Monte Carlo computer simulations of ground-based and space-based coherent DIAL water vapor profiling

Michael J. Kavaya; Sammy W. Henderson; Edward C. Russell; R. Milton Huffaker; Rod G. Frehlich

doi:10.1364/AO.28.000840

Applied Optics
Vol. 28,
Issue 5,
pp. 840-851
(1989)
•https://doi.org/10.1364/AO.28.000840

Monte Carlo computer simulations of ground-based and space-based coherent DIAL water vapor profiling

Michael J. Kavaya, Sammy W. Henderson, Edward C. Russell, R. Milton Huffaker, and Rod G. Frehlich

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Michael J. Kavaya, Sammy W. Henderson, Edward C. Russell, R. Milton Huffaker, and Rod G. Frehlich, "Monte Carlo computer simulations of ground-based and space-based coherent DIAL water vapor profiling," Appl. Opt. 28, 840-851 (1989)

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Abstract

Ground-based and space-based coherent DIAL water vapor measurement performance at the 2.1-μm Ho:YAG wavelength is presented using a Monte Carlo computer simulation. The stochastic simulation allowed improved modeling of lidar system, platform, atmospheric, and data processing parameter effects on performance and better understanding of their interrelationships. Results indicate that accurate water vapor measurements in the lower troposphere are potentially achievable from both ground- and space-based platforms.

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(1)	Read input parameters
(2)	Generate cross section, extinction, and true water vapor profiles
(3)	Generate Kolmogorov random number sequences for (1) aerosol backscatter, absorption, and scattering; and (2) molecular absorption and scattering
(4)	Calculate expected value of received signal power at both wavelengths at each range gate, dividing by the SRF
(5)	Apply exponential speckle fluctuations to signals
(6)	Add exponential coherent detection noise
(7)	Estimate and subtract mean value of noise
(8)	Perform range smoothing
(9)	Average N shot-pairs
(10)	Calculate measured water vapor concentration and concentration error vs range
(11)	Repeat steps (3)–(10) for other realizations
(12)	Calculate standard deviation of error and % error

	Ground		Space
Wavelength λ		∼21 μm
Pulse energy E	1 J		3 J
Pulse duration τ		0.2 μs
Focal altitude	5km		0
Beam diameter D	0.2m		1.25 m
Pulse repetition frequency	20 Hz		2 Hz
Efficiency η		0.2
Lidar altitude	0		800 km
Zenith/nadir angle	45°		52.67°
Model atmosphere		MLS
Relative velocity U(z)	7.071 m/s		6627 m/s
α,β fluctuations ∈		0.1
Range gate separation ΔR	75 m		150 m
Range gates smoothed	9		11
Vertical resolution	477 m		1 km
Shot-pairs averaged N	100		100
Noise samples		100

(1)	Read input parameters
(2)	Generate cross section, extinction, and true water vapor profiles
(3)	Generate Kolmogorov random number sequences for (1) aerosol backscatter, absorption, and scattering; and (2) molecular absorption and scattering
(4)	Calculate expected value of received signal power at both wavelengths at each range gate, dividing by the SRF
(5)	Apply exponential speckle fluctuations to signals
(6)	Add exponential coherent detection noise
(7)	Estimate and subtract mean value of noise
(8)	Perform range smoothing
(9)	Average N shot-pairs
(10)	Calculate measured water vapor concentration and concentration error vs range
(11)	Repeat steps (3)–(10) for other realizations
(12)	Calculate standard deviation of error and % error

	Ground		Space
Wavelength λ		∼21 μm
Pulse energy E	1 J		3 J
Pulse duration τ		0.2 μs
Focal altitude	5km		0
Beam diameter D	0.2m		1.25 m
Pulse repetition frequency	20 Hz		2 Hz
Efficiency η		0.2
Lidar altitude	0		800 km
Zenith/nadir angle	45°		52.67°
Model atmosphere		MLS
Relative velocity U(z)	7.071 m/s		6627 m/s
α,β fluctuations ∈		0.1
Range gate separation ΔR	75 m		150 m
Range gates smoothed	9		11
Vertical resolution	477 m		1 km
Shot-pairs averaged N	100		100
Noise samples		100

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Applied Optics