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Lecture 8: Rayleigh lidar for observations of middle atmospheric temperature

Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

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Page 1: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Lecture 8: Rayleigh lidar for observations

of middle atmospheric temperature

Page 2: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Rayleigh lidar equation

( )( )

⎟⎟

⎜⎜

⎛−−−=

Δ+−

=

∫ ∑ ∫∫= ==

z

zz i

z

zziLi

z

zzLMieLRay

LMieLRayL

LLLLRay

L LL

dzzNzdzzdzz

zzzTzzANzN

' ''

2

22

')'(),'(2 '),'(2 '),'(2exp T

),(),()(),(

λσλαλα

λβλβλλ

NRay is the number of photons received per laser shot at wavelength λR= λL NL is the number of photons emitted per laser shot at wavelength λL z is the altitude of the Δz-thick back-scattering layer AL is the area of the receiving telescope zL is the altitude of the emitting/receiving system βRay is the Rayleigh backscatter coefficient: βMie is the Mie back-scattering coefficient of the atmospheric aerosols particles αRay is the air Rayleigh extinction coefficient: αRay is the Mie extinction coefficient of the atmospheric aerosols particles σRay is the Rayleigh extinction cross-section of the air molecules NAir is the air number density at altitude z, i denotes all the atmospheric absorbers (ozone, water vapor, etc.) σi is the absorption cross-section of the constituent i Ni is the number density of the constituent i.

)()(83),( zNz AirLRayLRay λσπ

=λβ

)()(),( zNz AirLRayLRay λσ=λα

Page 3: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Density and temperature derivation

( )

( )

( )⎟⎟

⎜⎜

⎛+−=

⎟⎟

⎜⎜

⎛+−=

−=

=

=

z

zziOROLOO

z

zz

BRRayLRay

RayL

L

L

dzzNzzT

dzzRkzM

zNzzCz

'

2

'

Ray2

O2

Ray2

2

')'(),'(),'(exp

')'()'()()(exp T

TT)(

)(

3333

3

λσλσ

ρλσλσ

ρ

dzzgzzdp )()()( ρ−=hydrostatic equilibrium: Ideal gas law: )(

)()()( zT

zMRzzp ρ=

Only consider ozone observation, an a priori ozone profile is also necessary

Page 4: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Density and temperature derivation

Using an external source (from a model or from external measurements) of temperature information T0 at the top of the profile (integration downward, uncertainty converge)

⎟⎟⎠

⎞⎜⎜⎝

⎛+= ∫

=

TOP

RR

R

z

zz

CTOP

CTOPC zzgzS

RzMzSzT

zSzT

'0 ')'()'()()()(

)(1)( δλλ

λ

)()()()(

)()()( zS

zMKzRTzT

zMRzzp C

NRλ

=ρ=

( )C

)( TT

zN )()(

3O2

Ray2

Ray2 zzz

zS LCR

ρλ =

−=

Page 5: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Error analysis

The uncertainty is determined by the photon noise and upper altitude temperature T(z0). The variance of derived temperature is given by After 1-2 scale height (10-15 km), the error introduced by T(z0) is not important anymore. So the temperature error is primarily due to the photon noise.

Page 6: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Error analysis

Leblanc et al., 1998

Page 7: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

ARCtic LIdar Technology (ARCLITE) system

Page 8: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

System Specifications Transmitter: Spectra-Physics GCR5-30 Nd:YAG

Wavelength: 532nm Pulse width: 7 ns Pulse repetition rate: 30 Hz Pulse energy: 560 mJ Average power: 17 W Seeded linewidth: 105 MHz Beam divergence (X4): 0.1 mrad

Receiver: Newtonian Telescope Configuration

Telescope diameter: 92 cm Focal length: 203 cm Field of view: 0.5 mrad Number of channels: 2 Filter bandwidth: Nighttime: 10 Å Daytime: 0.8 Å

Signal Processing: Photon Counting Data Acquisition System Data system SR430 Maximum count rate: 100 MHz Range bin size: 192 m Number of range bins: 1024 On-line integration: 1 min Computer system: PC 486-33 PMTs (2)EMI 9863B/100

Page 9: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

ARCLITE lidar observations

Temperature

Page 10: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

ARCLITE lidar observations Noctilucent clouds

(Polar Mesospheric Clouds, or PMC )

Page 11: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Inter-comparisons of middle atmospheric temperature observed by lidars and NASA EOS Aura MLS satellite

Aura Satellite

Page 12: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

The Lidar stations

JPL TMF lidar station: - 50 miles NE of Los Angeles - Latitude: 34.4ºN - Longitude: 117.7ºW -  Elevation: 2285 m (7500 ft) JPL MLO Lidar station: - Near center of Big Island of Hawaii - Latitude: 19.5ºN - Longitude: 204.4ºW -  Elevation: 3400 m (12,000 ft) France OHP lidar station: -  southeast France - Latitude: 44ºN - Longitude: 6ºW - Elevation: 679m

Ny-Alesund lidar station: -west coast of Spitsbergen, Norway - Latitude: 78.9ºN - Longitude: 11.9ºE -  Elevation: 11m Germany HOH Lidar station -  Hohenpeissenberg, Germany -  Latitude: 47.8ºN -  Longitude: 11ºE -  Elevation: 1000m

Page 13: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS – TMF and MLO lidars (temperature profiles)

Page 14: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS – TMF (34.4ºN, 117.7ºW) lidar (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: lidar Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 15: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - TMF lidar (temperature)

Page 16: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - TMF NDSC Model (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: NDSC Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 17: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - TMF NCEP Model (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: NCEP Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 18: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS – MLO (19.5ºN, 204.4ºW) lidar (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: lidar Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 19: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - MLO lidar (temperature)

Page 20: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - MLO NDSC Model (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: NDSC Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 21: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - MLO NCEP Model (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: NCEP Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 22: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - MLO Radiosonde (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: RadioSonde Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 23: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - OHP (44ºN, 6ºE) lidar (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: lidar Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 24: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - HOH (47.8ºN, 11ºE) lidar (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: lidar Black: MLS-lidar (mean) Red and blue dotted: Precisions

Page 25: Lecture 8: Rayleigh lidar for observations of middle ...staff.ustc.edu.cn/~litao/ORS8_v2.ppt.pdf · Density and temperature derivation Using an external source (from a model or from

Comparisons MLS - NYA (78.9ºN, 11.9ºE) lidar (temperature)

Blue: MLS Green: MLS-lidar (individual) Red and blue solid: Standard deviations Red: lidar Black: MLS-lidar (mean) Red and blue dotted: Precisions