Articles | Volume 26, issue 1
https://doi.org/10.5194/acp-26-443-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-443-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jan 2026
Research article |
| 08 Jan 2026
| 08 Jan 2026
Demonstrating Aeolus capability to observe wind-cloud interactions
Zacharie Titus
CORRESPONDING AUTHOR
Laboratoire de Météorologie Dynamique/Institut Pierre Simon Laplace (IPSL), Sorbonne Université, CNRS, Institut Polytechnique de Paris, Paris, France
Marine Bonazzola
Laboratoire de Météorologie Dynamique/Institut Pierre Simon Laplace (IPSL), Sorbonne Université, CNRS, Institut Polytechnique de Paris, Paris, France
Hélène Chepfer
Laboratoire de Météorologie Dynamique/Institut Pierre Simon Laplace (IPSL), Sorbonne Université, CNRS, Institut Polytechnique de Paris, Paris, France
Artem G. Feofilov
Laboratoire de Météorologie Dynamique/Institut Pierre Simon Laplace (IPSL), Sorbonne Université, CNRS, Institut Polytechnique de Paris, Paris, France
Marie-Laure Roussel
Laboratoire de Météorologie Dynamique/Institut Pierre Simon Laplace (IPSL), Sorbonne Université, CNRS, Institut Polytechnique de Paris, Paris, France
Benjamin Witschas
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Physik der Atmosphäre, 82234 Oberpfaffenhofen, Germany
Sophie Bastin
Laboratoire ATmosphere Milieux Observations Spatiales/Institut Pierre Simon Laplace (IPSL), UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, CNES, Guyancourt, France
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Benjamin Witschas, Christian Lemmerz, Oliver Lux, Uwe Marksteiner, Oliver Reitebuch, Fabian Weiler, Frederic Fabre, Alain Dabas, Thomas Flament, Dorit Huber, and Michael Vaughan
Atmos. Meas. Tech., 15, 1465–1489, https://doi.org/10.5194/amt-15-1465-2022, https://doi.org/10.5194/amt-15-1465-2022, 2022
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In August 2018, the ESA launched the first Doppler wind lidar into space. In order to calibrate the instrument and to monitor the overall instrument conditions, instrument spectral registration measurements have been performed with Aeolus on a weekly basis. Based on these measurements, the alignment drift of the Aeolus satellite instrument is estimated by applying tools and mathematical model functions to analyze the spectrometer transmission curves.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 1303–1331, https://doi.org/10.5194/amt-15-1303-2022, https://doi.org/10.5194/amt-15-1303-2022, 2022
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The article discusses modifications in the wind retrieval of the ALADIN Airborne Demonstrator (A2D) – one of the key instruments for the validation of Aeolus. Thanks to the retrieval refinements, which are demonstrated in the context of two airborne campaigns in 2019, the systematic and random wind errors of the A2D were significantly reduced, thereby enhancing its validation capabilities. Finally, wind comparisons between A2D and Aeolus for the validation of the satellite data are presented.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, Rodrigo Guzman, Cyprien Gindre, Po-Lun Ma, and Marjolaine Chiriaco
Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, https://doi.org/10.5194/amt-15-1055-2022, 2022
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Space-borne lidars have been providing invaluable information of atmospheric optical properties since 2006, and new lidar missions are on the way to ensure continuous observations. In this work, we compare the clouds estimated from space-borne ALADIN and CALIOP lidar observations. The analysis of collocated data shows that the agreement between the retrieved clouds is good up to 3 km height. Above that, ALADIN detects 40 % less clouds than CALIOP, except for polar stratospheric clouds (PSCs).
Michael R. Gallagher, Matthew D. Shupe, Hélène Chepfer, and Tristan L'Ecuyer
The Cryosphere, 16, 435–450, https://doi.org/10.5194/tc-16-435-2022, https://doi.org/10.5194/tc-16-435-2022, 2022
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By using direct observations of snowfall and mass changes, the variability of daily snowfall mass input to the Greenland ice sheet is quantified for the first time. With new methods we conclude that cyclones west of Greenland in summer contribute the most snowfall, with 1.66 Gt per occurrence. These cyclones are contextualized in the broader Greenland climate, and snowfall is validated against mass changes to verify the results. Snowfall and mass change observations are shown to agree well.
Oscar Javier Rojas Muñoz, Marjolaine Chiriaco, Sophie Bastin, and Justine Ringard
Atmos. Chem. Phys., 21, 15699–15723, https://doi.org/10.5194/acp-21-15699-2021, https://doi.org/10.5194/acp-21-15699-2021, 2021
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A method is developed and evaluated to quantify each process that affects hourly 2 m temperature variations on a local scale, based almost exclusively on observations retrieved from an observatory near the Paris region. Each term involved in surface temperature variations is estimated, and its contribution and importance are also assessed. It is found that clouds are the main modulator on hourly temperature variations for most hours of the day, and thus their characterization is addressed.
Cited articles
Abramian, S., Muller, C., and Risi, C.: Shear-Convection Interactions and Orientation of Tropical Squall Lines, Geophys. Res. Lett., 49, https://doi.org/10.1029/2021GL095184, 2022.
Aeolus Data Innovation and Science Cluster (Aeolus DISC): The Earth Explorer Mission Aeolus for atmospheric wind observations – Final Report from the Aeolus Data Innovation and Science Cluster DISC of Phase E, https://doi.org/10.57676/93c3-n766, 2024.
Ali, S., Mehta, S. K., Ananthavel, A., and Reddy, T. V. R.: Temporal and vertical distributions of the occurrence of cirrus clouds over a coastal station in the Indian monsoon region, Atmos. Chem. Phys., 22, 8321–8342, https://doi.org/10.5194/acp-22-8321-2022, 2022.
Baars, H., Herzog, A., Heese, B., Ohneiser, K., Hanbuch, K., Hofer, J., Yin, Z., Engelmann, R., and Wandinger, U.: Validation of Aeolus wind products above the Atlantic Ocean, Atmos. Meas. Tech., 13, 6007–6024, https://doi.org/10.5194/amt-13-6007-2020, 2020.
Ban, N., Caillaud, C., Coppola, E., Pichelli, E., Sobol, A., Adinolfi, M., Ahrens, B., Alias, A., Anders, I., Bastin, S., Belušić, D., Berthou, S., Brisson, E., Cardoso, R. M., Chan, S. C., Christensen, O. B., Fernández, J., Fita, L., Frisius, T., Gašparac, G., Giorgi, F., Goergen, K., Haugen, J. E., Hodnebrog, Ø., Kartsios, S., Katragkou, E., Kendon, E. J., Keuler, K., Lavin-Gullon, A., Lenderink, G., Leutwyler, D., Lorenz, T., Maraun, D., Mercogliano, P., Milovac, J., Panitz, H.-J., Raffa, M., Remedio, A. R., Schär, C., Soares, P. M. M., Srnec, L., Steensen, B. M., Stocchi, P., Tölle, M. H., Truhetz, H., Vergara-Temprado, J., de Vries, H., Warrach-Sagi, K., Wulfmeyer, V., and Zander, M. J.: The first multi-model ensemble of regional climate simulations at the kilometer-scale resolution, Part I: Evaluation of precipitation, Clim. Dynam. 57, 275–302, https://doi.org/10.1007/s00382-021-05708-w, 2021.
Belova, E., Kirkwood, S., Voelger, P., Chatterjee, S., Satheesan, K., Hagelin, S., Lindskog, M., and Körnich, H.: Validation of Aeolus winds using ground-based radars in Antarctica and in northern Sweden, Atmos. Meas. Tech., 14, 5415–5428, https://doi.org/10.5194/amt-14-5415-2021, 2021.
Bernardino, M., Rusu, L., and Soares, C. G.: Evaluation of the wave energy resources in the Cape Verde Islands, Renewable Energy, 101, 316–326, https://doi.org/10.1016/j.renene.2016.08.040, 2017.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J. L., Klein, S. A., Zhang, Y., Marchand. R., Haynes, J. M., Pincus, R., and John, V. O.: COSP: Satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011.
Bony, S., Schulz, H., Vial, J., and Stevens, B.: Sugar, Gravel, Fish, and Flowers: Dependence of Mesoscale Patterns of Trade-Wind Clouds on Environmental Conditions, Geophys. Res. Lett., 48, https://doi.org/10.1029/2019GL085988, 2020.
Cesana, G., Del Genio, A. D., and Chepfer, H.: The Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), Earth Syst. Sci. Data, 11, 1745–1764, https://doi.org/10.5194/essd-11-1745-2019, 2019.
Chepfer, H., Bony, S., Winker, D., Cesana, G., Dufresne, J. L., Minnis, P., Stubenrauch, C. J., and Zeng, S.: The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP), J. Geophys. Res., 115, D00H16, https://doi.org/10.1029/2009JD012251, 2010.
Chepfer, H., Brogniez, H., and Noel, V.: Diurnal variations of cloud and relative humidity profiles across the tropics, Nature Scientific Report, 9, https://doi.org/10.1038/s41598-019-52437-6, 2019.
Ehlers, F., Flament, T., Dabas, A., Trapon, D., Lacour, A., Baars, H., and Straume-Lindner, A. G.: Optimization of Aeolus' aerosol optical properties by maximum-likelihood estimation, Atmos. Meas. Tech., 15, 185–203, https://doi.org/10.5194/amt-15-185-2022, 2022.
Das, S. K., Chiang, C- W., and Nee, J- B. : Influence of tropical easterly jet on upper tropical cirrus: An observational study from CALIPSO, Aura-MLS, and NCEP/NCAR data, J. Geophys. Res., 116, https://doi.org/10.1029/2011JD015923, 2011.
Donovan, D. P., van Zadelhoff, G.-J., and Wang, P.: Aeolus/ALADIN Algorithm Theoretical Basis Document Level 2A products AEL-FM, AEL-PRO, Document Version V2.00, https://earth.esa.int/documents/d/earth-online/aeolus-level-2a-algorithm-theoretical-baseline-document-ael-fm-and-ael-pro-products (last access: 8 August 2025), 2024.
Feofilov, A. G.: Interactive comment on “Characterization of dark current signal measurements of the ACCDs used on-board the Aeolus satellite” by Fabian Weiler et al., Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-458-RC1, 2021.
Feofilov, A. G. and Stubenrauch, C. J.: Diurnal variation of high-level clouds from the synergy of AIRS and IASI space-borne infrared sounders, Atmos. Chem. Phys., 19, 13957–13972, https://doi.org/10.5194/acp-19-13957-2019, 2019.
Feofilov, A. G., Chepfer, H., Noël, V., Guzman, R., Gindre, C., Ma, P.-L., and Chiriaco, M.: Comparison of scattering ratio profiles retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations and preliminary estimates of cloud fraction profiles, Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, 2022.
Flamant, P., Cuesta, J., Denneulin, M.-L., Dabas, A., and Huber, D.: ADM-Aeolus retrieval algorithms for aerosol and cloud products, Tellus A, 60, 273–288, https://doi.org/10.1111/j.1600-0870.2007.00287.x, 2008.
Fujiwara, M., Xie, S.-P., Shiotani, M., Hashizume, H., and Hasebe, F.: Upper-tropospheric inversion and easterly jet in the tropics, J. Geophys. Res., 108, https://doi.org/10.1029/2003JD003928 , 2003.
Goldberg, R. A., Feofilov, A. G., Pesnell, W. D., and Kutepov, A. A.: Inter-hemispheric Coupling during Northern Polar Summer Periods of 2002–2010 using TIMED/SABER Measurements, J. Atmos. Sol.-Terr. Phys., 104, 277–284, https://doi.org/10.1016/j.jastp.2012.11.018, 2013.
Grubisic, V. and Moncrieff, M. W.: Parameterization of Convective Momentum Transport in Highly Baroclinic Conditions, J. Atmos. Sci., 57, 3035–3049, https://doi.org/10.1175/1520-0469(2000)057<3035:POCMTI>2.0.CO;2, 2000.
Guzman, R., Chepfer, H., Noel, V., Vaillant de Guélis, T., Kay, J. E., Raberanto, P., Cesana, G., Vaughan, M. A., and Winker, D. M.: Direct atmosphere opacity observations from CALIPSO provide new constraints on cloud-radiation interactions, J. Geophys. Res.-Atmos., 122, 1066–1085, https://doi.org/10.1002/2016JD025946, 2017.
Helfer, K. C., Nuijens, L., de Roode, S. R., and Siebesma, A. P.: How wind shear affects trade-wind cumulus convection, J. Adv. Model. Earth Sy., 12, e2020MS002183, https://doi.org/10.1029/2020MS002183, 2020.
Hemanth Kumar, A., Venkat Ratnam, M., Sunilkumar, S. V., Parameswaran, K., and Krishna Murthy, B. V.: Role of deep convection on the tropical tropopause characteristics at sub-daily scales over the South India monsoon region, Atmos. Res., 14–24, https://doi.org/10.1016/j.atmosres.2015.03.012, 2015.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hibbert, K., Glenn, E., Smith, T. M., and González-Cruz, J. E.: Changes to sea surface temperatures and vertical wind shear and their influence on tropical cyclone activity in the Caribbean and the main developing region, Atmosphere, 14, 999, https://doi.org/10.3390/atmos14060999, 2023.
Hierro, R., Steiner, A. K., de la Torre, A., Alexander, P., Llamedo, P., and Cremades, P.: Orographic and convective gravity waves above the Alps and Andes Mountains during GPS radio occultation events – a case study, Atmos. Meas. Tech., 11, 3523–3539, https://doi.org/10.5194/amt-11-3523-2018, 2018.
Hildebrand, P. H.: Shear-Parallel Moist Convection over the Tropical Ocean: A Case Study from 18 February 1993 TOGA COARE, Mon. Weather Rev., 126, 1952–1976, https://doi.org/10.1175/1520-0493(1998)126<1952:spmcot>2.0.co;2, 1998.
Höjgård-Olsen, E., Chepfer, H., and Brogniez, H.: Satellite observed sensitivity of tropical clouds and moisture to sea surface temperature on various time and space scales: 2. Focus on marine low level clouds, J. Geophys. Res.-Atmos., 127, e2021JD035402, https://doi.org/10.1029/2021JD035402, 2022.
Houchi, K., Stoffelen, A., Marseille, G. J., and De Kloe, J.: Comparison of wind and wind shear climatologies derived from high-resolution radiosondes and the ECMWF model, J. Geophys. Res.-Atmos., 115, https://doi.org/10.1029/2009JD013196, 2010.
Hourdin, F., Jam, A., Rio, C., Couvreux, F., Sandu, I., Lefebvre, M. P., Brient, F., and Idelkadi, A.: Unified parameterization of convective boundary layer transport and clouds with the thermal plume model, J. Adv. Model. Earth Sy., 11, 2910–2933, https://doi.org/10.1029/2019MS001666, 2019.
Houze, R. A.: Mesoscale Convective Systems, Rev. Geophys., 42, https://doi.org/10.1029/2004RG000150, 2004.
Iwai, H., Aoki, M., Oshiro, M., and Ishii, S.: Validation of Aeolus Level 2B wind products using wind profilers, ground-based Doppler wind lidars, and radiosondes in Japan, Atmos. Meas. Tech., 14, 7255–7275, https://doi.org/10.5194/amt-14-7255-2021, 2021.
Jauregui, Y. R. and Chen, S. S.: MJO-induced warm pool eastward extension prior to the onset of El Niño: Observations from 1998 to 2019, J. Clim., 37, 855–873, https://doi.org/10.1175/JCLI-D-23-0234.1, 2024.
Jensen, E. J., Ueyama, R., Pfister, L., and Atlas, R. L.: The impacts of gravity waves and wind shear on the lifecycle of cirrus clouds in the tropical tropopause layer, J. Geophys. Res.-Atmos., 130, e2024JD042308, https://doi.org/10.1029/2024JD042308, 2025.
Koning, A. M., Nuijens, L., Mallaun, C., Witschas, B., and Lemmerz, C.: Momentum fluxes from airborne wind measurements in three cumulus cases over land, Atmos. Chem. Phys., 22, 7373–7388, https://doi.org/10.5194/acp-22-7373-2022, 2022.
Koren, I., Oreopoulos, L., Feingold, G., Remer, L. A., and Altaratz, O.: How small is a small cloud?, Atmos. Chem. Phys., 8, 3855–3864, https://doi.org/10.5194/acp-8-3855-2008, 2008.
Koren, I., Remer, L. A., Altaratz, O., Martins, J. V., and Davidi, A.: Aerosol-induced changes of convective cloud anvils produce strong climate warming, Atmos. Chem. Phys., 10, 5001–5010, https://doi.org/10.5194/acp-10-5001-2010, 2010.
Krisch, I., Hindley, N. P., Reitebuch, O., and Wright, C. J.: On the derivation of zonal and meridional wind components from Aeolus horizontal line-of-sight wind, Atmos. Meas. Tech., 15, 3465–3479, https://doi.org/10.5194/amt-15-3465-2022, 2022.
Koteswaram, P.: The easterly jet stream in the tropics, Tellus, 10, 43–57, https://doi.org/10.3402/tellusa.v10i1.9220, 1958.
Liu, S., Huang, S., Tan, Y., Wen, Z., Chen, X., and Guo, Y.: Characteristics and mechanisms of the interannual variability of the Northwest–Southeast shift of the tropical easterly Jet's core in July, J. Clim., 37, 3219–3235, https://doi.org/10.1175/JCLI-D-23-0291.1, 2024.
Lux, O., Lemmerz, C., Weiler, F., Marksteiner, U., Witschas, B., Rahm, S., Geiß, A., and Reitebuch, O.: Intercomparison of wind observations from the European Space Agency's Aeolus satellite mission and the ALADIN Airborne Demonstrator, Atmos. Meas. Tech., 13, 2075–2097, https://doi.org/10.5194/amt-13-2075-2020, 2020.
Lux, O., Witschas, B., Geiß, A., Lemmerz, C., Weiler, F., Marksteiner, U., Rahm, S., Schäfler, A., and Reitebuch, O.: Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign, Atmos. Meas. Tech., 15, 6467–6488, https://doi.org/10.5194/amt-15-6467-2022, 2022.
Marinescu, P. J., Cucurull, L., Apodaca, K., Bucci, L., and Genkova, I.: The characterization and impact of Aeolus wind profile observations in NOAA's regional tropical cyclone model (HWRF), Q. J. Roy. Meteor. Soc., 148, 3491–3508, https://doi.org/10.1002/qj.4370, 2022.
Massie, S., Gettelman, A., Randel, W., and Baumgardner, D.: Distribution of tropical cirrus in relation to convection, J. Geophys. Res.-Atmos., 107, AAC-19, https://doi.org/10.1029/2001JD001293, 2002.
McCoy, D. T., Eastman, R., Hartmann, D. L., and Wood, R.: The Change in Low Cloud Cover in a Warmed Climate Inferred from AIRS, MODIS, and ERA-Interim, J. Clim., 30, 3609–3620, https://doi.org/10.1175/JCLI-D-15-0734.1, 2017.
McGill, M. J., Yorks, J. E., Scott, V. S., Kupchock, A. W., and Selmer, P. A.: The Cloud-Aerosol Transport System (CATS): a technology demonstration on the International Space Station, Lidar Remote Sensing for Environmental Monitoring XV, edited by: Singh, U. N., International Society for Optics and Photonics, SPIE, 9612, 34–39, https://doi.org/10.1117/12.2190841, 2015.
Mieslinger, T., Horváth, Á., Buehler, S. A., and Sakradzija, M.: The dependence of shallow cumulus macrophysical properties on large-scale meteorology as observed in ASTER imagery, J. Geophys. Res.-Atmos., 124, 11477–11505, https://doi.org/10.1029/2019JD030768, 2019.
Mitra, A. P.: Indian ocean experiment [INDOEX]: an overview, 2004, Indian J. Mar. Sci., 33, 30–39, 2004.
Noel, V., Chepfer, H., Chiriaco, M., and Yorks, J.: The diurnal cycle of cloud profiles over land and ocean between 51° S and 51° N, seen by the CATS spaceborne lidar from the International Space Station, Atmos. Chem. Phys., 18, 9457–9473, https://doi.org/10.5194/acp-18-9457-2018, 2018.
Nuijens, L. and Stevens, B.: The Influence of Wind Speed on Shallow Marine Cumulus Convection, J. Atmos. Sci., 69, 168–184, https://doi.org/10.1175/JAS-D-11-02.1, 2012.
Parker, D. J.: Cold pools in shear, Q. J. Roy. Meteor. Soc., 122, 1655–1674, https://doi.org/10.1002/qj.49712253509, 1996.
Qu, X., A. Hall, S. Klein, and DeAngelis, A.: Positive tropical marine low-cloud cover feedback inferred from cloud-controlling factors, Geophys. Res. Lett., 42, 7767–7775, https://doi.org/10.1002/2015GL065627 , 2015.
Reitebuch, O.: The Spaceborne Wind Lidar Mission ADM-Aeolus, in: Atmospheric Physics. Research Topics in Aerospace, edited by: Schumann, U., Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-30183-4_49, 2012.
Reitebuch, O., Huber, D., and Nikolaus, I.: Algorithm Theoretical Basis Document ATBD Level1B Products, https://earth.esa.int/eogateway/documents/20142/37627/Aeolus-L1B-Algorithm-ATBD.pdf (last access: 12 November 2025), 2018.
Ratynski, M., Khaykin, S., Hauchecorne, A., Wing, R., Cammas, J.-P., Hello, Y., and Keckhut, P.: Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence, Atmos. Meas. Tech., 16, 997–1016, https://doi.org/10.5194/amt-16-997-2023, 2023.
Rennie, M., Tan, D., Andersson, E., Poli, P., Dabas, A., De Kloe, J., Marseille, G.-J., and Stoffelen, A.: Aeolus Level-2B algorithm theoretical basis document (mathematical description of the Aeolus Level-2B processor). Change, 3, 23–12, https://earth.esa.int/documents/20142/37627/Aeolus-L2B-Algorithm-ATBD.pdf (last access: 8 August 2025), 2020.
Robe, F. R. and Emanuel, K. A.: The Effect of Vertical Wind Shear on Radiative-Convective Equilibrium States, J. Atmos. Sci., 69, 1427–1445, https://doi.org/10.1175/1520-0469(2001)058<1427:TEOVWS>2.0.CO;2, 2001.
Rotunno, R., Klemp, J. B., and Weisman, M. L.: A Theory for Strong, Long-Lived Squall Lines, J. Atmos. Sci., 45, 463–485, https://doi.org/10.1175/1520-0469(1988)045<0463:ATFSLL>2.0.CO;2, 1988.
Sassen, K., Wang, Z., and Liu, D.: Cirrus clouds and deep convection in the tropics: Insights from CALIPSO and CloudSat, J. Geophys. Res.-Atmos., 114, https://doi.org/10.1029/2009JD011916, 2009.
Sathiyamoorthy, V., Pal, P. K., and Joshi, P. C.: Influence of the Upper-Tropospheric Wind Shear upon Cloud Radiative Forcing in the Asian Monsoon Region, Journal of Climate, 17, 2725–2735, https://doi.org/10.1175/1520-0442(2004)017<2725:IOTUWS>2.0.CO;2, 2004.
Savazzi, A. C. M., Nuijens, L., Sandu, I., George, G., and Bechtold, P.: The representation of the trade winds in ECMWF forecasts and reanalyses during EUREC4A, Atmos. Chem. Phys., 22, 13049–13066, https://doi.org/10.5194/acp-22-13049-2022, 2022.
Schäfler, A., Harvey, B., Methven, J., Doyle, J. D., Rahm, S., Reitebuch, O., and Witschas, B.: Observation of jet stream winds during NAWDEX and characterization of systematic meteorological analysis errors, Mon. Weather Rev., 148, 2889–290, https://doi.org/10.1175/MWR-D-19-0229.1, 2020.
Schulz, B. and Mellado, J. P.: Wind Shear Effects on Radiatively and Evaporatively Driven Stratocumulus Tops, J. Atmos. Sci., 75, 3245–3263, https://doi.org/10.1175/JAS-D-18-0027.1, 2018.
Schumacher, R. S. and Rasmussen, K. L.: The formation, character and changing nature of mesoscale convective systems, Nature Reviews Earth and Environment, 1, 300–314, https://doi.org/10.1038/s43017-020-0057-7, 2020.
Scott, R. C., Myers, T. A., Norris, J. R., Zelinka, M. D., Klein, S. A., Sun, M., and Doelling, D. R.: Observed sensitivity of low-cloud radiative effects to meteorological perturbations over the global oceans, J. Clim., 33, 7717–7734, https://doi.org/10.1175/JCLI-D-19-1028.1, 2020.
Siebesma, A. P., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J., Duynkerke, P. G., Jiang, H., Khairoutdinov, M., Lewellen, D., Moeng, C-H., Sanchez, E., Stevens, B., and Stevens, D. E.: A Large Eddy Simulation Intercomparison Study of Shallow Cumulus Convection, J. Atmos. Sci., 60, 1201–12019, https://doi.org/10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2, 2003.
Stoffelen, A., Pailleux, J., Källen, E., Vaughan, M., Isaksen, L., Flamant, P., Wergen, W., Andersson, E., Schyberg, H., Culoma, A., Meynart, R., Endemann, M., and Ingmann, P.: The atmospheric dynamics mission for global wind field measurement, B. Am. Meteorol. Soc., 86, 73–88, https://doi.org/10.1175/BAMS-86-1-73, 2005.
Thorpe, A. J., Miller, M. J., Moncrieff, M. W.: Two-dimensional convection in non-constant shear: A model of mid-latitude squall lines, Q. J. Roy. Meteor. Soc., 108, 739–762, https://doi.org/10.1002/qj.49710845802, 1982.
Tian, Y., Zhang, Y., Klein, S. A., and Schumacher, C.: Interpreting the diurnal cycle of clouds and precipitation in the ARM GoAmazon observations: Shallow to deep convection transition, J. Geophys. Res.-Atmos., 126, e2020JD033766, https://doi.org/10.1029/2020JD033766, 2021.
Titus, Z.: Data/* and Codes/*, Aeris [data set] and [code], https://doi.org/10.25326/746, 2024.
Voigt, A., Albern, N., Ceppi, P., Grise, K., Li, Y., and Medeiros, B.: Clouds, radiation, and atmospheric circulation in the present-day climate and under climate change, WIREs Clim Change, 12, e694, https://doi.org/10.1002/wcc.694, 2021.
Wang, P., Donovan, D. P., van Zadelhoff, G.-J., de Kloe, J., Huber, D., and Reissig, K.: Evaluation of Aeolus feature mask and particle extinction coefficient profile products using CALIPSO data, Atmos. Meas. Tech., 17, 5935–5955, https://doi.org/10.5194/amt-17-5935-2024, 2024.
Wang, S., Golaz, J. C., and Wang, Q.: Effect of intense wind shear across the inversion on stratocumulus clouds, Geophys. Res. Lett., 35, L15814, https://doi.org/10.1029/2008GL033865, 2008.
Weiler, F., Kanitz, T., Wernham, D., Rennie, M., Huber, D., Schillinger, M., Saint-Pe, O., Bell, R., Parrinello, T., and Reitebuch, O.: Characterization of dark current signal measurements of the ACCDs used on board the Aeolus satellite, Atmos. Meas. Tech., 14, 5153–5177, https://doi.org/10.5194/amt-14-5153-2021, 2021.
Weisman, M. L. Rotunno, R., and Klemp, J. B.: “A Theory for Strong, Long-Lived Squall Lines” revisited, J. Atmos. Sci., 55, 361–382, https://doi.org/10.1175/1520-0469(2004)061<0361:ATFSLS>2.0.CO;2, 2004.
Winker, D. M., Hunt, W. H., and Hostetler, C. A.: Status and Performance of the CALIOP Lidar, Proc. SPIE, 5575, 8–15, https://doi.org/10.1117/12.571955, 2004.
Witschas, B., Rahm, S., Dörnbrack, A., Wagner, J., and Rapp, M.: Airborne Wind Lidar Measurements of Vertical and Horizontal Winds for the Investigation of Orographically Induced Gravity Waves, J. Atmos. Ocean. Technol., 34, 1371–1386, https://doi.org/10.1175/jtech-d-17-0021.1, 2017.
Witschas, B., Lemmerz, C., Geiß, A., Lux, O., Marksteiner, U., Rahm, S., Reitebuch, O., and Weiler, F.: First validation of Aeolus wind observations by airborne Doppler wind lidar measurements, Atmos. Meas. Tech., 13, 2381–2396, https://doi.org/10.5194/amt-13-2381-2020, 2020.
Witschas, B., Lemmerz, C., Geiß, A., Lux, O., Marksteiner, U., Rahm, S., Reitebuch, O., Schäfler, A., and Weiler, F.: Validation of the Aeolus L2B wind product with airborne wind lidar measurements in the polar North Atlantic region and in the tropics, Atmos. Meas. Tech., 15, 7049–7070, https://doi.org/10.5194/amt-15-7049-2022, 2022.
Wood, R.: Stratocumulus clouds, Mon. Weather Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012.
Zamora Zapata, M., Heus, T., and Kleissl, J.: Effects of Surface and Top Wind Shear on the Spatial Organization of Marine Stratocumulus‐Topped Boundary Layers, Journal of Geophysical Research: Atmospheres, 126, https://doi.org/10.1029/2020JD034162, 2021.
Zuidema, P.: Convective clouds over the Bay of Bengal, Mon. Weather Rev., 131, 780–798, https://doi.org/10.1175/1520-0493(2003)131<0780:CCOTBO>2.0.CO;2, 2003.
Short summary
Aeolus spaceborne Doppler Wind Lidar observes perfectly co-located vertical profiles of clouds and vertical profiles of horizontal wind that can be used to study cloud-wind interactions. At regional scale, we show that over the Indian Ocean, high cloud fractions increase when the Tropical Easterly Jet is active. At a smaller scale, we observe for the first time from space differences in the wind profiles within the cloud and its surrounding clear sky, that can be imputed to convective motions.
Aeolus spaceborne Doppler Wind Lidar observes perfectly co-located vertical profiles of clouds...
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