Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Auteur(s) : Kovalev, Vladimir A.
Titre(s) : Solutions in lidar profiling of the atmosphere [Texte électronique] / Vladimir A Kovalev
Publication : Hoboken, New Jersey : Wiley, [2015]
Description matérielle : 1 online resource
Note(s) : Includes index. - Includes bibliographical references and index. - Print version record and CIP data provided by publisher.
Provides tools and techniques to identify and address distortions and to interpret
data coming from Lidar sensing technology This book covers the issues encountered
in separating the backscatter and transmission terms in the LIDAR equation when profiling
the atmosphere with zenith-directed and vertically-scanning Lidars. Solutions in Lidar
Profiling of the Atmosphere explains how to manage and interpret the Llidar signals
when the uncertainties of the involved atmospheric parameters are not treatable statistically.
The author discusses specific scenarios for using specific scenarios for p
Sujet(s) : Atmosphère -- Télédétection
Optique météorologique
Indice(s) Dewey :
551.502 87 (23e éd.) = Météorologie - Tests et mesure
Identifiants, prix et caractéristiques : ISBN 9781118963296
Identifiant de la notice : ark:/12148/cb446558297
Notice n° :
FRBNF44655829
(notice reprise d'un réservoir extérieur)
Table des matières : Cover; Contents; Preface; Acknowledgments; Definitions; Chapter 1 Inversion of Elastic-Lidar
Data as an ILL-Posed Problem; 1.1 Recording and Initial Processing of the Lidar Signal:
Essentials and~Specifics; 1.1.1 Lidar Equation and Real Lidar Signal: How Well Do
They Match?; 1.1.2 Multiplicative and Additive Distortions in the Lidar Signal: Essentials
and Specifics; 1.2 Algorithms for Extraction of the Extinction-Coefficient Profile
from the Elastic-Lidar Signal; 1.2.1 Basics; 1.2.2 Fernald's Boundary-Point Solution;
1.2.3 Optical Depth Solution.
1.2.4 Implicit Premises and Mandatory Assumptions Required for~Inversion of the Elastic
Lidar Signal into the Atmospheric Profile1.3 Profiling of the Optical Parameters of
the Atmosphere as a Simulation Based on Past Observations; 1.3.1 Definitions of the
Terms; 1.3.2 Random Systematic Errors in the Derived Atmospheric Profiles: Origin
and Examples; 1.4 Error Factor in Lidar Data Inversion; 1.5 Backscatter Signal Distortions
and Corresponding Errors in the Inverted Atmospheric Profiles; 1.6 Determination of
the Constant Offset in the Recorded Lidar Signal Using~the Slope Method.
1.6.1 Algorithm and Solution Uncertainty1.6.2 Numerical Simulations and Experimental
Data; 1.7 Examination of the Remaining Offset in the Backscatter Signal by~Analyzing
the Shape of the Integrated Signal; 1.8 Issues in the Examination of the Lidar Overlap
Function; 1.8.1 Influence of Distortions in the Lidar Signal when Determining the~Overlap
Function; 1.8.2 Issues of Lidar Signal Inversion within the Incomplete Overlap Area;
Chapter 2 Essentials and Issues in Separating the Backscatter and Transmission Terms
in The Lidar Equation.
2.1 Separation of the Backscatter and Transmission Terms in the Lidar Equation: Methods
and Intrinsic Assumptions2.1.1 Inversion Algorithm for the Signals of Raman Lidar;
2.1.2 Inversion Algorithm for the Signals of High Spectral Resolution Lidar (HSRL);
2.1.3 Inversion Algorithm for Signals of the Differential Absorption Lidar (DIAL);
2.2 Distortions in the Optical Depth and Extinction-Coefficient Profiles Derived from
Raman Lidar Data; 2.2.1 Distortion of the Derived Extinction Coefficient Due to Uncertainty
of the Angstrom Exponent.
2.2.2 Errors in the Derived Optical Depth Profile Caused by Distortions in the Raman
Lidar Signal2.2.3 Errors in the Derived Extinction-Coefficient Profile Caused by~Distortions
in the Raman Lidar Signal; 2.3 Distortions in the Extinction-Coefficient Profile Derived
from the HSRL~Signal; 2.4 Numerical Differentiation and the Uncertainty Inherent in
the Inverted Data; 2.4.1 Basics; 2.4.2 Nonlinear Fit in the Numerical Differentiation
Technique and~its~Issue; 2.4.3 Numerical Differentiation as a Filtering Procedure.