Articles | Volume 19, issue 18
https://doi.org/10.5194/amt-19-5843-2026
© 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/amt-19-5843-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Sep 2026
Research article |
| 16 Sep 2026
| 16 Sep 2026
A multi-angle and polarization-based retrieval algorithm for aerosol layer height of smoke and dust
Pei Li
CORRESPONDING AUTHOR
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Yong Xue
CORRESPONDING AUTHOR
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Davide Dionisi
Institute of Marine Sciences (ISMAR), Italian National Research Council (CNR), Rome – Tor Vergata, Italy
Huihui Li
Zhejiang Academy of Emergency Management Science, Hangzhou, 310000, China
Shuhui Wu
Yunlong Lake Laboratory of Deep Underground Science and Engineering, Xuzhou, Jiangsu province, 221100, China
Xingxing Jiang
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco–meteorological Experiment Field of CMA, Shouxian 232200, China
Botao He
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Peng Wang
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Liying Han
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
Related authors
Xingxing Jiang, Yong Xue, Mariarosaria Calvello, Shuhui Wu, and Pei Li
Atmos. Meas. Tech., 18, 4559–4571, https://doi.org/10.5194/amt-18-4559-2025, https://doi.org/10.5194/amt-18-4559-2025, 2025
Short summary
Short summary
A novel black carbon aerosol (BC) surface concentration retrieval algorithm was developed using MODIS data. The algorithm determined seasonal background aerosol model based on AERONET product, calculated the complex refractive index of the internal mixed aerosol, and combined 6SV2.1 to establish lookup tables to achieve the optimal estimation of BC fraction and column concentration. Using conversion coefficient generated by MERRA-2, column concentration was converted to surface concentration.
Patrick Chazette, Andreas Behrendt, Adolfo Comerón, Paolo Di Girolamo, Marco Di Paolantonio, Davide Dionisi, Cyrille Flamant, José Luis Gómez-Amo, Jérémy Lagarrigue, Frédéric Laly, Diego Lange, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Michaël Sicard, Donato Summa, Julien Totems, María Pilar Utrillas, Pedro C. Valdelomar, and Volker Wulfmeyer
Atmos. Meas. Tech., 19, 5223–5242, https://doi.org/10.5194/amt-19-5223-2026, https://doi.org/10.5194/amt-19-5223-2026, 2026
Short summary
Short summary
Between October 2022 and January 2023, the Water Vapour Lidar Network Assimilation (WaLiNeAs) campaign was conducted on the western Mediterranean by four European countries. To improve the forecasting of heavy precipitation events, eight ground-based stations equipped with water vapour Raman lidars were strategically deployed. They offered a valuable chance to verify the consistency of the water vapour products of both the Infrared Atmospheric Sounding Interferometer (IASI) and ERA5 reanalysis.
Xingxing Jiang, Yong Xue, Mariarosaria Calvello, Shuhui Wu, and Pei Li
Atmos. Meas. Tech., 18, 4559–4571, https://doi.org/10.5194/amt-18-4559-2025, https://doi.org/10.5194/amt-18-4559-2025, 2025
Short summary
Short summary
A novel black carbon aerosol (BC) surface concentration retrieval algorithm was developed using MODIS data. The algorithm determined seasonal background aerosol model based on AERONET product, calculated the complex refractive index of the internal mixed aerosol, and combined 6SV2.1 to establish lookup tables to achieve the optimal estimation of BC fraction and column concentration. Using conversion coefficient generated by MERRA-2, column concentration was converted to surface concentration.
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
Short summary
Short summary
EARLINET/ACTRIS organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Marco Di Paolantonio, Davide Dionisi, and Gian Luigi Liberti
Atmos. Meas. Tech., 15, 1217–1231, https://doi.org/10.5194/amt-15-1217-2022, https://doi.org/10.5194/amt-15-1217-2022, 2022
Short summary
Short summary
A procedure for the characterization of the lidar transmitter–receiver geometry was developed. This characterization is currently implemented in the Rome RMR lidar to optimize the telescope/beam alignment, retrieve the overlap function, and estimate the absolute and relative tilt of the laser beam. This procedure can be potentially used to complement the standard EARLINET quality assurance tests.
Cited articles
Chen, X., Xu, X., Wang, J., and Diner, D. J.: Can multi-angular polarimetric measurements in the oxygen-A and B bands improve the retrieval of aerosol vertical distribution?, J. Quant. Spectrosc. Ra., 270, 107679, https://doi.org/10.1016/j.jqsrt.2021.107679, 2021a.
Chen, X., Wang, J., Xu, X., Zhou, M., Zhang, H., Castro Garcia, L., Colarco, P. R., Janz, S. J., Yorks, J., McGill, M., Reid, J. S., de Graaf, M., and Kondragunta, S.: First retrieval of absorbing aerosol height over dark target using TROPOMI oxygen B band: Algorithm development and application for surface particulate matter estimates, Remote Sens. Environ., 265, 112674, https://doi.org/10.1016/j.rse.2021.112674, 2021b.
Choi, W., Lee, H., Kim, J., and Park, J.: First TROPOMI Retrieval of Aerosol Effective Height Using O4 Absorption Band at 477 nm and Aerosol Classification, IEEE T. Geosci. Remote, 59, 9873–9886, https://doi.org/10.1109/TGRS.2020.3044050, 2021.
Cohen, J. B., Ng, D. H. L., Lim, A. W. L., and Chua, X. R.: Vertical distribution of aerosols over the Maritime Continent during El Niño, Atmos. Chem. Phys., 18, 7095–7108, https://doi.org/10.5194/acp-18-7095-2018, 2018.
de Graaf, M., Sneep, M., ter Linden, M., Tilstra, L. G., Donovan, D. P., van Zadelhoff, G.-J., and Veefkind, J. P.: Improvements in aerosol layer height retrievals from TROPOMI oxygen A-band measurements by surface albedo fitting in optimal estimation, Atmos. Meas. Tech., 18, 2553–2571, https://doi.org/10.5194/amt-18-2553-2025, 2025.
Diner, D. J., Nelson, D. L., Chen, Y., Kahn, R. A., Logan, J., Leung, F.-Y., and Martin, M. V.: Quantitative studies of wildfire smoke injection heights with the Terra Multi-angle Imaging SpectroRadiometer, in: Remote Sensing of Fire: Science and Application, SPIE, 56–64, https://doi.org/10.1117/12.795215, 2008.
Ding, S., Wang, J., and Xu, X.: Polarimetric remote sensing in oxygen A and B bands: sensitivity study and information content analysis for vertical profile of aerosols, Atmos. Meas. Tech., 9, 2077–2092, https://doi.org/10.5194/amt-9-2077-2016, 2016.
Doherty, O. M., Riemer, N., and Hameed, S.: Saharan mineral dust transport into the Caribbean: Observed atmospheric controls and trends, J. Geophys. Res.-Atmos., 113, https://doi.org/10.1029/2007JD009171, 2008.
Dubovik, O. and King, M. D.: A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements, J. Geophys. Res.-Atmos., 105, 20673–20696, https://doi.org/10.1029/2000JD900282, 2000.
Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J.-F., Sorokin, M., and Slutsker, I.: Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust, J. Geophys. Res.-Atmos., 111, https://doi.org/10.1029/2005JD006619, 2006.
Dubovik, O., Herman, M., Holdak, A., Lapyonok, T., Tanré, D., Deuzé, J. L., Ducos, F., Sinyuk, A., and Lopatin, A.: Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations, Atmos. Meas. Tech., 4, 975–1018, https://doi.org/10.5194/amt-4-975-2011, 2011.
Dubovik, O., Li, Z., Mishchenko, M. I., Tanré, D., Karol, Y., Bojkov, B., Cairns, B., Diner, D. J., Espinosa, W. R., Goloub, P., Gu, X., Hasekamp, O., Hong, J., Hou, W., Knobelspiesse, K. D., Landgraf, J., Li, L., Litvinov, P., Liu, Y., Lopatin, A., Marbach, T., Maring, H., Martins, V., Meijer, Y., Milinevsky, G., Mukai, S., Parol, F., Qiao, Y., Remer, L., Rietjens, J., Sano, I., Stammes, P., Stamnes, S., Sun, X., Tabary, P., Travis, L. D., Waquet, F., Xu, F., Yan, C., and Yin, D.: Polarimetric remote sensing of atmospheric aerosols: Instruments, methodologies, results, and perspectives, J. Quant. Spectrosc. Ra., 224, 474–511, https://doi.org/10.1016/j.jqsrt.2018.11.024, 2019.
Earth Science Data Systems: PACE HARP2 Level-2 Regional Aerosol Over Ocean Optical Properties, FastMAPOL Algorithm Data, version 3.0, NASA Earthdata, https://www.earthdata.nasa.gov/data/catalog/ob-cloud-pace-harp2-l2-mapol-ocean-3.0 (last access: 25 July 2026), 2025.
Eck, T. F., Holben, B. N., Reid, J. S., Dubovik, O., Smirnov, A., O'Neill, N. T., Slutsker, I., and Kinne, S.: Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols, J. Geophys. Res.-Atmos., 104, 31333–31349, https://doi.org/10.1029/1999JD900923, 1999.
European Space Agency: TROPOMI Level 2 Aerosol Layer Height (mid-level pressure), European Space Agency, https://doi.org/10.5270/S5P-7g4iapn, 2021.
Fromm, M., Lindsey, D. T., Servranckx, R., Yue, G., Trickl, T., Sica, R., Doucet, P., and Godin-Beekmann, S.: The Untold Story of Pyrocumulonimbus, B. Am. Meteorol. Soc., 91, 1193–1210, https://doi.org/10.1175/2010BAMS3004.1, 2010.
Gandham, H., Dasari, H. P., Karumuri, A., Ravuri, P. M. K., and Hoteit, I.: Three-dimensional structure and transport pathways of dust aerosols over West Asia, npj Clim. Atmos. Sci., 5, 45, https://doi.org/10.1038/s41612-022-00266-2, 2022.
Gao, M., Franz, B. A., Knobelspiesse, K., Zhai, P.-W., Martins, V., Burton, S., Cairns, B., Ferrare, R., Gales, J., Hasekamp, O., Hu, Y., Ibrahim, A., McBride, B., Puthukkudy, A., Werdell, P. J., and Xu, X.: Efficient multi-angle polarimetric inversion of aerosols and ocean color powered by a deep neural network forward model, Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, 2021.
Gao, M., Franz, B. A., Zhai, P.-W., Knobelspiesse, K., Sayer, A. M., Xu, X., Martins, J. V., Cairns, B., Castellanos, P., Fu, G., Hannadige, N., Hasekamp, O., Hu, Y., Ibrahim, A., Patt, F., Puthukkudy, A., and Werdell, P. J.: Simultaneous retrieval of aerosol and ocean properties from PACE HARP2 with uncertainty assessment using cascading neural network radiative transfer models, Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, 2023.
Gu, H., Zhang, Y., Fan, C., Li, Z., Hou, W., Liu, Z., Xie, Y., Xu, H., Zhang, L., and Ma, J.: A Comprehensive Analysis of Ultraviolet Remote Sensing for Aerosol Layer Height Retrieval from Multi-Angle Polarization Satellite Measurements, Remote Sens., 14, 6258, https://doi.org/10.3390/rs14246258, 2022.
Hasekamp, O. P. and Landgraf, J.: Retrieval of aerosol properties over land surfaces: capabilities of multiple-viewing-angle intensity and polarization measurements, Appl. Opt., 46, 3332–3344, https://doi.org/10.1364/AO.46.003332, 2007.
Hasekamp, O. P., Litvinov, P., and Butz, A.: Aerosol properties over the ocean from PARASOL multiangle photopolarimetric measurements, J. Geophys. Res.-Atmos., 116, https://doi.org/10.1029/2010JD015469, 2011.
Hou, W., Li, Z., Wang, J., Xu, X., Goloub, P., and Qie, L.: Improving Remote Sensing of Aerosol Microphysical Properties by Near-Infrared Polarimetric Measurements Over Vegetated Land: Information Content Analysis, J. Geophys. Res.-Atmos., 123, 2215–2243, https://doi.org/10.1002/2017JD027388, 2018.
Hsu, N. C., Jeong, M.-J., Bettenhausen, C., Sayer, A. M., Hansell, R., Seftor, C. S., Huang, J., and Tsay, S.-C.: Enhanced Deep Blue aerosol retrieval algorithm: The second generation, J. Geophys. Res.-Atmos., 118, 9296–9315, https://doi.org/10.1002/jgrd.50712, 2013.
Illingworth, A. J., Barker, H. W., Beljaars, A., Ceccaldi, M., Chepfer, H., Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P., Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno, Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shephard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and van Zadelhoff, G.-J.: The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation, B. Am. Meteorol. Soc., 96, 1311–1332, https://doi.org/10.1175/BAMS-D-12-00227.1, 2015.
Jeong, M. and Hsu, N. C.: Retrievals of aerosol single‐scattering albedo and effective aerosol layer height for biomass‐burning smoke: Synergy derived from “A‐Train” sensors, Geophys. Res. Lett., 35, 2008GL036279, https://doi.org/10.1029/2008GL036279, 2008.
Kahn, R. A., Chen, Y., Nelson, D. L., Leung, F., Li, Q., Diner, D. J., and Logan, J. A.: Wildfire smoke injection heights: Two perspectives from space, Geophys. Res. Lett., 35, 2007GL032165, https://doi.org/10.1029/2007GL032165, 2008.
Kalashnikova, O. V., Garay, M. J., Davis, A. B., Diner, D. J., and Martonchik, J. V.: Sensitivity of multi-angle photo-polarimetry to vertical layering and mixing of absorbing aerosols: Quantifying measurement uncertainties, J. Quant. Spectrosc. Ra., 112, 2149–2163, https://doi.org/10.1016/j.jqsrt.2011.05.010, 2011.
Knippertz, P. and Todd, M. C.: Mineral dust aerosols over the Sahara: Meteorological controls on emission and transport and implications for modeling, Rev. Geophys., 50, https://doi.org/10.1029/2011RG000362, 2012.
Koffi, B., Schulz, M., Bréon, F.-M., Griesfeller, J., Winker, D., Balkanski, Y., Bauer, S., Berntsen, T., Chin, M., Collins, W. D., Dentener, F., Diehl, T., Easter, R., Ghan, S., Ginoux, P., Gong, S., Horowitz, L. W., Iversen, T., Kirkevåg, A., Koch, D., Krol, M., Myhre, G., Stier, P., and Takemura, T.: Application of the CALIOP layer product to evaluate the vertical distribution of aerosols estimated by global models: AeroCom phase I results, J. Geophys. Res.-Atmos., 117, https://doi.org/10.1029/2011JD016858, 2012.
Kokhanovsky, A. A., Davis, A. B., Cairns, B., Dubovik, O., Hasekamp, O. P., Sano, I., Mukai, S., Rozanov, V. V., Litvinov, P., Lapyonok, T., Kolomiets, I. S., Oberemok, Y. A., Savenkov, S., Martin, W., Wasilewski, A., Di Noia, A., Stap, F. A., Rietjens, J., Xu, F., Natraj, V., Duan, M., Cheng, T., and Munro, R.: Space-based remote sensing of atmospheric aerosols: The multi-angle spectro-polarimetric frontier, Earth-Sci. Rev., 145, 85–116, https://doi.org/10.1016/j.earscirev.2015.01.012, 2015.
Kylling, A., Vandenbussche, S., Capelle, V., Cuesta, J., Klüser, L., Lelli, L., Popp, T., Stebel, K., and Veefkind, P.: Comparison of dust-layer heights from active and passive satellite sensors, Atmos. Meas. Tech., 11, 2911–2936, https://doi.org/10.5194/amt-11-2911-2018, 2018.
Lee, J., Hsu, N. C., Bettenhausen, C., Sayer, A. M., Seftor, C. J., and Jeong, M.-J.: Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations, J. Geophys. Res.-Atmos., 120, 8372–8388, https://doi.org/10.1002/2015JD023567, 2015.
Li, P., Xue, Y., Li, H., He, B., Yin, W., and Wang, P.: Three-dimensional reconstruction of aerosols based on spectral radiance matching, Atmos. Environ., 326, 120485, https://doi.org/10.1016/j.atmosenv.2024.120485, 2024.
Li, P., Xue, Y., Dionisi, D., He, B., Wang, P., and Li, H.: Detecting the layer height of smoke and dust aerosols over land and ocean using ultraviolet dual-wavelength measurements, Remote Sens. Environ., 331, 115001, https://doi.org/10.1016/j.rse.2025.115001, 2025.
Li, Z., Hou, W., Hong, J., Zheng, F., Luo, D., Wang, J., Gu, X., and Qiao, Y.: Directional Polarimetric Camera (DPC): Monitoring aerosol spectral optical properties over land from satellite observation, J. Quant. Spectrosc. Ra., 218, 21–37, https://doi.org/10.1016/j.jqsrt.2018.07.003, 2018.
Litvinov, P., Hasekamp, O., and Cairns, B.: Models for surface reflection of radiance and polarized radiance: Comparison with airborne multi-angle photopolarimetric measurements and implications for modeling top-of-atmosphere measurements, Remote Sens. Environ., 115, 781–792, https://doi.org/10.1016/j.rse.2010.11.005, 2011.
Liu, D., Chen, S., Cheng, C., Barker, H. W., Dong, C., Ke, J., Wang, S., and Zheng, Z.: Analysis of global three-dimensional aerosol structure with spectral radiance matching, Atmos. Meas. Tech., 12, 6541–6556, https://doi.org/10.5194/amt-12-6541-2019, 2019.
Maignan, F., Bréon, F.-M., Fédèle, E., and Bouvier, M.: Polarized reflectances of natural surfaces: Spaceborne measurements and analytical modeling, Remote Sens. Environ., 113, 2642–2650, https://doi.org/10.1016/j.rse.2009.07.022, 2009.
Martins, J. V., Fernandez-Borda, R., McBride, B., Remer, L., and Barbosa, H. M. J.: The Harp Hype Ran Gular Imaging Polarimeter and the Need for Small Satellite Payloads with High Science Payoff for Earth Science Remote Sensing, in: IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, 6304–6307, https://doi.org/10.1109/IGARSS.2018.8518823, 2018.
Mishchenko, M. I., Cairns, B., Kopp, G., Schueler, C. F., Fafaul, B. A., Hansen, J. E., Hooker, R. J., Itchkawich, T., Maring, H. B., and Travis, L. D.: Accurate Monitoring of Terrestrial Aerosols and Total Solar Irradiance: Introducing the Glory Mission, B. Am. Meteorol. Soc., 88, 677–692, https://doi.org/10.1175/BAMS-88-5-677, 2007.
Nanda, S., de Graaf, M., Veefkind, J. P., ter Linden, M., Sneep, M., de Haan, J., and Levelt, P. F.: A neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithm, Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019, 2019.
Nanda, S., de Graaf, M., Veefkind, J. P., Sneep, M., ter Linden, M., Sun, J., and Levelt, P. F.: A first comparison of TROPOMI aerosol layer height (ALH) to CALIOP data, Atmos. Meas. Tech., 13, 3043–3059, https://doi.org/10.5194/amt-13-3043-2020, 2020.
NASA VIIRS Atmosphere Science Team: VIIRS/SNPP Deep Blue Aerosol L2 6-Min Swath 6 km (NRT), NASA Goddard Space Flight Center [data set], https://doi.org/10.5067/VIIRS/AERDB_L2_VIIRS_SNPP_NRT.002, 2023.
Nelson, D. L., Garay, M. J., Kahn, R. A., and Dunst, B. A.: Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX), Remote Sens., 5, 4593–4628, https://doi.org/10.3390/rs5094593, 2013.
Nelson, D. M., Hu, F. S., Scholes, D. R., Joshi, N., and Pearson, A.: Using SPIRAL (Single Pollen Isotope Ratio AnaLysis) to estimate C3- and C4-grass abundance in the paleorecord, Earth Planet. Sc. Lett., 269, 11–16, https://doi.org/10.1016/j.epsl.2008.03.001, 2008.
Nishizawa, T., Kudo, R., Oikawa, E., Higurashi, A., Jin, Y., Sugimoto, N., Sato, K., and Okamoto, H.: Algorithms to retrieve aerosol optical properties using lidar measurements on board the EarthCARE satellite, Atmos. Meas. Tech., 19, 729–744, https://doi.org/10.5194/amt-19-729-2026, 2026.
Parajuli, S. P., Stenchikov, G. L., Ukhov, A., Shevchenko, I., Dubovik, O., and Lopatin, A.: Aerosol vertical distribution and interactions with land/sea breezes over the eastern coast of the Red Sea from lidar data and high-resolution WRF-Chem simulations, Atmos. Chem. Phys., 20, 16089–16116, https://doi.org/10.5194/acp-20-16089-2020, 2020.
Peterson, D. A., Campbell, J. R., Hyer, E. J., Fromm, M. D., Kablick, G. P., Cossuth, J. H., and DeLand, M. T.: Wildfire-driven thunderstorms cause a volcano-like stratospheric injection of smoke, npj Clim. Atmos. Sci., 1, 30, https://doi.org/10.1038/s41612-018-0039-3, 2018.
Pierangelo, C., Chédin, A., Heilliette, S., Jacquinet-Husson, N., and Armante, R.: Dust altitude and infrared optical depth from AIRS, Atmos. Chem. Phys., 4, 1813–1822, https://doi.org/10.5194/acp-4-1813-2004, 2004.
Prospero, J. M., Collard, F.-X., Molinié, J., and Jeannot, A.: Characterizing the annual cycle of African dust transport to the Caribbean Basin and South America and its impact on the environment and air quality, Global Biogeochem. Cy., 28, 757–773, https://doi.org/10.1002/2013GB004802, 2014.
Sanders, A. F. J., de Haan, J. F., Sneep, M., Apituley, A., Stammes, P., Vieitez, M. O., Tilstra, L. G., Tuinder, O. N. E., Koning, C. E., and Veefkind, J. P.: Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A, Atmos. Meas. Tech., 8, 4947–4977, https://doi.org/10.5194/amt-8-4947-2015, 2015.
Savtchenko, A., Kummerer, R., Smith, P., Gopalan, A., Kempler, S., and Leptoukh, G.: A-Train Data Depot: Bringing Atmospheric Measurements Together, IEEE T. Geosci. Remote, 46, 2788–2795, https://doi.org/10.1109/TGRS.2008.917600, 2008.
Sayer, A. M., Hsu, N. C., Bettenhausen, C., Ahmad, Z., Holben, B. N., Smirnov, A., Thomas, G. E., and Zhang, J.: SeaWiFS Ocean Aerosol Retrieval (SOAR): Algorithm, validation, and comparison with other data sets, J. Geophys. Res.-Atmos., 117, https://doi.org/10.1029/2011JD016599, 2012.
Schaaf, C. and Wang, Z.: MCD43A1 MODIS/Terra+Aqua BRDF/Albedo Model Parameters Daily L3 Global – 500m V006, NASA EOSDIS Land Processes Distributed Active Archive Center (DAAC) [data set], https://doi.org/10.5067/MODIS/MCD43A1.006, 2015.
Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., Tsang, T., Strugnell, N. C., Zhang, X., Jin, Y., Muller, J.-P., Lewis, P., Barnsley, M., Hobson, P., Disney, M., Roberts, G., Dunderdale, M., Doll, C., d'Entremont, R. P., Hu, B., Liang, S., Privette, J. L., and Roy, D.: First operational BRDF, albedo nadir reflectance products from MODIS, Remote Sens. Environ., 83, 135–148, https://doi.org/10.1016/S0034-4257(02)00091-3, 2002.
Sienkiewicz, N., Martins, J. V., McBride, B. A., Xu, X., Puthukkudy, A., Smith, R., and Fernandez-Borda, R.: HARP2 pre-launch calibration: dealing with polarization effects of a wide field of view, Atmos. Meas. Tech., 18, 2447–2462, https://doi.org/10.5194/amt-18-2447-2025, 2025.
Sokolik, I. N.: The spectral radiative signature of wind-blown mineral dust: Implications for remote sensing in the thermal IR region, Geophys. Res. Lett., 29, 7-1–7-4, https://doi.org/10.1029/2002GL015910, 2002.
Spurr, R. and Christi, M.: On the generation of atmospheric property Jacobians from the (V)LIDORT linearized radiative transfer models, J. Quant. Spectrosc. Ra., 142, 109–115, https://doi.org/10.1016/j.jqsrt.2014.03.011, 2014.
Spurr, R. J. D.: VLIDORT: A linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media, J. Quant. Spectrosc. Ra., 102, 316–342, https://doi.org/10.1016/j.jqsrt.2006.05.005, 2006.
Torres, O., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Gleason, J.: Derivation of aerosol properties from satellite measurements of backscattered ultraviolet radiation: Theoretical basis, J. Geophys. Res.-Atmos., 103, 17099–17110, https://doi.org/10.1029/98JD00900, 1998.
Torres, O., Bhartia, P. K., Herman, J. R., Sinyuk, A., Ginoux, P., and Holben, B.: A Long-Term Record of Aerosol Optical Depth from TOMS Observations and Comparison to AERONET Measurements, J. Atmos. Sci., 59, 398–413, https://doi.org/10.1175/1520-0469(2002)059<0398:ALTROA>2.0.CO;2, 2002.
van Zadelhoff, G.-J., Donovan, D. P., and Wang, P.: Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product, Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, 2023.
Varotsos, C., Alexandris, D., Chronopoulos, G., and Tzanis, C.: Aircraft observations of the solar ultraviolet irradiance throughout the troposphere, J. Geophys. Res.-Atmos., 106, 14843–14854, https://doi.org/10.1029/2001JD900045, 2001.
Varotsos, C., Ondov, J., Tzanis, C., Öztürk, F., Nelson, M., Ke, H., and Christodoulakis, J.: An observational study of the atmospheric ultra-fine particle dynamics, Atmos. Environ., 59, 312–319, https://doi.org/10.1016/j.atmosenv.2012.05.015, 2012.
Wang, J., Xu, X., Ding, S., Zeng, J., Spurr, R., Liu, X., Chance, K., and Mishchenko, M.: A numerical testbed for remote sensing of aerosols, and its demonstration for evaluating retrieval synergy from a geostationary satellite constellation of GEO-CAPE and GOES-R, J. Quant. Spectrosc. Ra., 146, 510–528, https://doi.org/10.1016/j.jqsrt.2014.03.020, 2014.
Wanner, W., Li, X., and Strahler, A. H.: On the derivation of kernels for kernel-driven models of bidirectional reflectance, J. Geophys. Res.-Atmos., 100, 21077–21089, https://doi.org/10.1029/95JD02371, 1995.
Werdell, P. J., Behrenfeld, M. J., Bontempi, P. S., Boss, E., Cairns, B., Davis, G. T., Franz, B. A., Gliese, U. B., Gorman, E. T., Hasekamp, O., Knobelspiesse, K. D., Mannino, A., Martins, J. V., McClain, C. R., Meister, G., and Remer, L. A.: The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission: Status, Science, Advances, B. Am. Meteorol. Soc., 100, 1775–1794, https://doi.org/10.1175/BAMS-D-18-0056.1, 2019.
Winker, D. M., Hunt, W. H., and McGill, M. J.: Initial performance assessment of CALIOP, Geophys. Res. Lett., 34, https://doi.org/10.1029/2007GL030135, 2007.
Winker, D. M., Pelon, J., Coakley, J. A., Ackerman, S. A., Charlson, R. J., Colarco, P. R., Flamant, P. H., Fu, Q., Hoff, R. M., Kittaka, C., Kubar, T. L., Treut, H. L., McCormick, M. P., Mégie, G., Poole, L. R., Powell, K., Trepte, C. R., Vaughan, M. A., and Wielicki, B. A.: THE CALIPSO MISSION: A Global 3D View of Aerosols and Clouds, B. Am. Meteorol. Soc., 91, 1211–1229, 2010.
Wu, L., Hasekamp, O., van Diedenhoven, B., Cairns, B., Yorks, J. E., and Chowdhary, J.: Passive remote sensing of aerosol layer height using near-UV multiangle polarization measurements, Geophys. Res. Lett., 43, 8783–8790, https://doi.org/10.1002/2016GL069848, 2016.
Xu, X. and Wang, J.: UNL-VRTM, A Testbed for Aerosol Remote Sensing: Model Developments and Applications, in: Springer Series in Light Scattering: Volume 4: Light Scattering and Radiative Transfer, edited by: Kokhanovsky, A., Springer International Publishing, Cham, 1–69, https://doi.org/10.1007/978-3-030-20587-4_1, 2019.
Xu, X., Wang, J., Wang, Y., Zeng, J., Torres, O., Yang, Y., Marshak, A., Reid, J., and Miller, S.: Passive remote sensing of altitude and optical depth of dust plumes using the oxygen A and B bands: First results from EPIC/DSCOVR at Lagrange-1 point, Geophys. Res. Lett., 44, 7544–7554, https://doi.org/10.1002/2017GL073939, 2017.
Xu, X., Wang, J., Wang, Y., Zeng, J., Torres, O., Reid, J. S., Miller, S. D., Martins, J. V., and Remer, L. A.: Detecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep space, Atmos. Meas. Tech., 12, 3269–3288, https://doi.org/10.5194/amt-12-3269-2019, 2019.
Xu, X., Chen, X., Wang, J., and Remer, L. A.: Potential of NASA's Plankton, Aerosol, Cloud, and Ocean Ecosystem (PACE) Satellite Observations in the Oxygen Bands for Determining Aerosol Layer Height over Ocean, J. Remote Sens., 4, 0167, https://doi.org/10.34133/remotesensing.0167, 2024.
Zeng, J., Han, Q., and Wang, J.: High-spectral resolution simulation of polarization of skylight: Sensitivity to aerosol vertical profile, Geophys. Res. Lett., 35, https://doi.org/10.1029/2008GL035645, 2008.
Zeng, Z.-C., Natraj, V., Xu, F., Pongetti, T. J., Shia, R.-L., Kort, E. A., Toon, G. C., Sander, S. P., and Yung, Y. L.: Constraining Aerosol Vertical Profile in the Boundary Layer Using Hyperspectral Measurements of Oxygen Absorption, Geophys. Res. Lett., 45, 10772–10780, https://doi.org/10.1029/2018GL079286, 2018.
Zeng, Z.-C., Chen, S., Natraj, V., Le, T., Xu, F., Merrelli, A., Crisp, D., Sander, S. P., and Yung, Y. L.: Constraining the vertical distribution of coastal dust aerosol using OCO-2 O2 A-band measurements, Remote Sens. Environ., 236, 111494, https://doi.org/10.1016/j.rse.2019.111494, 2020.
Short summary
The vertical distribution of aerosols governs their interactions with solar radiation and clouds, making it a key factor in their climatic and environmental effects. Polarization provides independent constraints that reduce ALH (aerosol layer height)–AOD (aerosol optical depth) coupling. A joint optimal estimation method is developed using HARP2 (Hyper-Angular Rainbow Polarimeter-2) observations.
The vertical distribution of aerosols governs their interactions with solar radiation and...
