Literature DB >> 18319800

Microphysical particle parameters from extinction and backscatter lidar data by inversion with regularization: theory.

D Müller1, U Wandinger, A Ansmann.   

Abstract

A method is proposed that permits one to retrieve physical parameters of tropospheric particle size distributions, e.g., effective radius, volume, surface-area, and number concentrations, as well as the mean complex refractive index on a routine basis from backscatter and extinction coefficients at multiple wavelengths. The optical data in terms of vertical profiles are derived from multiple-wavelength lidar measurements at 355, 400, 532, 710, 800, and 1064 nm for backscatter data and 355 and 532 nm for extinction data. The algorithm is based on the concept of inversion with regularization. Regularization is performed by generalized cross-validation. This method does not require knowledge of the shape of the particle size distribution and can handle measurement errors of the order of 20%. It is shown that at least two extinction data are necessary to retrieve the particle parameters to an acceptable accuracy. Simulations with monomodal and bimodal logarithmic-normal size distributions show that it is possible to derive effective radius, volume, and surface-area concentrations to an accuracy of +/-50%, the real part of the complex refractive index to +/-0.05, and the imaginary part to +/-50%. Number concentrations may have errors larger than +/-50%.

Year:  1999        PMID: 18319800     DOI: 10.1364/ao.38.002346

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  6 in total

1.  Lidar Ratio-Depolarization Ratio Relations of Atmospheric Dust Aerosols: The Super-Spheroid Model and High Spectral Resolution Lidar Observations.

Authors:  Senyi Kong; Kaori Sato; Lei Bi
Journal:  J Geophys Res Atmos       Date:  2022-02-16       Impact factor: 5.217

2.  Forest fire smoke layers observed in the free troposphere over Portugal with a multiwavelength Raman lidar: optical and microphysical properties.

Authors:  Sérgio Nepomuceno Pereira; Jana Preißler; Juan Luis Guerrero-Rascado; Ana Maria Silva; Frank Wagner
Journal:  ScientificWorldJournal       Date:  2014-07-10

Review 3.  Current Research in Lidar Technology Used for the Remote Sensing of Atmospheric Aerosols.

Authors:  Adolfo Comerón; Constantino Muñoz-Porcar; Francesc Rocadenbosch; Alejandro Rodríguez-Gómez; Michaël Sicard
Journal:  Sensors (Basel)       Date:  2017-06-20       Impact factor: 3.576

Review 4.  Active and Passive Electro-Optical Sensors for Health Assessment in Food Crops.

Authors:  Thomas Fahey; Hai Pham; Alessandro Gardi; Roberto Sabatini; Dario Stefanelli; Ian Goodwin; David William Lamb
Journal:  Sensors (Basel)       Date:  2020-12-29       Impact factor: 3.576

5.  Atmospheric aerosol particle size distribution from Lidar data based on the lognormal distribution mode.

Authors:  Yuchen Shi; Wenqing Liu; Yunsheng Dong; Xuesong Zhao; Yan Xiang; Tianshu Zhang; Lihui Lv
Journal:  Heliyon       Date:  2022-07-19

6.  Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie-Raman lidar observations.

Authors:  Igor Veselovskii; Philippe Goloub; Thierry Podvin; Didier Tanre; Arlindo da Silva; Peter Colarco; Patricia Castellanos; Mikhail Korenskiy; Qiaoyun Hu; David N Whiteman; Daniel Pérez-Ramírez; Patrick Augustin; Marc Fourmentin; Alexei Kolgotin
Journal:  Atmos Meas Tech       Date:  2018-02-16       Impact factor: 4.176

  6 in total

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