Abstract

A Shuttle lidar technique based on the detection of backscattered resonance fluorescence radiation has been numerically modeled and applied to the measurements of sodium (Na) and potassium (K) number density in the upper atmosphere (80–110 km). The simulations use recently defined lidar system parameters and take into account the effect of saturation of atomic absorption due to the high intensity of laser pulses. Such an effect is shown to be important in daytime measurements, when there is a need to narrow the laser beam divergence in order to reduce the background light. When the saturation effect is important, an optimal laser beam divergence can usually be found as a result of a trade off between the reduction of signal return (due to saturation) and the reduction of background level (by narrowing the receiver field of view). A procedure for calibration of the saturation effect is discussed. The Shuttle lidar measurement capability for Na and K is compared to conventional techniques and requirements for conducting scientific investigations in the mesosphere.

© 1982 Optical Society of America

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References

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  1. G. Megie, F. Bos, J. E. Blamont, M. L. Chanin, Planet. Space Sci. 26, 27 (1977) and references therein.
    [CrossRef]
  2. E. V. Browell, Ed., “Shuttle Atmospheric Lidar Research Program—Final Report of Atmospheric Lidar Working Group,” NASA 433 (1979).
  3. R. V. Greco, “Atmospheric Lidar Multi-user Instrument System Definition Study,” NASA CR-3303 (1980).
  4. See, for example,J. I. Steinfeld, Molecules and Radiation: An Introduction to Modern Spectroscopy (MIT Press, Cambridge, 1974).
  5. J. Laver, “Approach for Estimating Errors in Density Profiles,” Appendix D of SAGE Ground Truth Plan, NASA TM 80076 (1979);P. B. Russell, B. M. Morley, J. M. Livingston, G. W. Grams, E. M. Patterson, in “Improved Simulation of Aerosol, Cloud, and Density Measurements by Shuttle Lidar,” Final Report, NASA contract NAS1-16052 (1981).
  6. See, for example,P. R. Bevington, Data Reduction and Error Analysis for the Physical Sciences (McGraw-Hill, New York, 1969), p. 336.
  7. P. B. Russell, T. J. Swissler, M. P. McCormick, Appl. Opt. 18, 3783 (1979).
    [PubMed]
  8. J. E. Blamont, M. L. Chanin, G. Megie, Ann. Geophys. 4, 833 (1972).
  9. A. J. Gibson, M. C. W. Sandford, J. Atmos. Terr. Phys. 33, 1675 (1971) and Ref. 1.
    [CrossRef]
  10. M. P. Thekaekara, Appl. Opt. 13, 518 (1974).
    [CrossRef] [PubMed]
  11. R. M. Goody, Atmospheric Radiation (Oxford U. P., London, 1964), p. 417.
  12. H. M. Sullivan, D. M. Hunten, Can. J. Phys. 42, 937 (1964).
    [CrossRef]

1980 (1)

R. V. Greco, “Atmospheric Lidar Multi-user Instrument System Definition Study,” NASA CR-3303 (1980).

1979 (3)

J. Laver, “Approach for Estimating Errors in Density Profiles,” Appendix D of SAGE Ground Truth Plan, NASA TM 80076 (1979);P. B. Russell, B. M. Morley, J. M. Livingston, G. W. Grams, E. M. Patterson, in “Improved Simulation of Aerosol, Cloud, and Density Measurements by Shuttle Lidar,” Final Report, NASA contract NAS1-16052 (1981).

P. B. Russell, T. J. Swissler, M. P. McCormick, Appl. Opt. 18, 3783 (1979).
[PubMed]

E. V. Browell, Ed., “Shuttle Atmospheric Lidar Research Program—Final Report of Atmospheric Lidar Working Group,” NASA 433 (1979).

1977 (1)

G. Megie, F. Bos, J. E. Blamont, M. L. Chanin, Planet. Space Sci. 26, 27 (1977) and references therein.
[CrossRef]

1974 (1)

1972 (1)

J. E. Blamont, M. L. Chanin, G. Megie, Ann. Geophys. 4, 833 (1972).

1971 (1)

A. J. Gibson, M. C. W. Sandford, J. Atmos. Terr. Phys. 33, 1675 (1971) and Ref. 1.
[CrossRef]

1964 (1)

H. M. Sullivan, D. M. Hunten, Can. J. Phys. 42, 937 (1964).
[CrossRef]

Bevington, P. R.

See, for example,P. R. Bevington, Data Reduction and Error Analysis for the Physical Sciences (McGraw-Hill, New York, 1969), p. 336.

Blamont, J. E.

G. Megie, F. Bos, J. E. Blamont, M. L. Chanin, Planet. Space Sci. 26, 27 (1977) and references therein.
[CrossRef]

J. E. Blamont, M. L. Chanin, G. Megie, Ann. Geophys. 4, 833 (1972).

Bos, F.

G. Megie, F. Bos, J. E. Blamont, M. L. Chanin, Planet. Space Sci. 26, 27 (1977) and references therein.
[CrossRef]

Chanin, M. L.

G. Megie, F. Bos, J. E. Blamont, M. L. Chanin, Planet. Space Sci. 26, 27 (1977) and references therein.
[CrossRef]

J. E. Blamont, M. L. Chanin, G. Megie, Ann. Geophys. 4, 833 (1972).

Gibson, A. J.

A. J. Gibson, M. C. W. Sandford, J. Atmos. Terr. Phys. 33, 1675 (1971) and Ref. 1.
[CrossRef]

Goody, R. M.

R. M. Goody, Atmospheric Radiation (Oxford U. P., London, 1964), p. 417.

Greco, R. V.

R. V. Greco, “Atmospheric Lidar Multi-user Instrument System Definition Study,” NASA CR-3303 (1980).

Hunten, D. M.

H. M. Sullivan, D. M. Hunten, Can. J. Phys. 42, 937 (1964).
[CrossRef]

Laver, J.

J. Laver, “Approach for Estimating Errors in Density Profiles,” Appendix D of SAGE Ground Truth Plan, NASA TM 80076 (1979);P. B. Russell, B. M. Morley, J. M. Livingston, G. W. Grams, E. M. Patterson, in “Improved Simulation of Aerosol, Cloud, and Density Measurements by Shuttle Lidar,” Final Report, NASA contract NAS1-16052 (1981).

McCormick, M. P.

Megie, G.

G. Megie, F. Bos, J. E. Blamont, M. L. Chanin, Planet. Space Sci. 26, 27 (1977) and references therein.
[CrossRef]

J. E. Blamont, M. L. Chanin, G. Megie, Ann. Geophys. 4, 833 (1972).

Russell, P. B.

Sandford, M. C. W.

A. J. Gibson, M. C. W. Sandford, J. Atmos. Terr. Phys. 33, 1675 (1971) and Ref. 1.
[CrossRef]

Steinfeld, J. I.

See, for example,J. I. Steinfeld, Molecules and Radiation: An Introduction to Modern Spectroscopy (MIT Press, Cambridge, 1974).

Sullivan, H. M.

H. M. Sullivan, D. M. Hunten, Can. J. Phys. 42, 937 (1964).
[CrossRef]

Swissler, T. J.

Thekaekara, M. P.

Ann. Geophys. (1)

J. E. Blamont, M. L. Chanin, G. Megie, Ann. Geophys. 4, 833 (1972).

Appendix D of SAGE Ground Truth Plan, NASA TM 80076 (1)

J. Laver, “Approach for Estimating Errors in Density Profiles,” Appendix D of SAGE Ground Truth Plan, NASA TM 80076 (1979);P. B. Russell, B. M. Morley, J. M. Livingston, G. W. Grams, E. M. Patterson, in “Improved Simulation of Aerosol, Cloud, and Density Measurements by Shuttle Lidar,” Final Report, NASA contract NAS1-16052 (1981).

Appl. Opt. (2)

Can. J. Phys. (1)

H. M. Sullivan, D. M. Hunten, Can. J. Phys. 42, 937 (1964).
[CrossRef]

J. Atmos. Terr. Phys. (1)

A. J. Gibson, M. C. W. Sandford, J. Atmos. Terr. Phys. 33, 1675 (1971) and Ref. 1.
[CrossRef]

NASA 433 (1)

E. V. Browell, Ed., “Shuttle Atmospheric Lidar Research Program—Final Report of Atmospheric Lidar Working Group,” NASA 433 (1979).

NASA CR-3303 (1)

R. V. Greco, “Atmospheric Lidar Multi-user Instrument System Definition Study,” NASA CR-3303 (1980).

Planet. Space Sci. (1)

G. Megie, F. Bos, J. E. Blamont, M. L. Chanin, Planet. Space Sci. 26, 27 (1977) and references therein.
[CrossRef]

Other (3)

See, for example,J. I. Steinfeld, Molecules and Radiation: An Introduction to Modern Spectroscopy (MIT Press, Cambridge, 1974).

See, for example,P. R. Bevington, Data Reduction and Error Analysis for the Physical Sciences (McGraw-Hill, New York, 1969), p. 336.

R. M. Goody, Atmospheric Radiation (Oxford U. P., London, 1964), p. 417.

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Figures (8)

Fig. 1
Fig. 1

Comparison of saturated and unsaturated backscattering signals for calibration of saturation effect. The solid curve represents the signal from a resonance cell containing the gas species of interest, the dashed curve is the straight-line extrapolation extending from the low-intensity limit of the measured curve, representing the unsaturated signal. E1 is the laser energy which gives a power density in the resonance cell equal to that in an actual shuttle lidar measurement. The saturation factor is obtained as N R / N R 0.

Fig. 2
Fig. 2

Number density profiles of sodium and potassium used in the simulations.

Fig. 3
Fig. 3

Signal returns (numbers of photoelectrons detected) from the observation region for daytime and nighttime measurements. The daytime signals are lower than the nighttime signals due to the use of a smaller laser beam divergence which causes a larger saturation effect. (The system parameters used are shown in Table II.) The inset shows the saturation factor across the altitude region for the daytime measurement case, there being no saturation in the nighttime case.

Fig. 4
Fig. 4

Signal measurement error and the saturation factor vs the laser beam divergence for the case of sodium for two typical altitudes and number densities. The arrow on the abscissa indicates the optimal beam divergence. The corresponding saturation factor can be read from the dashed curves.

Fig. 5
Fig. 5

Signal measurement error and the saturation factor vs the laser beam divergence for the case of potassium for two typical altitudes and number densities. The arrow on the abscissa indicates the optimal beam divergence. The corresponding saturation factor can be read from the dashed curves.

Fig. 6
Fig. 6

Errors in the measured number densities of Na and K across the 70–120-km region. The errors include a 4% error in the effective cross section and a 3% error in the molecular number density.

Fig. 7
Fig. 7

Horizontal–vertical resolution trade off for Na. The straight lines represent the amount of signal integration (along horizontal track integration or vertical range bin integration) to satisfy given measurement accuracies. Three sets of horizontal and vertical lines, labeled 1,2, and 3, represent spatial resolution requirements for different scientific purposes as discussed in the text. Two typical sodium number densities are chosen to represent the higher and lower ends of the number density encountered in this region. The labels D10, D20, N10, and N20 represent daytime and 10%, daytime and 20%, nighttime and 10%, and nighttime and 20%, respectively.

Fig. 8
Fig. 8

Horizontal–vertical resolution trade off for potassium. The straight lines represent the amount of signal integration (along horizontal track integration and vertical range bin integration) to satisfy given measurement accuracies. The set of vertical–horizontal lines represents the spatial resolution requirements appropriate for scientific objectives discussed in the text. Two typical potassium number densities are chosen to represent the higher and lower ends of the number density encountered in this region. The labels D50, D100, N50, and N100 represent daytime and 50%, daytime and 100%, nighttime and 50%, and nighttime and 100%, respectively.

Tables (3)

Tables Icon

Table I Temperature Dependence of Doppler Linewidth and Effective Absorption Cross Section

Tables Icon

Table II Shuttle Lidar System Parameters Assumed in the Simulations

Tables Icon

Table III Shuttle Lidar System Performance for Three Detector Bandwidths

Equations (16)

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P s = K s Δ z ( z L z ) 2 ( β 0 + n σ eff ) exp ( 2 τ ) ,
z z L α tot ( z ) dz ;
n = 1 σ eff [ P s ( z L z ) 2 K s Δ z exp ( + 2 τ ) β 0 ] .
n = 1 σ eff ( PQ β 0 c β 0 ) ,
( δ n n ) 2 = ( δ σ eff σ eff ) 2 + [ ( δ P P ) 2 + ( δ Q Q ) 2 + ( δ β 0 c β 0 c ) 2 ] ( 1 + β 0 n σ eff ) 2 + ( δ β 0 β 0 ) 2 ( β 0 n σ eff ) 2 .
( δ n n ) 2 = ( δ σ eff σ eff ) 2 + ( δ P P ) 2 + ( δ β 0 c β 0 c ) 2 .
( δ P P ) 2 = ( P s + P B P s 2 ) + ( P c + P B P c 2 ) ,
2 γ l ln 2 π exp ( 4 ln 2 Δ λ 2 / γ l 2 ) ,
2 γ D ln 2 π exp ( 4 ln 2 Δ λ 2 / γ D 2 ) ,
d n e dt = n e t N + ( n n e ) Q 1 ( z L z ) 2 Ω N ( t ) σ eff ( a ) n e Q 1 ( z L z ) 2 Ω N ( t ) σ eff ( a ) ,
N ( t ) = N 0 / t L , 0 < t < t L , 0 , t > t L .
n e ( t ) = { n t 2 t s [ 1 exp ( t / t ) ] , 0 < t < t L , n t 2 t s [ 1 exp ( t L / t ) ] exp [ ( t L t ) / t N ] , t > t L ,
1 t = 1 t N + 1 t s and t s = ( z L z ) 2 Ω t L 2 Q 1 N 0 σ eff ( a ) .
N R = A r Q 1 Ω Δ t 4 π 0 Δ z / c n e ( t ) t N dt = N R 0 1 1 + t N / t s ( 1 t N t L t N / t s 1 + t N / t s × { exp [ t L t N ( 1 + t N / t s ) ] 1 } ) ,
N R 0 = A r Q 1 2 4 π ( z L z ) 2 n σ eff ( a ) Δ z N 0
N R N R 0 t s t N { 1 t N t L [ exp ( t L / t s ) 1 ] } .

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