Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.400 IF 3.400
  • IF 5-year value: 3.841 IF 5-year
    3.841
  • CiteScore value: 3.71 CiteScore
    3.71
  • SNIP value: 1.472 SNIP 1.472
  • IPP value: 3.57 IPP 3.57
  • SJR value: 1.770 SJR 1.770
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 70 Scimago H
    index 70
  • h5-index value: 49 h5-index 49
AMT | Articles | Volume 12, issue 2
Atmos. Meas. Tech., 12, 1183–1206, 2019
https://doi.org/10.5194/amt-12-1183-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 12, 1183–1206, 2019
https://doi.org/10.5194/amt-12-1183-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 25 Feb 2019

Research article | 25 Feb 2019

Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides – Part 1: Retrieval development and characterization

Florian Ewald et al.

Related authors

The challenge of simulating the sensitivity of the Amazonian cloud microstructure to cloud condensation nuclei number concentrations
Pascal Polonik, Christoph Knote, Tobias Zinner, Florian Ewald, Tobias Kölling, Bernhard Mayer, Meinrat O. Andreae, Tina Jurkat-Witschas, Thomas Klimach, Christoph Mahnke, Sergej Molleker, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Christiane Voigt, Ralf Weigel, and Manfred Wendisch
Atmos. Chem. Phys., 20, 1591–1605, https://doi.org/10.5194/acp-20-1591-2020,https://doi.org/10.5194/acp-20-1591-2020, 2020
Short summary
Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements
Eleni Marinou, Matthias Tesche, Athanasios Nenes, Albert Ansmann, Jann Schrod, Dimitra Mamali, Alexandra Tsekeri, Michael Pikridas, Holger Baars, Ronny Engelmann, Kalliopi-Artemis Voudouri, Stavros Solomos, Jean Sciare, Silke Groß, Florian Ewald, and Vassilis Amiridis
Atmos. Chem. Phys., 19, 11315–11342, https://doi.org/10.5194/acp-19-11315-2019,https://doi.org/10.5194/acp-19-11315-2019, 2019
Short summary
A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP)
Heike Konow, Marek Jacob, Felix Ament, Susanne Crewell, Florian Ewald, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Mario Mech, and Bjorn Stevens
Earth Syst. Sci. Data, 11, 921–934, https://doi.org/10.5194/essd-11-921-2019,https://doi.org/10.5194/essd-11-921-2019, 2019
Short summary
Calibration of a 35 GHz airborne cloud radar: lessons learned and intercomparisons with 94 GHz cloud radars
Florian Ewald, Silke Groß, Martin Hagen, Lutz Hirsch, Julien Delanoë, and Matthias Bauer-Pfundstein
Atmos. Meas. Tech., 12, 1815–1839, https://doi.org/10.5194/amt-12-1815-2019,https://doi.org/10.5194/amt-12-1815-2019, 2019
Short summary
Cloud geometry from oxygen-A-band observations through an aircraft side window
Tobias Zinner, Ulrich Schwarz, Tobias Kölling, Florian Ewald, Evelyn Jäkel, Bernhard Mayer, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1167–1181, https://doi.org/10.5194/amt-12-1167-2019,https://doi.org/10.5194/amt-12-1167-2019, 2019

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations
Chenxi Wang, Steven Platnick, Kerry Meyer, Zhibo Zhang, and Yaping Zhou
Atmos. Meas. Tech., 13, 2257–2277, https://doi.org/10.5194/amt-13-2257-2020,https://doi.org/10.5194/amt-13-2257-2020, 2020
Short summary
SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Wanyi Xie, Dong Liu, Ming Yang, Shaoqing Chen, Benge Wang, Zhenzhu Wang, Yingwei Xia, Yong Liu, Yiren Wang, and Chaofang Zhang
Atmos. Meas. Tech., 13, 1953–1961, https://doi.org/10.5194/amt-13-1953-2020,https://doi.org/10.5194/amt-13-1953-2020, 2020
Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements
Brent A. McBride, J. Vanderlei Martins, Henrique M. J. Barbosa, William Birmingham, and Lorraine A. Remer
Atmos. Meas. Tech., 13, 1777–1796, https://doi.org/10.5194/amt-13-1777-2020,https://doi.org/10.5194/amt-13-1777-2020, 2020
Short summary
Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery
Jason M. Apke, Kyle A. Hilburn, Steven D. Miller, and David A. Peterson
Atmos. Meas. Tech., 13, 1593–1608, https://doi.org/10.5194/amt-13-1593-2020,https://doi.org/10.5194/amt-13-1593-2020, 2020
Short summary
Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020,https://doi.org/10.5194/amt-13-1575-2020, 2020
Short summary

Cited articles

Alexandrov, M. D., Cairns, B., Emde, C., Ackerman, A. S., and van Diedenhoven, B.: Accuracy assessments of cloud droplet size retrievals from polarized reflectance measurements by the research scanning polarimeter, Remote Sens. Environ., 125, 92–111, https://doi.org/10.1016/j.rse.2012.07.012, 2012. a
Anderson, G., Clough, S., Kneizys, F., Chetwynd, J., and Shettle, E.: AFGL Atmospheric Constituent Profiles (0–120 km), Tech. Rep. AFGL-TR-86-0110, 1986. a
Andreae, M. O., Afchine, A., Albrecht, R., Holanda, B. A., Artaxo, P., Barbosa, H. M. J., Borrmann, S., Cecchini, M. A., Costa, A., Dollner, M., Fütterer, D., Järvinen, E., Jurkat, T., Klimach, T., Konemann, T., Knote, C., Krämer, M., Krisna, T., Machado, L. A. T., Mertes, S., Minikin, A., Pöhlker, C., Pöhlker, M. L., Pöschl, U., Rosenfeld, D., Sauer, D., Schlager, H., Schnaiter, M., Schneider, J., Schulz, C., Spanu, A., Sperling, V. B., Voigt, C., Walser, A., Wang, J., Weinzierl, B., Wendisch, M., and Ziereis, H.: Aerosol characteristics and particle production in the upper troposphere over the Amazon Basin, Atmos. Chem. Phys., 18, 921–961, https://doi.org/10.5194/acp-18-921-2018, 2018. a
Arabas, S., Pawlowska, H., and Grabowski, W. W.: Effective radius and droplet spectral width from in-situ aircraft observations in trade-wind cumuli during RICO, Geophys. Res. Lett., 36, L11803, https://doi.org/10.1029/2009GL038257, 2009. a
Buras, R. and Mayer, B.: Efficient unbiased variance reduction techniques for Monte Carlo simulations of radiative transfer in cloudy atmospheres: the solution, J. Quant. Spectrosc. Ra., 112, 434–447, 2011. a, b
Publications Copernicus
Download
Short summary
This paper presents a new method for gaining insights into the vertical evolution of cloud droplet effective radii by using reflected solar radiation from cloud sides. The paper investigates how bi-spectral effective radius retrievals are affected by unknown cloud surface orientations and presents a method to mitigate this effect. Based on these findings, this study develops a statistical effective radius retrieval for airborne, side-looking imaging sensors.
This paper presents a new method for gaining insights into the vertical evolution of cloud...
Citation