Articles | Volume 22, issue 16
https://doi.org/10.5194/acp-22-10589-2022
© Author(s) 2022. 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-22-10589-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Retrieving instantaneous extinction of aerosol undetected by the CALIPSO layer detection algorithm
Feiyue Mao
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
Ruixing Shi
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Daniel Rosenfeld
Institute of Earth Sciences, The Hebrew University of Jerusalem,
Jerusalem 91904, Israel
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
Institute of Earth Sciences, The Hebrew University of Jerusalem,
Jerusalem 91904, Israel
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
School of Electronic Information, Wuhan University, Wuhan 430079,
China
Yannian Zhu
School of Atmospheric Sciences, Nanjing University, Nanjing 210023,
China
Joint International Research Laboratory of Atmospheric and Earth
System Sciences & Institute for Climate and Global Change Research,
Nanjing University, Nanjing 210023, China
Xin Lu
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
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Cited articles
Andersson, S. M., Martinsson, B. G., Vernier, J.-P., Friberg, J.,
Brenninkmeijer, C. A., Hermann, M., Van Velthoven, P. F., and Zahn, A.:
Significant radiative impact of volcanic aerosol in the lowermost
stratosphere, Nat. Commun., 6, 7692, https://doi.org/10.1038/ncomms8692, 2015.
Ansmann, A., Ohneiser, K., Chudnovsky, A., Baars, H., and Engelmann, R.:
CALIPSO Aerosol-Typing Scheme Misclassified Stratospheric Fire Smoke: Case
Study From the 2019 Siberian Wildfire Season, Frontiers in Environmental
Science, 9, https://doi.org/10.3389/fenvs.2021.769852, 2021.
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and Aerosols, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, 571–657, ISBN 978-1-107-66182-0, 2013.
Damadeo, R. P., Zawodny, J. M., Thomason, L. W., and Iyer, N.: SAGE version 7.0 algorithm: application to SAGE II, Atmos. Meas. Tech., 6, 3539–3561, https://doi.org/10.5194/amt-6-3539-2013, 2013.
de Leeuw, J., Schmidt, A., Witham, C. S., Theys, N., Taylor, I. A., Grainger, R. G., Pope, R. J., Haywood, J., Osborne, M., and Kristiansen, N. I.: The 2019 Raikoke volcanic eruption – Part 1: Dispersion model simulations and satellite retrievals of volcanic sulfur dioxide, Atmos. Chem. Phys., 21, 10851–10879, https://doi.org/10.5194/acp-21-10851-2021, 2021.
Deshler, T.: A review of global stratospheric aerosol: Measurements,
importance, life cycle, and local stratospheric aerosol, Atmos.
Res., 90, 223–232, https://doi.org/10.1016/j.atmosres.2008.03.016, 2008.
Dipu, S., Prabha, T. V., Pandithurai, G., Dudhia, J., Pfister, G., Rajesh,
K., and Goswami, B.: Impact of elevated aerosol layer on the cloud
macrophysical properties prior to monsoon onset, Atmos. Environ.,
70, 454–467, https://doi.org/10.1016/j.atmosenv.2012.12.036, 2013.
Fernald, F. G.: Analysis of atmospheric lidar observations: some comments,
Appl. Optics, 23, 652–653, 1984.
Fernald, F. G., Herman, B. M., and Reagan, J. A.: Determination of aerosol
height distributions by lidar, J. Appl. Meteorol.
Clim., 11, 482–489, 1972.
Huang, J., Guo, J., Wang, F., Liu, Z., Jeong, M. J., Yu, H., and Zhang, Z.:
CALIPSO inferred most probable heights of global dust and smoke layers,
J. Geophys. Res.-Atmos., 120, 5085–5100,
https://doi.org/10.1002/2014JD022898, 2015.
Hunt, W. H., Winker, D. M., Vaughan, M. A., Powell, K. A., Lucker, P. L.,
and Weimer, C.: CALIPSO lidar description and performance assessment,
J. Atmos. Ocean. Tech., 26, 1214–1228, 2009.
Kacenelenbogen, M., Vaughan, M. A., Redemann, J., Hoff, R. M., Rogers, R. R., Ferrare, R. A., Russell, P. B., Hostetler, C. A., Hair, J. W., and Holben, B. N.: An accuracy assessment of the CALIOP/CALIPSO version 2/version 3 daytime aerosol extinction product based on a detailed multi-sensor, multi-platform case study, Atmos. Chem. Phys., 11, 3981–4000, https://doi.org/10.5194/acp-11-3981-2011, 2011.
Kar, J., Vaughan, M. A., Lee, K.-P., Tackett, J. L., Avery, M. A., Garnier, A., Getzewich, B. J., Hunt, W. H., Josset, D., Liu, Z., Lucker, P. L., Magill, B., Omar, A. H., Pelon, J., Rogers, R. R., Toth, T. D., Trepte, C. R., Vernier, J.-P., Winker, D. M., and Young, S. A.: CALIPSO lidar calibration at 532 nm: version 4 nighttime algorithm, Atmos. Meas. Tech., 11, 1459–1479, https://doi.org/10.5194/amt-11-1459-2018, 2018.
Kar, J., Lee, K.-P., Vaughan, M. A., Tackett, J. L., Trepte, C. R., Winker, D. M., Lucker, P. L., and Getzewich, B. J.: CALIPSO level 3 stratospheric aerosol profile product: version 1.00 algorithm description and initial assessment, Atmos. Meas. Tech., 12, 6173–6191, https://doi.org/10.5194/amt-12-6173-2019, 2019.
Khaykin, S. M., Godin-Beekmann, S., Keckhut, P., Hauchecorne, A., Jumelet, J., Vernier, J.-P., Bourassa, A., Degenstein, D. A., Rieger, L. A., Bingen, C., Vanhellemont, F., Robert, C., DeLand, M., and Bhartia, P. K.: Variability and evolution of the midlatitude stratospheric aerosol budget from 22 years of ground-based lidar and satellite observations, Atmos. Chem. Phys., 17, 1829–1845, https://doi.org/10.5194/acp-17-1829-2017, 2017.
Kim, M. H., Omar, A. H., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu,
Y., Liu, Z., and Kim, S. W.: Quantifying the low bias of CALIPSO's column
aerosol optical depth due to undetected aerosol layers, J.
Geophys. Res.-Atmos., 122, 1098–1113, https://doi.org/10.3390/rs13081496,
2017.
Kim, M.-H., Omar, A. H., Tackett, J. L., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu, Y., Liu, Z., Poole, L. R., Pitts, M. C., Kar, J., and Magill, B. E.: The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm, Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, 2018.
Kim, M.-H., Yeo, H., Park, S., Park, D.-H., Omar, A., Nishizawa, T.,
Shimizu, A., and Kim, S.-W.: Assessing CALIOP-Derived Planetary Boundary
Layer Height Using Ground-Based Lidar, Remote Sensing, 13, 1496,
https://doi.org/10.1002/2016JD025797, 2021.
Kloss, C., Berthet, G., Sellitto, P., Ploeger, F., Taha, G., Tidiga, M., Eremenko, M., Bossolasco, A., Jégou, F., Renard, J.-B., and Legras, B.: Stratospheric aerosol layer perturbation caused by the 2019 Raikoke and Ulawun eruptions and their radiative forcing, Atmos. Chem. Phys., 21, 535–560, https://doi.org/10.5194/acp-21-535-2021, 2021.
Lee, L. A., Reddington, C. L., and Carslaw, K. S.: On the relationship
between aerosol model uncertainty and radiative forcing uncertainty,
P. Natl. Acad. Sci. USA, 113, 5820–5827,
https://doi.org/10.1073/pnas.1507050113, 2016.
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, 2013.
Li, Z., Guo, J., Ding, A., Liao, H., Liu, J., Sun, Y., Wang, T., Xue, H.,
Zhang, H., and Zhu, B.: Aerosol and boundary-layer interactions and impact
on air quality, Natl. Sci. Rev., 4, 810–833, https://doi.org/10.1093/nsr/nwx117,
2017.
Lu, X., Mao, F., Pan, Z., Gong, W., Wang, W., Tian, L., and Fang, S.:
Three-Dimensional Physical and Optical Characteristics of Aerosols over
Central China from Long-Term CALIPSO and HYSPLIT Data, Remote Sensing, 10,
314, https://doi.org/10.3390/rs10020314, 2018.
Ma, P. L., Rasch, P. J., Wang, M., Wang, H., Ghan, S. J., Easter, R. C.,
Gustafson Jr., W. I., Liu, X., Zhang, Y., and Ma, H. Y.: How does increasing
horizontal resolution in a global climate model improve the simulation of
aerosol-cloud interactions?, Geophys. Res. Lett., 42, 5058–5065,
https://doi.org/10.1002/2015GL064183, 2015.
Mao, F., Liang, Z., Pan, Z., Gong, W., Sun, J., Zhang, T., Huang, X., Zang,
L., Lu, X., and Hong, J.: A simple multiscale layer detection algorithm for
CALIPSO measurements, Remote Sens. Environ., 266, 112687,
https://doi.org/10.1016/j.rse.2021.112687, 2021.
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, Rev.
Geophys., 52, 750–808, https://doi.org/10.1002/2013RG000441, 2014.
Schoeberl, M., Jensen, E., Wang, T., Taha, G., Ueyama, R., Wang, Y., DeLand,
M., and Dessler, A.: Cloud and Aerosol Distributions From SAGE III/ISS
Observations, J. Geophys. Res.-Atmos., 126,
e2021JD035550, https://doi.org/10.1029/2021JD035550, 2021.
Smirnov, A., Holben, B. N., Giles, D. M., Slutsker, I., O'Neill, N. T., Eck, T. F., Macke, A., Croot, P., Courcoux, Y., Sakerin, S. M., Smyth, T. J., Zielinski, T., Zibordi, G., Goes, J. I., Harvey, M. J., Quinn, P. K., Nelson, N. B., Radionov, V. F., Duarte, C. M., Losno, R., Sciare, J., Voss, K. J., Kinne, S., Nalli, N. R., Joseph, E., Krishna Moorthy, K., Covert, D. S., Gulev, S. K., Milinevsky, G., Larouche, P., Belanger, S., Horne, E., Chin, M., Remer, L. A., Kahn, R. A., Reid, J. S., Schulz, M., Heald, C. L., Zhang, J., Lapina, K., Kleidman, R. G., Griesfeller, J., Gaitley, B. J., Tan, Q., and Diehl, T. L.: Maritime aerosol network as a component of AERONET – first results and comparison with global aerosol models and satellite retrievals, Atmos. Meas. Tech., 4, 583–597, https://doi.org/10.5194/amt-4-583-2011, 2011.
Song, Q., Zhang, Z., Yu, H., Ginoux, P., and Shen, J.: Global dust optical depth climatology derived from CALIOP and MODIS aerosol retrievals on decadal timescales: regional and interannual variability, Atmos. Chem. Phys., 21, 13369–13395, https://doi.org/10.5194/acp-21-13369-2021, 2021.
Teich, M. C.: Role of the doubly stochastic Neyman type-A and Thomas
counting distributions in photon detection, Appl. Optics, 20, 2457–2467,
1981.
Thomason, L. W., Pitts, M. C., and Winker, D. M.: CALIPSO observations of stratospheric aerosols: a preliminary assessment, Atmos. Chem. Phys., 7, 5283–5290, https://doi.org/10.5194/acp-7-5283-2007, 2007.
Thomason, L. W., Moore, J. R., Pitts, M. C., Zawodny, J. M., and Chiou, E. W.: An evaluation of the SAGE III version 4 aerosol extinction coefficient and water vapor data products, Atmos. Chem. Phys., 10, 2159–2173, https://doi.org/10.5194/acp-10-2159-2010, 2010 (data available at: https://asdc.larc.nasa.gov/project/SAGE III-ISS, last access: 6 August 2022).
Thorsen, T. J. and Fu, Q.: CALIPSO-inferred aerosol direct radiative
effects: Bias estimates using ground-based Raman lidars, J.
Geophys. Res.-Atmos., 120, 12209–12220,
https://doi.org/10.1002/2015JD024095, 2015.
Toth, T. D., Campbell, J. R., Reid, J. S., Tackett, J. L., Vaughan, M. A., Zhang, J., and Marquis, J. W.: Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products, Atmos. Meas. Tech., 11, 499–514, https://doi.org/10.5194/amt-11-499-2018, 2018.
Vaughan, M. A., Powell, K. A., Winker, D. M., Hostetler, C. A., Kuehn, R.
E., Hunt, W. H., Getzewich, B. J., Young, S. A., Liu, Z., and McGill, M. J.:
Fully automated detection of cloud and aerosol layers in the CALIPSO lidar
measurements, J. Atmos. Ocean. Tech., 26, 2034–2050,
2009.
Vernier, J.-P., Pommereau, J.-P., Garnier, A., Pelon, J., Larsen, N.,
Nielsen, J., Christensen, T., Cairo, F., Thomason, L. W., and Leblanc, T.:
Tropical stratospheric aerosol layer from CALIPSO lidar observations,
J. Geophys. Res.-Atmos., 114, D00H10, https://doi.org/10.1029/2009JD011946,
2009.
Vernier, J. P., Fairlie, T., Natarajan, M., Wienhold, F., Bian, J.,
Martinsson, B., Crumeyrolle, S., Thomason, L., and Bedka, K.: Increase in
upper tropospheric and lower stratospheric aerosol levels and its potential
connection with Asian pollution, J. Geophys. Res.-Atmos., 120, 1608–1619, https://doi.org/10.1002/2014JD022372, 2015.
Wang, H. J. R., Damadeo, R., Flittner, D., Kramarova, N., Taha, G., Davis,
S., Thompson, A. M., Strahan, S., Wang, Y., Froidevaux, L., Degenstein, D.,
Bourassa, A., Steinbrecht, W., Walker, K. A., Querel, R., Leblanc, T.,
Godin-Beekmann, S., Hurst, D., and Hall, E.: Validation of SAGE III/ISS
Solar Occultation Ozone Products With Correlative Satellite and Ground-Based
Measurements, J. Geophys. Res.-Atmos., 125,
e2020JD032430, https://doi.org/10.1029/2020JD032430, 2020.
Watson-Parris, D., Schutgens, N., Winker, D., Burton, S. P., Ferrare, R. A.,
and Stier, P.: On the limits of CALIOP for constraining modeled free
tropospheric aerosol, Geophys. Res. Lett., 45, 9260–9266,
https://doi.org/10.1029/2018GL078195, 2018.
Watson-Parris, D., Bellouin, N., Deaconu, L., Schutgens, N. A., Yoshioka,
M., Regayre, L. A., Pringle, K. J., Johnson, J. S., Smith, C., and Carslaw,
K.: Constraining uncertainty in aerosol direct forcing, Geophys. Res.
Lett., 47, e2020GL087141. https://doi.org/10.1029/2020GL087141, 2020.
Winker, D., Pelon, J., Coakley Jr., J., Ackerman, S., Charlson, R., Colarco, P., Flamant, P., Fu, Q., Hoff, R., and Kittaka, C.: The CALIPSO mission: A global 3D view of aerosols and clouds, B. Am. Meteorol. Soc., 91, 1211–1230, https://doi.org/10.1175/2010BAMS3009.1, 2010 (data available at: https://asdc.larc.nasa.gov/project/CALIPSO, last access: 6 August 2022).
Winker, D. M., Tackett, J. L., Getzewich, B. J., Liu, Z., Vaughan, M. A., and Rogers, R. R.: The global 3-D distribution of tropospheric aerosols as characterized by CALIOP, Atmos. Chem. Phys., 13, 3345–3361, https://doi.org/10.5194/acp-13-3345-2013, 2013.
Young, S. and Vaughan, M. A.: The Retrieval of Profiles of Particulate
Extinction from Cloud-Aerosol Lidar Infrared Pathfinder Satellite
Observations (CALIPSO) Data: Algorithm Description, J. Atmos.
Ocean. Tech., 26, 1105–1119, 2009.
Young, S. A., Vaughan, M. A., Kuehn, R. E., and Winker, D. M.: The retrieval
of profiles of particulate extinction from Cloud–Aerosol Lidar and Infrared
Pathfinder Satellite Observations (CALIPSO) data: Uncertainty and error
sensitivity analyses, J. Atmos. Ocean. Tech., 30,
395–428, 2013.
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.
Short summary
Previous studies generally ignored the faint aerosols undetected by the CALIPSO layer detection algorithm because they are too optically thin. Here, we retrieved the faint aerosol extinction based on instantaneous CALIPSO observations with the constraint of SAGE data. The correlation and normalized root-mean-square error of the retrievals with independent SAGE data are 0.66 and 100.6 %, respectively. The minimum retrieved extinction at night can be extended to 10-4 km-1 with 125 % uncertainty.
Previous studies generally ignored the faint aerosols undetected by the CALIPSO layer detection...
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