Wilkinson, and Gregory S. Elsaesser
Atmos. Chem. Phys., 18, 5821–5846, https://doi.org/10.5194/acp-18-5821-2018, https://doi.org/10.5194/acp-18-5821-2018, 2018
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Here we use a combination of global convection-permitting models, satellite observations and the Holuhraun volcanic eruption to demonstrate that aerosol enhances the cloud liquid content and brightness of midlatitude cyclones. This is important because the strength of anthropogenic radiative forcing is uncertain, leading to uncertainty in the climate sensitivity consistent with observed temperature record.
Daniel T. McCoy, Frida A.-M. Bender, Daniel P. Grosvenor, Johannes K. Mohrmann, Dennis L. Hartmann, Robert Wood, and Paul R. Field
Atmos. Chem. Phys., 18, 2035–2047, https://doi.org/10.5194/acp-18-2035-2018, https://doi.org/10.5194/acp-18-2035-2018, 2018
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The interaction between clouds and aerosols represents the largest source of uncertainty in the anthropogenic radiative forcing. Cloud droplet number concentration (CDNC) is the state variable that moderates the interaction between aerosol and clouds. Here we show that CDNC decreases off the coasts of East Asia and North America due to controls on emissions. We support this analysis through an examination of volcanism in Hawaii and Vanuatu.
Daniel P. Grosvenor, Paul R. Field, Adrian A. Hill, and Benjamin J. Shipway
Atmos. Chem. Phys., 17, 5155–5183, https://doi.org/10.5194/acp-17-5155-2017, https://doi.org/10.5194/acp-17-5155-2017, 2017
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We used a weather model to simulate low-level layer clouds that lie off the coast of Chile and tested how they would be affected by airborne particulate matter (aerosols) according to the model. We found that as aerosols were increased, the clouds reflected more and more of the sun’s incoming energy due to the combined effects of the cloud droplets becoming smaller, the thickening of clouds, and increased areal coverage. However, the latter two effects were only important at low aerosol levels.
D. P. Grosvenor, J. C. King, T. W. Choularton, and T. Lachlan-Cope
Atmos. Chem. Phys., 14, 9481–9509, https://doi.org/10.5194/acp-14-9481-2014, https://doi.org/10.5194/acp-14-9481-2014, 2014
D. P. Grosvenor and R. Wood
Atmos. Chem. Phys., 14, 7291–7321, https://doi.org/10.5194/acp-14-7291-2014, https://doi.org/10.5194/acp-14-7291-2014, 2014
Matthew Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel McCoy, Daniel 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. Discuss., https://doi.org/10.5194/acp-2021-559, https://doi.org/10.5194/acp-2021-559, 2021
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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.
Yang Wang, Guangjie Zheng, Michael P. Jensen, Daniel A. Knopf, Alexander Laskin, Alyssa A. Matthews, David Mechem, Fan Mei, Ryan Moffet, Arthur J. Sedlacek, John E. Shilling, Stephen Springston, Amy Sullivan, Jason Tomlinson, Daniel Veghte, Rodney Weber, Robert Wood, Maria A. Zawadowicz, and Jian Wang
Atmos. Chem. Phys., 21, 11079–11098, https://doi.org/10.5194/acp-21-11079-2021, https://doi.org/10.5194/acp-21-11079-2021, 2021
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This paper reports the vertical profiles of trace gas and aerosol properties over the eastern North Atlantic, a region of persistent but diverse subtropical marine boundary layer (MBL) clouds. We examined the key processes that drive the cloud condensation nuclei (CCN) population and how it varies with season and synoptic conditions. This study helps improve the model representation of the aerosol processes in the remote MBL, reducing the simulated aerosol indirect effects.
Kristina Pistone, Paquita Zuidema, Robert Wood, Michael Diamond, Arlindo M. da Silva, Gonzalo Ferrada, Pablo E. Saide, Rei Ueyama, Ju-Mee Ryoo, Leonhard Pfister, James Podolske, David Noone, Ryan Bennett, Eric Stith, Gregory Carmichael, Jens Redemann, Connor Flynn, Samuel LeBlanc, Michal Segal-Rozenhaimer, and Yohei Shinozuka
Atmos. Chem. Phys., 21, 9643–9668, https://doi.org/10.5194/acp-21-9643-2021, https://doi.org/10.5194/acp-21-9643-2021, 2021
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Using aircraft-based measurements off the Atlantic coast of Africa, we found the springtime smoke plume was strongly correlated with the amount of water vapor in the atmosphere (more smoke indicated more humidity). We see the same general feature in satellite-assimilated and free-running models. Our analysis suggests this relationship is not caused by the burning but originates due to coincident continental meteorology plus fires. This air is transported over the ocean without further mixing.
Johannes Mohrmann, Robert Wood, Tianle Yuan, Hua Song, Ryan Eastman, and Lazaros Oreopoulos
Atmos. Chem. Phys., 21, 9629–9642, https://doi.org/10.5194/acp-21-9629-2021, https://doi.org/10.5194/acp-21-9629-2021, 2021
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Observations of marine-boundary-layer conditions are composited by cloud type, based on a new classification dataset. It is found that two cloud types, representing regions of clustered and suppressed low-level clouds, occur in very similar large-scale conditions but are distinguished from each other by considering low-level circulation and surface wind fields, validating prior results from modeling.
Maria A. Zawadowicz, Kaitlyn Suski, Jiumeng Liu, Mikhail Pekour, Jerome Fast, Fan Mei, Arthur J. Sedlacek, Stephen Springston, Yang Wang, Rahul A. Zaveri, Robert Wood, Jian Wang, and John E. Shilling
Atmos. Chem. Phys., 21, 7983–8002, https://doi.org/10.5194/acp-21-7983-2021, https://doi.org/10.5194/acp-21-7983-2021, 2021
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This paper describes the results of a recent field campaign in the eastern North Atlantic, where two mass spectrometers were deployed aboard a research aircraft to measure the chemistry of aerosols and trace gases. Very clean conditions were found, dominated by local sulfate-rich acidic aerosol and very aged organics. Evidence of
long-range transport of aerosols from the continents was also identified.
Robert Wood
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-327, https://doi.org/10.5194/acp-2021-327, 2021
Revised manuscript accepted for ACP
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A simple model is described to assess the potential for increasing solar reflection by augmenting the aerosol population below marine low clouds, which increases the concentration of cloud droplets. The model is used to predict global cooling from marine cloud brightening climate intervention as a function of the quantity, size, and lifetime of salt particles injected per sprayer, the number of sprayers deployed, the cloud updraft speed and unperturbed aerosol size distribution.
Rachel Atlas, Johannes Mohrmann, Joseph Finlon, Jeremy Lu, Ian Hsiao, Robert Wood, and Minghui Diao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-123, https://doi.org/10.5194/amt-2021-123, 2021
Revised manuscript accepted for AMT
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Many clouds with temperatures between 0 °C and −40 °C contain both liquid and ice particles and the ratio of liquid to ice particles influences how the clouds interact with radiation and moderate Earth's climate. Here, we use a machine learning method called random forest to classify images of individual cloud particles as either liquid or ice. We apply our algorithm to images captured by aircraft within clouds overlying the Southern Ocean and we find that it outperforms two existing algorithms.
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. Discuss., https://doi.org/10.5194/acp-2021-333, https://doi.org/10.5194/acp-2021-333, 2021
Preprint under review for ACP
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Between July and October, biomass burning smoke is advected over the southeast 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 how these biases propagate to biases in forcing.
Ju-Mee Ryoo, Leonhard Pfister, Rei Ueyama, Paquita Zuidema, Robert Wood, Ian Chang, and Jens Redemann
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-274, https://doi.org/10.5194/acp-2021-274, 2021
Revised manuscript under review for ACP
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Meteorology influences the aerosol-cloud interaction. Thus, it is critical to understand the meteorological characteristics during the deployment to better interpret the airborne measurement. Furthermore, it is crucial to know how different they are compared to the climatological mean in various temporal and spatial scales. This paper provides a thorough overview of the meteorology reflecting the coupled land-ocean-atmosphere system and the representativeness of the deployment months.
Sara Bacer, Sylvia C. Sullivan, Odran Sourdeval, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Atmos. Chem. Phys., 21, 1485–1505, https://doi.org/10.5194/acp-21-1485-2021, https://doi.org/10.5194/acp-21-1485-2021, 2021
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We investigate the relative importance of the rates of both microphysical processes and unphysical correction terms that act as sources or sinks of ice crystals in cold clouds. By means of numerical simulations performed with a global chemistry–climate model, we assess the relevance of these rates at global and regional scales. This estimation is of fundamental importance to assign priority to the development of microphysics parameterizations and compare model output with observations.
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.
Jim M. Haywood, Steven J. Abel, Paul A. Barrett, Nicolas Bellouin, Alan Blyth, Keith N. Bower, Melissa Brooks, Ken Carslaw, Haochi Che, Hugh Coe, Michael I. Cotterell, Ian Crawford, Zhiqiang Cui, Nicholas Davies, Beth Dingley, Paul Field, Paola Formenti, Hamish Gordon, Martin de Graaf, Ross Herbert, Ben Johnson, Anthony C. Jones, Justin M. Langridge, Florent Malavelle, Daniel G. Partridge, Fanny Peers, Jens Redemann, Philip Stier, Kate Szpek, Jonathan W. Taylor, Duncan Watson-Parris, Robert Wood, Huihui Wu, and Paquita Zuidema
Atmos. Chem. Phys., 21, 1049–1084, https://doi.org/10.5194/acp-21-1049-2021, https://doi.org/10.5194/acp-21-1049-2021, 2021
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Every year, the seasonal cycle of biomass burning from agricultural practices in Africa creates a huge plume of smoke that travels many thousands of kilometres over the Atlantic Ocean. This study provides an overview of a measurement campaign called the cloud–aerosol–radiation interaction and forcing for year 2017 (CLARIFY-2017) and documents the rationale, deployment strategy, observations, and key results from the campaign which utilized the heavily equipped FAAM atmospheric research aircraft.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
Short summary
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
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.
Daniel P. Grosvenor and Kenneth S. Carslaw
Atmos. Chem. Phys., 20, 15681–15724, https://doi.org/10.5194/acp-20-15681-2020, https://doi.org/10.5194/acp-20-15681-2020, 2020
Short summary
Short summary
Particles arising from human activity interact with clouds and affect how much of the Sun's energy is reflected away. Lack of understanding about how to represent this in models leads to large uncertainties in climate predictions. We quantify cloud responses to particles in the latest UK Met Office climate model over the North Atlantic Ocean, showing that, in contrast to suggestions elsewhere, increases in cloud coverage and thickness are important over large areas.
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.
Martina Krämer, Christian Rolf, Nicole Spelten, Armin Afchine, David Fahey, Eric Jensen, Sergey Khaykin, Thomas Kuhn, Paul Lawson, Alexey Lykov, Laura L. Pan, Martin Riese, Andrew Rollins, Fred Stroh, Troy Thornberry, Veronika Wolf, Sarah Woods, Peter Spichtinger, Johannes Quaas, and Odran Sourdeval
Atmos. Chem. Phys., 20, 12569–12608, https://doi.org/10.5194/acp-20-12569-2020, https://doi.org/10.5194/acp-20-12569-2020, 2020
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To improve the representations of cirrus clouds in climate predictions, extended knowledge of their properties and geographical distribution is required. This study presents extensive airborne in situ and satellite remote sensing climatologies of cirrus and humidity, which serve as a guide to cirrus clouds. Further, exemplary radiative characteristics of cirrus types and also in situ observations of tropical tropopause layer cirrus and humidity in the Asian monsoon anticyclone are shown.
Yohei Shinozuka, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon, Karla Longo, Marc Mallet, Yan Feng, Qiaoqiao Wang, Yafang Cheng, Amie Dobracki, Steffen Freitag, Steven G. Howell, Samuel LeBlanc, Connor Flynn, Michal Segal-Rosenhaimer, Kristina Pistone, James R. Podolske, Eric J. Stith, Joseph Ryan Bennett, Gregory R. Carmichael, Arlindo da Silva, Ravi Govindaraju, Ruby Leung, Yang Zhang, Leonhard Pfister, Ju-Mee Ryoo, Jens Redemann, Robert Wood, and Paquita Zuidema
Atmos. Chem. Phys., 20, 11491–11526, https://doi.org/10.5194/acp-20-11491-2020, https://doi.org/10.5194/acp-20-11491-2020, 2020
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In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016.
Hamish Gordon, Paul R. Field, Steven J. Abel, Paul Barrett, Keith Bower, Ian Crawford, Zhiqiang Cui, Daniel P. Grosvenor, Adrian A. Hill, Jonathan Taylor, Jonathan Wilkinson, Huihui Wu, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10997–11024, https://doi.org/10.5194/acp-20-10997-2020, https://doi.org/10.5194/acp-20-10997-2020, 2020
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The Met Office's Unified Model is widely used both for weather forecasting and climate prediction. We present the first version of the model in which both aerosol and cloud particle mass and number concentrations are allowed to evolve separately and independently, which is important for studying how aerosols affect weather and climate. We test the model against aircraft observations near Ascension Island in the Atlantic, focusing on how aerosols can "activate" to become cloud droplets.
Leighton A. Regayre, Julia Schmale, Jill S. Johnson, Christian Tatzelt, Andrea Baccarini, Silvia Henning, Masaru Yoshioka, Frank Stratmann, Martin Gysel-Beer, Daniel P. Grosvenor, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10063–10072, https://doi.org/10.5194/acp-20-10063-2020, https://doi.org/10.5194/acp-20-10063-2020, 2020
Short summary
Short summary
The amount of energy reflected back into space because of man-made particles is highly uncertain. Processes related to naturally occurring particles cause most of the uncertainty, but these processes are poorly constrained by present-day measurements. We show that measurements over the Southern Ocean, far from pollution sources, efficiently reduce climate model uncertainties. Our results pave the way to designing experiments and measurement campaigns that reduce this uncertainty even further.
Francesca Gallo, Janek Uin, Stephen Springston, Jian Wang, Guangjie Zheng, Chongai Kuang, Robert Wood, Eduardo B. Azevedo, Allison McComiskey, Fan Mei, Adam Theisen, Jenni Kyrouac, and Allison C. Aiken
Atmos. Chem. Phys., 20, 7553–7573, https://doi.org/10.5194/acp-20-7553-2020, https://doi.org/10.5194/acp-20-7553-2020, 2020
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Continuous high-time-resolution ambient data can include periods when aerosol properties do not represent regional aerosol processes due to high-concentration local events. We develop a novel aerosol mask at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) facility in the eastern North Atlantic (ENA). We use two ground sites to validate the mask, include a comparison with aircraft overflights, and provide guidance to increase data quality at ENA and other locations.
Montserrat Costa-Surós, Odran Sourdeval, Claudia Acquistapace, Holger Baars, Cintia Carbajal Henken, Christa Genz, Jonas Hesemann, Cristofer Jimenez, Marcel König, Jan Kretzschmar, Nils Madenach, Catrin I. Meyer, Roland Schrödner, Patric Seifert, Fabian Senf, Matthias Brueck, Guido Cioni, Jan Frederik Engels, Kerstin Fieg, Ksenia Gorges, Rieke Heinze, Pavan Kumar Siligam, Ulrike Burkhardt, Susanne Crewell, Corinna Hoose, Axel Seifert, Ina Tegen, and Johannes Quaas
Atmos. Chem. Phys., 20, 5657–5678, https://doi.org/10.5194/acp-20-5657-2020, https://doi.org/10.5194/acp-20-5657-2020, 2020
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The impact of anthropogenic aerosols on clouds is a key uncertainty in climate change. This study analyses large-domain simulations with a new high-resolution model to investigate the differences in clouds between 1985 and 2013 comparing multiple observational datasets. The differences in aerosol and in cloud droplet concentrations are clearly detectable. For other quantities, the detection and attribution proved difficult, despite a substantial impact on the Earth's energy budget.
Daniel T. McCoy, Paul Field, Hamish Gordon, Gregory S. Elsaesser, and Daniel P. Grosvenor
Atmos. Chem. Phys., 20, 4085–4103, https://doi.org/10.5194/acp-20-4085-2020, https://doi.org/10.5194/acp-20-4085-2020, 2020
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Incomplete understanding of how aerosol affects clouds degrades our ability to predict future climate. In particular, it is unclear how aerosol affects the lifetime of clouds. Does it increase or decrease it? This confusion is partially because causality flows from aerosol to clouds and clouds to aerosol, and it is hard to tell what is happening in observations. Here, we use simulations to tell us about how clouds affect aerosol and use this to interpret observations, showing increased lifetime.
Mary Kacarab, K. Lee Thornhill, Amie Dobracki, Steven G. Howell, Joseph R. O'Brien, Steffen Freitag, Michael R. Poellot, Robert Wood, Paquita Zuidema, Jens Redemann, and Athanasios Nenes
Atmos. Chem. Phys., 20, 3029–3040, https://doi.org/10.5194/acp-20-3029-2020, https://doi.org/10.5194/acp-20-3029-2020, 2020
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We find that extensive biomass burning aerosol plumes from southern Africa can profoundly influence clouds in the southeastern Atlantic. Concurrent variations in vertical velocity, however, are found to magnify the relationship between boundary layer aerosol and the cloud droplet number. Neglecting these covariances may strongly bias the sign and magnitude of aerosol impacts on the cloud droplet number.
Claudia Unglaub, Karoline Block, Johannes Mülmenstädt, Odran Sourdeval, and Johannes Quaas
Atmos. Chem. Phys., 20, 2407–2418, https://doi.org/10.5194/acp-20-2407-2020, https://doi.org/10.5194/acp-20-2407-2020, 2020
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In cloud research, it is necessary to classify clouds. The World Meteorological Organization proposes distinguishing stratiform and cumuliform clouds in three altitude layers. The paper explains why previous approaches to classify clouds fail for many applications and proposes a new classification on the basis of new approaches for satellite retrievals to derive cloud-base height, in combination with cloud inhomogeneity. It is demonstrated that this discriminates cloud characteristics well.
Sam Pennypacker, Michael Diamond, and Robert Wood
Atmos. Chem. Phys., 20, 2341–2351, https://doi.org/10.5194/acp-20-2341-2020, https://doi.org/10.5194/acp-20-2341-2020, 2020
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Using observations from instruments deployed to a small island in the southeast Atlantic, we study days when the atmospheric concentrations of particles near the surface are exceptionally low. Interestingly, these ultra-clean boundary layers occur in the same months as the smokiest boundary layers associated with biomass burning in Africa. We find evidence that enhancements in drizzle scavenging, on top of a seasonal maximum in cloudiness and precipitation, likely drive these conditions.
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.
Nils Madenach, Cintia Carbajal Henken, René Preusker, Odran Sourdeval, and Jürgen Fischer
Atmos. Chem. Phys., 19, 13535–13546, https://doi.org/10.5194/acp-19-13535-2019, https://doi.org/10.5194/acp-19-13535-2019, 2019
Edward Gryspeerdt, Tom Goren, Odran Sourdeval, Johannes Quaas, Johannes Mülmenstädt, Sudhakar Dipu, Claudia Unglaub, Andrew Gettelman, and Matthew Christensen
Atmos. Chem. Phys., 19, 5331–5347, https://doi.org/10.5194/acp-19-5331-2019, https://doi.org/10.5194/acp-19-5331-2019, 2019
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The liquid water path (LWP) is the strongest control on cloud albedo, such that a small change in LWP can have a large radiative impact. By changing the droplet number concentration (Nd) aerosols may be able to change the LWP, but the sign and magnitude of the effect is unclear. This work uses satellite data to investigate the relationship between Nd and LWP at a global scale and in response to large aerosol perturbations, suggesting that a strong decrease in LWP at high Nd may be overestimated.
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.
Christoph Böhm, Odran Sourdeval, Johannes Mülmenstädt, Johannes Quaas, and Susanne Crewell
Atmos. Meas. Tech., 12, 1841–1860, https://doi.org/10.5194/amt-12-1841-2019, https://doi.org/10.5194/amt-12-1841-2019, 2019
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The cloud base height (CBH) is important for air traffic, for describing the energy budget of the Earth and for other applications. Ground-based CBH measurements are only available for individual sites and mostly limited to land. Satellites are a powerful tool for global coverage. While the cloud top height is derived operationally, the derivation of CBH from space is more difficult as the clouds hide their base. Here, we present a method to retrieve the CBH from multi-angle satellite data.
Johannes Mülmenstädt, Odran Sourdeval, David S. Henderson, Tristan S. L'Ecuyer, Claudia Unglaub, Leonore Jungandreas, Christoph Böhm, Lynn M. Russell, and Johannes Quaas
Earth Syst. Sci. Data, 10, 2279–2293, https://doi.org/10.5194/essd-10-2279-2018, https://doi.org/10.5194/essd-10-2279-2018, 2018
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One of the key pieces of information about a cloud is how high its base is. Unlike cloud top, cloud base is hard to observe from a satellite perspective – the cloud blocks the view. But without using satellites, it is difficult to compile global datasets. Here we describe how we worked around the limitations of a cloud-detecting laser satellite to observe global cloud base heights. This dataset will expand our knowledge of the cloudy atmosphere and its interaction with the planetary surface.
Guangjie Zheng, Yang Wang, Allison C. Aiken, Francesca Gallo, Michael P. Jensen, Pavlos Kollias, Chongai Kuang, Edward Luke, Stephen Springston, Janek Uin, Robert Wood, and Jian Wang
Atmos. Chem. Phys., 18, 17615–17635, https://doi.org/10.5194/acp-18-17615-2018, https://doi.org/10.5194/acp-18-17615-2018, 2018
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Here, we elucidate the key processes that drive marine boundary layer (MBL) aerosol size distribution in the eastern North Atlantic (ENA) using long-term measurements. The governing equations of particle concentration are established for different modes. Particles entrained from the free troposphere represent the major source of MBL cloud condensation nuclei (CCN), contributing both directly to CCN population and indirectly by supplying Aitken-mode particles that grow to CCN in the MBL.
Anna Possner, Hailong Wang, Robert Wood, Ken Caldeira, and Thomas P. Ackerman
Atmos. Chem. Phys., 18, 17475–17488, https://doi.org/10.5194/acp-18-17475-2018, https://doi.org/10.5194/acp-18-17475-2018, 2018
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We quantify aerosol–cloud radiative interactions in a regime of deep open-cell stratocumuli (boundary layer depth 1.5 km), a regime which remains largely unexplored within this context and yet is more dominant than cases of shallow stratocumuli previously studied. We simulate substantial increases in albedo in a regime where ship tracks are not found and argue that such changes may escape detection and attribution through remote sensing due to the large natural variability in the system.
Hamish Gordon, Paul R. Field, Steven J. Abel, Mohit Dalvi, Daniel P. Grosvenor, Adrian A. Hill, Ben T. Johnson, Annette K. Miltenberger, Masaru Yoshioka, and Ken S. Carslaw
Atmos. Chem. Phys., 18, 15261–15289, https://doi.org/10.5194/acp-18-15261-2018, https://doi.org/10.5194/acp-18-15261-2018, 2018
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Smoke from African fires is frequently transported across the Atlantic Ocean, where it interacts with clouds. We simulate the interaction of the smoke with the clouds, and the consequences of this for the solar radiation the clouds reflect. The simulations use a new regional configuration of the UK Met Office climate model. Our simulations indicate that the properties of the clouds, in particular their height and reflectivity, and the fractional cloud cover, are strongly affected by the smoke.
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.
Odran Sourdeval, Edward Gryspeerdt, Martina Krämer, Tom Goren, Julien Delanoë, Armin Afchine, Friederike Hemmer, and Johannes Quaas
Atmos. Chem. Phys., 18, 14327–14350, https://doi.org/10.5194/acp-18-14327-2018, https://doi.org/10.5194/acp-18-14327-2018, 2018
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The number concentration of ice crystals (Ni) is a key cloud property that remains very uncertain due to difficulties in determining it using satellites. This lack of global observational constraints limits our ability to constrain this property in models responsible for predicting future climate. This pair of papers fills this gap by showing and analyzing the first rigorously evaluated global climatology of Ni, leading to new information shedding light on the processes that control high clouds.
Edward Gryspeerdt, Odran Sourdeval, Johannes Quaas, Julien Delanoë, Martina Krämer, and Philipp Kühne
Atmos. Chem. Phys., 18, 14351–14370, https://doi.org/10.5194/acp-18-14351-2018, https://doi.org/10.5194/acp-18-14351-2018, 2018
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The concentration of ice crystals in a cloud affects both the properties and the life cycle of the cloud. This work uses a new satellite retrieval to investigate controls on the ice crystal concentration at a global scale. Both temperature and vertical wind speed in a cloud have a strong impact on the concentration of ice crystals. The ice crystal number is also related to the aerosol environment; defining this relation opens up new ways to investigate human impacts on clouds and the climate.
Daniel T. McCoy, Paul R. Field, Anja Schmidt, Daniel P. Grosvenor, Frida A.-M. Bender, Ben J. Shipway, Adrian A. Hill, Jonathan M. Wilkinson, and Gregory S. Elsaesser
Atmos. Chem. Phys., 18, 5821–5846, https://doi.org/10.5194/acp-18-5821-2018, https://doi.org/10.5194/acp-18-5821-2018, 2018
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Here we use a combination of global convection-permitting models, satellite observations and the Holuhraun volcanic eruption to demonstrate that aerosol enhances the cloud liquid content and brightness of midlatitude cyclones. This is important because the strength of anthropogenic radiative forcing is uncertain, leading to uncertainty in the climate sensitivity consistent with observed temperature record.
Daniel T. McCoy, Frida A.-M. Bender, Daniel P. Grosvenor, Johannes K. Mohrmann, Dennis L. Hartmann, Robert Wood, and Paul R. Field
Atmos. Chem. Phys., 18, 2035–2047, https://doi.org/10.5194/acp-18-2035-2018, https://doi.org/10.5194/acp-18-2035-2018, 2018
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The interaction between clouds and aerosols represents the largest source of uncertainty in the anthropogenic radiative forcing. Cloud droplet number concentration (CDNC) is the state variable that moderates the interaction between aerosol and clouds. Here we show that CDNC decreases off the coasts of East Asia and North America due to controls on emissions. We support this analysis through an examination of volcanism in Hawaii and Vanuatu.
Xiaoli Zhou, Andrew S. Ackerman, Ann M. Fridlind, Robert Wood, and Pavlos Kollias
Atmos. Chem. Phys., 17, 12725–12742, https://doi.org/10.5194/acp-17-12725-2017, https://doi.org/10.5194/acp-17-12725-2017, 2017
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Shallow maritime clouds make a well-known transition from stratocumulus to trade cumulus with flow from the subtropics equatorward. Three-day large-eddy simulations that investigate the potential influence of overlying African biomass burning plumes during that transition indicate that cloud-related impacts are likely substantially cooling to negligible at the top of the atmosphere, with magnitude sensitive to background and perturbation aerosol and cloud properties.
Daniel P. Grosvenor, Paul R. Field, Adrian A. Hill, and Benjamin J. Shipway
Atmos. Chem. Phys., 17, 5155–5183, https://doi.org/10.5194/acp-17-5155-2017, https://doi.org/10.5194/acp-17-5155-2017, 2017
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We used a weather model to simulate low-level layer clouds that lie off the coast of Chile and tested how they would be affected by airborne particulate matter (aerosols) according to the model. We found that as aerosols were increased, the clouds reflected more and more of the sun’s incoming energy due to the combined effects of the cloud droplets becoming smaller, the thickening of clouds, and increased areal coverage. However, the latter two effects were only important at low aerosol levels.
Kuan-Ting O and Robert Wood
Atmos. Chem. Phys., 16, 7239–7249, https://doi.org/10.5194/acp-16-7239-2016, https://doi.org/10.5194/acp-16-7239-2016, 2016
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In this work, based on the well-known formulae of classical nucleation theory (CNT), the temperature at which the mean number of critical embryos inside a droplet is unity is derived from the Boltzmann distribution function and explored as a new simplified approximation for homogeneous freezing temperature. It thus appears that the simplicity of this approximation makes it potentially useful for predicting homogeneous freezing temperatures of water droplets in the atmosphere.
D. P. Grosvenor, J. C. King, T. W. Choularton, and T. Lachlan-Cope
Atmos. Chem. Phys., 14, 9481–9509, https://doi.org/10.5194/acp-14-9481-2014, https://doi.org/10.5194/acp-14-9481-2014, 2014
C. R. Terai, C. S. Bretherton, R. Wood, and G. Painter
Atmos. Chem. Phys., 14, 8071–8088, https://doi.org/10.5194/acp-14-8071-2014, https://doi.org/10.5194/acp-14-8071-2014, 2014
D. P. Grosvenor and R. Wood
Atmos. Chem. Phys., 14, 7291–7321, https://doi.org/10.5194/acp-14-7291-2014, https://doi.org/10.5194/acp-14-7291-2014, 2014
A. Muhlbauer, I. L. McCoy, and R. Wood
Atmos. Chem. Phys., 14, 6695–6716, https://doi.org/10.5194/acp-14-6695-2014, https://doi.org/10.5194/acp-14-6695-2014, 2014
A. H. Berner, C. S. Bretherton, R. Wood, and A. Muhlbauer
Atmos. Chem. Phys., 13, 12549–12572, https://doi.org/10.5194/acp-13-12549-2013, https://doi.org/10.5194/acp-13-12549-2013, 2013
C. R. Terai and R. Wood
Atmos. Chem. Phys., 13, 9899–9914, https://doi.org/10.5194/acp-13-9899-2013, https://doi.org/10.5194/acp-13-9899-2013, 2013
A. Gettelman, H. Morrison, C. R. Terai, and R. Wood
Atmos. Chem. Phys., 13, 9855–9867, https://doi.org/10.5194/acp-13-9855-2013, https://doi.org/10.5194/acp-13-9855-2013, 2013
O. Sourdeval, L. C. -Labonnote, G. Brogniez, O. Jourdan, J. Pelon, and A. Garnier
Atmos. Chem. Phys., 13, 8229–8244, https://doi.org/10.5194/acp-13-8229-2013, https://doi.org/10.5194/acp-13-8229-2013, 2013
R. C. George, R. Wood, C. S. Bretherton, and G. Painter
Atmos. Chem. Phys., 13, 6305–6328, https://doi.org/10.5194/acp-13-6305-2013, https://doi.org/10.5194/acp-13-6305-2013, 2013
C. H. Twohy, J. R. Anderson, D. W. Toohey, M. Andrejczuk, A. Adams, M. Lytle, R. C. George, R. Wood, P. Saide, S. Spak, P. Zuidema, and D. Leon
Atmos. Chem. Phys., 13, 2541–2562, https://doi.org/10.5194/acp-13-2541-2013, https://doi.org/10.5194/acp-13-2541-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Physical characteristics of frozen hydrometeors inferred with parameter estimation
Cloud height measurement by a network of all-sky imagers
Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples
Why we need radar, lidar, and solar radiance observations to constrain ice cloud microphysics
Estimating the optical extinction of liquid water clouds in the cloud base region
W-band radar observations for fog forecast improvement: an analysis of model and forward operator errors
Identification of snowfall microphysical processes from Eulerian vertical gradients of polarimetric radar variables
Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra
MICRU: an effective cloud fraction algorithm designed for UV–vis satellite instruments with large viewing angles
A simplified method for the detection of convection using high-resolution imagery from GOES-16
Introducing hydrometeor orientation into all-sky microwave and submillimeter assimilation
Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part II: Results over oceans
Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms
Observation of cirrus clouds with GLORIA during the WISE campaign: detection methods and cirrus characterization
Applying machine learning methods to detect convection using Geostationary Operational Environmental Satellite-16 (GOES-16) advanced baseline imager (ABI) data
A new method to detect and classify polar stratospheric nitric acid trihydrate clouds derived from radiative transfer simulations and its first application to airborne infrared limb emission observations
A study of polarimetric error induced by satellite motion: application to the 3MI and similar sensors
A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar
Two-dimensional and multi-channel feature detection algorithm for the CALIPSO lidar measurements
Analysis of 3D cloud effects in OCO-2 XCO2 retrievals
Improving cloud type classification of ground-based images using region covariance descriptors
Global cloud property models for real-time triage on board visible–shortwave infrared spectrometers
Applying deep learning to NASA MODIS data to create a community record of marine low-cloud mesoscale morphology
Microwave single-scattering properties of non-spheroidal raindrops
Determining cloud thermodynamic phase from the polarized Micro Pulse Lidar
Improved cloud detection over sea ice and snow during Arctic summer using MERIS data
A kernel-driven BRDF model to inform satellite-derived visible anvil cloud detection
Cloud-top pressure retrieval with DSCOVR EPIC oxygen A- and B-band observations
Estimating total attenuation using Rayleigh targets at cloud top: applications in multilayer and mixed-phase clouds observed by ground-based multifrequency radars
A new Orbiting Carbon Observatory 2 cloud flagging method and rapid retrieval of marine boundary layer cloud properties
CALIOP V4 cloud thermodynamic phase assignment and the impact of near-nadir viewing angles
Detection of the cloud liquid water path horizontal inhomogeneity in a coastline area by means of ground-based microwave observations: feasibility study
Synergistic radar and radiometer retrievals of ice hydrometeors
Improvement in cloud retrievals from VIIRS through the use of infrared absorption channels constructed from VIIRS+CrIS data fusion
Using two-stream theory to capture fluctuations of satellite-perceived TOA SW radiances reflected from clouds over ocean
Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds
Three-dimensional wind profiles using a stabilized shipborne cloud radar in wind profiler mode
Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm
A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations
SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements
Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery
Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)
Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds
Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: evaluation of candidate approaches with MODIS observations
Estimation of cloud optical thickness, single scattering albedo and effective droplet radius using a shortwave radiative closure study in Payerne
Towards an operational Ice Cloud Imager (ICI) retrieval product
Ice crystal number concentration from lidar, cloud radar and radar wind profiler measurements
Retrieval of cloud properties from spectral zenith radiances observed by sky radiometers
A new approach to estimate supersaturation fluctuations in stratocumulus cloud using ground-based remote-sensing measurements
Alan J. Geer
Atmos. Meas. Tech., 14, 5369–5395, https://doi.org/10.5194/amt-14-5369-2021, https://doi.org/10.5194/amt-14-5369-2021, 2021
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Satellite observations sensitive to cloud and precipitation help improve the quality of weather forecasts. However, they are sensitive to things that models do not forecast, such as the shapes and sizes of snow and ice particles. These details can be estimated from the observations themselves and then incorporated in the satellite simulators used in weather forecasting. This approach, known as parameter estimation, will be increasingly useful to build models of poorly known physical processes.
Niklas Benedikt Blum, Bijan Nouri, Stefan Wilbert, Thomas Schmidt, Ontje Lünsdorf, Jonas Stührenberg, Detlev Heinemann, Andreas Kazantzidis, and Robert Pitz-Paal
Atmos. Meas. Tech., 14, 5199–5224, https://doi.org/10.5194/amt-14-5199-2021, https://doi.org/10.5194/amt-14-5199-2021, 2021
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Cloud base height (CBH) is important, e.g., to forecast solar irradiance and, with it, photovoltaic production. All-sky imagers (ASIs), cameras monitoring the sky above their point of installation, can provide such forecasts and also measure CBH. We present a network of ASIs to measure CBH. The network provides numerous readings of CBH simultaneously. We combine these with a statistical procedure. Validation attests to significantly higher accuracy of the combination compared to two ASIs alone.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
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The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Florian Ewald, Silke Groß, Martin Wirth, Julien Delanoë, Stuart Fox, and Bernhard Mayer
Atmos. Meas. Tech., 14, 5029–5047, https://doi.org/10.5194/amt-14-5029-2021, https://doi.org/10.5194/amt-14-5029-2021, 2021
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In this study, we show how solar radiance observations can be used to validate and further constrain ice cloud microphysics retrieved from the synergy of radar–lidar measurements. Since most radar–lidar retrievals rely on a global assumption about the ice particle shape, ice water content and particle size biases are to be expected in individual cloud regimes. In this work, we identify and correct these biases by reconciling simulated and measured solar radiation reflected from these clouds.
Karolina Sarna, David P. Donovan, and Herman W. J. Russchenberg
Atmos. Meas. Tech., 14, 4959–4970, https://doi.org/10.5194/amt-14-4959-2021, https://doi.org/10.5194/amt-14-4959-2021, 2021
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We show a method for obtaining cloud optical extinction with a lidar system. We use a scheme in which a lidar signal is inverted based on the estimated value of cloud extinction at the far end of the cloud and apply a correction for multiple scattering within the cloud and a range resolution correction. By applying our technique, we show that it is possible to obtain the cloud optical extinction with an error better than 5 % up to 90 m within the cloud.
Alistair Bell, Pauline Martinet, Olivier Caumont, Benoît Vié, Julien Delanoë, Jean-Charles Dupont, and Mary Borderies
Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, https://doi.org/10.5194/amt-14-4929-2021, 2021
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This paper presents work towards making retrievals on the liquid water content in fog and low clouds. Future retrievals will rely on a radar simulator and high-resolution forecast. In this work, real observations are used to assess the errors associated with the simulator and forecast. A selection method to reduce errors associated with the forecast is proposed. It is concluded that the distribution of errors matches the requirements for future retrievals.
Noémie Planat, Josué Gehring, Étienne Vignon, and Alexis Berne
Atmos. Meas. Tech., 14, 4543–4564, https://doi.org/10.5194/amt-14-4543-2021, https://doi.org/10.5194/amt-14-4543-2021, 2021
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We implement a new method to identify microphysical processes during cold precipitation events based on the sign of the vertical gradient of polarimetric radar variables. We analytically asses the meteorological conditions for this vertical analysis to hold, apply it on two study cases and successfully compare it with other methods informing about the microphysics. Finally, we are able to obtain the main vertical structure and characteristics of the different processes during these study cases.
Christopher R. Williams, Karen L. Johnson, Scott E. Giangrande, Joseph C. Hardin, Ruşen Öktem, and David M. Romps
Atmos. Meas. Tech., 14, 4425–4444, https://doi.org/10.5194/amt-14-4425-2021, https://doi.org/10.5194/amt-14-4425-2021, 2021
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In addition to detecting clouds, vertically pointing cloud radars detect individual insects passing over head. If these insects are not identified and removed from raw observations, then radar-derived cloud properties will be contaminated. This work identifies clouds in radar observations due to their continuous and smooth structure in time, height, and velocity. Cloud masks are produced that identify cloud vertical structure that are free of insect contamination.
Holger Sihler, Steffen Beirle, Steffen Dörner, Marloes Gutenstein-Penning de Vries, Christoph Hörmann, Christian Borger, Simon Warnach, and Thomas Wagner
Atmos. Meas. Tech., 14, 3989–4031, https://doi.org/10.5194/amt-14-3989-2021, https://doi.org/10.5194/amt-14-3989-2021, 2021
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MICRU is an algorithm for the retrieval of effective cloud fractions (CFs) from satellite measurements. CFs describe the amount of clouds, which have a significant impact on the vertical sensitivity profile of trace gases like NO2 and HCHO. MICRU retrieves small CFs with an accuracy of 0.04 over the entire satellite swath. It features an empirical surface reflectivity model accounting for physical anisotropy (BRDF, sun glitter) and instrumental effects. MICRU is also applicable to imager data.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 14, 3755–3771, https://doi.org/10.5194/amt-14-3755-2021, https://doi.org/10.5194/amt-14-3755-2021, 2021
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This study suggests two methods to detect convection using 1 min data from GOES-16: one method detects early convective clouds using their vertical growth rate and the other method detects mature convective clouds using their lumpy cloud top surfaces. Applying the two methods to 1-month data showed that the accuracy of the combined methods was 85.8 % and showed their potential to be used in regions where radar data are not available.
Vasileios Barlakas, Alan J. Geer, and Patrick Eriksson
Atmos. Meas. Tech., 14, 3427–3447, https://doi.org/10.5194/amt-14-3427-2021, https://doi.org/10.5194/amt-14-3427-2021, 2021
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Oriented nonspherical ice particles induce polarization that is ignored when cloud-sensitive satellite observations are used in numerical weather prediction systems. We present a simple approach for approximating particle orientation, requiring minor adaption of software and no additional calculation burden. With this approach, the system realistically simulates the observed polarization patterns, increasing the physical consistency between instruments with different polarizations.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, https://doi.org/10.5194/amt-14-3277-2021, 2021
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, https://doi.org/10.5194/amt-14-3253-2021, 2021
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results are presented in a companion paper (Part II).
Irene Bartolome Garcia, Reinhold Spang, Jörn Ungermann, Sabine Griessbach, Martina Krämer, Michael Höpfner, and Martin Riese
Atmos. Meas. Tech., 14, 3153–3168, https://doi.org/10.5194/amt-14-3153-2021, https://doi.org/10.5194/amt-14-3153-2021, 2021
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Cirrus clouds contribute to the general radiation budget of the Earth. Measuring optically thin clouds is challenging but the IR limb sounder GLORIA possesses the necessary technical characteristics to make it possible. This study analyses data from the WISE campaign obtained with GLORIA. We developed a cloud detection method and derived characteristics of the observed cirrus-like cloud top, cloud bottom or position with respect to the tropopause.
Yoonjin Lee, Christian D. Kummerow, and Imme Ebert-Uphoff
Atmos. Meas. Tech., 14, 2699–2716, https://doi.org/10.5194/amt-14-2699-2021, https://doi.org/10.5194/amt-14-2699-2021, 2021
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Convective clouds are usually associated with intense rain that can cause severe damage, and thus it is important to accurately detect convective clouds. This study develops a machine learning model that can identify convective clouds from five temporal visible and infrared images as humans can point at convective regions by finding bright and bubbling areas. The results look promising when compared to radar-derived products, which are commonly used for detecting convection.
Christoph Kalicinsky, Sabine Griessbach, and Reinhold Spang
Atmos. Meas. Tech., 14, 1893–1915, https://doi.org/10.5194/amt-14-1893-2021, https://doi.org/10.5194/amt-14-1893-2021, 2021
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For an airborne viewing geometry, radiative transfer simulations of infrared limb emission spectra in the presence of polar stratospheric clouds – nitric acid trihydrate (NAT), supercooled ternary solution, ice, and mixtures – were used to develop a size-sensitive NAT detection algorithm. Characteristic size-dependent spectral features in the 810–820 cm−1 region were exploited to subgroup the NAT into three size regimes: small NAT (≤ 1.0 μm), medium NAT (1.5–4.0 μm), and large NAT (≥ 3.5 μm).
Souichiro Hioki, Jérôme Riedi, and Mohamed S. Djellali
Atmos. Meas. Tech., 14, 1801–1816, https://doi.org/10.5194/amt-14-1801-2021, https://doi.org/10.5194/amt-14-1801-2021, 2021
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This research estimates the magnitude of a motion-induced error in the measurement of polarimetric state of light by a planned instrument on a future satellite. We discovered that the motion-induced error can not be cancelled out by spatiotemporal averaging, but it can be predicted from the along-track change of the intensity of light. With the estimated statistics and the simulation model, this research paves a way to provide pixel-level quality information in the future satellite products.
Xiaoyu Hu, Jinming Ge, Jiajing Du, Qinghao Li, Jianping Huang, and Qiang Fu
Atmos. Meas. Tech., 14, 1743–1759, https://doi.org/10.5194/amt-14-1743-2021, https://doi.org/10.5194/amt-14-1743-2021, 2021
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Cloud radars are powerful instruments that can probe detailed cloud structures. However, radar echoes in the lower atmosphere are always contaminated by clutter. We proposed a multi-dimensional probability distribution function that can effectively discriminate low-level clouds from clutter by considering their different features in several variables. We applied this method to the radar observations at the SACOL site and found the results have good agreement with lidar detection.
Thibault Vaillant de Guélis, Mark A. Vaughan, David M. Winker, and Zhaoyan Liu
Atmos. Meas. Tech., 14, 1593–1613, https://doi.org/10.5194/amt-14-1593-2021, https://doi.org/10.5194/amt-14-1593-2021, 2021
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We introduce a new lidar feature detection algorithm that dramatically improves the fine details of layers identified in the CALIOP data. By applying our two-dimensional scanning technique to the measurements in all three channels, we minimize false positives while accurately identifying previously undetected features such as subvisible cirrus and the full vertical extent of dense smoke plumes. Multiple comparisons to version 4.2 CALIOP retrievals illustrate the scope of the improvements made.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Christopher O'Dell, K. Sebastian Schmidt, Hong Chen, and David Baker
Atmos. Meas. Tech., 14, 1475–1499, https://doi.org/10.5194/amt-14-1475-2021, https://doi.org/10.5194/amt-14-1475-2021, 2021
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The OCO-2 science team is working to retrieve CO2 measurements that can be used by the carbon cycle community to calculate regional sources and sinks of CO2. The retrieved data, however, are in need of improvements in accuracy. This paper discusses several ways in which 3D cloud metrics (such as the distance of a measurement to the nearest cloud) can be used to account for cloud effects in the OCO-2 CO2 data files.
Yuzhu Tang, Pinglv Yang, Zeming Zhou, Delu Pan, Jianyu Chen, and Xiaofeng Zhao
Atmos. Meas. Tech., 14, 737–747, https://doi.org/10.5194/amt-14-737-2021, https://doi.org/10.5194/amt-14-737-2021, 2021
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An automatic cloud classification method on whole-sky images is presented. We first extract multiple pixel-level features to form region covariance descriptors (RCovDs) and then encode RCovDs by the Riemannian bag-of-feature (BoF) method to output the histogram representation. Reults show that a very high prediction accuracy can be obtained with a small number of training samples, which validate the proposed method and exhibit the competitive performance against state-of-the-art methods.
Macey W. Sandford, David R. Thompson, Robert O. Green, Brian H. Kahn, Raffaele Vitulli, Steve Chien, Amruta Yelamanchili, and Winston Olson-Duvall
Atmos. Meas. Tech., 13, 7047–7057, https://doi.org/10.5194/amt-13-7047-2020, https://doi.org/10.5194/amt-13-7047-2020, 2020
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We demonstrate an onboard cloud-screening approach to significantly reduce the amount of cloud-contaminated data transmitted from orbit. We have produced location-specific models that improve performance by taking into account the unique cloud statistics in different latitudes. We have shown that screening clouds based on their location or surface type will improve the ability for a cloud-screening tool to improve the volume of usable science data.
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.
Robin Ekelund, Patrick Eriksson, and Michael Kahnert
Atmos. Meas. Tech., 13, 6933–6944, https://doi.org/10.5194/amt-13-6933-2020, https://doi.org/10.5194/amt-13-6933-2020, 2020
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Raindrops become flattened due to aerodynamic drag as they increase in mass and fall speed. This study calculated the electromagnetic interaction between microwave radiation and non-spheroidal raindrops. The calculations are made publicly available to the scientific community, in order to promote accurate representations of raindrops in measurements. Tests show that the drop shape can have a noticeable effect on microwave observations of heavy rainfall.
Jasper R. Lewis, James R. Campbell, Sebastian A. Stewart, Ivy Tan, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 13, 6901–6913, https://doi.org/10.5194/amt-13-6901-2020, https://doi.org/10.5194/amt-13-6901-2020, 2020
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In this work, the authors describe a process to determine the thermodynamic cloud phase using the Micro Pulse Lidar Network volume depolarization ratio measurements and temperature profiles from the Global Modeling and Assimilation Office GEOS-5 model. A multi-year analysis and comparisons to supercooled liquid water fractions derived from CALIPSO satellite measurements are used to demonstrate the efficacy of the method.
Larysa Istomina, Henrik Marks, Marcus Huntemann, Georg Heygster, and Gunnar Spreen
Atmos. Meas. Tech., 13, 6459–6472, https://doi.org/10.5194/amt-13-6459-2020, https://doi.org/10.5194/amt-13-6459-2020, 2020
Benjamin R. Scarino, Kristopher Bedka, Rajendra Bhatt, Konstantin Khlopenkov, David R. Doelling, and William L. Smith Jr.
Atmos. Meas. Tech., 13, 5491–5511, https://doi.org/10.5194/amt-13-5491-2020, https://doi.org/10.5194/amt-13-5491-2020, 2020
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This paper highlights a technique for facilitating anvil cloud detection based on visible observations that relies on comparative analysis with expected cloud reflectance for a given set of angles. A 1-year database of anvil-identified pixels, as determined from IR observations, from several geostationary satellites was used to construct a bidirectional reflectance distribution function model to quantify typical anvil reflectance across almost all expected viewing, solar, and azimuth angles.
Bangsheng Yin, Qilong Min, Emily Morgan, Yuekui Yang, Alexander Marshak, and Anthony B. Davis
Atmos. Meas. Tech., 13, 5259–5275, https://doi.org/10.5194/amt-13-5259-2020, https://doi.org/10.5194/amt-13-5259-2020, 2020
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Cloud-top pressure (CTP) is an important cloud property for climate and weather studies. Based on differential oxygen absorption, both oxygen A-band and B-band pairs can be used to retrieve CTP. However, it is currently very challenging to perform a CTP retrieval accurately due to the complicated in-cloud penetration effect. To address this issue, we propose an analytic transfer inverse model for DSCOVR EPIC observations to retrieve CTP considering in-cloud photon penetration.
Frédéric Tridon, Alessandro Battaglia, and Stefan Kneifel
Atmos. Meas. Tech., 13, 5065–5085, https://doi.org/10.5194/amt-13-5065-2020, https://doi.org/10.5194/amt-13-5065-2020, 2020
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The droplets and ice crystals composing clouds and precipitation interact with microwaves and can therefore be observed by radars, but they can also attenuate the signal they emit. By combining the observations made by two ground-based radars, this study describes an original approach for estimating such attenuation. As a result, the latter can be not only corrected in the radar observations but also exploited for providing an accurate characterization of droplet and ice crystal properties.
Mark Richardson, Matthew D. Lebsock, James McDuffie, and Graeme L. Stephens
Atmos. Meas. Tech., 13, 4947–4961, https://doi.org/10.5194/amt-13-4947-2020, https://doi.org/10.5194/amt-13-4947-2020, 2020
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We previously combined CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data and reflected-sunlight measurements from OCO-2 (Orbiting Carbon Observatory 2) for information about low clouds over oceans. The satellites are no longer formation-flying, so this work is a step towards getting new information about these clouds using only OCO-2. We can rapidly and accurately identify liquid oceanic clouds and obtain their height better than a widely used passive sensor.
Melody A. Avery, Robert A. Ryan, Brian J. Getzewich, Mark A. Vaughan, David M. Winker, Yongxiang Hu, Anne Garnier, Jacques Pelon, and Carolus A. Verhappen
Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, https://doi.org/10.5194/amt-13-4539-2020, 2020
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CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6 %–9 % for high-confidence cloud phases and 1 %–2 % for all cloudy bins, including cloud fringes and unknown cloud phases. In V4 there are many fewer cloud layers identified as horizontally oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
Vladimir S. Kostsov, Dmitry V. Ionov, and Anke Kniffka
Atmos. Meas. Tech., 13, 4565–4587, https://doi.org/10.5194/amt-13-4565-2020, https://doi.org/10.5194/amt-13-4565-2020, 2020
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Previously, observations from satellites provided evidence for systematic differences between the values of the cloud liquid water path over land and water areas in northern Europe. An attempt is made to detect such differences by means of ground-based microwave measurements performed near the coastline of the Gulf of Finland. The results demonstrate the existence of the cloud liquid water path gradient, which is positive as in the case of the satellite measurements (larger values over land).
Simon Pfreundschuh, Patrick Eriksson, Stefan A. Buehler, Manfred Brath, David Duncan, Richard Larsson, and Robin Ekelund
Atmos. Meas. Tech., 13, 4219–4245, https://doi.org/10.5194/amt-13-4219-2020, https://doi.org/10.5194/amt-13-4219-2020, 2020
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The next generation of European operational weather satellites will carry a novel microwave sensor, the Ice Cloud Imager (ICI), which will provide observations of clouds at microwave frequencies that were not available before. We investigate the potential benefits of combining observations from ICI with that of a radar. We find that such combined observations provide additional information on the properties of the cloud and help to reduce uncertainties in retrieved mass and number densities.
Yue Li, Bryan A. Baum, Andrew K. Heidinger, W. Paul Menzel, and Elisabeth Weisz
Atmos. Meas. Tech., 13, 4035–4049, https://doi.org/10.5194/amt-13-4035-2020, https://doi.org/10.5194/amt-13-4035-2020, 2020
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Use of VIIRS+CrIS fusion products, which provide VIIRS with MODIS-like IR sounding channels, improves cloud mask, cloud phase, and cloud top height retrievals when compared to those using VIIRS data only. NOAA CLAVR-x cloud retrievals for both S-NPP and NOAA-20 data are evaluated through comparisons to the CALIPSO v4 and MODIS Collection 6.1 cloud products. Cloud height retrievals show significant improvement for semitransparent ice clouds, with a reduction in retrieval uncertainties.
Florian Tornow, Carlos Domenech, Howard W. Barker, René Preusker, and Jürgen Fischer
Atmos. Meas. Tech., 13, 3909–3922, https://doi.org/10.5194/amt-13-3909-2020, https://doi.org/10.5194/amt-13-3909-2020, 2020
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Clouds reflect sunlight unevenly, which makes it difficult to quantify the portion reflected back to space via satellite observation. To improve quantification, we propose a new statistical model that incorporates more satellite-inferred cloud and atmospheric properties than state-of-the-art models. We use concepts from radiative transfer theory that we statistically optimize to fit observations. The new model often explains past satellite observations better and predicts reflection plausibly.
Rocco Sedona, Lars Hoffmann, Reinhold Spang, Gabriele Cavallaro, Sabine Griessbach, Michael Höpfner, Matthias Book, and Morris Riedel
Atmos. Meas. Tech., 13, 3661–3682, https://doi.org/10.5194/amt-13-3661-2020, https://doi.org/10.5194/amt-13-3661-2020, 2020
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Polar stratospheric clouds (PSCs) play a key role in polar ozone depletion in the stratosphere. In this paper, we explore the potential of applying machine learning (ML) methods to classify PSC observations of infrared spectra to classify PSC types. ML methods have proved to reach results in line with those obtained using well-established approaches. Among the considered ML methods, random forest (RF) seems to be the most promising one, being able to produce explainable classification results.
Alain Protat and Ian McRobert
Atmos. Meas. Tech., 13, 3609–3620, https://doi.org/10.5194/amt-13-3609-2020, https://doi.org/10.5194/amt-13-3609-2020, 2020
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Three-dimensional (3D) wind motions play a major role in driving the life cycle of clouds. In this pilot study we have developed a technique to measure the 3D winds in clouds, using a shipborne Doppler cloud radar on a stabilized platform. The stabilized platform is driven to point in a series of predefined directions to collect the required measurements. Comparisons with radiosondes demonstrate that accurate 1 min resolution 3D wind motions can be obtained from this instrumental setup.
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.
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.
Wanyi Xie, Dong Liu, Ming Yang, Shaoqing Chen, Benge Wang, Zhenzhu Wang, Yingwei Xia, Yong Liu, Yiren Wang, and Chaofan Zhang
Atmos. Meas. Tech., 13, 1953–1961, https://doi.org/10.5194/amt-13-1953-2020, https://doi.org/10.5194/amt-13-1953-2020, 2020
Brent A. McBride, J. Vanderlei Martins, Henrique M. J. Barbosa, William Birmingham, and Lorraine A. Remer
Atmos. Meas. Tech., 13, 1777–1796, https://doi.org/10.5194/amt-13-1777-2020, https://doi.org/10.5194/amt-13-1777-2020, 2020
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Clouds play a large role in the way our Earth system distributes energy. The measurement of cloud droplet size distribution (DSD) is one way to connect small-scale cloud processes to scattered radiation. Our small satellite instrument, the Airborne Hyper-Angular Rainbow Polarimeter, is the first to infer DSDs over a wide spatial cloud field using polarized light. This study improves the way we interpret cloud properties and shows that high-quality science does not require a large taxpayer cost.
Jason M. Apke, Kyle A. Hilburn, Steven D. Miller, and David A. Peterson
Atmos. Meas. Tech., 13, 1593–1608, https://doi.org/10.5194/amt-13-1593-2020, https://doi.org/10.5194/amt-13-1593-2020, 2020
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Objective identification of deep convection outflow boundaries (OFBs) in next-generation geostationary satellite imagery is explored here using motion derived from a tuned advanced optical flow algorithm. Motion discontinuity preservation within the derivation is found crucial for successful OFB tracking between images, which yields new meteorological data for objective systems to use. These results provide the first step towards a fully automated satellite-based OFB identification algorithm.
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020, https://doi.org/10.5194/amt-13-1575-2020, 2020
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Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and the bright and cold surfaces; the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has very limited channels. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios for cloud detection over snow and ice surfaces.
Maria P. Cadeddu, Virendra P. Ghate, and Mario Mech
Atmos. Meas. Tech., 13, 1485–1499, https://doi.org/10.5194/amt-13-1485-2020, https://doi.org/10.5194/amt-13-1485-2020, 2020
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A combination of ground-based active and passive observations is used to partition cloud and precipitation liquid water path in precipitating stratocumulous clouds. Results show that neglecting scattering effects from drizzle drops leads to 8–15 % overestimation of the liquid amount in the cloud. In closed-cell systems only ~20 % of the available drizzle in the cloud falls below the cloud base, compared to ~40 % in open-cell systems.
Frank Werner and Hartwig Deneke
Atmos. Meas. Tech., 13, 1089–1111, https://doi.org/10.5194/amt-13-1089-2020, https://doi.org/10.5194/amt-13-1089-2020, 2020
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The reliability of remotely sensed cloud variables from space depends on the horizontal resolution of the instrument. This study presents and evaluates several candidate approaches for increasing the spatial resolution of observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) from the native 3 km scale to a horizontal resolution of 1 km. It is shown that uncertainties in the derived cloud products can be significantly mitigated by applying an appropriate downscaling scheme.
Christine Aebi, Julian Gröbner, Stelios Kazadzis, Laurent Vuilleumier, Antonis Gkikas, and Niklaus Kämpfer
Atmos. Meas. Tech., 13, 907–923, https://doi.org/10.5194/amt-13-907-2020, https://doi.org/10.5194/amt-13-907-2020, 2020
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Clouds are one of the largest sources of uncertainties in climate models. The current study estimates the cloud optical thickness (COT), the effective droplet radius and the single scattering albedo of stratus–altostratus and cirrus–cirrostratus clouds in Payerne, Switzerland, by combining ground- and satellite-based measurements and radiative transfer models. The estimated values are thereafter compared with data retrieved from other methods. The mean COT is distinct for different seasons.
Patrick Eriksson, Bengt Rydberg, Vinia Mattioli, Anke Thoss, Christophe Accadia, Ulf Klein, and Stefan A. Buehler
Atmos. Meas. Tech., 13, 53–71, https://doi.org/10.5194/amt-13-53-2020, https://doi.org/10.5194/amt-13-53-2020, 2020
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The Ice Cloud Imager (ICI) will be the first operational satellite sensor operating at sub-millimetre wavelengths and this novel mission will thus provide important new data to weather forecasting and climate studies. The series of ICI instruments will together cover about 20 years. This article presents the basic technical characteristics of the sensor and outlines the day-one operational retrievals. An updated estimation of the expected retrieval performance is also presented.
Johannes Bühl, Patric Seifert, Martin Radenz, Holger Baars, and Albert Ansmann
Atmos. Meas. Tech., 12, 6601–6617, https://doi.org/10.5194/amt-12-6601-2019, https://doi.org/10.5194/amt-12-6601-2019, 2019
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In the present paper, we present a novel remote-sensing technique for the measurement of ice crystal number concentrations in clouds. The fall velocity of ice crystals measured with values from cloud radar and a radar wind profiler is used in order to derive information about ice crystal size and number concentration. In contrast to existing methods based on the combination of lidar and cloud radar, the present method can also be used in optically thick clouds.
Pradeep Khatri, Hironobu Iwabuchi, Tadahiro Hayasaka, Hitoshi Irie, Tamio Takamura, Akihiro Yamazaki, Alessandro Damiani, Husi Letu, and Qin Kai
Atmos. Meas. Tech., 12, 6037–6047, https://doi.org/10.5194/amt-12-6037-2019, https://doi.org/10.5194/amt-12-6037-2019, 2019
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In an attempt to make cloud retrievals from the surface more common and convenient, we developed a cloud retrieval algorithm applicable for sky radiometers. It is based on an optimum method by fitting measured transmittances with modeled values. Further, a cost-effective and easy-to-use calibration procedure is proposed and validated using data obtained from the standard method. A detailed error analysis and quality assessment are also performed.
Fan Yang, Robert McGraw, Edward P. Luke, Damao Zhang, Pavlos Kollias, and Andrew M. Vogelmann
Atmos. Meas. Tech., 12, 5817–5828, https://doi.org/10.5194/amt-12-5817-2019, https://doi.org/10.5194/amt-12-5817-2019, 2019
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Short summary
In-cloud supersaturation is crucial for droplet activation, growth, and drizzle initiation but is poorly known and hardly measured. Here we provide a novel method to estimate supersaturation fluctuation in stratocumulus clouds using remote-sensing measurements, and results show that our estimated supersaturation agrees reasonably well with in situ measurements. Our method provides a unique way to estimate supersaturation in stratocumulus clouds from long-term ground-based observations.
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Short summary
We provide a parameterized correction to the retrieval of cloud effective radius from satellite instruments to account for the assumption that the retrieved value is representative of that at cloud top, whereas in reality it is representative of that lower down. The error leads to errors (which we quantify) in the retrieved cloud droplet concentrations of up to 38 % for stratocumulus regions and also to liquid water path errors, both of which can be corrected using our parameterizations.
We provide a parameterized correction to the retrieval of cloud effective radius from satellite...
