Simulation and assessment of solar background noise for spaceborne lidar

Chuanliang Zhang; Xuejin Sun; Riwei Zhang; Yanwen Liu

doi:10.1364/AO.57.009471

Applied Optics
Vol. 57,
Issue 31,
pp. 9471-9479
(2018)
•https://doi.org/10.1364/AO.57.009471

Simulation and assessment of solar background noise for spaceborne lidar

Chuanliang Zhang, Xuejin Sun, Riwei Zhang, and Yanwen Liu

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Chuanliang Zhang, Xuejin Sun, Riwei Zhang, and Yanwen Liu, "Simulation and assessment of solar background noise for spaceborne lidar," Appl. Opt. 57, 9471-9479 (2018)

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Abstract

The properties for six typical land cover types and three sky conditions were derived in this paper, which allows to make seasonal upper estimations of solar background radiation for a given atmospheric scenario. Solar background noise can be derived from the estimations for a spaceborne lidar based on optical parameters. Comparisons among simulated solar background noise and measurements of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) and a Moderate Resolution Imaging Spectroradiometer (MODIS) demonstrate the feasibility of this method. The upper estimates of solar background radiation can be used for lidar engineers to assess the upper estimates of solar background noise for given atmospheric scenarios, which would be a step forward in comparison with using the worst-case scenario everywhere.

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Land Cover Type	Aerosol Type	Atmospheric Climatology
Land Cover Type	Aerosol Type	Spr./Aut.	Sum.	Win.
Oceans	Antarctic	US76	Sub. Sum.	Sub. Sum.
Deciduous forests	Continental clean	US76	Mid. Sum.	Mid. Win.
Evergreen forests	Continental clean	Tro.	Tro.	Tro.
Deserts	Deserts	US76	Mid. Sum.	Mid. Win.
Grasslands	Continental clean	US76	Mid. Sum.	Mid. Win.
Snow and ice	Antarctic	US76	Sub. Sum.	Sub. Win.

Season	355 nm		532 nm		355 nm		532 nm
Season	AOD	SD ^a	AOD	SD	Albedo	SD	Albedo	SD
Ocean
Spr.	0.095	0.039	0.068	0.037	0.098	0.053	0.043	0.052
Sum.			0.064	0.042	0.095	0.059	0.040	0.043
Aut.			0.067	0.033	0.096	0.046	0.040	0.041
Win.			0.070	0.034	0.095	0.045	0.039	0.039
Deciduous Forest
Spr.	0.158	0.048	0.089	0.050	0.053	0.008	0.047	0.006
Sum.			0.143	0.056	0.047	0.011	0.040	0.006
Aut.			0.088	0.048	0.040	0.010	0.038	0.006
Win.			0.084	0.056	0.061	0.048	0.064	0.039
Evergreen Forest
Spr.	0.332	0.186	0.173	0.164	0.059	0.016	0.044	0.014
Sum.			0.162	0.111	0.057	0.021	0.045	0.019
Aut.			0.207	0.136	0.058	0.015	0.043	0.011
Win.			0.188	0.161	0.059	0.018	0.047	0.016
Deserts
Spr	0.211	0.140	0.191	0.137	0.104	0.075	0.164	0.075
Sum			0.232	0.197	0.091	0.018	0.145	0.047
Aut			0.136	0.096	0.100	0.044	0.154	0.052
Win			0.101	0.073	0.096	0.056	0.159	0.066
Grasslands
Spr.	0.103	0.079	0.076	0.052	0.064	0.014	0.082	0.022
Sum.			0.080	0.064	0.057	0.014	0.070	0.018
Aut.			0.058	0.056	0.050	0.012	0.072	0.017
Win.			0.046	0.129	0.134	0.155	0.120	0.120
Snow_ice
Spr.	0.002	0.004	0.001	0.002	0.927	0.048	0.717	0.084
Sum.			0.002	0.004	0.917	0.061	0.711	0.093
Aut.			0.001	0.002	0.914	0.054	0.696	0.068
Win.			0.001	0.003	0.921	0.048	0.756	0.071

Season	Cloud Top Height (km)		Cloud Thickness (km)
Season	Mean	SD	Mean	SD
Spr	10.78	1.6	1.84	1.4
Sum	12.38	1.7	2.01	1.6
Aut	11.55	1.7	1.99	1.5
Win	9.67	1.4	1.59	1.2

Cloud Type	LWC ( ${gm}^{- 3}$ )	$R_eff$ (μm)	$H_top$ (m)	CTH (m)
Stratus, continental	0.28	7.33	700	500
Stratus, maritime	0.30	11.30	700	500
Cumulus, cont. clean	0.26	5.77	1000	250
Cumulus, cont. polluted	0.30	4.00	1000	250
Cumulus, maritime	0.44	12.68	1000	250

Season	Clear Skies ( ${mWm}^{- 2} {sr}^{- 1} {nm}^{- 1}$ )				Ice Cloudy Skies ( ${mWm}^{- 2} {sr}^{- 1} {nm}^{- 1}$ )
	355 nm		532 nm		355 nm		532 nm
	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Ocean
Spr.	98.376	13.5	45.941	26.4	201.752	210.8	177.579	262.5
Sum.	94.926	14.5	43.193	21.2	209.676	212.8	183.260	263.9
Aut.	99.177	11.9	45.026	20.9	214.127	217.4	188.269	270.9
Win.	101.699	12.0	45.572	20.5	195.298	212.6	165.997	261.2
Deciduous Forest
Spr.	89.434	1.8	48.611	3.5	194.241	209.3	180.756	251.6
Sum.	85.946	2.4	44.806	3.6	200.812	211.3	184.717	256.0
Aut.	87.765	2.3	44.766	3.7	204.530	218.5	188.838	264.4
Win.	95.256	11.4	59.148	20.8	188.300	212.5	178.814	255.4
Evergreen Forest
Spr.	94.377	5.4	50.003	10.4	198.014	205.7	185.012	259.3
Sum.	91.492	6.3	48.940	11.5	206.681	209.5	191.614	261.4
Aut.	95.375	5.2	50.881	8.4	210.443	213.5	197.485	268.6
Win.	98.282	6.0	53.889	11.7	189.819	204.5	177.439	259.8
Deserts
Spr.	100.293	19.1	104.626	41.9	203.050	214.2	228.840	243.9
Sum.	95.058	4.8	92.654	27.0	208.138	209.6	225.454	243.6
Aut.	100.686	11.5	102.168	29.3	215.119	218.2	238.730	247.2
Win.	102.911	14.7	107.896	37.5	194.314	213.5	222.771	243.4
Grasslands
Spr.	91.194	3.9	64.551	12.1	197.549	210.7	195.778	247.5
Sum.	87.449	3.7	57.304	9.7	203.506	212.2	196.768	252.3
Aut.	89.317	3.2	60.740	9.7	207.594	219.3	203.695	258.7
Win.	109.957	37.6	105.141	68.7	203.529	203.5	221.715	260.3
Snow and Ice
Spr.	382.811	23.1	416.764	49.2	478.369	149.9	535.657	180.7
Sum.	367.968	28.0	402.677	53.2	473.469	151.7	526.413	182.0
Aut.	381.459	25.9	409.620	40.3	487.182	152.5	537.481	172.5
Win.	395.888	23.9	455.566	43.7	482.989	159.3	566.627	180.5

Cloud Type	Solar Background Radiation ( ${mWm}^{- 2} {sr}^{- 1} {nm}^{- 1}$ )
	Deserts		Snow and Ice
	355 nm	532 nm	355 nm	532 nm
Stratus, continental	294.728	434.844	404.675	524.630
Stratus, maritime	259.199	370.565	401.839	497.530
Cumulus, cont. clean	253.295	365.507	401.359	493.956
Cumulus, cont. polluted	280.911	414.914	403.331	513.713
Cumulus, maritime	212.592	287.786	399.374	468.805

Parameters	Value
Telescope diameter	1 m
Field of view	130 μrad
Number of shots	1
Optical filter bandwidth	35 pm
Optical system transmission	0.25 ^a
Detector effective quantum efficiency	0.11
Depth of range bins	15 m

Abstract

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Figures (3)

Tables (7)

Equations (1)

Applied Optics