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E-grāmata: Solutions in LIDAR Profiling of the Atmosphere

(University of Iowa, Institute of Hydraulic Research, USA)
  • Formāts: PDF+DRM
  • Izdošanas datums: 17-Feb-2015
  • Izdevniecība: John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781118963289
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Solutions in LIDAR Profiling of the AtmospherePalielināt
  • Formāts: PDF+DRM
  • Izdošanas datums: 17-Feb-2015
  • Izdevniecība: John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781118963289
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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 profiling vertical aerosol loading. Solutions in Lidar Profiling of the Atmosphere emphasizes the use of common sense when interacting with potentially large distortions inherent in most inversion techniques.





Addresses the systematic errors in LIDAR measurements Proposes specific methods to estimate systematic distortions Explains how to apply these methods to both simulated and real data

Solutions in Lidar Profiling of the Atmosphere is written for scientists, researchers, and graduate students in Meteorology and Geophysics.
Preface ix
Acknowledgments xv
Definitions xvii
1 Inversion of Elastic-Lidar Data as an ILL-Posed Problem 1(77)
1.1 Recording and Initial Processing of the Lidar Signal: Essentials and Specifics,
1(10)
1.1.1 Lidar Equation and Real Lidar Signal: How Well Do They Match?
1(3)
1.1.2 Multiplicative and Additive Distortions in the Lidar Signal: Essentials and Specifics,
4(7)
1.2 Algorithms for Extraction of the Extinction-Coefficient Profile from the Elastic-Lidar Signal,
11(10)
1.2.1 Basics,
11(4)
1.2.2 Fernald's Boundary-Point Solution,
15(1)
1.2.3 Optical Depth Solution,
16(2)
1.2.4 Implicit Premises and Mandatory Assumptions Required for Inversion of the Elastic Lidar Signal into the Atmospheric Profile,
18(3)
1.3 Profiling of the Optical Parameters of the Atmosphere as a Simulation Based on Past Observations,
21(10)
1.3.1 Definitions of the Terms,
21(3)
1.3.2 Random Systematic Errors in the Derived Atmospheric Profiles: Origin and Examples,
24(7)
1.4 Error Factor in Lidar Data Inversion,
31(10)
1.5 Backscatter Signal Distortions and Corresponding Errors in the Inverted Atmospheric Profiles,
41(7)
1.6 Determination of the Constant Offset in the Recorded Lidar Signal Using the Slope Method,
48(7)
1.6.1 Algorithm and Solution Uncertainty,
49(2)
1.6.2 Numerical Simulations and Experimental Data,
51(4)
1.7 Examination of the Remaining Offset in the Backscatter Signal by Analyzing the Shape of the Integrated Signal,
55(10)
1.8 Issues in the Examination of the Lidar Overlap Function,
65(13)
1.8.1 Influence of Distortions in the Lidar Signal when Determining the Overlap Function,
65(8)
1.8.2 Issues of Lidar Signal Inversion within the Incomplete Overlap Area,
73(5)
2 Essentials and Issues in Separating the Backscatter and Transmission Terms in The Lidar Equation 78(110)
2.1 Separation of the Backscatter and Transmission Terms in the Lidar Equation: Methods and Intrinsic Assumptions,
78(11)
2.1.1 Inversion Algorithm for the Signals of Raman Lidar,
80(2)
2.1.2 Inversion Algorithm for the Signals of High Spectral Resolution Lidar (HSRL),
82(3)
2.1.3 Inversion Algorithm for Signals of the Differential Absorption Lidar (DIAL),
85(4)
2.2 Distortions in the Optical Depth and Extinction-Coefficient Profiles Derived from Raman Lidar Data,
89(11)
2.2.1 Distortion of the Derived Extinction Coefficient Due to Uncertainty of the Angstrom Exponent,
90(5)
2.2.2 Errors in the Derived Optical Depth Profile Caused by Distortions in the Raman Lidar Signal,
95(2)
2.2.3 Errors in the Derived Extinction-Coefficient Profile Caused by Distortions in the Raman Lidar Signal,
97(3)
2.3 Distortions in the Extinction-Coefficient Profile Derived from the HSRL Signal,
100(7)
2.4 Numerical Differentiation and the Uncertainty Inherent in the Inverted Data,
107(12)
2.4.1 Basics,
107(4)
2.4.2 Nonlinear Fit in the Numerical Differentiation Technique and its Issue,
111(2)
2.4.3 Numerical Differentiation as a Filtering Procedure,
113(6)
2.5 Correction and Extrapolation Techniques for the Optical Depth Profile Derived from the Splitting Lidar Data,
119(18)
2.5.1 Removal of Erroneous Bulges and Concavities in the Optical Depth Profile: Merits and Shortcomings,
119(6)
2.5.2 Implementation of Constraints for the Maximum Range of the Shaped Optical Depth Profile,
125(4)
2.5.3 Modeling the Optical Parameters of the Atmosphere in the Near Zone of Lidar Searching,
129(8)
2.6 Profiling of the Extinction Coefficient Using the Optical Depth and Backscatter-Coefficient Profiles,
137(11)
2.6.1 Theoretical Basics and Methodology,
137(4)
2.6.2 Distortions in the Derived Particulate Extinction Coefficient Due to Inaccuracies in the Involved Parameters,
141(4)
2.6.3 Extraction of the Particulate Extinction Coefficient by Minimizing the Discrepancy between the Alternative Piecewise Transmittances,
145(3)
2.7 Profiling of the Extinction Coefficient Within Intervals Selected A Priori,
148(10)
2.7.1 Determination of Piecewise Continuous Profiles of the Extinction Coefficient and the Column Lidar Ratio Using Equal Length Intervals,
148(6)
2.7.2 Determination of the Piecewise Continuous Profiles of the Extinction Coefficient and the Column Lidar Ratio Using Range-Dependent Overlapping Intervals,
154(4)
2.8 Determination of the Extinction-Coefficient Profile Using Uncertainly Boundaries of the Inverted Optical Depth,
158(16)
2.8.1 Computational Model for Estimating the Uncertainty Boundaries in the Particulate Optical Depth Profile Extracted from Lidar Data,
159(4)
2.8.2 Essentials of the Data Processing Technique,
163(6)
2.8.3 Examples of Experimental Data obtained in the Clear Atmospheres,
169(5)
2.9 Monitoring the Boundaries and Dynamics of Atmospheric Layers with Increased Backscattering,
174(14)
2.9.1 Methodology,
175(2)
2.9.2 Determining the Boundaries of Layers Having Increased Backscattering,
177(11)
3 Profiling of the Atmosphere with Scanning Lidar 188(72)
3.1 Profiling of the Atmosphere Using the Kano-Hamilton Inversion Technique,
188(11)
3.1.1 Basics,
188(7)
3.1.2 Essentials and Specifics of the Methodology for Profiling of the Atmosphere with Scanning Lidar,
195(4)
3.2 Issues in Practical Application of the Kano-Hamilton Multiangle Inversion Technique,
199(14)
3.2.1 Multiplicative and Additive Distortions of the Backscatter Signal and Their Influence on the Inverted Optical Depth Profile,
199(7)
3.2.2 Issues and Deficiencies in the Multiangle Inversion Technique,
206(3)
3.2.3 Profiling of the Atmosphere Using Alternative Estimates of the Constant Offset in the Multiangle Signals,
209(4)
3.3 Determination of the Effective Overlap Using the Signals of the Scanning Lidar,
213(8)
3.3.1 Effective Overlap: Definition and the Derivation Algorithm,
213(3)
3.3.2 Divergence of geff(h) from q(h): Numerical Simulations and the Case Study,
216(5)
3.4 Profiling of the Atmosphere with Scanning Lidar Using the Alternative Inversion Techniques,
221(15)
3.4.1 Comparison of the Uncertainty in the Backscatter Coefficient and the Optical Depth Profiles Extracted from the Signals of the Scanning Lidar,
221(3)
3.4.2 Extraction of the Vertical Extinction Coefficient by Equalizing Alternative Transmittance Profiles in the Fixed Slope Direction: Basics,
224(1)
3.4.3 Equalizing Alternative Transmittance Profiles along a Fixed Slope Direction: Numerical Simulations,
225(5)
3.4.4 Essentials and Issues of the Practical Application of the Piecewise Inversion Technique,
230(6)
3.5 Direct Multiangle Solution,
236(13)
3.5.1 Essentials of the Data Processing,
236(5)
3.5.2 Selection of the Maximum Range for the Multiangle Lidar Signals,
241(6)
3.5.3 Direct Solution for High Spectral Resolution Lidar Operating in Multiangle Mode,
247(2)
3.6 Monitoring Boundaries of the Areas of Increased Backscattering with Scanning Lidar,
249(11)
3.6.1 Images of Scanning Lidar Data and their Quantification,
249(4)
3.6.2 Determination of the Upper Boundary of Increased Backscattering Area,
253(7)
Bibliography 260(11)
Index 271
Vladimir A. Kovalev, PhD, is a Senior Scientist for the Fire, Fuel, and Smoke Science Program in Missoula, Montana, since 2001. He received his B.S. in Radio Technology from the Technical College in Riga, Latvia. He received his M.S. in Radio Engineering from LETI and his PhD in Geophysics from the Main Geophysical Observatory in Leningrad, U.S.S.R.

In 1991, Kovalev joined the research team at the US EPA Environmental Monitoring Systems Laboratory in Las Vegas. He later became a Research Associate for the US National Research Council. In 1999-2001 he was a Visiting Associate at the University of Iowa. Dr. Kovalev has written three books and over a hundred scientific papers published in Russian and English.
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