Articles | Volume 13, issue 5
Research article 08 May 2020
Research article | 08 May 2020
A convolutional neural network for classifying cloud particles recorded by imaging probes
Georgios Touloupas et al.
No articles found.
Zane Dedekind, Annika Lauber, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys. Discuss.,
Preprint under review for ACPShort summary
The RACLETS campaign combined cloud and snow research to improve the understanding of precipitation formation in clouds. A numerical weather prediction model, COSMO, was used to assess the importance of ice crystal enhancement by ice-ice collisions on cloud properties. We found that the number of ice crystals increased 1 to 3 orders of magnitude when ice-ice collisions were permitted to occur reducing localized regions of high precipitation and thereby improving the model performance.
Claudia Mignani, Jörg Wieder, Michael A. Sprenger, Zamin A. Kanji, Jan Henneberger, Christine Alewell, and Franz Conen
Atmos. Chem. Phys., 21, 657–664,Short summary
Most precipitation above land starts with ice in clouds. It is promoted by extremely rare particles. Some ice-nucleating particles (INPs) cause cloud droplets to already freeze above −15°C, a temperature at which many clouds begin to snow. We found that the abundance of such INPs among other particles of similar size is highest in precipitating air masses and lowest when air carries desert dust. This brings us closer to understanding the interactions between land, clouds, and precipitation.
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys. Discuss.,
Preprint under review for ACPShort summary
Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol-cloud droplet link in mixed-phase Alpine clouds. Predicted droplet number, Nd, agrees with observations, and never exceeds a characteristic
limiting droplet number, Ndlim, which depends solely on σw. Nd becomes velocity-limited when it is to within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol-cloud interactions.
Annika Lauber, Jan Henneberger, Claudia Mignani, Fabiola Ramelli, Julie T. Pasquier, Jörg Wieder, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys. Discuss.,
Revised manuscript accepted for ACPShort summary
An accurate prediction of the ice crystal number concentration (ICNC) is important to determine the radiation budget, lifetime, and precipitation formation of clouds. Even though secondary ice processes can increase the ICNC by several orders of magnitude, they are poorly constrained and lack a well-founded quantification. During measurements on a mountain slope, a high ICNC of small ice crystals was observed just below 0 °C, attributed to a secondary ice process and parameterized in this study.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Johannes Bühl, Martin Radenz, Patric Seifert, Jörg Wieder, Annika Lauber, Julie T. Pasquier, Ronny Engelmann, Claudia Mignani, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys. Discuss.,
Revised manuscript under review for ACPShort summary
Orographic mixed-phase clouds are an important source of precipitation, but the ice formation processes within them remain uncertain. Here we investigate the origins of ice crystals in a mixed-phase cloud in the Swiss Alps using aerosol and cloud data from in situ and remote sensing observations. We found that ice formation primarily occurs in cloud top generating cells and low-level feeder clouds. Our results indicate that secondary ice processes occur in both of these regions.
Fabiola Ramelli, Jan Henneberger, Robert Oscar David, Annika Lauber, Julie Thérèse Pasquier, Jörg Wieder, Johannes Bühl, Patric Seifert, Ronny Engelmann, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys. Discuss.,
Revised manuscript accepted for ACPShort summary
Interactions between dynamics, microphysics and orography can enhance precipitation. Yet the exact role of these interactions is still uncertain. Here we investigate the role of low-level blocking and turbulence for hydrometeor growth by combining remote sensing and in situ observations. The observations show that blocked flow can induce the formation of liquid layers and that turbulence can enhance ice growth, demonstrating the importance of local flow effects for orographic precipitation.
Fabiola Ramelli, Alexander Beck, Jan Henneberger, and Ulrike Lohmann
Atmos. Meas. Tech., 13, 925–939,Short summary
Boundary layer clouds are influenced by many physical and dynamical processes, making accurate forecasting difficult. Here we present a new measurement platform on a tethered balloon to measure cloud microphysical and meteorological profiles. The unique combination of holography and balloon-borne observations allows high-resolution measurements in a well-defined volume. Field measurements in stratus clouds over the Swiss Plateau revealed unique microphysical signatures in the cloud structure.
Alexander Beck, Jan Henneberger, Jacob P. Fugal, Robert O. David, Larissa Lacher, and Ulrike Lohmann
Atmos. Chem. Phys., 18, 8909–8927,Short summary
This study assesses the impact of surface processes (e.g. blowing snow) on in situ cloud observations at Sonnblick Observatory. Vertical profiles of ice crystal number concentrations (ICNCs) above a snow-covered surface were observed up to a height of 10 m. The ICNC near the ground is at least a factor of 2 larger than at 10 m. Therefore, in situ measurements of ICNCs at mountain-top research stations close to the surface are strongly influenced by surface processes and overestimate the ICNC.
Alexander Beck, Jan Henneberger, Sarah Schöpfer, Jacob Fugal, and Ulrike Lohmann
Atmos. Meas. Tech., 10, 459–476,Short summary
In situ observations of cloud properties in complex alpine terrain are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. In this work example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps are presented.
J. Grazioli, G. Lloyd, L. Panziera, C. R. Hoyle, P. J. Connolly, J. Henneberger, and A. Berne
Atmos. Chem. Phys., 15, 13787–13802,Short summary
This study investigates the microphysics of winter alpine snowfall occurring in mixed-phase clouds in an inner-Alpine valley during CLACE2014. From polarimetric radar and in situ observations, riming is shown to be an important process leading to more intense snowfall. Riming is usually associated with more intense turbulence providing supercooled liquid water. Distinct features are identified in the vertical structure of polarimetric radar variables.
G. Lloyd, T. W. Choularton, K. N. Bower, M. W. Gallagher, P. J. Connolly, M. Flynn, R. Farrington, J. Crosier, O. Schlenczek, J. Fugal, and J. Henneberger
Atmos. Chem. Phys., 15, 12953–12969,Short summary
The paper explores the microphysical structure of clouds at the high-alpine measurement site Jungfraujoch, Switzerland. High concentrations of ice crystals were measured by a range of instruments. The presence of these high concentrations could not be explained through conventional understanding of ice formation processes in clouds and the possibility that the surface provides a significant source of ice crystals is investigated.
J. Henneberger, J. P. Fugal, O. Stetzer, and U. Lohmann
Atmos. Meas. Tech., 6, 2975–2987,
Related subject area
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Ilona Ylivinkka, Santeri Kaupinmäki, Meri Virman, Maija Peltola, Ditte Taipale, Tuukka Petäjä, Veli-Matti Kerminen, Markku Kulmala, and Ekaterina Ezhova
Atmos. Meas. Tech., 13, 5595–5619,Short summary
In this study, we developed a new algorithm for cloud classification using solar radiation and cloud base height measurements. Our objective was to develop a simple and inexpensive but effective algorithm for the needs of studies related to ecosystem and atmosphere interactions. In the present study, we used the algorithm for obtaining cloud statistics at a measurement station in southern Finland, and we discuss the advantages and shortcomings of the algorithm.
Carola Barrientos Velasco, Hartwig Deneke, Hannes Griesche, Patric Seifert, Ronny Engelmann, and Andreas Macke
Atmos. Meas. Tech., 13, 1757–1775,Short summary
In the changing Arctic, quantifying the resulting variability of incoming solar radiation is important to better elucidate the net radiative effect of clouds. As part of a multidisciplinary expedition in the central Arctic held in early summer 2017, a novel network of pyranometers was deployed over an ice floe to investigate the spatiotemporal variability of solar radiation under different sky conditions. This study presents the collected data and an analysis of the spatiotemporal variability.
Sylke Boyd, Stephen Sorenson, Shelby Richard, Michelle King, and Morton Greenslit
Atmos. Meas. Tech., 12, 4241–4259,Short summary
How cirroform clouds affect the radiation balance of the atmosphere depends on their properties, including ice particle types such as crystals, pellets, and fragments. Ice halos form if ice particles in these clouds are in a smooth hexagonal crystalline form. This paper introduces a method to search long-term records of sky images for ice halos, as gathered by total sky imagers (TSIs). Such an analysis will allow one to explore geographical and seasonal variations in cirrus cloud particle types.
Thibault Vaillant de Guélis, Alfons Schwarzenböck, Valery Shcherbakov, Christophe Gourbeyre, Bastien Laurent, Régis Dupuy, Pierre Coutris, and Christophe Duroure
Atmos. Meas. Tech., 12, 2513–2529,
Michael L. Larsen and Raymond A. Shaw
Atmos. Meas. Tech., 11, 4261–4272,Short summary
A statistical tool frequently utilized to measure scale-dependent departures from perfect randomness is the radial distribution function. This tool has many strengths, but it is not easy to calculate for particle detections within a three-dimensional sample volume. In this manuscript, we introduce and test a new method to estimate the three-dimensional radial distribution function in realistic measurement volumes.
Jiangchuan Tao, Chunsheng Zhao, Ye Kuang, Gang Zhao, Chuanyang Shen, Yingli Yu, Yuxuan Bian, and Wanyun Xu
Atmos. Meas. Tech., 11, 895–906,Short summary
Existing chamber technologies for direct measurements of number concentration of cloud condensation nuclei (NCCN) are sophisticated and expensive. In this paper, a new method is proposed to calculate NCCN based only on measurements of a humidified nephelometer system which have accounted for influences of both aerosol size and aerosol hygroscopicity on NCCN calculation. This new method makes NCCN measurements more convenient and is capable of obtaining NCCN at lower supersaturations.
Christine Aebi, Julian Gröbner, Niklaus Kämpfer, and Laurent Vuilleumier
Atmos. Meas. Tech., 10, 4587–4600,Short summary
The current study analyses the cloud radiative effect during the daytime depending on cloud fraction and cloud type at two stations in Switzerland over a time period of 3–5 years. Information about fractional cloud coverage and cloud type is retrieved from images taken by visible all-sky cameras. Cloud cover, cloud type and other atmospheric parameters have an influence on the magnitude of the longwave cloud effect as well as on the shortwave.
Emmanuel Fontaine, Delphine Leroy, Alfons Schwarzenboeck, Julien Delanoë, Alain Protat, Fabien Dezitter, Alice Grandin, John Walter Strapp, and Lyle Edward Lilie
Atmos. Meas. Tech., 10, 2239–2252,Short summary
In this study we evaluate a method to estimate cloud water content (CWC) knowing cloud reflectivity. Ice hydrometeors are replace by ice oblate spheroids to simulate their reflectivity. There is no assumption on the relation between mass and their size. Then, a broad range of CWCs are compared with direct measurements of CWC. The accuracy of the method is ~ ±32 %. This study is performed in areas of convective clouds where reflectivity and CWC are especially high, what makes it unique.
Hsu-Yung Cheng and Chih-Lung Lin
Atmos. Meas. Tech., 10, 199–208,Short summary
A cloud detection method for all-sky images is proposed. Obtaining improved cloud detection results is helpful for cloud classification, tracking and solar irradiance prediction. The features are extracted from local image patches with different sizes to include local structure and multi-resolution information. The cloud models are learned through the training process. We have shown that taking advantages of multiple classifiers and various patch sizes is able to increase the detection accuracy.
Qingyong Li, Zhen Zhang, Weitao Lu, Jun Yang, Ying Ma, and Wen Yao
Atmos. Meas. Tech., 9, 753–764,Short summary
This paper proposes a new cloud classification method, named bag of micro-structures (BoMS), for whole-sky imagers. BoMS treats an all-sky image as a collection of micro-structures mapped from image patches, rather than a collection of pixels. BoMS identifies five different sky conditions: cirriform, cumuliform, stratiform, clear sky, and mixed cloudiness (often appearing in all-sky images but seldom addressed in the literature). The performance of BoMS overperforms those of traditional methods.
Som Sharma, Rajesh Vaishnav, Munn V. Shukla, Prashant Kumar, Prateek Kumar, Pradeep K. Thapliyal, Shyam Lal, and Yashwant B. Acharya
Atmos. Meas. Tech., 9, 711–719,Short summary
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S. Gagné, L. P. MacDonald, W. R. Leaitch, and J. R. Pierce
Atmos. Meas. Tech., 9, 619–630,Short summary
Measurements of clouds with an aircraft are essential to understand how clouds form and how they affect the Earth's climate. These measurements are used in climate models to help predict how our climate might develop in the next century. Aircraft measurements are, however, difficult for modellers to interpret because the way they were acquired and analyzed varies from one team of scientists to the next. We present a software platform for scientists to share and compare their analysis tools.
H.-Y. Cheng and C.-C. Yu
Atmos. Meas. Tech., 8, 1173–1182,Short summary
This work performs cloud classification on all-sky images. To deal with mixed cloud types, we propose performing block-based classification. The proposed method combines local texture features with classical statistical texture features. The experimental results have shown that applying the combined feature results in higher classification accuracy. It is also validated that using block-based classification outperforms classification on the entire images.
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Atmos. Meas. Tech., 8, 761–777,
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Atmos. Meas. Tech., 2, 779–788,
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Images of cloud particles give important information for improving our understanding of microphysical cloud processes. For phase-resolved measurements, a large number of water droplets and ice crystals need to be classified by an automated approach. In this study, a convolutional neural network was designed, which exceeds the classification ability of traditional methods and therefore shortens the analysis procedure of cloud particle images.
Images of cloud particles give important information for improving our understanding of...