Articles | Volume 8, issue 9
https://doi.org/10.5194/amt-8-3601-2015
© 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-8-3601-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Sensitivity analysis of polarimetric O2 A-band spectra for potential cloud retrievals using OCO-2/GOSAT measurements
S. Sanghavi
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
Department of Atmospheric Science, Colorado State University, Fort Collins, USA
M. Lebsock
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
G. Stephens
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA
Department of Atmospheric Science, Colorado State University, Fort Collins, USA
Related authors
No articles found.
Marcin J. Kurowski, Matthew D. Lebsock, and Kevin M. Smalley
Atmos. Chem. Phys., 25, 15329–15342, https://doi.org/10.5194/acp-25-15329-2025, https://doi.org/10.5194/acp-25-15329-2025, 2025
Short summary
Short summary
This study explores how clouds respond to pollution throughout the day using high-resolution simulations. Polluted clouds show stronger daily changes: thicker clouds at night and in the morning but faster thinning in the afternoon. Pollution reduces rainfall but enhances drying, deepening the cloud layer. While the pollution initially brightens clouds, the daily cycle of cloudiness slightly reduces this brightening effect.
Nitika Yadlapalli Yurk, Matt D. Lebsock, Juan M. Socuellamos, Raquel Rodriguez Monje, Ken B. Cooper, and Pavlos Kollias
Atmos. Meas. Tech., 18, 5141–5155, https://doi.org/10.5194/amt-18-5141-2025, https://doi.org/10.5194/amt-18-5141-2025, 2025
Short summary
Short summary
Current knowledge of the link between clouds and climate is limited by a lack of observations of the drop size distribution (DSD) within clouds, especially for the smallest drops. We demonstrate a method of retrieving DSDs down to small drop sizes using observations of drizzling marine layer clouds captured by the CloudCube millimeter-wave Doppler radar. We compare the shape of the observed spectra to theoretical expectations of radar echoes to solve for DSDs at each time step and elevation.
Luis F. Millán, Matthew D. Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 18, 4483–4495, https://doi.org/10.5194/amt-18-4483-2025, https://doi.org/10.5194/amt-18-4483-2025, 2025
Short summary
Short summary
This study explores the potential of a hypothetical spaceborne radar to observe water vapor within clouds.
Juan Socuellamos, Matthew Lebsock, Raquel Rodriguez Monje, Marcin Kurowski, Derek Posselt, and Robert Beauchamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-4248, https://doi.org/10.5194/egusphere-2025-4248, 2025
Preprint archived
Short summary
Short summary
Using simulated airborne and spaceborne W-band (94 GHz) and G-band (239 GHz) radar observations, this article presents an optimal estimation framework that includes dual-frequency reflectivity and differential absorption measurements to obtain more accurate drizzle retrievals. We demonstrate that an improvement of more than one order of magnitude in the retrieval of the drizzle mixing ratio, droplet concentration, and mass-weighted diameter can be achieved compared to W-band only results.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
Atmos. Meas. Tech., 17, 6965–6981, https://doi.org/10.5194/amt-17-6965-2024, https://doi.org/10.5194/amt-17-6965-2024, 2024
Short summary
Short summary
This article presents a novel technique to estimate liquid water content (LWC) profiles 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 retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
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.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
Short summary
Short summary
This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
Atmos. Meas. Tech., 17, 539–559, https://doi.org/10.5194/amt-17-539-2024, https://doi.org/10.5194/amt-17-539-2024, 2024
Short summary
Short summary
In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
Matthew D. Lebsock and Mikael Witte
Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, https://doi.org/10.5194/acp-23-14293-2023, 2023
Short summary
Short summary
This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.
Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes
Atmos. Meas. Tech., 16, 3531–3546, https://doi.org/10.5194/amt-16-3531-2023, https://doi.org/10.5194/amt-16-3531-2023, 2023
Short summary
Short summary
In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
Short summary
Short summary
We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
Short summary
Short summary
Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
Short summary
Short summary
This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
Cited articles
Abreu, L. and Anderson, G.: The MODTRAN 2/3 report and LOWTRAN 7 model, Contract, 19628, 0132, 1996.
Ackerman, S., Holz, R., Frey, R., Eloranta, E., Maddux, B., and McGill, M.: Cloud detection with MODIS. Part II: validation, J. Atmos. Ocean. Tech., 25, 1073–1086, 2008.
Anderson, G. P., Clough, S., Kneizys, F., Chetwynd, J., and Shettle, E. P.: AFGL atmospheric constituent profiles (0.120 km), Tech. rep., DTIC Document, 1986.
Baker, M.: Cloud microphysics and climate, Science, 276, 1072–1078, 1997.
Bodhaine, B. A., Wood, N. B., Dutton, E. G., and Slusser, J. R.: On Rayleigh optical depth calculations., J. Atmos. Ocean. Tech., 16, 1854–1861, 1999.
Boesche, E., Stammes, P., and Bennartz, R.: Aerosol influence on polarization and intensity in near-infrared O2 and CO2 absorption bands observed from space, J. Quant. Spectrosc. Ra., 110, 223–239, 2009.
Bohren, C. F. and Huffman, D. R.: Absorption and scattering of light by small particles, Wiley, New York, 1983.
Cairns, B., Russell, E. E., and Travis, L. D.: Research scanning polarimeter: calibration and ground-based measurements, in: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, International Society for Optics and Photonics, 186–196, 1999.
Chahine, M. T.: The hydrological cycle and its influence on climate, Nature, 359, 373–380, 1992.
Crisp, D., Atlas, R., Breon, F.-M., Brown, L., Burrows, J., Ciais, P., Connor, B., Doney, S., Fung, I., Jacob, D., Miller, C., O'Brien, D., Pawson, S., Randerson, J., Rayner, P., Salawitch, R., Sander, S., Sen, B., Stephens, G., Tans, P., Toon, G., Wennberg, P., Wofsy, S., Yung, Y., Kuang, Z., Chudasama, B., Sprague, G., Weiss, B., Pollock, R., Kenyon, D., and Schroll, S.: The orbiting carbon observatory (OCO) mission, Adv. Space Res., 34, 700–709, 2004.
Deirmendjian, D.: Electromagnetic Radiation Scattering by Spherical Polydispersed Particles, Elsevier, New York, 1969.
Deschamps, P.-Y., Bréon, F.-M., Leroy, M., Podaire, A., Bricaud, A., Buriez, J.-C., and Seze, G.: The POLDER mission: Instrument characteristics and scientific objectives, IEEE T. Geosci. Remote, 32, 598–615, 1994.
Dessler, A., Palm, S., and Spinhirne, J.: Tropical cloud-top height distributions revealed by the Ice, Cloud, and Land Elevation Satellite (ICESat)/Geoscience Laser Altimeter System (GLAS), J. Geophys. Res.-Atmos., 111, D12215, https://doi.org/10.1029/2005JD006705, 2006.
Diner, D. J., Beckert, J. C., Reilly, T. H., Bruegge, C. J., Conel, J. E., Kahn, R. A., Martonchik, J. V., Ackerman, T. P., Davies, R., Gerstl, S. A., Gordon, H., Muller, J.-P., Myneni, R., Sellers, P., Pinty, B., and Verstraete, M.: Multi-angle Imaging SpectroRadiometer (MISR) instrument description and experiment overview, IEEE T. Geosci. Remote, 36, 1072–1087, 1998.
Diner, D. J., Mischna, M., Chipman, R. A., Davis, A., Cairns, B., Davies, R., Kahn, R. A., Muller, J.-P., and Torres, O.: WindCam and MSPI: two cloud and aerosol instrument concepts derived from Terra/MISR heritage, in: Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, vol. 7081, p. 25, 2008.
Fischer, J. and Grassl, H.: Detection of cloud-top height from backscattered radiances within the oxygen A band. Part 1: Theoretical study, J. Appl. Meteorol., 30, 1245–1259, 1991.
Fischer, J., Cordes, W., Schmitz-Peiffer, A., Renger, W., and Mörl, P.: Detection of cloud-top height from backscattered radiances within the oxygen A band. Part 2: Measurements, J. Appl. Meteorol., 30, 1260–1267, 1991.
Fowler, L. D., Randall, D. A., and Rutledge, S. A.: Liquid and ice cloud microphysics in the CSU general circulation model. Part 1: Model description and simulated microphysical processes, J. Climate, 9, 489–529, 1996.
Frankenberg, C., Hasekamp, O., O'Dell, C., Sanghavi, S., Butz, A., and Worden, J.: Aerosol information content analysis of multi-angle high spectral resolution measurements and its benefit for high accuracy greenhouse gas retrievals, Atmos. Meas. Tech., 5, 1809–1821, https://doi.org/10.5194/amt-5-1809-2012, 2012.
Gómez-Chova, L., Camps-Valls, G., Amorós-López, J., Guanter, L., Alonso, L., Calpe, J., and Moreno, J.: New cloud detection algorithm for multispectral and hyperspectral images: Application to ENVISAT/MERIS and PROBA/CHRIS sensors, in: IEEE International Geoscience and Remote Sensing Symposium, IGARSS, 2757–2760, 2006.
Hamazaki, T., Kaneko, Y., Kuze, A., and Kondo, K.: Fourier transform spectrometer for greenhouse gases observing satellite (GOSAT), in: Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, International Society for Optics and Photonics, 73–80, 2005.
Hasekamp, O. P. and Butz, A.: Efficient calculation of intensity and polarization spectra in vertically inhomogeneous scattering and absorbing atmospheres, J. Geophys. Res.-Atmos., 113, 20309, https://doi.org/10.1029/2008JD010379, 2008.
Heidinger, A. K. and Stephens, G. L.: Molecular line absorption in a scattering atmosphere. Part II: Application to remote sensing in the O2 A band, J. Atmos. Sci., 57, 1615–1634, 2000.
Hovenier, J.: Multiple scattering of polarized light in planetary atmospheres, Astron. Astrophys., 13, 7, 1971.
Key, J. and Barry, R.: Cloud cover analysis with Arctic AVHRR data: 1. Cloud detection, J. Geophys. Res.-Atmos., 94, 18521–18535, 1989.
Koelemeijer, R. B., Stammes, P., Hovenier, J., and de Haan, J.: A fast method for retrieval of cloud parameters using oxygen A band measurements from the Global Ozone Monitoring Experiment, J. Geophys. Res.-Atmos., 106, 3475–3490, 2001.
Kokhanovsky, A. A.: Cloud optics, vol. 34, Springer, 2006.
Kuze, A. and Chance, K. V.: Analysis of cloud top height and cloud coverage from satellites using the O2 A and B bands, J. Geophys. Res.-Atmos., 99, 14481–14491, 1994.
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl. Optics, 48, 6716–6733, 2009.
Lohmann, U. and Feichter, J.: Impact of sulfate aerosols on albedo and lifetime of clouds: A sensitivity study with the ECHAM4 GCM, J. Geophys. Res.-Atmos., 102, 13685–13700, 1997.
Lohmann, U., Stier, P., Hoose, C., Ferrachat, S., Kloster, S., Roeckner, E., and Zhang, J.: Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM, Atmos. Chem. Phys., 7, 3425–3446, https://doi.org/10.5194/acp-7-3425-2007, 2007.
Manolis, I., Grabarnik, S., Caron, J., Bézy, J.-L., Loiselet, M., Betto, M., Barré, H., Mason, G., and Meynart, R.: The MetOp second generation 3MI instrument, in: SPIE Remote Sensing, 88890J–88890J, International Society for Optics and Photonics, 2013.
Mayer, B., Schröder, M., Preusker, R., and Schüller, L.: Remote sensing of water cloud droplet size distributions using the backscatter glory: a case study, Atmos. Chem. Phys., 4, 1255–1263, https://doi.org/10.5194/acp-4-1255-2004, 2004.
Nakajima, T. and King, M. D.: Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: Theory, J. Atmos. Sci., 47, 1878–1893, 1990.
Nakajima, T., King, M. D., Spinhirne, J. D., and Radke, L. F.: Determination of the Optical Thickness and Effective Particle Radius of Clouds from Reflected Solar Radiation Measurements. Part II: Marine Stratocumulus Observations, J. Atmos. Sci., 48, 728–751, 1991.
Nakajima, T. Y. and Nakajma, T.: Wide-area determination of cloud microphysical properties from NOAA AVHRR measurements for FIRE and ASTEX regions, J. Atmos. Sci., 52, 4043–4059, 1995.
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.
O'Brien, D. and Mitchell, R.: Error estimates for retrieval of cloud-top pressure using absorption in the A band of oxygen, J. Appl. Meteorol., 31, 1179–1192, 1992.
O'Brien, D. M., Polonsky, I., O'Dell, C., Kuze, A., Kikuchi, N., Yoshida, Y., and Natraj, V.: Testing the Polarization Model for TANSO-FTS on GOSAT Against Clear-Sky Observations of Sun Glint Over the Ocean, IEEE T. Geosci. Remote, 51, 5199–5209, 2013.
Peng, Y. and Lohmann, U.: Sensitivity study of the spectral dispersion of the cloud droplet size distribution on the indirect aerosol effect, Geophys. Res. Lett., 30, 1507, https://doi.org/10.1029/2003GL017192, 2003.
Peralta, R. J., Nardell, C., Cairns, B., Russell, E. E., Travis, L. D., Mishchenko, M. I., Fafaul, B. A., and Hooker, R. J.: Aerosol polarimetry sensor for the Glory Mission, in: International Symposium on Multispectral Image Processing and Pattern Recognition, 67865L–67865L, International Society for Optics and Photonics, 2007.
Pfeilsticker, K., Erle, F., Funk, O., Veitel, H., and Platt, U.: First geometrical pathlengths probability density function derivation of the skylight from spectroscopically highly resolving oxygen A-band observations: 1. Measurement technique, atmospheric observations and model calculations, J. Geophys. Res.-Atmos., 103, 11483–11504, 1998.
Platnick, S. and Valero, F. P.: A validation of a satellite cloud retrieval during ASTEX, J. Atmos. Sci., 52, 2985–3001, 1995.
Pollock, R., Haring, R. E., Holden, J. R., Johnson, D. L., Kapitanoff, A., Mohlman, D., Phillips, C., Randall, D., Rechsteiner, D., Rivera, J., Rodriguez, J. I., Schwochert, M. A., and Sutin, B. M.: The Orbiting Carbon Observatory Instrument: performance of the OCO instrument and plans for the OCO-2 instrument, in: Remote Sensing, 78260W–78260W, International Society for Optics and Photonics, 2010.
Rodgers, C. D.: Inverse methods for atmospheric sounding: theory and practice, vol. 2, World scientific Singapore, 2000.
Rothman, L. S., Gordon, I. E., Barbe, A., Benner, D. C., Bernath, P. F., Birk, M., Boudon, V., Brown, L. R., Campargue, A., Champion, J.-P., Chance, K., Coudert, L., Dana, V., Devi, V., Fally, S., Flaud, J.-M., Gamache, R., Goldman, A., Jaquemart, D., Kleiner, I., Lacome, N., Lafferty, W., Mandin, J.-Y., Massie, S., Mikhailenko, S., Miller, C., Moazzen-Ahmadi, N., Naumenko, O., Nikitin, A., Orphal, J., Perevalov, V., Perrin, A., Predoi-Cross, A., Rinsland, C., Rotger, M., Simeckova, M., Smith, M., Sung, K., and Tashkun, S.: The HITRAN 2008 molecular spectroscopic database, J. Quant. Spectrosc. Ra., 110, 533–572, 2009.
Rozanov, V. V. and Kokhanovsky, A. A.: Semianalytical cloud retrieval algorithm as applied to the cloud top altitude and the cloud geometrical thickness determination from top-of-atmosphere reflectance measurements in the oxygen A band, J. Geophys. Res.-Atmos., 109, D05202, https://doi.org/10.1029/2003JD004104, 2004.
Rozanov, V. V., Kokhanovsky, A. A., and Burrows, J. P.: The determination of cloud altitudes using GOME reflectance spectra: multilayered cloud systems, IEEE T. Geosci. Remote, 42, 1009–1017, 2004.
Sanghavi, S., Martonchik, J. V., Landgraf, J., and Platt, U.: Retrieval of the optical depth and vertical distribution of particulate scatterers in the atmosphere using O2 A- and B-band SCIAMACHY observations over Kanpur: a case study, Atmos. Meas. Tech., 5, 1099–1119, https://doi.org/10.5194/amt-5-1099-2012, 2012.
Sanghavi, S., Davis, A. B., and Eldering, A.: vSmartMOM: A vector matrix operator method-based radiative transfer model linearized with respect to aerosol properties, J. Quant. Spectrosc. Ra., 133, 412–433, 2014.
Sanghavi, S. V., Martonchik, J. V., Davis, A. B., and Diner, D. J.: Linearization of a scalar matrix operator method radiative transfer model with respect to aerosol and surface properties, J. Quant. Spectrosc. Ra., 116, 1–16, 2013.
Sassen, K., Wang, Z., and Liu, D.: Global distribution of cirrus clouds from CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements, J. Geophys. Res.-Atmos., 113, D00A12, 2008.
Schutgens, N., Tilstra, L., Stammes, P., and Bréon, F.-M.: On the relationship between Stokes parameters Q and U of atmospheric ultraviolet/visible/near-infrared radiation, J. Geophys. Res.-Atmos., 109, D09205, https://doi.org/10.1029/2003JD004081, 2004.
Slingo, A.: Sensitivity of the Earth's radiation budget to changes in low clouds, Nature, 343, 49–51, 1990.
Slingo, A. and Slingo, J.: The response of a general circulation model to cloud longwave radiative forcing. I: Introduction and initial experiments, Q. J. Roy. Meteor. Soc., 114, 1027–1062, 1988.
Stephens, G.: Radiation profiles in extended water clouds. II: Parameterization schemes, J. Atmos. Sci., 35, 2123–2132, 1978.
Stephens, G. L.: Cloud feedbacks in the climate system: A critical review, J. Climate, 18, 237–273, 2005.
Stephens, G. L. and Platt, C.: Aircraft observations of the radiative and microphysical properties of stratocumulus and cumulus cloud fields, J. Climate and applied meteorology, 26, 1243–1269, 1987.
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z., Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller, S., RT, A., Benedetti, A., and Mirescu, C.: 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, 2002.
Stephens, G. L., Vane, D. G., Tanelli, S., Im, E., Durden, S., Rokey, M., Reinke, D., Partain, P., Mace, G. G., Austin, R., Benedetti, A., and Mitrescu, C.: CloudSat mission: Performance and early science after the first year of operation, J. Geophys. Res.-Atmos., 113, D00A18, https://doi.org/10.1029/2008JD009982, 2008.
Tran, H. and Hartmann, J.-M.: An improved O2 A band absorption model and its consequences for retrievals of photon paths and surface pressures, J. Geophys. Res.-Atmos., 113, 18104, https://doi.org/10.1029/2008JD010011, 2008.
van de Hulst, H. C.: Light scattering by small particles, Courier Dover Publications, New York, 1957.
Van Diedenhoven, B., Hasekamp, O., and Landgraf, J.: Retrieval of cloud parameters from satellite-based reflectance measurements in the ultraviolet and the oxygen A-band, J. Geophys. Res.-Atmos., 112, 15208, https://doi.org/10.1029/2006JD008155, 2007.
Wiscombe, W. J.: Improved Mie scattering algorithms, Appl. Optics, 19, 1505–1509, 1980.