Articles | Volume 8, issue 7
https://doi.org/10.5194/amt-8-2663-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-2663-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
02 Jul 2015
Research article |
| 02 Jul 2015
Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances
M. D. Fielding
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
J. C. Chiu
Department of Meteorology, University of Reading, Reading, UK
R. J. Hogan
Department of Meteorology, University of Reading, Reading, UK
G. Feingold
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
E. Eloranta
Space Science and Engineering Center, University of Wisconsin, Madison, Wisconsin, USA
E. J. O'Connor
Department of Meteorology, University of Reading, Reading, UK
Finnish Meteorological Institute, Helsinki, Finland
M. P. Cadeddu
Argonne National Laboratory, Argonne, Illinois, USA
Related authors
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yao-Sheng Chen, Jianhao Zhang, Fabian Hoffmann, Takanobu Yamaguchi, Franziska Glassmeier, Xiaoli Zhou, and Graham Feingold
Atmos. Chem. Phys., 24, 12661–12685, https://doi.org/10.5194/acp-24-12661-2024, https://doi.org/10.5194/acp-24-12661-2024, 2024
Short summary
Short summary
Marine stratocumulus cloud is a type of shallow cloud that covers the vast areas of Earth's surface. It plays an important role in Earth's energy balance by reflecting solar radiation back to space. We used numerical models to simulate a large number of marine stratocumuli with different characteristics. We found that how the clouds develop throughout the day is affected by the level of humidity in the air above the clouds and how closely the clouds connect to the ocean surface.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Johanna Tjernström, Michael Gallagher, Jareth Holt, Gunilla Svensson, Matthew D. Shupe, Jonathan J. Day, Lara Ferrighi, Siri Jodha Khalsa, Leslie M. Hartten, Ewan O'Connor, Zen Mariani, and Øystein Godøy
EGUsphere, https://doi.org/10.5194/egusphere-2024-2088, https://doi.org/10.5194/egusphere-2024-2088, 2024
Short summary
Short summary
The value of numerical weather predictions can be enhanced in several ways, one is to improve the representations of small-scale processes in models. To understand what needs to be improved, the model results need to be evaluated. Following standardized principles, a file format has been defined to be as similar as possible for both observational and model data. Python packages and toolkits are presented as a community resource in the production of the files and evaluation analysis.
Jianhao Zhang, Yao-Sheng Chen, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 24, 10425–10440, https://doi.org/10.5194/acp-24-10425-2024, https://doi.org/10.5194/acp-24-10425-2024, 2024
Short summary
Short summary
Quantifying cloud response to aerosol perturbations presents a major challenge in understanding the human impact on climate. Using a large number of process-resolving simulations of marine stratocumulus, we show that solar heating drives a negative feedback mechanism that buffers the persistent negative trend in cloud water adjustment after sunrise. This finding has implications for the dependence of the cloud cooling effect on the timing of deliberate aerosol perturbations.
Jutta Kesti, Ewan J. O'Connor, Anne Hirsikko, John Backman, Maria Filioglou, Anu-Maija Sundström, Juha Tonttila, Heikki Lihavainen, Hannele Korhonen, and Eija Asmi
Atmos. Chem. Phys., 24, 9369–9386, https://doi.org/10.5194/acp-24-9369-2024, https://doi.org/10.5194/acp-24-9369-2024, 2024
Short summary
Short summary
The study combines aerosol particle measurements at the surface and vertical profiling of the atmosphere with a scanning Doppler lidar to investigate how particle transportation together with boundary layer evolution can affect particle and SO2 concentrations at the surface in the Arabian Peninsula region. The instrumentation enabled us to see elevated nucleation mode particle and SO2 concentrations at the surface when air masses transported from polluted areas are mixed in the boundary layer.
Howard W. Barker, Jason N. S. Cole, Najda Villefranque, Zhipeng Qu, Almudena Velázquez Blázquez, Carlos Domenech, Shannon L. Mason, and Robin J. Hogan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1651, https://doi.org/10.5194/egusphere-2024-1651, 2024
Short summary
Short summary
Measurements made by three instruments aboard EarthCARE are used to retrieve estimates of cloud and aerosol properties. A radiative closure assessment of these retrievals is performed by the ACMB-DF processor. Radiative transfer models acting on retrieved information produce broadband radiances commensurate with measurements made by EarthCARE’s broadband radiometer. Measured and modelled radiances for small domains are compared and the likelihood of them differing by 10 W/m2 defines the closure.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, Xavier Fettweis, and Marilaure Grégoire
EGUsphere, https://doi.org/10.5194/egusphere-2024-1858, https://doi.org/10.5194/egusphere-2024-1858, 2024
Short summary
Short summary
The MAR model is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can decompose solar radiation into various ranges. In particular, MAR can now simulate precisely solar radiation in the ultraviolet and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Johannes Röttenbacher, André Ehrlich, Hanno Müller, Florian Ewald, Anna E. Luebke, Benjamin Kirbus, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 8085–8104, https://doi.org/10.5194/acp-24-8085-2024, https://doi.org/10.5194/acp-24-8085-2024, 2024
Short summary
Short summary
Weather prediction models simplify the physical processes related to light scattering by clouds consisting of complex ice crystals. Whether these simplifications are the cause for uncertainties in their prediction can be evaluated by comparing them with measurement data. Here we do this for Arctic ice clouds over sea ice using airborne measurements from two case studies. The model performs well for thick ice clouds but not so well for thin ones. This work can be used to improve the model.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Fabian Hoffmann, Franziska Glassmeier, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2024-1725, https://doi.org/10.5194/egusphere-2024-1725, 2024
Short summary
Short summary
Clouds constitute a major cooling influence on Earth's climate system by reflecting a large fraction of the incident solar radiation back to space. This ability is controlled by the number of cloud droplets, which is governed by the number of aerosol particles in the atmosphere, laying out the foundation for so-called aerosol-cloud-climate interactions. In this study, a simple model to understand the effect of aerosol on cloud water is developed and applied.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1118, https://doi.org/10.5194/egusphere-2024-1118, 2024
Short summary
Short summary
Radiation is relevant for the atmospheric impact on humans and infrastructure in cities since it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model assuming a more realistic form of urban morphology is coupled with the urban climate model TEB. The coupled model is evaluated using a more detailed radiation model for a variety of urban morphologies and an improvement of the most relevant urban radiation variables is found.
Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024, https://doi.org/10.5194/acp-24-4157-2024, 2024
Short summary
Short summary
A weather model is used to compare solar radiation with measurements from an aircraft campaign in the Arctic. Model and observations agree on the downward radiation but show differences in the radiation reflected by the surface and the clouds, which in the model is too low above sea ice and too high above open ocean. The model–observation bias is reduced above open ocean by a realistic fraction of clouds and less cloud liquid water and above sea ice by less dark sea ice and more cloud droplets.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
EGUsphere, https://doi.org/10.5194/egusphere-2024-937, https://doi.org/10.5194/egusphere-2024-937, 2024
Short summary
Short summary
A doppler lidar was placed in highly built-up area in London to measure wakes from tall buildings during a period of one year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Prasanth Prabhakaran, Fabian Hoffmann, and Graham Feingold
Atmos. Chem. Phys., 24, 1919–1937, https://doi.org/10.5194/acp-24-1919-2024, https://doi.org/10.5194/acp-24-1919-2024, 2024
Short summary
Short summary
In this study, we explore the impact of deliberate aerosol perturbation in the northeast Pacific region using large-eddy simulations. Our results show that cloud reflectivity is sensitive to the aerosol sprayer arrangement in the pristine system, whereas in the polluted system it is largely proportional to the total number of aerosol particles injected. These insights would aid in assessing the efficiency of various aerosol injection strategies for climate intervention applications.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
Short summary
Short summary
This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
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
Short summary
Short summary
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.
Megan A. Stretton, William Morrison, Robin J. Hogan, and Sue Grimmond
Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, https://doi.org/10.5194/gmd-16-5931-2023, 2023
Short summary
Short summary
Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Maria Filioglou, Ari Leskinen, Ville Vakkari, Ewan O'Connor, Minttu Tuononen, Pekko Tuominen, Samuli Laukkanen, Linnea Toiviainen, Annika Saarto, Xiaoxia Shang, Petri Tiitta, and Mika Komppula
Atmos. Chem. Phys., 23, 9009–9021, https://doi.org/10.5194/acp-23-9009-2023, https://doi.org/10.5194/acp-23-9009-2023, 2023
Short summary
Short summary
Pollen impacts climate and public health, and it can be detected in the atmosphere by lidars which measure the linear particle depolarization ratio (PDR), a shape-relevant optical parameter. As aerosols also cause depolarization, surface aerosol and pollen observations were combined with measurements from ground-based lidars operating at different wavelengths to determine the optical properties of birch and pine pollen and quantify their relative contribution to the PDR.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
Short summary
Short summary
We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Peter Ukkonen and Robin J. Hogan
Geosci. Model Dev., 16, 3241–3261, https://doi.org/10.5194/gmd-16-3241-2023, https://doi.org/10.5194/gmd-16-3241-2023, 2023
Short summary
Short summary
Climate and weather models suffer from uncertainties resulting from approximated processes. Solar and thermal radiation is one example, as it is computationally too costly to simulate precisely. This has led to attempts to replace radiation codes based on physical equations with neural networks (NNs) that are faster but uncertain. In this paper we use global weather simulations to demonstrate that a middle-ground approach of using NNs only to predict optical properties is accurate and reliable.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
Short summary
Short summary
The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
Short summary
Short summary
In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
Pyry Pentikäinen, Ewan J. O'Connor, and Pablo Ortiz-Amezcua
Geosci. Model Dev., 16, 2077–2094, https://doi.org/10.5194/gmd-16-2077-2023, https://doi.org/10.5194/gmd-16-2077-2023, 2023
Short summary
Short summary
We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
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
Short summary
Short summary
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.
Maria P. Cadeddu, Virendra P. Ghate, David D. Turner, and Thomas E. Surleta
Atmos. Chem. Phys., 23, 3453–3470, https://doi.org/10.5194/acp-23-3453-2023, https://doi.org/10.5194/acp-23-3453-2023, 2023
Short summary
Short summary
We analyze the variability in marine boundary layer moisture at the Eastern North Atlantic site on a monthly and daily temporal scale and examine its fundamental role in the control of boundary layer cloudiness and precipitation. The study also highlights the complex interaction between large-scale and local processes controlling the boundary layer moisture and the importance of the mesoscale spatial distribution of vapor to support convection and precipitation.
Konstantinos Matthaios Doulgeris, Ville Vakkari, Ewan J. O'Connor, Veli-Matti Kerminen, Heikki Lihavainen, and David Brus
Atmos. Chem. Phys., 23, 2483–2498, https://doi.org/10.5194/acp-23-2483-2023, https://doi.org/10.5194/acp-23-2483-2023, 2023
Short summary
Short summary
We investigated how different long-range-transported air masses can affect the microphysical properties of low-level clouds in a clean subarctic environment. A connection was revealed. Higher values of cloud droplet number concentrations were related to continental air masses, whereas the lowest values of number concentrations were related to marine air masses. These were characterized by larger cloud droplets. Clouds in all regions were sensitive to increases in cloud number concentration.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
Short summary
Short summary
Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Jianhao Zhang and Graham Feingold
Atmos. Chem. Phys., 23, 1073–1090, https://doi.org/10.5194/acp-23-1073-2023, https://doi.org/10.5194/acp-23-1073-2023, 2023
Short summary
Short summary
Using observations from space, we show maps of potential brightness changes in marine warm clouds in response to increases in cloud droplet concentrations. The environmental and aerosol conditions in which these clouds reside covary differently in each ocean basin, leading to distinct evolutions of cloud brightness changes. This work stresses the central importance of the covariability between meteorology and aerosol for scaling up the radiative response of cloud brightness changes.
Jenna Ritvanen, Ewan O'Connor, Dmitri Moisseev, Raisa Lehtinen, Jani Tyynelä, and Ludovic Thobois
Atmos. Meas. Tech., 15, 6507–6519, https://doi.org/10.5194/amt-15-6507-2022, https://doi.org/10.5194/amt-15-6507-2022, 2022
Short summary
Short summary
Doppler lidars and weather radars provide accurate wind measurements, with Doppler lidar usually performing better in dry weather conditions and weather radar performing better when there is precipitation. Operating both instruments together should therefore improve the overall performance. We investigate how well a co-located Doppler lidar and X-band radar perform with respect to various weather conditions, including changes in horizontal visibility, cloud altitude, and precipitation.
Michael S. Diamond, Pablo E. Saide, Paquita Zuidema, Andrew S. Ackerman, Sarah J. Doherty, Ann M. Fridlind, Hamish Gordon, Calvin Howes, Jan Kazil, Takanobu Yamaguchi, Jianhao Zhang, Graham Feingold, and Robert Wood
Atmos. Chem. Phys., 22, 12113–12151, https://doi.org/10.5194/acp-22-12113-2022, https://doi.org/10.5194/acp-22-12113-2022, 2022
Short summary
Short summary
Smoke from southern Africa blankets the southeast Atlantic from June-October, overlying a major transition region between overcast and scattered clouds. The smoke affects Earth's radiation budget by absorbing sunlight and changing cloud properties. We investigate these effects in regional climate and large eddy simulation models based on international field campaigns. We find that large-scale circulation changes more strongly affect cloud transitions than smoke microphysical effects in our case.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
Short summary
Short summary
A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
Edward Gryspeerdt, Franziska Glassmeier, Graham Feingold, Fabian Hoffmann, and Rebecca J. Murray-Watson
Atmos. Chem. Phys., 22, 11727–11738, https://doi.org/10.5194/acp-22-11727-2022, https://doi.org/10.5194/acp-22-11727-2022, 2022
Short summary
Short summary
The response of clouds to changes in aerosol remains a large uncertainty in our understanding of the climate. Studies typically look at aerosol and cloud processes in snapshot images, measuring all properties at the same time. Here we use multiple images to characterise how cloud temporal development responds to aerosol. We find a reduction in liquid water path with increasing aerosol, party due to feedbacks. This suggests the aerosol impact on cloud water may be weaker than in previous studies.
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432, https://doi.org/10.5194/amt-15-2417-2022, https://doi.org/10.5194/amt-15-2417-2022, 2022
Short summary
Short summary
To study the complex structure of the lowest tens of metres of atmosphere in urban areas, measurement methods with great spatial and temporal coverage are needed. In our study, we analyse measurements with a promising and relatively new method, distributed temperature sensing, capable of providing detailed information on the near-surface atmosphere. We present multiple ways to utilise these kinds of measurements, as well as important considerations for planning new studies using the method.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
Short summary
Short summary
The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
Graham Feingold, Tom Goren, and Takanobu Yamaguchi
Atmos. Chem. Phys., 22, 3303–3319, https://doi.org/10.5194/acp-22-3303-2022, https://doi.org/10.5194/acp-22-3303-2022, 2022
Short summary
Short summary
The evaluation of radiative forcing associated with aerosol–cloud interactions remains a significant source of uncertainty in future climate projections. Using high-resolution numerical model output, we mimic typical satellite retrieval methodologies to show that data aggregation can introduce significant error (hundreds of percent) in the cloud albedo susceptibility metric. Spatial aggregation errors tend to be countered by temporal aggregation errors.
Jianhao Zhang, Xiaoli Zhou, Tom Goren, and Graham Feingold
Atmos. Chem. Phys., 22, 861–880, https://doi.org/10.5194/acp-22-861-2022, https://doi.org/10.5194/acp-22-861-2022, 2022
Short summary
Short summary
Oceanic liquid-form clouds are effective sunlight reflectors. Their brightness is highly sensitive to changes in the amount of aerosol particles in the atmosphere and the state of the atmosphere they reside in. This study quantifies this sensitivity using long-term satellite observations and finds an overall cloud brightening (a cooling effect) potential and an essential role of the covarying meteorological conditions in governing this sensitivity for northeastern Pacific stratocumulus.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Jutta Kesti, John Backman, Ewan J. O'Connor, Anne Hirsikko, Eija Asmi, Minna Aurela, Ulla Makkonen, Maria Filioglou, Mika Komppula, Hannele Korhonen, and Heikki Lihavainen
Atmos. Chem. Phys., 22, 481–503, https://doi.org/10.5194/acp-22-481-2022, https://doi.org/10.5194/acp-22-481-2022, 2022
Short summary
Short summary
In this study we combined aerosol particle measurements at the surface with a scanning Doppler lidar providing vertical profiles of the atmosphere to study the effect of different boundary layer conditions on aerosol particle properties in the understudied Arabian Peninsula region. The instrumentation used in this study enabled us to identify periods when pollution from remote sources was mixed down to the surface and initiated new particle formation in the growing boundary layer.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
Short summary
Short summary
We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Nicholas J. Kedzuf, J. Christine Chiu, V. Chandrasekar, Sounak Biswas, Shashank S. Joshil, Yinghui Lu, Peter Jan van Leeuwen, Christopher Westbrook, Yann Blanchard, and Sebastian O'Shea
Atmos. Meas. Tech., 14, 6885–6904, https://doi.org/10.5194/amt-14-6885-2021, https://doi.org/10.5194/amt-14-6885-2021, 2021
Short summary
Short summary
Ice clouds play a key role in our climate system due to their strong controls on precipitation and the radiation budget. However, it is difficult to characterize co-existing ice species using radar observations. We present a new method that separates the radar signals of pristine ice embedded in snow aggregates and retrieves their respective abundances and sizes for the first time. The ability to provide their quantitative microphysical properties will open up many research opportunities.
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021, https://doi.org/10.5194/amt-14-6159-2021, 2021
Short summary
Short summary
The long-range-transported smoke particles from a Canadian wildfire event were observed with a multi-wavelength Raman polarization lidar and a ceilometer over Kuopio, Finland, in June 2019. The optical properties and the mass concentration estimations were reported for such aged smoke aerosols over northern Europe.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
David Meyer, Thomas Nagler, and Robin J. Hogan
Geosci. Model Dev., 14, 5205–5215, https://doi.org/10.5194/gmd-14-5205-2021, https://doi.org/10.5194/gmd-14-5205-2021, 2021
Short summary
Short summary
A major limitation in training machine-learning emulators is often caused by the lack of data. This paper presents a cheap way to increase the size of training datasets using statistical techniques and thereby improve the performance of machine-learning emulators.
Robert Pincus, Chris W. Fairall, Adriana Bailey, Haonan Chen, Patrick Y. Chuang, Gijs de Boer, Graham Feingold, Dean Henze, Quinn T. Kalen, Jan Kazil, Mason Leandro, Ashley Lundry, Ken Moran, Dana A. Naeher, David Noone, Akshar J. Patel, Sergio Pezoa, Ivan PopStefanija, Elizabeth J. Thompson, James Warnecke, and Paquita Zuidema
Earth Syst. Sci. Data, 13, 3281–3296, https://doi.org/10.5194/essd-13-3281-2021, https://doi.org/10.5194/essd-13-3281-2021, 2021
Short summary
Short summary
This paper describes observations taken from a research aircraft during a field experiment in the western Atlantic Ocean during January and February 2020. The plane made 11 flights, most 8-9 h long, and measured the properties of the atmosphere and ocean with a combination of direct measurements, sensors falling from the plane to profile the atmosphere and ocean, and remote sensing measurements of clouds and the ocean surface.
Ville Vakkari, Holger Baars, Stephanie Bohlmann, Johannes Bühl, Mika Komppula, Rodanthi-Elisavet Mamouri, and Ewan James O'Connor
Atmos. Chem. Phys., 21, 5807–5820, https://doi.org/10.5194/acp-21-5807-2021, https://doi.org/10.5194/acp-21-5807-2021, 2021
Short summary
Short summary
The depolarization ratio is a valuable parameter for aerosol categorization from remote sensing measurements. Here, we introduce particle depolarization ratio measurements at the 1565 nm wavelength, which is substantially longer than previously utilized wavelengths and enhances our capabilities to study the wavelength dependency of the particle depolarization ratio.
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
Short summary
Short summary
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.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
Short summary
Short summary
We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
Robin J. Hogan and Marco Matricardi
Geosci. Model Dev., 13, 6501–6521, https://doi.org/10.5194/gmd-13-6501-2020, https://doi.org/10.5194/gmd-13-6501-2020, 2020
Short summary
Short summary
A key component of computer models used to predict weather and climate is the radiation scheme, which calculates how solar and infrared radiation heats and cools the atmosphere and surface, including the important role of greenhouse gases. This paper describes the experimental protocol and large datasets for a new project, CKDMIP, to evaluate and improve the accuracy of the treatment of atmospheric gases in the radiation schemes used worldwide, as well as their computational speed.
Peggy Achtert, Ewan J. O'Connor, Ian M. Brooks, Georgia Sotiropoulou, Matthew D. Shupe, Bernhard Pospichal, Barbara J. Brooks, and Michael Tjernström
Atmos. Chem. Phys., 20, 14983–15002, https://doi.org/10.5194/acp-20-14983-2020, https://doi.org/10.5194/acp-20-14983-2020, 2020
Short summary
Short summary
We present observations of precipitating and non-precipitating Arctic liquid and mixed-phase clouds during a research cruise along the Russian shelf in summer and autumn of 2014. Active remote-sensing observations, radiosondes, and auxiliary measurements are combined in the synergistic Cloudnet retrieval. Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. About 8 % of all liquid clouds show a liquid water path below the infrared black body limit.
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
Short summary
Short summary
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.
Shi Kuang, Bo Wang, Michael J. Newchurch, Kevin Knupp, Paula Tucker, Edwin W. Eloranta, Joseph P. Garcia, Ilya Razenkov, John T. Sullivan, Timothy A. Berkoff, Guillaume Gronoff, Liqiao Lei, Christoph J. Senff, Andrew O. Langford, Thierry Leblanc, and Vijay Natraj
Atmos. Meas. Tech., 13, 5277–5292, https://doi.org/10.5194/amt-13-5277-2020, https://doi.org/10.5194/amt-13-5277-2020, 2020
Short summary
Short summary
Ozone lidar is a state-of-the-art remote-sensing instrument to measure atmospheric ozone concentrations with high spatiotemporal resolution. In this study, we show that an ozone lidar can also provide reliable aerosol measurements through intercomparison with colocated aerosol lidar observations.
Maria Filioglou, Elina Giannakaki, John Backman, Jutta Kesti, Anne Hirsikko, Ronny Engelmann, Ewan O'Connor, Jari T. T. Leskinen, Xiaoxia Shang, Hannele Korhonen, Heikki Lihavainen, Sami Romakkaniemi, and Mika Komppula
Atmos. Chem. Phys., 20, 8909–8922, https://doi.org/10.5194/acp-20-8909-2020, https://doi.org/10.5194/acp-20-8909-2020, 2020
Short summary
Short summary
Dust optical properties are region-dependent. Saharan, Asian, and Arabian dusts do not pose similar optical properties in terms of lidar ratios; thus, a universal lidar ratio for dust particles will lead to biases. The present study analyses observations over the United Arab Emirates, quantifying the optical and geometrical extents of the aerosol layers in the area, providing at the same time the Arabian dust properties along with chemical analysis of dust samples collected in the region.
Pyry Pentikäinen, Ewan James O'Connor, Antti Juhani Manninen, and Pablo Ortiz-Amezcua
Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020, https://doi.org/10.5194/amt-13-2849-2020, 2020
Short summary
Short summary
We provide a methodology for obtaining a function describing how the Doppler lidar telescope configuration
impacts the measurements. Together with the function itself, we also provide the uncertainties in the function, which propagate through to provide uncertainties in the geophysical quantities obtained from the measurements. The method can be used to determine how stable the instrument is over time and also identify if changes have been made in the instrument setup.
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
Short summary
Short summary
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.
Steven D. Miller, Louie D. Grasso, Qijing Bian, Sonia M. Kreidenweis, Jack F. Dostalek, Jeremy E. Solbrig, Jennifer Bukowski, Susan C. van den Heever, Yi Wang, Xiaoguang Xu, Jun Wang, Annette L. Walker, Ting-Chi Wu, Milija Zupanski, Christine Chiu, and Jeffrey S. Reid
Atmos. Meas. Tech., 12, 5101–5118, https://doi.org/10.5194/amt-12-5101-2019, https://doi.org/10.5194/amt-12-5101-2019, 2019
Short summary
Short summary
Satellite–based detection of lofted mineral via infrared–window channels, well established in the literature, faces significant challenges in the presence of atmospheric moisture. Here, we consider a case featuring the juxtaposition of two dust plumes embedded within dry and moist air masses. The case is considered from the vantage points of numerical modeling, multi–sensor observations, and radiative transfer theory arriving at a new method for mitigating the water vapor masking effect.
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
Short summary
Short summary
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.
Shannon L. Mason, Robin J. Hogan, Christopher D. Westbrook, Stefan Kneifel, Dmitri Moisseev, and Leonie von Terzi
Atmos. Meas. Tech., 12, 4993–5018, https://doi.org/10.5194/amt-12-4993-2019, https://doi.org/10.5194/amt-12-4993-2019, 2019
Short summary
Short summary
The mass contents of snowflakes are critical to remotely sensed estimates of snowfall. The signatures of snow measured at three radar frequencies can distinguish fluffy, fractal snowflakes from dense and more homogeneous rimed snow. However, we show that the shape of the particle size spectrum also has a significant impact on triple-frequency radar signatures and must be accounted for when making triple-frequency radar estimates of snow that include variations in particle structure and density.
Franziska Glassmeier, Fabian Hoffmann, Jill S. Johnson, Takanobu Yamaguchi, Ken S. Carslaw, and Graham Feingold
Atmos. Chem. Phys., 19, 10191–10203, https://doi.org/10.5194/acp-19-10191-2019, https://doi.org/10.5194/acp-19-10191-2019, 2019
Short summary
Short summary
The climatic relevance of aerosol–cloud interactions depends on the sensitivity of the radiative effect of clouds to certain cloud properties. We derive the dependence of cloud fraction, cloud albedo, and the relative cloud radiative effect on the number of cloud droplets and on liquid water path from a large set of detailed simulations of stratocumulus clouds.
Carolin Klinger, Graham Feingold, and Takanobu Yamaguchi
Atmos. Chem. Phys., 19, 6295–6313, https://doi.org/10.5194/acp-19-6295-2019, https://doi.org/10.5194/acp-19-6295-2019, 2019
Short summary
Short summary
The effect of 1-D and 3-D thermal radiation on cloud droplet growth in shallow cumulus clouds is investigated using large eddy simulations with size-resolved cloud microphysics. A two-step approach is used for separating microphysical effects from dynamical feedbacks. In a parcel framework the main effect on rain production arises from recirculating parcels. Large eddy simulations show that radiative effects on dynamics are stronger than on microphysics, as far as rain production is concerned.
Tatiana Nomokonova, Kerstin Ebell, Ulrich Löhnert, Marion Maturilli, Christoph Ritter, and Ewan O'Connor
Atmos. Chem. Phys., 19, 4105–4126, https://doi.org/10.5194/acp-19-4105-2019, https://doi.org/10.5194/acp-19-4105-2019, 2019
Short summary
Short summary
In this study, properties of clouds at the French–German Arctic research station in Ny-Ålesund are related to in-cloud thermodynamic conditions. The dataset used was collected within the Arctic Amplification project with a set of active and passive remote instruments. The results are compared with a model output. Significant divergence in observations and modelling of single-layer ice and mixed-phase clouds was found.
Jeronimo Escribano, Alessio Bozzo, Philippe Dubuisson, Johannes Flemming, Robin J. Hogan, Laurent C.-Labonnote, and Olivier Boucher
Geosci. Model Dev., 12, 805–827, https://doi.org/10.5194/gmd-12-805-2019, https://doi.org/10.5194/gmd-12-805-2019, 2019
Short summary
Short summary
Accurate shortwave radiance computations are becoming increasingly important for some applications in atmospheric composition. In this work we propose a benchmark protocol and dataset to asses the accuracy and computing runtime of radiance calculations of radiative transfer models. It is applied to four models, showing the potential of this benchmark to evaluate the model performance under a variety of atmospheric conditions, viewing geometries, aerosol loading, and optical properties.
Minttu Tuononen, Ewan J. O'Connor, and Victoria A. Sinclair
Atmos. Chem. Phys., 19, 1985–2000, https://doi.org/10.5194/acp-19-1985-2019, https://doi.org/10.5194/acp-19-1985-2019, 2019
Short summary
Short summary
Many applications require accurate forecasts of the amount of solar radiation reaching the surface, such as solar energy and UV radiation forecasts. This also means that cloud must be correctly forecast. We investigated the skill of these forecasts over Helsinki, Finland, using cloud and solar radiation observations. We found that there were errors in the model radiation forecast even when the clouds were correctly forecast, which we attribute to incorrect representation of the cloud properties.
Ville Vakkari, Antti J. Manninen, Ewan J. O'Connor, Jan H. Schween, Pieter G. van Zyl, and Eleni Marinou
Atmos. Meas. Tech., 12, 839–852, https://doi.org/10.5194/amt-12-839-2019, https://doi.org/10.5194/amt-12-839-2019, 2019
Short summary
Short summary
Commercially available Doppler lidars have been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more.
Anna Nikandrova, Ksenia Tabakova, Antti Manninen, Riikka Väänänen, Tuukka Petäjä, Markku Kulmala, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Chem. Phys., 18, 10575–10591, https://doi.org/10.5194/acp-18-10575-2018, https://doi.org/10.5194/acp-18-10575-2018, 2018
Short summary
Short summary
We investigated temporal and vertical aerosol properties in a rural environment during BAECC (Biogenic Aerosols – Effects on Cloud and Climate) campaign. Differences were observed in aerosol number size distribution, variability and mixing in the layers between two case studies: clear-sky and partly cloudy case. We also conclude that care should be taken in selecting appropriate arrival heights of backward trajectories, since the modelled and observed layer heights did not always coincide.
Ermanno Fionda, Maria Cadeddu, Vinia Mattioli, and Rosa Pacione
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-161, https://doi.org/10.5194/amt-2018-161, 2018
Publication in AMT not foreseen
Short summary
Short summary
The purpose of the present study is to contribute to the understanding of the differences in integrated water vapour (IWV) measurements between Global Positioning System and other observing systems to characterize the uncertainties associated with GPS measurements in Finland. Results show that the GPS agrees with other instruments within 0.5 kg/m2 during winter. During summer the differences increase to 1.5 kg/m2 due to the spatial variability of water vapor in the observation region.
Jake J. Gristey, J. Christine Chiu, Robert J. Gurney, Cyril J. Morcrette, Peter G. Hill, Jacqueline E. Russell, and Helen E. Brindley
Atmos. Chem. Phys., 18, 5129–5145, https://doi.org/10.5194/acp-18-5129-2018, https://doi.org/10.5194/acp-18-5129-2018, 2018
Robin J. Hogan, Tristan Quaife, and Renato Braghiere
Geosci. Model Dev., 11, 339–350, https://doi.org/10.5194/gmd-11-339-2018, https://doi.org/10.5194/gmd-11-339-2018, 2018
Short summary
Short summary
This paper describes a fast new method for calculating how much sunlight is absorbed and reflected by forests and other types of vegetation, rigorously taking account of the complex 3-D structure. Careful evaluation shows it to perform well even in difficult scenes with snow on the ground. The method is suitable for use within the computer models used to make weather and climate forecasts, where it has the potential to improve predictions of near-surface temperature and photosynthesis rates.
Xiaoyi Zhao, Dan Weaver, Kristof Bognar, Gloria Manney, Luis Millán, Xin Yang, Edwin Eloranta, Matthias Schneider, and Kimberly Strong
Atmos. Chem. Phys., 17, 14955–14974, https://doi.org/10.5194/acp-17-14955-2017, https://doi.org/10.5194/acp-17-14955-2017, 2017
Short summary
Short summary
Few scientific questions about surface ozone depletion have been addressed, using a variety of measurements and atmospheric models. The lifetime of reactive bromine is only a few hours in the absence of recycling. Evidence of this recycling over aerosol or blowing-snow/ice particles was found at Eureka. The blowing snow sublimation process is a key step in producing bromine-enriched sea-salt aerosol. Ground-based FTIR isotopologue measurements at Eureka provided evidence of this key step.
Maximilian Maahn, Gijs de Boer, Jessie M. Creamean, Graham Feingold, Greg M. McFarquhar, Wei Wu, and Fan Mei
Atmos. Chem. Phys., 17, 14709–14726, https://doi.org/10.5194/acp-17-14709-2017, https://doi.org/10.5194/acp-17-14709-2017, 2017
Short summary
Short summary
Liquid-containing clouds are a key component of the Arctic climate system and their radiative properties depend strongly on cloud drop sizes. Here, we investigate how cloud drop sizes are modified in the presence of local emissions from industrial facilities at the North Slope of Alaska using aircraft in situ observations. We show that near local anthropogenic sources, the concentrations of black carbon and condensation nuclei are enhanced and cloud drop sizes are reduced.
Shannon L. Mason, J. Christine Chiu, Robin J. Hogan, and Lin Tian
Atmos. Chem. Phys., 17, 11567–11589, https://doi.org/10.5194/acp-17-11567-2017, https://doi.org/10.5194/acp-17-11567-2017, 2017
Short summary
Short summary
Airborne Doppler radar measurements are used to estimate the properties of tropical stratiform rain. Doppler velocity measurements provide sufficient information to estimate the rain rate over land and also to retrieve the raindrop size distribution over ocean, addressing major uncertainties in current satellite measurements of rain. These results suggest that EarthCARE, with the first space-borne Doppler radar, will facilitate improved global measurements of rain.
Elisa T. Sena, Allison McComiskey, and Graham Feingold
Atmos. Chem. Phys., 16, 11301–11318, https://doi.org/10.5194/acp-16-11301-2016, https://doi.org/10.5194/acp-16-11301-2016, 2016
Short summary
Short summary
A new method for assessing aerosol effects on clouds is proposed. For the first time, 14 years of collocated, coincident ground-based observations have been used to study cloud–aerosol–meteorology–radiation interactions in the USA. For this site, the results indicate that the influence of the aerosol on cloud radiative effect and cloud albedo is weak, and that macroscopic cloud properties play a much larger role in determining the cloud radiative effect compared to aerosol effects.
Simone Kotthaus, Ewan O'Connor, Christoph Münkel, Cristina Charlton-Perez, Martial Haeffelin, Andrew M. Gabey, and C. Sue B. Grimmond
Atmos. Meas. Tech., 9, 3769–3791, https://doi.org/10.5194/amt-9-3769-2016, https://doi.org/10.5194/amt-9-3769-2016, 2016
Short summary
Short summary
Ceilometers lidars are useful to study clouds, aerosol layers and atmospheric boundary layer structures. As sensor optics and acquisition algorithms can strongly influence the observations, sensor specifics need to be incorporated into the physical interpretation. Here, recommendations are made for the operation and processing of profile observations from the widely deployed Vaisala CL31 ceilometer. Proposed corrections are shown to increase data quality and even data availability at times.
Moa K. Sporre, Ewan J. O'Connor, Nina Håkansson, Anke Thoss, Erik Swietlicki, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 3193–3203, https://doi.org/10.5194/amt-9-3193-2016, https://doi.org/10.5194/amt-9-3193-2016, 2016
Short summary
Short summary
Satellite measurements of cloud top height and liquid water path are compared to ground-based remote sensing to evaluate the satellite retrievals. The overall performance of the satellite retrievals of cloud top height are good, but they become more problematic when several layers of clouds are present. The liquid water path retrievals also agree well, and the average differences are within the estimated measurement uncertainties.
Riikka Väänänen, Radovan Krejci, Hanna E. Manninen, Antti Manninen, Janne Lampilahti, Stephany Buenrostro Mazon, Tuomo Nieminen, Taina Yli-Juuti, Jenni Kontkanen, Ari Asmi, Pasi P. Aalto, Petri Keronen, Toivo Pohja, Ewan O'Connor, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-556, https://doi.org/10.5194/acp-2016-556, 2016
Revised manuscript has not been submitted
Short summary
Short summary
A light aircraft was used as a platform to explore the horizontal and vertical variability of the aerosol particles over a boreal forest in Central Finland. This information is needed when data measured at ground level station is extrapolated and parameterized to represent the
conditions of the larger scale. The measurements showed that despite local fluctuations there was a good agreement between the on-ground and airborne measurements inside the planetary boundary layer.
Eunsil Jung, Bruce A. Albrecht, Graham Feingold, Haflidi H. Jonsson, Patrick Chuang, and Shaunna L. Donaher
Atmos. Chem. Phys., 16, 8643–8666, https://doi.org/10.5194/acp-16-8643-2016, https://doi.org/10.5194/acp-16-8643-2016, 2016
Short summary
Short summary
This study discusses the properties and variations of aerosol, cloud, and precipitation associated with shallow marine cumulus clouds observed in the North-Atlantic trades during a field campaign (aircraft measurements), which included the most intense African dust event of 2010 at Barbados. The results provide characteristics of Saharan dust as well as marine shallow cumulus clouds from radar measurements, which can provide a basis for the numerical study.
Christopher Perro, Glen Lesins, Thomas J. Duck, and Maria Cadeddu
Atmos. Meas. Tech., 9, 2241–2252, https://doi.org/10.5194/amt-9-2241-2016, https://doi.org/10.5194/amt-9-2241-2016, 2016
Short summary
Short summary
A new microwave satellite water vapour retrieval method for use in the Arctic winter has been developed that uses auxiliary information for atmospheric conditions. When compared to ground-based measurements, the new retrieval has a smaller root mean square deviation than other satellite measurement techniques and can produce high-resolution pan-Arctic water vapour column maps.
Jan Kazil, Graham Feingold, and Takanobu Yamaguchi
Atmos. Chem. Phys., 16, 5811–5839, https://doi.org/10.5194/acp-16-5811-2016, https://doi.org/10.5194/acp-16-5811-2016, 2016
Short summary
Short summary
Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine clouds respond to changes in wind speed? This work presents an investigation of the dynamical response of marine low clouds to different wind speeds over 1 day.
Antti J. Manninen, Ewan J. O'Connor, Ville Vakkari, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 817–827, https://doi.org/10.5194/amt-9-817-2016, https://doi.org/10.5194/amt-9-817-2016, 2016
Short summary
Short summary
Current commercially available Doppler lidars provide a cost-effective solution for measuring vertical and horizontal wind velocities, and the co- and cross-polarised backscatter profiles. However, the background noise behaviour becomes a limiting factor for the instrument sensitivity in low aerosol load regions. In this paper we present a correction method which can improve the data availability up to 50 % and greatly improves the calculation of turbulent properties in weak signal regimes.
Y. Feng, V. R. Kotamarthi, R. Coulter, C. Zhao, and M. Cadeddu
Atmos. Chem. Phys., 16, 247–264, https://doi.org/10.5194/acp-16-247-2016, https://doi.org/10.5194/acp-16-247-2016, 2016
Short summary
Short summary
Aerosol radiative effects are of great importance for climate studies over South Asia, such as the weakening of the South Asian monsoon in the 20th century. This study reveals the altitude dependence of commonly underestimated aerosol radiative properties over this region. It further demonstrates the importance of constraining aerosol vertical distributions and partitioning of scattering vs absorbing aerosols in simulating the subsequent regional dynamical and hydrological responses to aerosols.
A. Solomon, G. Feingold, and M. D. Shupe
Atmos. Chem. Phys., 15, 10631–10643, https://doi.org/10.5194/acp-15-10631-2015, https://doi.org/10.5194/acp-15-10631-2015, 2015
Short summary
Short summary
The maintenance of cloud ice production in Arctic mixed-phase stratocumulus is investigated in large eddy simulations that include a prognostic ice nuclei (IN) formulation and a diurnal cycle. It is demonstrated that IN recycling through subcloud sublimation prolongs ice production. Competing feedbacks between dynamical mixing and recycling are found to slow the rate of ice lost. The results of this study have important implications for the maintenance of phase partitioning in Arctic clouds.
G. Feingold, I. Koren, T. Yamaguchi, and J. Kazil
Atmos. Chem. Phys., 15, 7351–7367, https://doi.org/10.5194/acp-15-7351-2015, https://doi.org/10.5194/acp-15-7351-2015, 2015
Short summary
Short summary
Most research on the relationship between aerosol and closed/open cell transitions tends to focus on the closed to open transition. Here we address the two-way transition between closed and open cellular states using a cloud resolving model. We find inherent asymmetry in the transitions and explain the source of the asymmetry. Results are supported by a dynamical system analogue to the full system.
J. Tonttila, E. J. O'Connor, A. Hellsten, A. Hirsikko, C. O'Dowd, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 5873–5885, https://doi.org/10.5194/acp-15-5873-2015, https://doi.org/10.5194/acp-15-5873-2015, 2015
T. Yamaguchi and G. Feingold
Atmos. Chem. Phys., 15, 1237–1251, https://doi.org/10.5194/acp-15-1237-2015, https://doi.org/10.5194/acp-15-1237-2015, 2015
Short summary
Short summary
Precipitation is necessary but insufficient for transformation to open cells from closed cells. The transformation to open cells occurs for sufficiently small droplet number concentration and/or large rain area. Both of these factors appear to be of similar importance. The distance selects the resulting state for rain regions that alone are too weak to initiate the transformation. The phase trajectory of the variance and mean cloud field properties follow one path.
F. Madonna, M. Rosoldi, J. Güldner, A. Haefele, R. Kivi, M. P. Cadeddu, D. Sisterson, and G. Pappalardo
Atmos. Meas. Tech., 7, 3813–3823, https://doi.org/10.5194/amt-7-3813-2014, https://doi.org/10.5194/amt-7-3813-2014, 2014
Short summary
Short summary
The paper provides the community with criteria to quantify the value of complementary climate measurements and to assess how the uncertainty in a measurement of an ECV is reduced by measurement complementarity. The study demonstrates the potential of entropy and mutual correlation, defined in information theory as metrics for quantifying synergies, and shows that the random uncertainties of a single instrument time series of TCWV can be strongly reduced by including complementary measurements.
Z. J. Lebo and G. Feingold
Atmos. Chem. Phys., 14, 11817–11831, https://doi.org/10.5194/acp-14-11817-2014, https://doi.org/10.5194/acp-14-11817-2014, 2014
J. C. Chiu, J. A. Holmes, R. J. Hogan, and E. J. O'Connor
Atmos. Chem. Phys., 14, 8389–8401, https://doi.org/10.5194/acp-14-8389-2014, https://doi.org/10.5194/acp-14-8389-2014, 2014
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
R. H. Heiblum, I. Koren, and G. Feingold
Atmos. Chem. Phys., 14, 6063–6074, https://doi.org/10.5194/acp-14-6063-2014, https://doi.org/10.5194/acp-14-6063-2014, 2014
A. Hirsikko, E. J. O'Connor, M. Komppula, K. Korhonen, A. Pfüller, E. Giannakaki, C. R. Wood, M. Bauer-Pfundstein, A. Poikonen, T. Karppinen, H. Lonka, M. Kurri, J. Heinonen, D. Moisseev, E. Asmi, V. Aaltonen, A. Nordbo, E. Rodriguez, H. Lihavainen, A. Laaksonen, K. E. J. Lehtinen, T. Laurila, T. Petäjä, M. Kulmala, and Y. Viisanen
Atmos. Meas. Tech., 7, 1351–1375, https://doi.org/10.5194/amt-7-1351-2014, https://doi.org/10.5194/amt-7-1351-2014, 2014
V. S. Manoharan, R. Kotamarthi, Y. Feng, and M. P. Cadeddu
Atmos. Chem. Phys., 14, 1159–1165, https://doi.org/10.5194/acp-14-1159-2014, https://doi.org/10.5194/acp-14-1159-2014, 2014
J. Kazil, G. Feingold, H. Wang, and T. Yamaguchi
Atmos. Chem. Phys., 14, 61–79, https://doi.org/10.5194/acp-14-61-2014, https://doi.org/10.5194/acp-14-61-2014, 2014
G. Feingold and I. Koren
Nonlin. Processes Geophys., 20, 1011–1021, https://doi.org/10.5194/npg-20-1011-2013, https://doi.org/10.5194/npg-20-1011-2013, 2013
M. P. Cadeddu, J. C. Liljegren, and D. D. Turner
Atmos. Meas. Tech., 6, 2359–2372, https://doi.org/10.5194/amt-6-2359-2013, https://doi.org/10.5194/amt-6-2359-2013, 2013
M. Di Pierro, L. Jaeglé, E. W. Eloranta, and S. Sharma
Atmos. Chem. Phys., 13, 7075–7095, https://doi.org/10.5194/acp-13-7075-2013, https://doi.org/10.5194/acp-13-7075-2013, 2013
S.-S. Lee and G. Feingold
Atmos. Chem. Phys., 13, 6713–6726, https://doi.org/10.5194/acp-13-6713-2013, https://doi.org/10.5194/acp-13-6713-2013, 2013
J. L. Petters, H. Jiang, G. Feingold, D. L. Rossiter, D. Khelif, L. C. Sloan, and P. Y. Chuang
Atmos. Chem. Phys., 13, 2507–2529, https://doi.org/10.5194/acp-13-2507-2013, https://doi.org/10.5194/acp-13-2507-2013, 2013
M. Antón, L. Alados-Arboledas, J. L. Guerrero-Rascado, M. J. Costa, J. C Chiu, and F. J. Olmo
Atmos. Chem. Phys., 12, 11723–11732, https://doi.org/10.5194/acp-12-11723-2012, https://doi.org/10.5194/acp-12-11723-2012, 2012
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
PEAKO and peakTree: tools for detecting and interpreting peaks in cloud radar Doppler spectra – capabilities and limitations
An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI
Contrail altitude estimation using GOES-16 ABI data and deep learning
The Ice Cloud Imager: retrieval of frozen water column properties
Supercooled liquid water cloud classification using lidar backscatter peak properties
Marine cloud base height retrieval from MODIS cloud properties using machine learning
How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties
ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data
Simulation and detection efficiency analysis for measurements of polar mesospheric clouds using a spaceborne wide-field-of-view ultraviolet imager
The Chalmers Cloud Ice Climatology: retrieval implementation and validation
The algorithm of microphysical-parameter profiles of aerosol and small cloud droplets based on the dual-wavelength lidar data
Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds
Bayesian cloud-top phase determination for Meteosat Second Generation
Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Using machine learning algorithm to retrieve cloud fraction based on FY-4A AGRI observations
Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Severe hail detection with C-band dual-polarisation radars using convolutional neural networks
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Optimal estimation of cloud properties from thermal infrared observations with a combination of deep learning and radiative transfer simulation
Retrieval of cloud fraction and optical thickness from multi-angle polarization observations
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Infrared Radiometric Image Classification and Segmentation of Cloud Structure Using Deep-learning Framework for Ground-based Infrared Thermal Camera Observations
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
3-D Cloud Masking Across a Broad Swath using Multi-angle Polarimetry and Deep Learning
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 6547–6568, https://doi.org/10.5194/amt-17-6547-2024, https://doi.org/10.5194/amt-17-6547-2024, 2024
Short summary
Short summary
In this study, we present a toolkit of two Python algorithms to extract information from Doppler spectra measured by ground-based cloud radars. In these Doppler spectra, several peaks can be formed due to populations of droplets/ice particles with different fall velocities coexisting in the same measurement time and height. The two algorithms can detect peaks and assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.
Athina Argyrouli, Diego Loyola, Fabian Romahn, Ronny Lutz, Víctor Molina García, Pascal Hedelt, Klaus-Peter Heue, and Richard Siddans
Atmos. Meas. Tech., 17, 6345–6367, https://doi.org/10.5194/amt-17-6345-2024, https://doi.org/10.5194/amt-17-6345-2024, 2024
Short summary
Short summary
This paper describes a new treatment of the spatial misregistration of cloud properties for Sentinel-5 Precursor, when the footprints of different spectral bands are not perfectly aligned. The methodology exploits synergies between spectrometers and imagers, like TROPOMI and VIIRS. The largest improvements have been identified for heterogeneous scenes at cloud edges. This approach is generic and can also be applied to future Sentinel-4 and Sentinel-5 instruments.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R. H. Barrett
Atmos. Meas. Tech., 17, 6145–6162, https://doi.org/10.5194/amt-17-6145-2024, https://doi.org/10.5194/amt-17-6145-2024, 2024
Short summary
Short summary
Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
Atmos. Meas. Tech., 17, 5957–5987, https://doi.org/10.5194/amt-17-5957-2024, https://doi.org/10.5194/amt-17-5957-2024, 2024
Short summary
Short summary
The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Luke Edgar Whitehead, Adrian James McDonald, and Adrien Guyot
Atmos. Meas. Tech., 17, 5765–5784, https://doi.org/10.5194/amt-17-5765-2024, https://doi.org/10.5194/amt-17-5765-2024, 2024
Short summary
Short summary
Supercooled liquid water cloud is important to represent in weather and climate models, particularly in the Southern Hemisphere. Previous work has developed a new machine learning method for measuring supercooled liquid water in Antarctic clouds using simple lidar observations. We evaluate this technique using a lidar dataset from Christchurch, New Zealand, and develop an updated algorithm for accurate supercooled liquid water detection at mid-latitudes.
Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic
Atmos. Meas. Tech., 17, 5655–5677, https://doi.org/10.5194/amt-17-5655-2024, https://doi.org/10.5194/amt-17-5655-2024, 2024
Short summary
Short summary
Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of their base are of essential interest to quantify their radiative effects but remain difficult to derive from satellite data. In this study, we combine observations from the surface and satellite retrievals of cloud properties to build a robust and accurate method to retrieve the cloud base height, based on a computer vision model and ordinal regression.
Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, and Christiane Voigt
Atmos. Meas. Tech., 17, 5161–5185, https://doi.org/10.5194/amt-17-5161-2024, https://doi.org/10.5194/amt-17-5161-2024, 2024
Short summary
Short summary
This study uses radiative transfer calculations to characterize the relation of two satellite channel combinations (namely infrared window brightness temperature differences – BTDs – of SEVIRI) to the thermodynamic cloud phase. A sensitivity analysis reveals the complex interplay of cloud parameters and their contribution to the observed phase dependence of BTDs. This knowledge helps to design optimal cloud-phase retrievals and to understand their potential and limitations.
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Sophie Réthoré, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, Pieter du Preez, and Dirk Furrer
Atmos. Meas. Tech., 17, 4891–4914, https://doi.org/10.5194/amt-17-4891-2024, https://doi.org/10.5194/amt-17-4891-2024, 2024
Short summary
Short summary
ampycloud is a new algorithm developed at MeteoSwiss to characterize the height and sky coverage fraction of cloud layers above aerodromes via ceilometer data. This algorithm was devised as part of a larger effort to fully automate the creation of meteorological aerodrome reports (METARs) at Swiss civil airports. The ampycloud algorithm is implemented as a Python package that is made publicly available to the community under the 3-Clause BSD license.
Ke Ren, Haiyang Gao, Shuqi Niu, Shaoyang Sun, Leilei Kou, Yanqing Xie, Liguo Zhang, and Lingbing Bu
Atmos. Meas. Tech., 17, 4825–4842, https://doi.org/10.5194/amt-17-4825-2024, https://doi.org/10.5194/amt-17-4825-2024, 2024
Short summary
Short summary
Ultraviolet imaging technology has significantly advanced the research and development of polar mesospheric clouds (PMCs). In this study, we proposed the wide-field-of-view ultraviolet imager (WFUI) and built a forward model to evaluate the detection capability and efficiency. The results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. The relationship between ice water content and detection efficiency follows an exponential function distribution.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
Short summary
Short summary
The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Huige Di, Xinhong Wang, Ning Chen, Jing Guo, Wenhui Xin, Shichun Li, Yan Guo, Qing Yan, Yufeng Wang, and Dengxin Hua
Atmos. Meas. Tech., 17, 4183–4196, https://doi.org/10.5194/amt-17-4183-2024, https://doi.org/10.5194/amt-17-4183-2024, 2024
Short summary
Short summary
This study proposes an inversion method for atmospheric-aerosol or cloud microphysical parameters based on dual-wavelength lidar data. It is suitable for the inversion of uniformly mixed and single-property aerosol layers or small cloud droplets. For aerosol particles, the inversion range that this algorithm can achieve is 0.3–1.7 μm. For cloud droplets, it is 1.0–10 μm. This algorithm can quickly obtain the microphysical parameters of atmospheric particles and has better robustness.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2024-2090, https://doi.org/10.5194/egusphere-2024-2090, 2024
Short summary
Short summary
This article presents a novel technique to estimate the liquid water content (LWC) in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows to retrieve the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of the LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024, https://doi.org/10.5194/amt-17-4015-2024, 2024
Short summary
Short summary
ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI) is a method to detect clouds and their thermodynamic phase with a geostationary satellite, distinguishing between clear sky and ice, mixed-phase, supercooled and warm liquid clouds. It uses a Bayesian approach based on the lidar–radar product DARDAR. The method allows studying cloud phases, especially mixed-phase and supercooled clouds, rarely observed from geostationary satellites. This can be used for comparison with climate models.
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024, https://doi.org/10.5194/amt-17-3863-2024, 2024
Short summary
Short summary
Radar–lidar synergy is used to retrieve ice, supercooled water and mixed-phase cloud properties, making the most of the radar sensitivity to ice crystals and the lidar sensitivity to supercooled droplets. A first analysis of the output of the algorithm run on the satellite data is compared with in situ data during an airborne Arctic field campaign, giving a mean percent error of 49 % for liquid water content and 75 % for ice water content.
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024, https://doi.org/10.5194/amt-17-3679-2024, 2024
Short summary
Short summary
The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers. We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
Short summary
Short summary
This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Jinyi Xia and Li Guan
EGUsphere, https://doi.org/10.5194/egusphere-2024-977, https://doi.org/10.5194/egusphere-2024-977, 2024
Short summary
Short summary
This study presents a method for estimating cloud cover from FY4A AGRI observations using LSTM neural networks. The results demonstrate excellent performance in distinguishing clear sky scenes and reducing errors in cloud cover estimation. It shows significant improvements compared to existing methods.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024, https://doi.org/10.5194/amt-17-3323-2024, 2024
Short summary
Short summary
Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024, https://doi.org/10.5194/amt-17-3171-2024, 2024
Short summary
Short summary
This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloe David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1336, https://doi.org/10.5194/egusphere-2024-1336, 2024
Short summary
Short summary
This study demonstrates the potential for enhancing severe hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 17, 3011–3028, https://doi.org/10.5194/amt-17-3011-2024, https://doi.org/10.5194/amt-17-3011-2024, 2024
Short summary
Short summary
We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view.
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-87, https://doi.org/10.5194/amt-2024-87, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study introduces a cloud property retrieval method which integrates traditional radiative transfer simulations with a machine-learning method. Retrievals from a machine learning algorithm are used to provide initial guesses, and a radiative transfer model is used to create radiance lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and is applicable both daytime and nighttime conditions.
Claudia Emde, Veronika Pörtge, Mihail Manev, and Bernhard Mayer
EGUsphere, https://doi.org/10.5194/egusphere-2024-1180, https://doi.org/10.5194/egusphere-2024-1180, 2024
Short summary
Short summary
We introduce an innovative method to retrieve cloud fraction and optical thickness based on polarimetry, well-suited for satellite observations providing multi-angle polarization measurements. The cloud fraction and the cloud optical thickness can be derived from measurements at two viewing angles: one within the cloudbow and a second in the sun-glint region or at a scattering angle of approximately 90°.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-40, https://doi.org/10.5194/amt-2024-40, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Our study investigates the impact of cloud shadows on satellite-based aerosol index measurements over Europe by TROPOMI. Using a cloud shadow detection algorithm and simulations, we found that the overall effect on the aerosol index is minimal. Interestingly, we measured that cloud shadows are significantly bluer than their shadow-free surroundings, but the traditional algorithm already (partly) automatically corrects for this increased blueness.
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
Short summary
Short summary
We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Kélian Sommer, Wassim Kabalan, and Romain Brunet
EGUsphere, https://doi.org/10.5194/egusphere-2024-101, https://doi.org/10.5194/egusphere-2024-101, 2024
Short summary
Short summary
Our research introduces a novel deep-learning approach for classifying and segmenting ground-based infrared thermal images, a crucial step in cloud monitoring. Tests on self-captured data showcase its excellent accuracy in distinguishing image types and in structure segmentation. With potential applications in astronomical observations, our work pioneers a robust solution for ground-based sky quality assessment, promising advancements in the photometric observations experiments.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
Short summary
Short summary
In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
Short summary
Short summary
The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
Short summary
Short summary
We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
Short summary
Short summary
The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
EGUsphere, https://doi.org/10.5194/egusphere-2023-2392, https://doi.org/10.5194/egusphere-2023-2392, 2024
Short summary
Short summary
Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles, and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
Short summary
Short summary
The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
Short summary
Short summary
The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
Short summary
Short summary
The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
Short summary
Short summary
Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
Short summary
Short summary
A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
Short summary
Short summary
Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
Short summary
Short summary
The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
Short summary
Short summary
We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
Short summary
Short summary
Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
Short summary
Short summary
We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
Short summary
Short summary
We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
Short summary
Short summary
The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
Short summary
Short summary
We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
Short summary
Short summary
The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
Short summary
Short summary
JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
Short summary
Short summary
This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
Short summary
Short summary
The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
Short summary
Short summary
The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
Short summary
Short summary
We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Cited articles
Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B.: The impact of humidity above stratiform clouds on indirect aerosol climate forcing, Nature, 432, 1014–1017, 2004.
Ahlgrimm, M. and Forbes, R.: Improving the Representation of Low Clouds and Drizzle in the ECMWF Model Based on ARM Observations from the Azores, Mon. Weather Rev., 142, 668–685, https://doi.org/10.1175/mwr-d-13-00153.1, 2014.
Beard, K.: Terminal velocity and shape of cloud and precipitation drops aloft, J. Atmos. Sci., 33, 851–864, 1976.
Boutle, I. A., Abel, S. J., Hill, P. G., and Morcrette, C. J.: Spatial variability of liquid cloud and rain: observations and microphysical effects, Q. J. Roy. Meteor. Soc., 140, 583–594, https://doi.org/10.1002/qj.2140, 2014.
Cadeddu, M. P., Liljegren, J. C., and Turner, D. D.: The Atmospheric radiation measurement (ARM) program network of microwave radiometers: instrumentation, data, and retrievals, Atmos. Meas. Tech., 6, 2359–2372, https://doi.org/10.5194/amt-6-2359-2013, 2013.
Cheng, A. and Xu, K.-M.: A PDF-based microphysics parameterization for simulation of drizzling boundary layer clouds, J. Atmos. Sci., 66, 2317–2334, 2009.
Chiu, J. C., Marshak, A., Huang, C.-H., Várnai, T., Hogan, R. J., Giles, D. M., Holben, B. N., O'Connor, E. J., Knyazikhin, Y., and Wiscombe, W. J.: Cloud droplet size and liquid water path retrievals from zenith radiance measurements: examples from the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network, Atmos. Chem. Phys., 12, 10313–10329, https://doi.org/10.5194/acp-12-10313-2012, 2012.
Chiu, J. C., Holmes, J. A., Hogan, R. J., and O'Connor, E. J.: The interdependence of continental warm cloud properties derived from unexploited solar background signals in ground-based lidar measurements, Atmos. Chem. Phys., 14, 8389–8401, https://doi.org/10.5194/acp-14-8389-2014, 2014.
Christensen, M. W., Stephens, G. L., and Lebsock, M. D.: Exposing biases in retrieved low cloud properties from CloudSat: a guide for evaluating observations and climate data, J. Geophys. Res.-Atmos., 118, 12120–12131, https://doi.org/10.1002/2013jd020224, 2013.
Clothiaux, E., Mace, G., Ackerman, T., Kane, T., Spinhirne, J., and Scott, V.: An automated algorithm for detection of hydrometeor returns in micropulse lidar data, J. Atmos. Ocean. Tech., 15, 1035–1042, 1998.
Comstock, K. K., Wood, R., Yuter, S. E., and Bretherton, C. S.: Reflectivity and rain rate in and below drizzling stratocumulus, Q. J. Roy. Meteor. Soc., 130, 2891–2918, 2004.
Devenish, B. J., Bartello, P., Brenguier, J. L., Collins, L. R., Grabowski, W. W., IJzermans, R. H. A., Malinowski, S. P., Reeks, M. W., Vassilicos, J. C., Wang, L. P., and Warhaft, Z.: Droplet growth in warm turbulent clouds, Q. J. Roy. Meteor. Soc., 138, 1401–1429, https://doi.org/10.1002/Qj.1897, 2012.
Dong, X. Q. and Mace, G. G.: Profiles of low-level stratus cloud microphysics deduced from ground-based measurements, J. Atmos. Ocean. Tech., 20, 42–53, https://doi.org/10.1175/1520-0426(2003)020<0042:Pollsc>2.0.Co;2, 2003.
Donovan, D. and Lammeren, A.: Cloud effective particle size and water content profile retrievals using combined lidar and radar observations: 1. Theory and examples, J. Geophys. Res.-Atmos., 106, 27425–27448, 2001.
Eloranta, E. W.: Practical model for the calculation of multiply scattered lidar returns, Appl. Optics, 37, 2464–2472, 1998.
Evans, K. F.: The spherical harmonics discrete ordinate method for three-dimensional atmospheric radiative transfer, J. Atmos. Sci., 55, 429–446, https://doi.org/10.1175/1520-0469(1998)055<0429:Tshdom>2.0.Co;2, 1998.
Feingold, G., Cotton, W., Stevens, B., and Frisch, A.: The relationship between drop in-cloud residence time and drizzle production in numerically simulated stratocumulus clouds, J. Atmos. Sci., 53, 1108–1122, 1996.
Feingold, G., Koren, I., Wang, H., Xue, H., and Brewer, W. A.: Precipitation-generated oscillations in open cellular cloud fields, Nature, 466, 849–852, 2010.
Fielding, M. D., Chiu, J. C., Hogan, R. J., and Feingold, G.: A novel ensemble method for retrieving properties of warm cloud in 3-D using ground-based scanning radar and zenith radiances, J. Geophys. Res.-Atmos., 119, 10912–10930, 2014.
Fox, N. I. and Illingworth, A. J.: The retrieval of stratocumulus cloud properties by ground-based cloud radar, J. Appl. Meteorol., 36, 485–492, https://doi.org/10.1175/1520-0450(1997)036<0485:troscp>2.0.co;2, 1997.
Frisch, A. S., Fairall, C. W., and Snider, J. B.: Measurement of stratus cloud and drizzle parameters in astex with a K-alpha-band doppler radar and a microwave radiometer, J. Atmos. Sci., 52, 2788–2799, https://doi.org/10.1175/1520-0469(1995)052<2788:Moscad>2.0.Co;2, 1995.
Frisch, A. S., Feingold, G., Fairall, C. W., Uttal, T., and Snider, J. B.: On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles, J. Geophys. Res.-Atmos., 103, 23195–23197, https://doi.org/10.1029/98jd01827, 1998.
Gerber, H.: Microphysics of marine stratocumulus clouds with two drizzle modes, J. Atmos. Sci., 53, 1649–1662, 1996.
Grecu, M. and Olson, W. S.: Precipitating snow retrievals from combined airborne cloud radar and millimeter-wave radiometer observations, J. Appl. Meteorol. Clim., 47, 1634–1650, https://doi.org/10.1175/2007jamc1728.1, 2008.
Guo, H., Golaz, J. C., and Donner, L.: Aerosol effects on stratocumulus water paths in a PDF-based parameterization, Geophys. Res. Lett., 38, L17808, https://doi.org/10.1029/2011GL048611, 2011.
Hogan, R. J., Gaussiat, N., and Illingworth, A. J.: Stratocumulus liquid water content from dual-wavelength radar, J. Atmos. Ocean. Tech., 22, 1207–1218, https://doi.org/10.1175/Jtech1768.1, 2005.
Hogan, R. J.: Fast approximate calculation of multiply scattered lidar returns, Appl. Optics, 45, 5984–5992, 2006.
Hogan, R. J.: Fast lidar and radar multiple-scattering models. Part I: Small-angle scattering using the photon variance-covariance method, J. Atmos. Sci., 65, 3621–3635, 2008.
Holben, B. N., Eck, T. F., Slutsker, I., Tanre, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F., Jankowiak, I., and Smirnov, A.: AERONET – A federated instrument network and data archive for aerosol characterization, Remote Sens. Environ., 66, 1–16, https://doi.org/10.1016/S0034-4257(98)00031-5, 1998.
Ichimura, I., Fujiwara, M., and Yanase, T.: The size distribution of cloud droplets measured in small maritime cumulus clouds, Meteorol. Soc. Japan J., 58, 403–415, 1980.
Iglesias, M. A., Law, K. J. H., and Stuart, A. M.: Ensemble Kalman methods for inverse problems, Inverse Probl., 29, 045001, https://doi.org/10.1088/0266-5611/29/4/045001, 2013.
Illingworth, A. J., Hogan, R. J., O'Connor, E. J., Bouniol, D., Brooks, M. E., Delanoe, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, J. W. F., Haeffelin, M., Baltink, H. K., Krasnov, O. A., Pelon, J., Piriou, J. M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins, A. M., van Zadelhoff, G. J., Vinit, F., Willen, U., Wilson, D. R., and Wrench, C. L.: Cloudnet – Continuous evaluation of cloud profiles in seven operational models using ground-based observations, B. Am. Meteorol. Soc., 88, 883–898, https://doi.org/10.1175/Bams-88-6-883, 2007.
King, N. J., Bower, K. N., Crosier, J., and Crawford, I.: Evaluating MODIS cloud retrievals with in situ observations from VOCALS-REx, Atmos. Chem. Phys., 13, 191–209, https://doi.org/10.5194/acp-13-191-2013, 2013.
Klein, S. A., Zhang, Y. Y., Zelinka, M. D., Pincus, R., Boyle, J., and Gleckler, P. J.: Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator, J. Geophys. Res.-Atmos., 118, 1329–1342, https://doi.org/10.1002/Jgrd.50141, 2013.
Kollias, P., Szyrmer, W., Rémillard, J., and Luke, E.: Cloud radar Doppler spectra in drizzling stratiform clouds: 2. Observations and microphysical modeling of drizzle evolution, J. Geophys. Res.-Atmos., 116, D13203, https://doi.org/10.1029/2010JD015238, 2011.
Lebsock, M., Morrison H., and Gettelman A.: Microphysical implications of cloud-precipitation covariance derived from satellite remote sensing, J. Geophys. Res. Atmos., 118, 6521–6533, https://doi.org/10.1002/jgrd.50347, 2013
Lee, S., Kahn, B. H., and Teixeira, J.: Characterization of cloud liquid water content distributions from CloudSat, J. Geophys. Res.-Atmos., 115, D20203, https://doi.org/10.1029/2009jd013272, 2010.
Leon, D., Wang C. Z., and Liu D.: Climatology of drizzle in marine boundary layer clouds based on 1 year of data from CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), J. Geophys. Res., 113, D00A14, https://doi.org/10.1029/2008JD009835, 2008
Lewis, E. and Teixeira, J.: The MAGIC of Clouds, Eos, Transactions American Geophysical Union, accepted, 2015.
Liebe, H. J.: An updated model for millimeter wave propagation in moist air, Radio Sci., 20, 1069–1089, https://doi.org/10.1029/RS020i005p01069, 1985.
Liu, Y., Geerts, B., Miller, M., Daum, P., and McGraw, R.: Threshold radar reflectivity for drizzling clouds, Geophys. Res. Lett., 35, L03807, https://doi.org/10.1029/2007GL031201, 2008.
Lolli, S., Welton, E. J., and Campbell, J. R.: Evaluating light rain drop size estimates from multiwavelength micropulse lidar network profiling, J. Atmos. Ocean. Tech., 30, 2798–2807, https://doi.org/10.1175/Jtech-D-13-00062.1, 2013.
Lu, M. L., Sorooshian, A., Jonsson, H. H., Feingold, G., Flagan, R. C., and Seinfeld, J. H.: Marine stratocumulus aerosol-cloud relationships in the MASE-II experiment: precipitation susceptibility in eastern Pacific marine stratocumulus, J. Geophys. Res.-Atmos., 114, D24203, https://doi.org/10.1029/2009JD012774, 2009.
Luke, E. P. and Kollias, P.: Separating cloud and drizzle radar moments during precipitation onset using Doppler spectra, J. Atmos. Ocean. Tech., 30, 1656–1671, 2013.
Mann, J. A. L., Chiu, J. C., Hogan, R. J., O'Connor, E. J., L'Ecuyer, T. S., Stein, T. H. M., and Jefferson, A.: Aerosol impacts on drizzle properties in warm clouds from ARM Mobile Facility maritime and continental deployments, J. Geophys. Res.-Atmos., 119, 4136–4148, 2014.
Martin, W., Cairns, B., and Bal, G.: Adjoint methods for adjusting three-dimensional atmosphere and surface properties to fit multi-angle/multi-pixel polarimetric measurements, J. Quant. Spectrosc. Ra., 144, 68–85, 2014.
Matrosov, S. Y., Uttal, T., and Hazen, D. A.: Evaluation of radar reflectivity-based estimates of water content in stratiform marine clouds, J. Appl. Meteorol., 43, 405–419, https://doi.org/10.1175/1520-0450(2004)043<0405:Eorreo>2.0.Co;2, 2004.
Miles, N. L., Verlinde, J., and Clothiaux, E. E.: Cloud droplet size distributions in low-level stratiform clouds, J. Atmos. Sci., 57, 295–311, https://doi.org/10.1175/1520-0469(2000)057<0295:Cdsdil>2.0.Co;2, 2000.
Nakajima, T. Y., Suzuki, K., and Stephens, G. L.: Droplet growth in warm water clouds observed by the A-Train. Part I: Sensitivity analysis of the MODIS-derived cloud droplet sizes, J. Atmos. Sci., 67, 1884–1896, 2010.
Nicholls, S.: The dynamics of stratocumulus: aircraft observations and comparisons with a mixed layer model, Q. J. Roy. Meteor. Soc., 110, 783–820, 1984.
O'Connor, E. J., Illingworth, A. J., and Hogan, R. J.: A technique for autocalibration of cloud lidar, J. Atmos. Ocean. Tech., 21, 777–786, 2004.
O'Connor, E. J., Hogan, R. J., and Illingworth, A. J.: Retrieving stratocumulus drizzle parameters using Doppler radar and lidar, J. Appl. Meteorol., 44, 14–27, https://doi.org/10.1175/Jam-2181.1, 2005.
Painemal, D. and Zuidema, P.: Assessment of MODIS cloud effective radius and optical thickness retrievals over the Southeast Pacific with VOCALS-REx in situ measurements, J. Geophys. Res.-Atmos., 116, D24206, https://doi.org/10.1029/2011JD016155, 2011.
Pawlowska, H. and Brenguier, J. L.: An observational study of drizzle formation in stratocumulus clouds for general circulation model (GCM) parameterizations, J. Geophys. Res.-Atmos., 108, 8630, https://doi.org/10.1029/2002JD002679, 2003.
Platt, C., Young, S., Carswell, A., Pal, S., McCormick, M., Winker, D., DelGuasta, M., Stefanutti, L., Eberhard, W., and Hardesty, M.: The experimental cloud lidar pilot study (ECLIPS) for cloud-radiation research, B. Am. Meteorol. Soc., 75, 1635–1654, 1994.
Rémillard, J., Kollias, P., and Szyrmer, W.: Radar-radiometer retrievals of cloud number concentration and dispersion parameter in nondrizzling marine stratocumulus, Atmos. Meas. Tech., 6, 1817–1828, https://doi.org/10.5194/amt-6-1817-2013, 2013.
Rosenfeld, D., Wang, H., and Rasch, P. J.: The roles of cloud drop effective radius and LWP in determining rain properties in marine stratocumulus, Geophys. Res. Lett., 39, L13801, https://doi.org/10.1029/2012GL052028, 2012.
Squires, P.: The growth of cloud drops by condensation. I. General characteristics, Austral. J. Chem., 5, 59–86, 1952.
Steiner, M., Smith, J. A., and Uijlenhoet, R.: A microphysical interpretation of radar reflectivity-rain rate relationships, J. Atmos. Sci., 61, 1114–1131, 2004.
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z. E., Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller, S. D., Austin, R. T., Benedetti, A., Mitrescu, C., and Team, C. S.: The cloudsat mission and the a-train – a new dimension of space-based observations of clouds and precipitation, B. Am. Meteorol. Soc., 83, 1771–1790, https://doi.org/10.1175/Bams-83-12-1771, 2002.
Stevens, B. and Lenschow, D. H.: Observations, experiments, and large eddy simulation, B. Am. Meteorol. Soc., 82, 283–294, 2001.
Teixeira, J., Cardoso, S., Bonazzola, M., Cole, J., DelGenio, A., DeMott, C., Franklin, C., Hannay, C., Jakob, C., and Jiao, Y.: Tropical and subtropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI), J. Climate, 24, 5223–5256, 2011.
Twohy, C. H., Petters, M. D., Snider, J. R., Stevens, B., Tahnk, W., Wetzel, M., Russell, L., and Burnet, F.: Evaluation of the aerosol indirect effect in marine stratocumulus clouds: droplet number, size, liquid water path, and radiative impact, J. Geophys. Res.-Atmos., 110, D08203, https://doi.org/10.1029/2004JD005116, 2005.
Twomey, S.: The nuclei of natural cloud formation part II: The supersaturation in natural clouds and the variation of cloud droplet concentration, Geofis. Pura Appl., 43, 243–249, 1959.
Ulbrich, C. W.: Natural variations in the analytical form of the raindrop size distribution, J. Clim. Appl. Meteorol., 22, 1764–1775, 1983.
Vali, G., Kelly, R. D., French, J., Haimov, S., Leon, D., McIntosh, R. E., and Pazmany, A.: Finescale structure and microphysics of coastal stratus, J. Atmos. Sci., 55, 3540–3564, 1998.
Van de Hulst, H. D.: Light Scattering by Small Particles, Wiley, New York, 1957.
vanZanten, M. C., Stevens, B., Vali, G., and Lenschow, D. H.: Observations of drizzle in nocturnal marine stratocumulus, J. Atmos. Sci., 62, 88–106, https://doi.org/10.1175/Jas-3355.1, 2005.
Wang, J. and Geerts, B.: Identifying drizzle within marine stratus with W-band radar reflectivity, Atmos. Res., 69, 1–27, 2003.
Wang, J., Daum, P. H., Yum, S. S., Liu, Y. A., Senum, G. I., Lu, M. L., Seinfeld, J. H., and Jonsson, H.: Observations of marine stratocumulus microphysics and implications for processes controlling droplet spectra: results from the Marine Stratus/Stratocumulus Experiment, J. Geophys. Res.-Atmos., 114, D18210, https://doi.org/10.1029/2008jd011035, 2009.
Wang, M., Ghan, S., Ovchinnikov, M., Liu, X., Easter, R., Kassianov, E., Qian, Y., and Morrison, H.: Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF, Atmos. Chem. Phys., 11, 5431–5455, https://doi.org/10.5194/acp-11-5431-2011, 2011.
Weber, T. and Quaas, J.: Incorporating the subgrid-scale variability of clouds in the autoconversion parameterization using a PDF-scheme, J. Adv. Model. Earth Syst., 4, M11003, https://doi.org/10.1029/2012MS000156, 2012.
Westbrook, C. D., Hogan, R. J., O'Connor, E. J., and Illingworth, A. J.: Estimating drizzle drop size and precipitation rate using two-colour lidar measurements, Atmos. Meas. Tech., 3, 671–681, https://doi.org/10.5194/amt-3-671-2010, 2010.
Widener, K. and Johnson, K.: W-band ARM Cloud Radar (WACR) Handbook, The US Department of Energy, Washington DC, USA, 2006.
Widener, K., Bharadwaj, N., and Johnson, K.: Ka-band ARM Zenith Radar (KAZR) instrument handbook, DOE Office of Science Atmospheric Radiation Measurement (ARM) Program, US Department of Energy (DOE), Washington DC, USA, 2012.
Wood, R.: Parametrization of the effect of drizzle upon the droplet effective radius in stratocumulus clouds, Q. J. Roy. Meteor. Soc., 126, 3309–3324, 2000.
Wood, R.: Drizzle in stratiform boundary layer clouds. Part I: Vertical and horizontal structure, J. Atmos. Sci., 62, 3011–3033, 2005.
Wood, R.: Rate of loss of cloud droplets by coalescence in warm clouds, J. Geophys. Res.-Atmos., 111, D21205, https://doi.org/10.1029/2006jd007553, 2006.
Wood, R. and Hartmann, D. L.: Spatial variability of liquid water path in marine low cloud: the importance of mesoscale cellular convection, J. Climate, 19, 1748–1764, 2006.
Wood, R., Wyant, M., Bretherton, C. S., Rémillard, J., Kollias, P., Fletcher, J., Stemmler, J., deSzoeke, S., Yuter, S., and Miller, M.: clouds, Aerosol, and precipitation in the marine boundary layer: an ARM mobile facility deployment, B. Am. Meteorol. Soc., https://doi.org/10.1175/BAMS-D-13-00180.1, online first, 2014.
Xue, H., Feingold, G., and Stevens, B.: Aerosol effects on clouds, precipitation, and the organization of shallow cumulus convection, J. Atmos. Sci., 65, 392–406, 2008.
Zhang, Z. B., Ackerman, A. S., Feingold, G., Platnick, S., Pincus, R., and Xue, H. W.: Effects of cloud horizontal inhomogeneity and drizzle on remote sensing of cloud droplet effective radius: case studies based on large-eddy simulations, J. Geophys. Res.-Atmos., 117, D19208, https://doi.org/10.1029/2012jd017655, 2012.
Zhou X., Kollias P., and Lewis E. R.: Clouds, Precipitation, and Marine Boundary Layer Structure during the MAGIC Field Campaign, J. Climate, 28, 2420–2442, https://doi.org/10.1175/JCLI-D-14-00320.1, 2015
Zinner, T., Wind, G., Platnick, S., and Ackerman, A. S.: Testing remote sensing on artificial observations: impact of drizzle and 3-D cloud structure on effective radius retrievals, Atmos. Chem. Phys., 10, 9535–9549, https://doi.org/10.5194/acp-10-9535-2010, 2010.
