Articles | Volume 12, issue 8
https://doi.org/10.5194/amt-12-4421-2019
https://doi.org/10.5194/amt-12-4421-2019
Research article
 | 
19 Aug 2019
Research article |  | 19 Aug 2019

3+2 + X: what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?

Matthias Tesche, Alexei Kolgotin, Moritz Haarig, Sharon P. Burton, Richard A. Ferrare, Chris A. Hostetler, and Detlef Müller

Related authors

Pristine oceans are a significant source of uncertainty in quantifying global cloud condensation nuclei
Goutam Choudhury, Karoline Block, Mahnoosh Haghighatnasab, Johannes Quaas, Tom Goren, and Matthias Tesche
Atmos. Chem. Phys., 25, 3841–3856, https://doi.org/10.5194/acp-25-3841-2025,https://doi.org/10.5194/acp-25-3841-2025, 2025
Short summary
Increased number concentrations of small particles explain perceived stagnation in air quality over Korea
Sohee Joo, Juseon Shin, Matthias Tesche, Naghmeh Dehkhoda, Taegyeong Kim, and Youngmin Noh
Atmos. Chem. Phys., 25, 1023–1036, https://doi.org/10.5194/acp-25-1023-2025,https://doi.org/10.5194/acp-25-1023-2025, 2025
Short summary
Arctic Multilayer Clouds Require Accurate Thermodynamic Profiles and Efficient Primary and Secondary Ice Processes for a Realistic Structure and Composition
Gabriella Wallentin, Annika Oertel, Luisa Ickes, Peggy Achtert, Matthias Tesche, and Corinna Hoose
EGUsphere, https://doi.org/10.5194/egusphere-2024-2988,https://doi.org/10.5194/egusphere-2024-2988, 2024
Short summary
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
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
Multi-section reference value for the analysis of horizontally scanning aerosol lidar observations
Juseon Shin, Gahyeong Kim, Dukhyeon Kim, Matthias Tesche, Gahyeon Park, and Youngmin Noh
Atmos. Meas. Tech., 17, 397–406, https://doi.org/10.5194/amt-17-397-2024,https://doi.org/10.5194/amt-17-397-2024, 2024
Short summary

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Multi-layer retrieval of aerosol optical depth in the troposphere using SEVIRI data: a case study of the European continent
Maryam Pashayi, Mehran Satari, and Mehdi Momeni Shahraki
Atmos. Meas. Tech., 18, 1415–1439, https://doi.org/10.5194/amt-18-1415-2025,https://doi.org/10.5194/amt-18-1415-2025, 2025
Short summary
Star photometry with all-sky cameras to retrieve aerosol optical depth at night-time
Roberto Román, Daniel González-Fernández, Juan Carlos Antuña-Sánchez, Celia Herrero del Barrio, Sara Herrero-Anta, África Barreto, Victoria E. Cachorro, Lionel Doppler, Ramiro González, Christoph Ritter, David Mateos, Natalia Kouremeti, Gustavo Copes, Abel Calle, María José Granados-Muñoz, Carlos Toledano, and Ángel M. de Frutos
EGUsphere, https://doi.org/10.5194/egusphere-2025-667,https://doi.org/10.5194/egusphere-2025-667, 2025
Short summary
Ground-based contrail observations: comparisons with reanalysis weather data and contrail model simulations
Jade Low, Roger Teoh, Joel Ponsonby, Edward Gryspeerdt, Marc Shapiro, and Marc E. J. Stettler
Atmos. Meas. Tech., 18, 37–56, https://doi.org/10.5194/amt-18-37-2025,https://doi.org/10.5194/amt-18-37-2025, 2025
Short summary
Improvements in aerosol layer height retrievals from TROPOMI oxygen A-band measurements by surface albedo fitting in optimal estimation
Martin de Graaf, Maarten Sneep, Mark ter Linden, L. Gijsbert Tilstra, and J. Pepijn Veefkind
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-198,https://doi.org/10.5194/amt-2024-198, 2025
Revised manuscript accepted for AMT
Short summary
Satellite Aerosol Composition Retrieval from a combination of three different Instruments: Information content analysis
Ulrike Stöffelmair, Thomas Popp, Marco Vountas, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2024-2800,https://doi.org/10.5194/egusphere-2024-2800, 2024
Short summary

Cited articles

Ansmann, A. and Müller, D.: Lidar and atmospheric aerosol particles, in: LIDAR–Range-resolved optical remote sensing of the atmosphere, edited by: Weitkamp, C., 105–141, Springer, New York, NY, USA, 2005. a, b, c
Baars, H., Kanitz, T., Engelmann, R., Althausen, D., Heese, B., Komppula, M., Preißler, J., Tesche, M., Ansmann, A., Wandinger, U., Lim, J.-H., Ahn, J. Y., Stachlewska, I. S., Amiridis, V., Marinou, E., Seifert, P., Hofer, J., Skupin, A., Schneider, F., Bohlmann, S., Foth, A., Bley, S., Pfüller, A., Giannakaki, E., Lihavainen, H., Viisanen, Y., Hooda, R. K., Pereira, S. N., Bortoli, D., Wagner, F., Mattis, I., Janicka, L., Markowicz, K. M., Achtert, P., Artaxo, P., Pauliquevis, T., Souza, R. A. F., Sharma, V. P., van Zyl, P. G., Beukes, J. P., Sun, J., Rohwer, E. G., Deng, R., Mamouri, R.-E., and Zamorano, F.: An overview of the first decade of PollyNET: an emerging network of automated Raman-polarization lidars for continuous aerosol profiling, Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, 2016. a
Bi, L., Lin, W., Liu, D., and Zhang, K.: Assessing the depolarization capabilities of nonspherical particles in a super-ellipsoidal shape space, Opt. Express, 26, 1726-1742, https://doi.org/10.1364/OE.26.001726, 2018. a, b
Burton, S. P., Ferrare, R. A., Hostetler, C. A., Hair, J. W., Rogers, R. R., Obland, M. D., Butler, C. F., Cook, A. L., Harper, D. B., and Froyd, K. D.: Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples, Atmos. Meas. Tech., 5, 73–98, https://doi.org/10.5194/amt-5-73-2012, 2012. a, b, c, d, e, f, g, h, i
Burton, S. P., Vaughan, M. A., Ferrare, R. A., and Hostetler, C. A.: Separating mixtures of aerosol types in airborne High Spectral Resolution Lidar data, Atmos. Meas. Tech., 7, 419–436, https://doi.org/10.5194/amt-7-419-2014, 2014. a, b, c, d, e
Download
Short summary
Today, few lidar are capable of triple-wavelength particle linear depolarization ratio (PLDR) measurements. This study is the first systematic investigation of the effect of different choices of PLDR input on the inversion of lidar measurements of mineral dust and dusty mixtures using light scattering by randomly oriented spheroids. We provide recommendations of the most suitable input parameters for use with the applied methodology, based on a relational assessment of the inversion output.
Share