Articles | Volume 9, issue 11
https://doi.org/10.5194/amt-9-5555-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-5555-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Nov 2016
Research article |
| 22 Nov 2016
Information content and sensitivity of the 3β + 2α lidar measurement system for aerosol microphysical retrievals
Sharon P. Burton
CORRESPONDING AUTHOR
NASA Langley Research Center, Hampton, VA, USA
Eduard Chemyakin
Science Systems and Applications, Inc., Hampton, VA, USA
NASA Langley Research Center, Hampton, VA, USA
Kirk Knobelspiesse
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Snorre Stamnes
NASA Langley Research Center, Hampton, VA, USA
Patricia Sawamura
Universities Space Research Association, Columbia, MD, USA
Richard H. Moore
NASA Langley Research Center, Hampton, VA, USA
Chris A. Hostetler
NASA Langley Research Center, Hampton, VA, USA
Richard A. Ferrare
NASA Langley Research Center, Hampton, VA, USA
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45 citations as recorded by crossref.
- This is FAST: multivariate Full-permutAtion based Stochastic foresT method—improving the retrieval of fine-mode aerosol microphysical properties with multi-wavelength lidar N. Wang et al. 10.1016/j.rse.2022.113226
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- Retrieval of Aerosol Microphysical Properties from Multi-Wavelength Mie–Raman Lidar Using Maximum Likelihood Estimation: Algorithm, Performance, and Application Y. Chang et al. 10.3390/rs14246208
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- Separate retrieval of microphysical characteristics in aerosol fractions from laser sensing data S. Samoiliva et al. 10.1016/j.jqsrt.2022.108168
- Calibration of a high spectral resolution lidar using a Michelson interferometer, with data examples from ORACLES S. Burton et al. 10.1364/AO.57.006061
- Investigating the dependence of mineral dust depolarization on complex refractive index and size with a laboratory polarimeter at 180.0° lidar backscattering angle A. Miffre et al. 10.5194/amt-16-403-2023
- Polarization lidar for detecting dust orientation: system design and calibration A. Tsekeri et al. 10.5194/amt-14-7453-2021
- Spatiotemporal changes in aerosol properties by hygroscopic growth and impacts on radiative forcing and heating rates during DISCOVER-AQ 2011 D. Pérez-Ramírez et al. 10.5194/acp-21-12021-2021
- Scattering and absorbing aerosols in the climate system J. Li et al. 10.1038/s43017-022-00296-7
- Method to retrieve cloud condensation nuclei number concentrations using lidar measurements W. Tan et al. 10.5194/amt-12-3825-2019
- Simultaneous reconstruction of two microphysical aerosol characteristics from the lidar data S. Samoilova et al. 10.1016/j.jqsrt.2018.10.014
- Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations I. Veselovskii et al. 10.5194/amt-11-949-2018
- Efficient multi-angle polarimetric inversion of aerosols and ocean color powered by a deep neural network forward model M. Gao et al. 10.5194/amt-14-4083-2021
- A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations P. Patel et al. 10.5194/acp-24-2861-2024
- Combined use of Mie–Raman and fluorescence lidar observations for improving aerosol characterization: feasibility experiment I. Veselovskii et al. 10.5194/amt-13-6691-2020
- ORACLES Campaign, September 2016: Inversion of HSRL-2 Observations with Regularization Algorithm into Particle Microphysical Parameters and Comparison to Airborne In-Situ Data A. Kolgotin et al. 10.3390/atmos14111661
- Ambient Aerosol Hygroscopic Growth From Combined Raman Lidar and HSRL K. Dawson et al. 10.1029/2019JD031708
- Polar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory D. Zhang et al. 10.3390/rs14184638
- Upgraded Three-Wavelength Lidar for Real-Time Observations of Volcanic Aerosol Optical and Microphysical Properties at Etna (Italy): Calibration Procedures and Measurement Tests M. Manzo et al. 10.3390/s24061762
- Simultaneous Reconstruction of the Complex Refractive Index and the Particle Size Distribution Function from Lidar Measurements: Testing the Developed Algorithms S. Samoilova 10.1134/S1024856019060137
- Retrievals of aerosol single scattering albedo by multiwavelength lidar measurements: Evaluations with NASA Langley HSRL-2 during discover-AQ field campaigns D. Pérez-Ramírez et al. 10.1016/j.rse.2018.12.022
- Automated, unsupervised inversion of multiwavelength lidar data with TiARA: assessment of retrieval performance of microphysical parameters using simulated data D. Müller et al. 10.1364/AO.58.004981
- A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data A. Sorrentino et al. 10.5194/amt-15-149-2022
- Atmospheric Aerosol Measurement Using High-Spectral-Resolution Lidar Methods Y. JIN 10.2184/lsj.48.11_585
- Temporal variations in optical and microphysical properties of mineral dust and biomass burning aerosol derived from daytime Raman lidar observations over Warsaw, Poland L. Janicka et al. 10.1016/j.atmosenv.2017.09.022
- Retrievals of aerosol microphysics from simulations of spaceborne multiwavelength lidar measurements D. Whiteman et al. 10.1016/j.jqsrt.2017.09.009
- Information content of bistatic lidar observations of aerosols from space M. Alexandrov & M. Mishchenko 10.1364/OE.25.00A134
- Optical and microphysical characterization of atmospheric aerosol in the Central Mediterranean during simultaneous volcanic ash and desert dust transport events A. Sannino et al. 10.1016/j.atmosres.2022.106099
- 1064 nm rotational Raman polarization lidar for profiling aerosol and cloud characteristics L. Wang et al. 10.1364/OE.518259
- On the use of light polarization to investigate the size, shape, and refractive index dependence of backscattering Ångström exponents A. Miffre et al. 10.1364/OL.385107
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- Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic E. Lenhardt et al. 10.5194/amt-16-2037-2023
- Advantages of an Additional Raman Channel in Laser Sounding at Wavelengths of 355–1064 nm for Retrieving Microphysical Parameters of Atmospheric Aerosol S. Samoilova et al. 10.1134/S1024856023060179
- Extinction-related Angström exponent characterization of submicrometric volume fraction in atmospheric aerosol particles A. Quirantes et al. 10.1016/j.atmosres.2019.06.009
- Retrieval of aerosol microphysical parameters based on a few optical parameters from lidar S. Li et al. 10.1002/mop.33131
- Modelling optical properties of atmospheric black carbon aerosols M. Kahnert & F. Kanngießer 10.1016/j.jqsrt.2020.106849
- Optimized profile retrievals of aerosol microphysical properties from simulated spaceborne multiwavelength Lidar D. Pérez-Ramírez et al. 10.1016/j.jqsrt.2020.106932
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- Potential Retrieval of Aerosol Microphysics From Multistatic Space-Borne Lidar N. Levitan et al. 10.1051/epjconf/201817605017
- Information constraints in variational data assimilation M. Kahnert 10.1002/qj.3347
- How much information do extinction and backscattering measurements contain about the chemical composition of atmospheric aerosol? M. Kahnert & E. Andersson 10.5194/acp-17-3423-2017
- Particle Microphysical Parameters and the Complex Refractive Index from 3β + 2α HSRL/Raman Lidar Measurements: Conditions of Accurate Retrieval, Retrieval Uncertainties and Constraints to Suppress the Uncertainties A. Kolgotin et al. 10.3390/atmos14071159
Latest update: 19 Apr 2024
Short summary
Retrievals of aerosol microphysics exist for ground-based, airborne, and future space-borne lidar measurements. We investigate the information content of a lidar measurement system, using only a forward model but no explicit inversion. The simplified aerosol used here is applicable as a best case for all retrievals in the absence of additional constraints. We report (1) information content of the measurements; (2) uncertainties on the retrieved parameters; and (3) sources of compensating errors.
Retrievals of aerosol microphysics exist for ground-based, airborne, and future space-borne...
