Articles | Volume 18, issue 20
https://doi.org/10.5194/amt-18-5841-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-5841-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Oct 2025
Research article |
| 29 Oct 2025
| 29 Oct 2025
A new technique to retrieve aerosol vertical profiles using micropulse lidar and ground-based aerosol measurements
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
Seth A. Thompson
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
Brianna H. Matthews
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
now at: Savannah River National Laboratory, Aiken, South Carolina, 29808, United States
Milind Sharma
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
Ron Li
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
Christopher J. Nowotarski
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
Anita D. Rapp
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
Sarah D. Brooks
CORRESPONDING AUTHOR
Department of Atmospheric Sciences, Texas A&M University, College Station, 77843, United States
Related authors
No articles found.
Paul J. DeMott, Jessica A. Mirrielees, Sarah Suda Petters, Daniel J. Cziczo, Markus D. Petters, Heinz G. Bingemer, Thomas C. J. Hill, Karl Froyd, Sarvesh Garimella, A. Gannet Hallar, Ezra J. T. Levin, Ian B. McCubbin, Anne E. Perring, Christopher N. Rapp, Thea Schiebel, Jann Schrod, Kaitlyn J. Suski, Daniel Weber, Martin J. Wolf, Maria Zawadowicz, Jake Zenker, Ottmar Möhler, and Sarah D. Brooks
Atmos. Meas. Tech., 18, 639–672, https://doi.org/10.5194/amt-18-639-2025, https://doi.org/10.5194/amt-18-639-2025, 2025
Short summary
Short summary
The Fifth International Ice Nucleation Workshop Phase 3 (FIN-03) compared the ambient atmospheric performance of ice-nucleating particle (INP) measuring systems and explored general methods for discerning atmospheric INP compositions. Mirroring laboratory results, INP concentrations agreed within 5–10 factors. Measurements of total aerosol properties and investigations of INP compositions supported a dominant role of soil and plant organic aerosol elements as INPs during the study.
Daniel C. O. Thornton, Sarah D. Brooks, Elise K. Wilbourn, Jessica Mirrielees, Alyssa N. Alsante, Gerardo Gold-Bouchot, Andrew Whitesell, and Kiana McFadden
Atmos. Chem. Phys., 23, 12707–12729, https://doi.org/10.5194/acp-23-12707-2023, https://doi.org/10.5194/acp-23-12707-2023, 2023
Short summary
Short summary
A major uncertainty in our understanding of clouds and climate is the sources and properties of the aerosol on which clouds grow. We found that aerosol containing organic matter from fast-growing marine phytoplankton was a source of ice-nucleating particles (INPs). INPs facilitate freezing of ice crystals at warmer temperatures than otherwise possible and therefore change cloud formation and properties. Our results show that ecosystem processes and the properties of sea spray aerosol are linked.
Guangyu Li, Elise K. Wilbourn, Zezhen Cheng, Jörg Wieder, Allison Fagerson, Jan Henneberger, Ghislain Motos, Rita Traversi, Sarah D. Brooks, Mauro Mazzola, Swarup China, Athanasios Nenes, Ulrike Lohmann, Naruki Hiranuma, and Zamin A. Kanji
Atmos. Chem. Phys., 23, 10489–10516, https://doi.org/10.5194/acp-23-10489-2023, https://doi.org/10.5194/acp-23-10489-2023, 2023
Short summary
Short summary
In this work, we present results from an Arctic field campaign (NASCENT) in Ny-Ålesund, Svalbard, on the abundance, variability, physicochemical properties, and potential sources of ice-nucleating particles (INPs) relevant for mixed-phase cloud formation. This work improves the data coverage of Arctic INPs and aerosol properties, allowing for the validation of models predicting cloud microphysical and radiative properties of mixed-phase clouds in the rapidly warming Arctic.
Kevin M. Smalley and Anita D. Rapp
Atmos. Chem. Phys., 21, 2765–2779, https://doi.org/10.5194/acp-21-2765-2021, https://doi.org/10.5194/acp-21-2765-2021, 2021
Short summary
Short summary
We use satellite observations of shallow cumulus clouds to investigate the influence of cloud size on the ratio of cloud water path to rainwater (WRR) in different environments. For a fixed temperature and relative humidity, WRR increases with cloud size, but it varies little with aerosols. These results imply that increasing WRR with rising temperature relates not only to deeper clouds but also to more frequent larger clouds.
Cited articles
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989.
Andreae, M. O., Rosenfeld, D., Artaxo, P., Costa, A. A., Frank, G., Longo, K. M., and Silva-Dias, M. A. F.: Smoking rain clouds over the Amazon, Science, 303, 1337–1342, https://doi.org/10.1126/science.1092779, 2004.
Ansmann, A., Ohneiser, K., Mamouri, R.-E., Knopf, D. A., Veselovskii, I., Baars, H., Engelmann, R., Foth, A., Jimenez, C., Seifert, P., and Barja, B.: Tropospheric and stratospheric wildfire smoke profiling with lidar: mass, surface area, CCN, and INP retrieval, Atmos. Chem. Phys., 21, 9779–9807, https://doi.org/10.5194/acp-21-9779-2021, 2021.
Brooks, S. and Chen, B.: Mini-Micropulse Lidar data from TAMU TRACER campaign in the Houston TX region from July to September 2022, Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.5439/1972461, 2023.
Brooks, S. and Thompson, S.: Ice nucleation measurements from DRUM impactors during TRACER campaign in the Houston TX region from July to September 2022, Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.5439/1972460, 2023.
Brooks, S. D., DeMott, P. J., and Kreidenweis, S. M.: Water uptake by particles containing humic materials and mixtures of humic materials with ammonium sulfate, Atmospheric Environment, 38, 1859–1868, https://doi.org/10.1016/j.atmosenv.2004.01.009, 2004a.
Brooks, S. D., Toon, O. B., Tolbert, M. A., Baumgardner, D., Gandrud, B. W., Browell, E. V., Flentje, H., and Wilson, J. C.: Polar stratospheric clouds during SOLVE/THESEO: Comparison of lidar observations with in situ measurements, Journal of Geophysical Research: Atmospheres, 109, https://doi.org/10.1029/2003jd003463, 2004b.
Cai, T. T. and Silverman, B. W.: Incorporating information on neighbouring coefficients into wavelet estimation, Sankhyā: The Indian Journal of Statistics, Series B, 127–148, http://www.jstor.org/stable/25053168 (last access: 20 October 2025), 2001.
Campbell, J. R., Hlavka, D. L., Welton, E. J., Flynn, C. J., Turner, D. D., Spinhirne, J. D., Scott III, V. S., and Hwang, I.: Full-time, eye-safe cloud and aerosol lidar observation at atmospheric radiation measurement program sites: Instruments and data processing, Journal of Atmospheric and Oceanic Technology, 19, 431–442, https://doi.org/10.1175/1520-0426(2002)019<0431:ftesca>2.0.co;2, 2002.
Chen, B., Thompson, S. A., and Brooks, S. D.: TAMU TRACER SMPS-POPS Merged Size Distribution (V1), Texas Data Repository [data set], https://doi.org/10.18738/T8/NUX5AZ, 2024.
Cotterell, M. I., Willoughby, R. E., Bzdek, B. R., Orr-Ewing, A. J., and Reid, J. P.: A complete parameterisation of the relative humidity and wavelength dependence of the refractive index of hygroscopic inorganic aerosol particles, Atmos. Chem. Phys., 17, 9837–9851, https://doi.org/10.5194/acp-17-9837-2017, 2017.
Dadashazar, H., Crosbie, E., Choi, Y., Corral, A. F., DiGangi, J. P., Diskin, G. S., Dmitrovic, S., Kirschler, S., McCauley, K., and Moore, R. H.: Analysis of MONARC and ACTIVATE Airborne Aerosol Data for Aerosol-Cloud Interaction Investigations: Efficacy of Stairstepping Flight Legs for Airborne In Situ Sampling, Atmosphere, 13, 1242, https://doi.org/10.3390/atmos13081242, 2022.
DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D., Twohy, C. H., Richardson, M., Eidhammer, T., and Rogers, D.: Predicting global atmospheric ice nuclei distributions and their impacts on climate, Proceedings of the National Academy of Sciences, 107, 11217–11222, https://doi.org/10.1073/pnas.0910818107, 2010.
DeMott, P. J., Prenni, A. J., McMeeking, G. R., Sullivan, R. C., Petters, M. D., Tobo, Y., Niemand, M., Möhler, O., Snider, J. R., Wang, Z., and Kreidenweis, S. M.: Integrating laboratory and field data to quantify the immersion freezing ice nucleation activity of mineral dust particles, Atmos. Chem. Phys., 15, 393–-409, https://doi.org/10.5194/acp-15-393-2015, 2015.
Du, P., Kibbe, W. A., and Lin, S. M.: Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching, Bioinformatics, 22, 2059-2065, https://doi.org/10.1093/bioinformatics/btl355, 2006.
Fan, J., Zhang, R., Li, G., and Tao, W. K.: Effects of aerosols and relative humidity on cumulus clouds, Journal of Geophysical Research: Atmospheres, 112, https://doi.org/10.1029/2006JD008136, 2007.
Fan, J., Wang, Y., Rosenfeld, D., and Liu, X.: Review of aerosol–cloud interactions: Mechanisms, significance, and challenges, Journal of the Atmospheric Sciences, 73, 4221–4252, https://doi.org/10.1175/JAS-D-16-0037.1, 2016.
Fan, J., Rosenfeld, D., Zhang, Y., Giangrande, S. E., Li, Z., Machado, L. A., Martin, S. T., Yang, Y., Wang, J., and Artaxo, P.: Substantial convection and precipitation enhancements by ultrafine aerosol particles, Science, 359, 411–418, https://doi.org/10.1126/science.aan8461, 2018.
Fang, H.-T. and Huang, D.-S.: Noise reduction in lidar signal based on discrete wavelet transform, Optics Communications, 233, 67–76, https://doi.org/10.1016/j.optcom.2004.01.017, 2004.
Fernald, F. G.: Analysis of atmospheric lidar observations: some comments, Applied optics, 23, 652–653, https://doi.org/10.1364/ao.23.000652, 1984.
Fernald, F. G., Herman, B. M., and Reagan, J. A.: Determination of aerosol height distributions by lidar, Journal of Applied Meteorology and Climatology, 11, 482–489, https://doi.org/10.1175/1520-0450(1972)011<0482:doahdb>2.0.co;2, 1972.
Flynn, C. J., Mendozaa, A., Zhengb, Y., and Mathurb, S.: Novel polarization-sensitive micropulse lidar measurement technique, Optics Express, 15, 2785–2790, https://doi.org/10.1364/OE.15.002785, 2007.
Fornea, A. P., Brooks, S. D., Dooley, J. B., and Saha, A.: Heterogeneous freezing of ice on atmospheric aerosols containing ash, soot, and soil, Journal of Geophysical Research: Atmospheres, 114, https://doi.org/10.1029/2009JD011958, 2009.
Geisinger, A., Behrendt, A., Wulfmeyer, V., Strohbach, J., Förstner, J., and Potthast, R.: Development and application of a backscatter lidar forward operator for quantitative validation of aerosol dispersion models and future data assimilation, Atmos. Meas. Tech., 10, 4705–4726, https://doi.org/10.5194/amt-10-4705-2017, 2017.
Ghan, S. J. and Collins, D. R.: Use of in situ data to test a Raman lidar–based cloud condensation nuclei remote sensing method, Journal of Atmospheric and Oceanic Technology, 21, 387-394, https://doi.org/10.1175/1520-0426(2004)021<0387:UOISDT>2.0.CO;2, 2004.
Ghan, S. J., Rissman, T. A., Elleman, R., Ferrare, R. A., Turner, D., Flynn, C., Wang, J., Ogren, J., Hudson, J., and Jonsson, H. H.: Use of in situ cloud condensation nuclei, extinction, and aerosol size distribution measurements to test a method for retrieving cloud condensation nuclei profiles from surface measurements, Journal of Geophysical Research: Atmospheres, 111, https://doi.org/10.1029/2004JD005752, 2006.
Gimmestad, G. G. and Roberts, D. W.: Lidar engineering: introduction to basic principles, Cambridge University Presshttps://doi.org/10.1017/9781139014106, 2023.
Igel, A. L. and van den Heever, S. C.: Invigoration or enervation of convective clouds by aerosols?, Geophysical Research Letters, 48, e2021GL093804, https://doi.org/10.1029/2021GL093804, 2021.
Jensen, M.: Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.2172/2202672, 2023.
Kapustin, V., Clarke, A., Shinozuka, Y., Howell, S., Brekhovskikh, V., Nakajima, T., and Higurashi, A.: On the determination of a cloud condensation nuclei from satellite: Challenges and possibilities, Journal of Geophysical Research: Atmospheres, 111, https://doi.org/10.1029/2004JD005527, 2006.
Keeler, E., Burk, K., and Kyrouac, J.: Balloon-Borne Sounding System (SONDEWNPN), Atmospheric Radiation Measurement (ARM)[data set], https://doi.org/10.5439/1595321, 2021.
Klett, J. D.: Stable analytical inversion solution for processing lidar returns, Applied optics, 20, 211–220, https://doi.org/10.1364/AO.20.000211, 1981.
Koontz, A., Uin, J., Andrews, E., Enekwizu, O., Hayes, C., and Salwen, C.: Cloud Condensation Nuclei Particle Counter (AOSCCN2COLASPECTRA), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.5439/1323896, 2021.
Kotchenruther, R. A., Hobbs, P. V., and Hegg, D. A.: Humidification factors for atmospheric aerosols off the mid-Atlantic coast of the United States, Journal of Geophysical Research: Atmospheres, 104, 2239–2251, https://doi.org/10.1029/98JD01751, 1999.
Kulkarni, G., Sivaraman, C., and Shilling, J.: Retrieved Number Concentration of Cloud Condensation Nuclei (RNCCN) Profile Value-Added Product Report, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.2172/2205615, 2023.
Lebo, Z.: A numerical investigation of the potential effects of aerosol-induced warming and updraft width and slope on updraft intensity in deep convective clouds, Journal of the Atmospheric Sciences, 75, 535–554, https://doi.org/10.1175/JAS-D-16-0368.1, 2018.
Lebo, Z. J.: The sensitivity of a numerically simulated idealized squall line to the vertical distribution of aerosols, Journal of the Atmospheric Sciences, 71, 4581–4596, https://doi.org/10.1175/JAS-D-14-0068.1, 2014.
Lebo, Z. J. and Seinfeld, J. H.: Theoretical basis for convective invigoration due to increased aerosol concentration, Atmos. Chem. Phys., 11, 5407–5429, https://doi.org/10.5194/acp-11-5407-2011, 2011.
Lei, Z., Chen, B., and Brooks, S. D.: Effect of acidity on ice nucleation by inorganic–organic mixed droplets, ACS Earth and Space Chemistry, 7, 2562–2573, https://doi.org/10.1021/acsearthspacechem.3c00242, 2023.
Lei, Z., Peña, T., Thompson, S. A., Chen, B., Matthews, B. H., Li, R., Rapp, A. D., Nowotarski, C. J., and Brooks, S. D.: Aerosol Physicochemical Mixing State and Cloud Nucleation Potential during Tracking Aerosol Convection Interactions Experiment (TRACER) Campaign, Environmental Science & Technology, https://doi.org/10.1021/acs.est.5c03508, 2025.
Lenhardt, E. D., Gao, L., Redemann, J., Xu, F., Burton, S. P., Cairns, B., Chang, I., Ferrare, R. A., Hostetler, C. A., Saide, P. E., Howes, C., Shinozuka, Y., Stamnes, S., Kacarab, M., Dobracki, A., Wong, J., Freitag, S., and Nenes, A.: Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic, Atmos. Meas. Tech., 16, 2037–2054, https://doi.org/10.5194/amt-16-2037-2023, 2023.
Lin, Y., Takano, Y., Gu, Y., Wang, Y., Zhou, S., Zhang, T., Zhu, K., Wang, J., Zhao, B., and Chen, G.: Characterization of the aerosol vertical distributions and their impacts on warm clouds based on multi-year ARM observations, Science of The Total Environment, 904, 166582, https://doi.org/10.1016/j.scitotenv.2023.166582, 2023.
Liu, J. and Li, Z.: Estimation of cloud condensation nuclei concentration from aerosol optical quantities: influential factors and uncertainties, Atmos. Chem. Phys., 14, 471–483, https://doi.org/10.5194/acp-14-471-2014, 2014.
Lv, M., Wang, Z., Li, Z., Luo, T., Ferrare, R., Liu, D., Wu, D., Mao, J., Wan, B., and Zhang, F.: Retrieval of cloud condensation nuclei number concentration profiles from lidar extinction and backscatter data, Journal of Geophysical Research: Atmospheres, 123, 6082–6098, https://doi.org/10.1029/2017JD028102, 2018.
Mamouri, R.-E. and Ansmann, A.: Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters, Atmos. Chem. Phys., 16, 5905–5931, https://doi.org/10.5194/acp-16-5905-2016, 2016.
Marinescu, P. J., van den Heever, S. C., Saleeby, S. M., Kreidenweis, S. M., and DeMott, P. J.: The microphysical roles of lower-tropospheric versus midtropospheric aerosol particles in mature-stage MCS precipitation, Journal of the Atmospheric Sciences, 74, 3657–3678, https://doi.org/10.1175/JAS-D-16-0361.1, 2017.
Marinou, E., Tesche, M., Nenes, A., Ansmann, A., Schrod, J., Mamali, D., Tsekeri, A., Pikridas, M., Baars, H., Engelmann, R., Voudouri, K.-A., Solomos, S., Sciare, J., Groß, S., Ewald, F., and Amiridis, V.: Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements, Atmos. Chem. Phys., 19, 11315–11342, https://doi.org/10.5194/acp-19-11315-2019, 2019.
Mishchenko, M. I. and Travis, L. D.: T-matrix computations of light scattering by large spheroidal particles, Optics communications, 109, 16–21, https://doi.org/10.1117/12.196663, 1994.
Moore, R. H., Bahreini, R., Brock, C. A., Froyd, K. D., Cozic, J., Holloway, J. S., Middlebrook, A. M., Murphy, D. M., and Nenes, A.: Hygroscopicity and composition of Alaskan Arctic CCN during April 2008, Atmos. Chem. Phys., 11, 11807–-11825, https://doi.org/10.5194/acp-11-11807-2011, 2011.
Müller, D., Kolgotin, A., Mattis, I., Petzold, A., and Stohl, A.: Vertical profiles of microphysical particle properties derived from inversion with two-dimensional regularization of multiwavelength Raman lidar data: experiment, Applied Optics, 50, 2069–2079, https://doi.org/10.1364/AO.50.002069, 2011.
Müller, D., Hostetler, C. A., Ferrare, R. A., Burton, S. P., Chemyakin, E., Kolgotin, A., Hair, J. W., Cook, A. L., Harper, D. B., Rogers, R. R., Hare, R. W., Cleckner, C. S., Obland, M. D., Tomlinson, J., Berg, L. K., and Schmid, B.: Airborne Multiwavelength High Spectral Resolution Lidar (HSRL-2) observations during TCAP 2012: vertical profiles of optical and microphysical properties of a smoke/urban haze plume over the northeastern coast of the US, Atmos. Meas. Tech., 7, 3487–-3496, https://doi.org/10.5194/amt-7-3487-2014, 2014.
Muradyan, P., Cromwell, E., Koontz, A., Coulter, R., Flynn, C., Ermold, B., and OBrien, J.: Micropulse Lidar (MPLPOLFS), Oak Ridge National Lab (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.5439/1320657, 2021.
Niemand, M., Möhler, O., Vogel, B., Vogel, H., Hoose, C., Connolly, P., Klein, H., Bingemer, H., DeMott, P., and Skrotzki, J.: A particle-surface-area-based parameterization of immersion freezing on desert dust particles, Journal of the Atmospheric Sciences, 69, 3077–3092, https://doi.org/10.1175/JAS-D-11-0249.1, 2012.
Onasch, T. B., Siefert, R. L., Brooks, S. D., Prenni, A. J., Murray, B., Wilson, M. A., and Tolbert, M. A.: Infrared spectroscopic study of the deliquescence and efflorescence of ammonium sulfate aerosol as a function of temperature, Journal of Geophysical Research: Atmospheres, 104, 21317–21326, https://doi.org/10.1029/1999JD900384, 1999.
Perkins, R. J., Marinescu, P. J., Levin, E. J. T., Collins, D. R., and Kreidenweis, S. M.: Long- and short-term temporal variability in cloud condensation nuclei spectra over a wide supersaturation range in the Southern Great Plains site, Atmos. Chem. Phys., 22, 6197–6215, https://doi.org/10.5194/acp-22-6197-2022, 2022.
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007.
Pöhlker, M. L., Pöhlker, C., Ditas, F., Klimach, T., Hrabe de Angelis, I., Araújo, A., Brito, J., Carbone, S., Cheng, Y., Chi, X., Ditz, R., Gunthe, S. S., Kesselmeier, J., Könemann, T., Lavrič, J. V., Martin, S. T., Mikhailov, E., Moran-Zuloaga, D., Rose, D., Saturno, J., Su, H., Thalman, R., Walter, D., Wang, J., Wolff, S., Barbosa, H. M. J., Artaxo, P., Andreae, M. O., and Pöschl, U.: Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction, Atmos. Chem. Phys., 16, 15709–15740, https://doi.org/10.5194/acp-16-15709-2016, 2016.
Prahl, S.: miepython: Pure python implementation of Mie scattering, Zenodo [code], https://doi.org/10.5281/zenodo.7949263, 2023.
Raes, F., Bates, T., McGOVERN, F., and Van Liedekerke, M.: The 2nd Aerosol Characterization Experiment (ACE-2): General overview and main results, Tellus B: Chemical and Physical Meteorology, 52, 111–125, https://doi.org/10.3402/tellusb.v52i2.16088, 2000.
Rapp, A. D., Brooks, S. D., Nowotarski, C. J., Sharma, M., Thompson, S. A., Chen, B., Matthews, B. H., Etten-Bohm, M., Nielsen, E. R., and Li, R.: TAMU TRACER: Targeted Mobile Measurements to Isolate the Impacts of Aerosols and Meteorology on Deep Convection, Bulletin of the American Meteorological Society, https://doi.org/10.1175/BAMS-D-23-0218.1, 2024.
Rollins, M. G.: LANDFIRE: a nationally consistent vegetation, wildland fire, and fuel assessment, International Journal of Wildland Fire, 18, 235–249, https://doi.org/10.1071/WF08088, 2009.
Rosenfeld, D., Lohmann, U., Raga, G. B., O'Dowd, C. D., Kulmala, M., Fuzzi, S., Reissell, A., and Andreae, M. O.: Flood or drought: how do aerosols affect precipitation?, Science, 321, 1309–1313, https://doi.org/10.1126/science.1160606, 2008.
Rosenfeld, D., Andreae, M. O., Asmi, A., Chin, M., de Leeuw, G., Donovan, D. P., Kahn, R., Kinne, S., Kivekäs, N., and Kulmala, M.: Global observations of aerosol-cloud-precipitation-climate interactions, Reviews of Geophysics, 52, 750–808, https://doi.org/10.1002/2013RG000441, 2014.
Sasano, Y., Browell, E. V., and Ismail, S.: Error caused by using a constant extinction/backscattering ratio in the lidar solution, Applied Optics, 24, 3929–3932, https://doi.org/10.1364/AO.24.003929, 1985.
Schmale, J., Henning, S., Decesari, S., Henzing, B., Keskinen, H., Sellegri, K., Ovadnevaite, J., Pöhlker, M. L., Brito, J., Bougiatioti, A., Kristensson, A., Kalivitis, N., Stavroulas, I., Carbone, S., Jefferson, A., Park, M., Schlag, P., Iwamoto, Y., Aalto, P., Äijälä, M., Bukowiecki, N., Ehn, M., Frank, G., Fröhlich, R., Frumau, A., Herrmann, E., Herrmann, H., Holzinger, R., Kos, G., Kulmala, M., Mihalopoulos, N., Nenes, A., O'Dowd, C., Petäjä, T., Picard, D., Pöhlker, C., Pöschl, U., Poulain, L., Prévôt, A. S. H., Swietlicki, E., Andreae, M. O., Artaxo, P., Wiedensohler, A., Ogren, J., Matsuki, A., Yum, S. S., Stratmann, F., Baltensperger, U., and Gysel, M.: Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories, Atmos. Chem. Phys., 18, 2853–2881, https://doi.org/10.5194/acp-18-2853-2018, 2018.
Seinfeld, J. H., Bretherton, C., Carslaw, K. S., Coe, H., DeMott, P. J., Dunlea, E. J., Feingold, G., Ghan, S., Guenther, A. B., and Kahn, R.: Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system, Proceedings of the National Academy of Sciences, 113, 5781–5790, https://doi.org/10.1073/pnas.1514043113, 2016.
Sharma, M., Rapp, A., and Nowotarski, C.: TAMU TRACER Upper Air Radiosonde Data June-September 2022 Southeast Texas, Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.5439/1968819, 2023.
Shilling, J. E. and Levin, M. S.: merged size distribution from SMPS and APS (MERGEDSMPSAPS), Oak Ridge National Lab (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.5439/1871375, 2021.
Shilling, J. E. and Levin, M. S.: Scanning mobility particle sizer (smps)-aerodynamic particle sizer (aps) merged size distribution (mergedsmpsaps) value-added product report, Oak Ridge National Lab (ORNL), Oak Ridge, TN (United States), Atmospheric Radiation Measurement (ARM) Data Center [data set], https://doi.org/10.2172/2234267, 2023.
Shinozuka, Y., Clarke, A. D., Nenes, A., Jefferson, A., Wood, R., McNaughton, C. S., Ström, J., Tunved, P., Redemann, J., Thornhill, K. L., Moore, R. H., Lathem, T. L., Lin, J. J., and Yoon, Y. J.: The relationship between cloud condensation nuclei (CCN) concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates, Atmos. Chem. Phys., 15, 7585–7604, https://doi.org/10.5194/acp-15-7585-2015, 2015.
Steinke, I., Hoose, C., Möhler, O., Connolly, P., and Leisner, T.: A new temperature- and humidity-dependent surface site density approach for deposition ice nucleation, Atmos. Chem. Phys., 15, 3703–3717, https://doi.org/10.5194/acp-15-3703-2015, 2015.
Stith, J., Ramanathan, V., Cooper, W., Roberts, G., DeMott, P., Carmichael, G., Hatch, C., Adhikary, B., Twohy, C., and Rogers, D.: An overview of aircraft observations from the Pacific Dust Experiment campaign, Journal of Geophysical Research: Atmospheres, 114, https://doi.org/10.1029/2008JD010924, 2009.
Su, H., Rose, D., Cheng, Y. F., Gunthe, S. S., Massling, A., Stock, M., Wiedensohler, A., Andreae, M. O., and Pöschl, U.: Hygroscopicity distribution concept for measurement data analysis and modeling of aerosol particle mixing state with regard to hygroscopic growth and CCN activation, Atmos. Chem. Phys., 10, 7489–7503, https://doi.org/10.5194/acp-10-7489-2010, 2010.
Tao, W. K., Chen, J. P., Li, Z., Wang, C., and Zhang, C.: Impact of aerosols on convective clouds and precipitation, Reviews of Geophysics, 50, https://doi.org/10.1029/2011RG000369, 2012.
Thompson, S. A., Chen, B., and Brooks, S. D.: CCN data from TAMU TRACER campaign in the Houston TX region from July to September 2022, DOE ARM Archive User Services [data set], https://doi.org/10.5439/1972179, 2023.
Thompson, S. A., Chen, B., Matthews, B. H., Li, R., Nowotarski, C. J., Rapp, A. D., and Brooks, S. D.: Characterizing Greater Houston's aerosol by air mass during TRACER, Journal of Geophysical Research: Atmospheres, 130, e2025JD044164, https://doi.org/10.1029/2025JD043353, 2025a.
Thompson, S. A., Peña, T. A., Chen, B., Sharma, M., Matthews, B. H., Li, R., Nowotarski, C. J., Rapp, A. D., and Brooks, S. D.: Variability in ice nucleating particles across Greater Houston Texas, Journal of Geophysical Research: Atmospheres, 130, e2025JD044164, https://doi.org/10.1029/2025JD044164, 2025b.
Titos, G., Cazorla, A., Zieger, P., Andrews, E., Lyamani, H., Granados-Muñoz, M. J., Olmo, F., and Alados-Arboledas, L.: Effect of hygroscopic growth on the aerosol light-scattering coefficient: A review of measurements, techniques and error sources, Atmospheric Environment, 141, 494–507, https://doi.org/10.1016/j.atmosenv.2016.07.021, 2016.
Tobo, Y., Prenni, A. J., DeMott, P. J., Huffman, J. A., McCluskey, C. S., Tian, G., Pöhlker, C., Pöschl, U., and Kreidenweis, S. M.: Biological aerosol particles as a key determinant of ice nuclei populations in a forest ecosystem, Journal of Geophysical Research: Atmospheres, 118, 10100–110110, https://doi.org/10.1002/jgrd.50801, 2013.
Tomlinson, J. M., Li, R., and Collins, D. R.: Physical and chemical properties of the aerosol within the southeastern Pacific marine boundary layer, Journal of Geophysical Research: Atmospheres, 112, https://doi.org/10.1029/2006JD007771, 2007.
Twohy, C. H., Petters, M. D., Snider, J. R., Stevens, B., Tahnk, W., Wetzel, M., Russell, L., and Burnet, F.: Evaluation of the aerosol indirect effect in marine stratocumulus clouds: Droplet number, size, liquid water path, and radiative impact, Journal of Geophysical Research: Atmospheres, 110, https://doi.org/10.1029/2004JD005116, 2005.
Twomey, S.: The influence of pollution on the shortwave albedo of clouds, Journal of the Atmospheric Sciences, 34, 1149–1152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2, 1977.
Ullrich, R., Hoose, C., Möhler, O., Niemand, M., Wagner, R., Höhler, K., Hiranuma, N., Saathoff, H., and Leisner, T.: A new ice nucleation active site parameterization for desert dust and soot, Journal of the Atmospheric Sciences, 74, 699–717, https://doi.org/10.1175/JAS-D-16-0074.1, 2017.
Vali, G.: Quantitative evaluation of experimental results on the heterogeneous freezing nucleation of supercooled liquids, Journal of Atmospheric Sciences, 28, 402–409, https://doi.org/10.1175/1520-0469(1971)028<0402:QEOERA>2.0.CO;2, 1971.
Varble, A. C., Igel, A. L., Morrison, H., Grabowski, W. W., and Lebo, Z. J.: Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection, Atmos. Chem. Phys., 23, 13791–13808, https://doi.org/10.5194/acp-23-13791-2023, 2023.
Wang, B. and Knopf, D. A.: Heterogeneous ice nucleation on particles composed of humic-like substances impacted by O3, Journal of Geophysical Research: Atmospheres, 116, https://doi.org/10.1029/2010JD014964, 2011.
Welton, E. J. and Campbell, J. R.: Micropulse lidar signals: Uncertainty analysis, Journal of Atmospheric and Oceanic Technology, 19, 2089–2094, https://doi.org/10.1175/1520-0426(2002)019<2089:MLSUA>2.0.CO;2, 2002.
Xie, H., Zhou, T., Fu, Q., Huang, J., Huang, Z., Bi, J., Shi, J., Zhang, B., and Ge, J.: Automated detection of cloud and aerosol features with SACOL micro-pulse lidar in northwest China, Optics Express, 25, 30732–30753, https://doi.org/10.1364/OE.25.030732, 2017.
Yao, Y., Curtis, J. H., Ching, J., Zheng, Z., and Riemer, N.: Quantifying the effects of mixing state on aerosol optical properties, Atmos. Chem. Phys., 22, 9265–9282, https://doi.org/10.5194/acp-22-9265-2022, 2022.
Young, S. A., Vaughan, M. A., Garnier, A., Tackett, J. L., Lambeth, J. D., and Powell, K. A.: Extinction and optical depth retrievals for CALIPSO's Version 4 data release, Atmos. Meas. Tech., 11, 5701–5727, https://doi.org/10.5194/amt-11-5701-2018, 2018.
Zhang, M., Deng, X., Zhu, R., Ren, Y., and Xue, H.: The impact of aerosol vertical distribution on a deep convective cloud, Atmosphere, 12, 675, https://doi.org/10.3390/atmos12060675, 2021.
Zieger, P., Fierz-Schmidhauser, R., Weingartner, E., and Baltensperger, U.: Effects of relative humidity on aerosol light scattering: results from different European sites, Atmos. Chem. Phys., 13, 10609–10631, https://doi.org/10.5194/acp-13-10609-2013, 2013.
Short summary
This study presents a new method combining ground-based measurements and lidar to track how aerosols are distributed at different heights in the atmosphere. By correcting for humidity, which causes aerosols to grow and intensify the lidar signal, the method provides more accurate aerosol vertical profiles. Our results show that aerosol profiles can vary significantly over short distances. This technique can help improve understanding of aerosol-cloud interactions.
This study presents a new method combining ground-based measurements and lidar to track how...
