Articles | Volume 6, issue 12
Atmos. Meas. Tech., 6, 3441–3457, 2013
https://doi.org/10.5194/amt-6-3441-2013
Atmos. Meas. Tech., 6, 3441–3457, 2013
https://doi.org/10.5194/amt-6-3441-2013

Research article 10 Dec 2013

Research article | 10 Dec 2013

Assessing remote polarimetric measurement sensitivities to aerosol emissions using the geos-chem adjoint model

B. S. Meland et al.

Related authors

Dust vertical profile impact on global radiative forcing estimation using a coupled chemical-transport–radiative-transfer model
L. Zhang, Q. B. Li, Y. Gu, K. N. Liou, and B. Meland
Atmos. Chem. Phys., 13, 7097–7114, https://doi.org/10.5194/acp-13-7097-2013,https://doi.org/10.5194/acp-13-7097-2013, 2013

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Inferring the absorption properties of organic aerosol in Siberian biomass burning plumes from remote optical observations
Igor B. Konovalov, Nikolai A. Golovushkin, Matthias Beekmann, Mikhail V. Panchenko, and Meinrat O. Andreae
Atmos. Meas. Tech., 14, 6647–6673, https://doi.org/10.5194/amt-14-6647-2021,https://doi.org/10.5194/amt-14-6647-2021, 2021
Short summary
Mass concentration estimates of long-range-transported Canadian biomass burning aerosols from a multi-wavelength Raman polarization lidar and a ceilometer in Finland
Xiaoxia Shang, Tero Mielonen, Antti Lipponen, Elina Giannakaki, Ari Leskinen, Virginie Buchard, Anton S. Darmenov, Antti Kukkurainen, Antti Arola, Ewan O'Connor, Anne Hirsikko, and Mika Komppula
Atmos. Meas. Tech., 14, 6159–6179, https://doi.org/10.5194/amt-14-6159-2021,https://doi.org/10.5194/amt-14-6159-2021, 2021
Short summary
Retrievals of dust-related particle mass and ice-nucleating particle concentration profiles with ground-based polarization lidar and sun photometer over a megacity in central China
Yun He, Yunfei Zhang, Fuchao Liu, Zhenping Yin, Yang Yi, Yifan Zhan, and Fan Yi
Atmos. Meas. Tech., 14, 5939–5954, https://doi.org/10.5194/amt-14-5939-2021,https://doi.org/10.5194/amt-14-5939-2021, 2021
Short summary
Introducing the MISR level 2 near real-time aerosol product
Marcin L. Witek, Michael J. Garay, David J. Diner, Michael A. Bull, Felix C. Seidel, Abigail M. Nastan, and Earl G. Hansen
Atmos. Meas. Tech., 14, 5577–5591, https://doi.org/10.5194/amt-14-5577-2021,https://doi.org/10.5194/amt-14-5577-2021, 2021
Short summary
Estimation of PM2.5 concentration in China using linear hybrid machine learning model
Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang
Atmos. Meas. Tech., 14, 5333–5347, https://doi.org/10.5194/amt-14-5333-2021,https://doi.org/10.5194/amt-14-5333-2021, 2021
Short summary

Cited articles

Alexander, B., Savarino, J. , Lee, C. C. W., Park, R. J., Jacob, D. J., Thiemens, M. H., Li, Q. B., and Yantosca, R. M.: Sulfate formation in sea-salt aerosols: Constraints from oxygen isotopes, J. Geophys. Res., 110, D10307, https://doi.org/10.1029/2004JD005659, 2005.
Benedetti, A., Morcrette, J. J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., and Suttie, M.: Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation, J. Geophys. Res.-Atmos., 114, D13205, https://doi.org/10.1029/2008JD011115, 2009.
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B., Fiore, A. M., Li, Q., Liu, H., Mickley, L. J., and Schultz, M.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res., 106, 23073–23096, 2001.
Binkowski, F. S. and Roselle, S. J.: Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component: 1. Model description, J. Geophys. Res., 108, 4183, https://doi.org/10.1029/2001JD001409, 2003.
Bodhaine, B. A., Wood, N. B., Dutton, E. G., and Slusser, J. R.: On Rayleigh Optical Depth Calculations, J. Atmos. Ocean. Tech., 16, 1854–1861, 1999.
Download