Abstract

Accurate aerosol optical properties could be obtained via the high spectral resolution lidar (HSRL) technique, which employs a narrow spectral filter to suppress the Rayleigh or Mie scattering in lidar return signals. The ability of the filter to suppress Rayleigh or Mie scattering is critical for HSRL. Meanwhile, it is impossible to increase the rejection of the filter without limitation. How to optimize the spectral discriminator and select the appropriate suppression rate of the signal is important to us. The HSRL technology was thoroughly studied based on error propagation. Error analyses and sensitivity studies were carried out on the transmittance characteristics of the spectral discriminator. Moreover, ratwo different spectroscopic methods for HSRL were described and compared: one is to suppress the Mie scattering; the other is to suppress the Rayleigh scattering. The corresponding HSRLs were simulated and analyzed. The results show that excessive suppression of Rayleigh scattering or Mie scattering in a high-spectral channel is not necessary if the transmittance of the spectral filter for molecular and aerosol scattering signals can be well characterized. When the ratio of transmittance of the spectral filter for aerosol scattering and molecular scattering is less than 0.1 or greater than 10, the detection error does not change much with its value. This conclusion implies that we have more choices for the high-spectral discriminator in HSRL. Moreover, the detection errors of HSRL regarding the two spectroscopic methods vary greatly with the atmospheric backscattering ratio. To reduce the detection error, it is necessary to choose a reasonable spectroscopic method. The detection method of suppressing the Rayleigh signal and extracting the Mie signal can achieve less error in a clear atmosphere, while the method of suppressing the Mie signal and extracting the Rayleigh signal can achieve less error in a polluted atmosphere.

© 2017 Optical Society of America

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References

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    [Crossref] [PubMed]
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    [Crossref]
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    [Crossref]
  15. D. Hua, M. Uchida, and T. Kobayashi, “Ultraviolet Rayleigh-Mie lidar with Mie-scattering correction by Fabry-Perot etalons for temperature profiling of the troposphere,” Appl. Opt. 44(7), 1305–1314 (2005).
    [Crossref] [PubMed]

2015 (1)

2014 (1)

Z. Cheng, D. Liu, L. Jing, Y. Yang, Z. Wang, Y. Zhou, H. Huang, and Y. Shen, “Influences analysis of the spectral filter transmission on the performance of high-spectral-resolution lidar,” Acta Opt. Sin. 34(8), 0801003 (2014).
[Crossref]

2013 (1)

2012 (1)

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

2009 (1)

2008 (1)

2005 (3)

D. Hua, M. Uchida, and T. Kobayashi, “Ultraviolet Rayleigh-Mie lidar with Mie-scattering correction by Fabry-Perot etalons for temperature profiling of the troposphere,” Appl. Opt. 44(7), 1305–1314 (2005).
[Crossref] [PubMed]

M. Imaki, Y. Takegoshi, and T. Kobayashi, “Ultraviolet high-spectral-resolution lidar with Fabry-Pérot filter for accurate measurement of extinction and lidar ratio,” Jpn. J. Appl. Phys. 44(5A), 3063–3067 (2005).
[Crossref]

D. Hua and T. Kobayashi, “UV rayleigh–mie raman lidar for simultaneous measurement of atmospheric temperature and relative humidity profiles in the troposphere,” Jpn. J. Appl. Phys. 44(3), 1287–1291 (2005).
[Crossref]

2002 (1)

J. A. Reagan, X. Wang, and M. T. Osborn, “Spaceborne lidar calibration from cirrus and molecular backscatter returns,” IEEE Trans. Geo. Sci. Remote 40(10), 2285–2290 (2002).
[Crossref]

1990 (1)

1983 (2)

Ansmann, A.

Bai, J.

Bakalski, I.

Bond, R.

Burton, S. P.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

Butler, C. F.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

Cheng, Z.

Cook, A. L.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

J. W. Hair, C. A. Hostetler, A. L. Cook, D. B. Harper, R. A. Ferrare, T. L. Mack, W. Welch, L. R. Izquierdo, and F. E. Hovis, “Airborne high spectral resolution lidar for profiling aerosol optical properties,” Appl. Opt. 47(36), 6734–6752 (2008).
[Crossref] [PubMed]

Delev, A.

Duan, L.

Eloranta, E. W.

Ferrare, R. A.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

J. W. Hair, C. A. Hostetler, A. L. Cook, D. B. Harper, R. A. Ferrare, T. L. Mack, W. Welch, L. R. Izquierdo, and F. E. Hovis, “Airborne high spectral resolution lidar for profiling aerosol optical properties,” Appl. Opt. 47(36), 6734–6752 (2008).
[Crossref] [PubMed]

Foster, M. J.

Froyd, K. D.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

Hair, J. W.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

J. W. Hair, C. A. Hostetler, A. L. Cook, D. B. Harper, R. A. Ferrare, T. L. Mack, W. Welch, L. R. Izquierdo, and F. E. Hovis, “Airborne high spectral resolution lidar for profiling aerosol optical properties,” Appl. Opt. 47(36), 6734–6752 (2008).
[Crossref] [PubMed]

Harper, D. B.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

J. W. Hair, C. A. Hostetler, A. L. Cook, D. B. Harper, R. A. Ferrare, T. L. Mack, W. Welch, L. R. Izquierdo, and F. E. Hovis, “Airborne high spectral resolution lidar for profiling aerosol optical properties,” Appl. Opt. 47(36), 6734–6752 (2008).
[Crossref] [PubMed]

Hélière, A.

Hostetler, C. A.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

J. W. Hair, C. A. Hostetler, A. L. Cook, D. B. Harper, R. A. Ferrare, T. L. Mack, W. Welch, L. R. Izquierdo, and F. E. Hovis, “Airborne high spectral resolution lidar for profiling aerosol optical properties,” Appl. Opt. 47(36), 6734–6752 (2008).
[Crossref] [PubMed]

Hovis, F. E.

Hua, D.

D. Hua, M. Uchida, and T. Kobayashi, “Ultraviolet Rayleigh-Mie lidar with Mie-scattering correction by Fabry-Perot etalons for temperature profiling of the troposphere,” Appl. Opt. 44(7), 1305–1314 (2005).
[Crossref] [PubMed]

D. Hua and T. Kobayashi, “UV rayleigh–mie raman lidar for simultaneous measurement of atmospheric temperature and relative humidity profiles in the troposphere,” Jpn. J. Appl. Phys. 44(3), 1287–1291 (2005).
[Crossref]

Huang, H.

Z. Cheng, D. Liu, L. Jing, Y. Yang, Z. Wang, Y. Zhou, H. Huang, and Y. Shen, “Influences analysis of the spectral filter transmission on the performance of high-spectral-resolution lidar,” Acta Opt. Sin. 34(8), 0801003 (2014).
[Crossref]

D. Liu, Y. Yang, Z. Cheng, H. Huang, B. Zhang, T. Ling, and Y. Shen, “Retrieval and analysis of a polarized high-spectral-resolution lidar for profiling aerosol optical properties,” Opt. Express 21(11), 13084–13093 (2013).
[Crossref] [PubMed]

Imaki, M.

M. Imaki, Y. Takegoshi, and T. Kobayashi, “Ultraviolet high-spectral-resolution lidar with Fabry-Pérot filter for accurate measurement of extinction and lidar ratio,” Jpn. J. Appl. Phys. 44(5A), 3063–3067 (2005).
[Crossref]

Izquierdo, L. R.

Jing, L.

Z. Cheng, D. Liu, L. Jing, Y. Yang, Z. Wang, Y. Zhou, H. Huang, and Y. Shen, “Influences analysis of the spectral filter transmission on the performance of high-spectral-resolution lidar,” Acta Opt. Sin. 34(8), 0801003 (2014).
[Crossref]

Kobayashi, T.

M. Imaki, Y. Takegoshi, and T. Kobayashi, “Ultraviolet high-spectral-resolution lidar with Fabry-Pérot filter for accurate measurement of extinction and lidar ratio,” Jpn. J. Appl. Phys. 44(5A), 3063–3067 (2005).
[Crossref]

D. Hua and T. Kobayashi, “UV rayleigh–mie raman lidar for simultaneous measurement of atmospheric temperature and relative humidity profiles in the troposphere,” Jpn. J. Appl. Phys. 44(3), 1287–1291 (2005).
[Crossref]

D. Hua, M. Uchida, and T. Kobayashi, “Ultraviolet Rayleigh-Mie lidar with Mie-scattering correction by Fabry-Perot etalons for temperature profiling of the troposphere,” Appl. Opt. 44(7), 1305–1314 (2005).
[Crossref] [PubMed]

Labandibar, J. Y.

Lee, S. A.

Ling, T.

Liu, D.

Luo, J.

Mack, T. L.

Obland, M. D.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

Osborn, M. T.

J. A. Reagan, X. Wang, and M. T. Osborn, “Spaceborne lidar calibration from cirrus and molecular backscatter returns,” IEEE Trans. Geo. Sci. Remote 40(10), 2285–2290 (2002).
[Crossref]

Reagan, J. A.

J. A. Reagan, X. Wang, and M. T. Osborn, “Spaceborne lidar calibration from cirrus and molecular backscatter returns,” IEEE Trans. Geo. Sci. Remote 40(10), 2285–2290 (2002).
[Crossref]

Rees, D.

Riebesell, M.

Roesler, F. L.

Rogers, R. R.

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

She, C. Y.

Shen, Y.

Shimizu, H.

Shipley, S. T.

Slimm, M.

Sroga, J. T.

Storey, J.

Su, L.

Takegoshi, Y.

M. Imaki, Y. Takegoshi, and T. Kobayashi, “Ultraviolet high-spectral-resolution lidar with Fabry-Pérot filter for accurate measurement of extinction and lidar ratio,” Jpn. J. Appl. Phys. 44(5A), 3063–3067 (2005).
[Crossref]

Thwaite, C.

Tracy, D. H.

Trauger, J. T.

Uchida, M.

Wang, K.

Wang, X.

J. A. Reagan, X. Wang, and M. T. Osborn, “Spaceborne lidar calibration from cirrus and molecular backscatter returns,” IEEE Trans. Geo. Sci. Remote 40(10), 2285–2290 (2002).
[Crossref]

Wang, Z.

Z. Cheng, D. Liu, L. Jing, Y. Yang, Z. Wang, Y. Zhou, H. Huang, and Y. Shen, “Influences analysis of the spectral filter transmission on the performance of high-spectral-resolution lidar,” Acta Opt. Sin. 34(8), 0801003 (2014).
[Crossref]

Weinman, J. A.

Weitkamp, C.

Welch, W.

Yang, L.

Yang, Y.

Zhang, B.

Zhang, Y.

Zhou, Y.

Z. Cheng, D. Liu, J. Luo, Y. Yang, Y. Zhou, Y. Zhang, L. Duan, L. Su, L. Yang, Y. Shen, K. Wang, and J. Bai, “Field-widened Michelson interferometer for spectral discrimination in high-spectral-resolution lidar: theoretical framework,” Opt. Express 23(9), 12117–12134 (2015).
[Crossref] [PubMed]

Z. Cheng, D. Liu, L. Jing, Y. Yang, Z. Wang, Y. Zhou, H. Huang, and Y. Shen, “Influences analysis of the spectral filter transmission on the performance of high-spectral-resolution lidar,” Acta Opt. Sin. 34(8), 0801003 (2014).
[Crossref]

Acta Opt. Sin. (1)

Z. Cheng, D. Liu, L. Jing, Y. Yang, Z. Wang, Y. Zhou, H. Huang, and Y. Shen, “Influences analysis of the spectral filter transmission on the performance of high-spectral-resolution lidar,” Acta Opt. Sin. 34(8), 0801003 (2014).
[Crossref]

Appl. Opt. (4)

Atmos. Meas. Tech. (1)

S. P. Burton, R. A. Ferrare, C. A. Hostetler, J. W. Hair, R. R. Rogers, M. D. Obland, C. F. Butler, A. L. Cook, D. B. Harper, and K. D. Froyd, “Aerosol classification using airborne high spectral resolution lidar measurements – methodology and examples,” Atmos. Meas. Tech. 5(1), 73–98 (2012).
[Crossref]

IEEE Trans. Geo. Sci. Remote (1)

J. A. Reagan, X. Wang, and M. T. Osborn, “Spaceborne lidar calibration from cirrus and molecular backscatter returns,” IEEE Trans. Geo. Sci. Remote 40(10), 2285–2290 (2002).
[Crossref]

Jpn. J. Appl. Phys. (2)

D. Hua and T. Kobayashi, “UV rayleigh–mie raman lidar for simultaneous measurement of atmospheric temperature and relative humidity profiles in the troposphere,” Jpn. J. Appl. Phys. 44(3), 1287–1291 (2005).
[Crossref]

M. Imaki, Y. Takegoshi, and T. Kobayashi, “Ultraviolet high-spectral-resolution lidar with Fabry-Pérot filter for accurate measurement of extinction and lidar ratio,” Jpn. J. Appl. Phys. 44(5A), 3063–3067 (2005).
[Crossref]

Opt. Express (3)

Opt. Lett. (1)

Other (2)

A. Ansmann and D. Müller, “Lidar and atmospheric aerosol particles,” in Lidar, C. Weitkamp, ed. (Academic, 2005).

E. W. Eloranta, “High spectral resolution lidar,” in Lidar, C. Weitkamp, ed. (Academic, 2005).

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Figures (7)

Fig. 1
Fig. 1 The relative error of the backscatter coefficient (βa) with SR variation. The four figures (a, b, c and d) show the error of the backscatter coefficient at Ra = 1.1, 2, 5 and 10, respectively. The curves for different input error are expressed using different line-types and colors. The black solid lines show the error at δ = 0.01, the magenta dash-dot-dot lines show the error at δ = 0.05, the blue short-dashed lines show the error at δ = 0.1, and the dark-yellow dashed lines show the error at δ = 0.2.
Fig. 2
Fig. 2 The absolute error curves of optical depth (τ) with SR variation. The four figures show the error of optical depth at Ra = 1.1, 2, 5 and 10. The curves at different input error are expressed using different line-types and colors. The black solid lines show the error at δ = 0.01, the magenta dash-dot-dot lines show the error at δ = 0.05, the blue short-dashed lines show the error at δ = 0.1, and the dark-yellow dashed lines show the error at δ = 0.2.
Fig. 3
Fig. 3 Schematic illustration of the spectral transmission at the reflection field of the HSRL spectral filter: (left) the spectral transmission in the reflection field of FPE (ρ = 0.4, L = 45 mm, FSR = 3.3 GHz), (right) the molecular and aerosol components in the output spectrum of the filter.
Fig. 4
Fig. 4 Schematic illustration of the spectral transmission at the transmission field of the HSRL spectral filter: (left) the spectral transmission in the transmission fields of FPE (ρ = 0.96, L = 12.236, FSR = 12.26 GHz, FWHM = 159 MHz), (right) the molecular and aerosol components in the output spectrum of the filter.
Fig. 5
Fig. 5 Profiles of atmospheric backscatter ratio at 532 nm versus height used for numerical calculation (left: the standard atmospheric model, right: the actual profile obtained from lidar observation on a day with haze and smog).
Fig. 6
Fig. 6 Retrieval errors of optical parameters for HSRL1 for different cases of Ra and atmospheric condition. (a) Relative error of the backscatter coefficient for the atmospheric standard model, (b) absolute error of optical depth for the standard atmospheric model, (c) relative error of the backscatter coefficient for the actual atmospheric model, and (d) absolute error of optical depth for the standard atmospheric model.
Fig. 7
Fig. 7 Retrieval errors of optical parameters for HSRL2 for different cases of Ra and atmospheric condition. (a) Relative error of the backscatter coefficient for the atmospheric standard model, (b) absolute error of optical depth for the standard atmospheric model, (c) relative error of the backscatter coefficient for the actual atmospheric model, and (d) absolute error of optical depth for the standard atmospheric model.

Tables (1)

Tables Icon

Table 1 HSRL system specifications employed by simulation

Equations (21)

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P 1 = E 0 C 1 r 2 ( β m + β a )exp( 2 0 r [ α a (ξ)+ α m (ξ) ] dξ ),
P 2 = E 0 C 2 r 2 ( β m T m + β a T a )exp( 2 0 r [ α a (ξ)+ α m (ξ) ] dξ ),
T m = h m (ν'v) G i (v')dv' T a = h a (ν'v) G i (v')dv' .
B 1 =( β m + β a )exp(2τ),
B 1 =( β m T m + β a T a )exp(2τ),
τ= 0 r [ α a (ξ)+ α m (ξ) ]dξ ,
β a = 1K T m K T a 1 β m ,
τ=0.5ln( B 1 T a B 2 ( T a T m ) β m ).
α a = τ r α m = T a B 1 ' B 2 ' 2( T a B 1 B 2 ) + β m ' 2 β m α m ,
R a = ( T m T a )K 1 T a K .
η β a T a = β a β a T a Δ T a = ( K T m 1 ) R a 2 ( R a 1 ) ( T m T a ) 2 K Δ T a SR= T a T m , δ T a = Δ T a T a η β a T a = R a Δ T a T m T a = R a SR 1SR δ T a ,
η β a T m = β a β a T m Δ T m = R a ( R a 1 )( T m T a ) Δ T m SR= T a T m , δ T m = Δ T m T m η β a T m = R a ( R a 1 )( 1SR ) δ T m .
η β a K = β a β a K ΔK= R a 2 ( R a 1 )( T m T a ) K 2 ΔK SR= T a T m , δ K = ΔK K η β a K = R a ( R a SR+1SR ) ( R a 1 )( 1SR ) δ K .
η β a β m = β a β a β m Δ β m = 1K T m ( K T a 1 ) β a Δ β m = Δ β m β m . δ β m = Δ β m β m η β a β m = δ β m
η β a = ( η β a T a ) 2 + ( η β a T m ) 2 + ( η β a K ) 2 + ( η β a β m ) 2 .
σ τ B 1 = τ B 1 Δ B 1 = R a SR 2( 1SR ) δ B 1 δ B 1 = Δ B 1 B 1 ,
σ τ B 2 = τ B 2 Δ B 2 = ( R a SR+1SR ) 2(SR1) δ B 2 δ B 2 = Δ B 2 B 2 ,
σ τ T m = τ T m Δ T m = 1 2( 1SR ) δ T m ,
σ τ T a = τ T a Δ T a = SR( R a 1 ) 2( 1SR ) δ T a .
σ τ β m = τ β m Δ β m = Δ β m 2 β m = 1 2 δ β m .
σ τ = ( σ τ T a ) 2 + ( σ τ T m ) 2 + ( σ τ B 1 ) 2 + ( σ τ B 2 ) 2 + ( σ τ β m ) 2 .

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