Description:
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PI: Alain HAUCHECORNE & Philippe KECKHUT
Instrument: Rayleigh Lidar
Site(s): Observatoire de Haute Provence (43.9°N, 5.7°E, )
Measurement Quantities: Temperature (30-80 km)

Contact Information:
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Name: Philippe Keckhut
Address: Service d'Aéronomie, BP 3, 91371 Verrieres-le-Buisson, France
Phone:  (33) 1 64 47 43 11
  FAX: (33) 1 69 20 29 99
Email:  keckhut@aerov.jussieu.fr

Reference Articles:
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DENSITY AND TEMPERATURE PROFILES OBTAINED BY LIDAR BETWEEN 35 AND 70 KM,
Hauchecorne A., and M.L. Chanin, Geophys. Res. Lett., 7, 565-568, 1980.

LIDAR MONITORING OF THE TEMPERATURE IN THE MIDDLE AND LOWER ATMOSPHERE,
Hauchecorne A., M.L. Chanin, P. Keckhut, and D. 
Nedeljkovic, Applied Physics, B 54, 2573-2579, 
1992.

A CRITICAL REVIEW ON THE DATA BASE ACQUIRED FOR THE LONG TERM SURVEILLANCE OF
THE MIDDLE ATMOSPHERE BY FRENCH RAYLEIGH LIDARS,
Keckhut P., A. Hauchecorne and M.L. Chanin, J. 
Atmos. Oceanic Technol., 10, 850-867, 1993.

COMPARISON OF STRATOSPHERIC TEMPERATURE FROM SEVERAL LIDARS USING NMC AND MLS
DATA AS TRANSFER REFERENCE,
Wild J.D., M.E. Gelman, A.J. Miller, M.L. Chanin, 
A. Hauchecorne, P. Keckhut, R. Farley, P.D. Dao, 
G.P. Gobbi, A. Adriani, F. Coneduti, I.S. 
McDermid, T.J. McGee, and E.F.Fisbein, J. 
Geophys. Res., 100, 11105-11111, 1995.

STRATOSPHERIC TEMPERATURE MEASUREMENTS BY TWO COLLCATED NDSC LIDARS AT OHP
DURING UARS VALIDATION CAMPAIGN,
Singh U.N., P. Keckhut, T.J. McGee, M.R. Gross, 
A. Hauchecorne, E.F. Fishbein, J.W. Waters, J.C. 
Gille, A.E. Roche, and J.M. Russell III, J. 
Geophys. Res., special issue on UARS Data 
Validation, 101, 10287-10298, 1996.

EVALUATION AND OPTIMIZATION OF LIDAR TEMPERATURE ANALYSIS ALGORITHMS USING
SIMULATED DATA,
Leblanc T., I.S. McDermid, A. Hauchecorne, and P. 
Keckhut, J. Geophys. Res., 103, 6177-6187, 1998.

TEMPERATURE CLIMATOLOGY OF THE MIDDLE ATMOSPHERE 
FROM LONG-TERM LIDAR MEASUREMENTS AT MID- AND 
LOW-LATITUDES,
Leblanc T., I.S. McDermid, A. Hauchecorne, and P. 
Keckhut, J. Geophys. Res., 103, 17.191-17.204, 
1998.
STRATOSPHERIC TEMPERATURE TRENDS: OBSERVATIONS AND MODEL SIMULATIONS,
Ramaswamy V., M.L. Chanin, J. Angell, J. Barnett, 
D. Gaffen, M. Gelman, P. Keckhut, Y. Kolshelkov, 
K. Labitzke, J-J. R. Lin, A. O'Neill, J. Nash, W. 
Randel, R. Rood, K. Shine, M. Shiotani, and R. 
Swinbank,
Review of Geophysics, Rev. Geophys., 39, 71-122, 2001.

INVESTIGATIONS ON LONG-TERM TEMPERATURE CHANGES 
IN THE UPPER STRATOSPHERE USING LIDAR DATA AND 
NCEP ANALYSES,
Keckhut P., Wild J., Gelman M., Miller A.J., and Hauchecorne A.,
J. Geophys. Res., 106, 7937-7944, 2001.

SPRINGTIME TRANSITION IN UPPER MESOSPHERIC 
TEMPERATURE IN THE NORTHERN HEMISPHERE
Shepherd M.G., P.J. Espy, C.Y. She, W. Hocking, 
P. Keckhut, G. Gavrilyeva, G.G. Shepherd, B. 
Naujokat
J. Atmos. Sol. Terr. Phys., 64, 1183-1199, 2002.

INTERANNUAL CHANGES OF TEMPERATURE AND OZONE : 
RELATIONSHIP BEETWEN THE LOWER AND UPPER 
STRATOSPHERE,
Salby M., P. Callaghan, P. Keckhut, S. Godin, and 
M. Guirlet, J. Geophys. Res., J. Geophys. Res., 
107(D18), 10.1029/2001jD000421, 2002.

MESOSPHERIC INVERSIONS AND THEIR RELATIONSHIP TO PLANETARY WAVE STRUCTURE,
Salby M., F. Sassi, P. Callaghan, D. Wu, P. 
Keckhut, and A. Hauchecorne, J. Geophys. Res., 
107(D4), 10.1029/2001jD900756, 2002.

AN ASSESSMENT OF THE QUALITY OF HALOE TEMPERATURE 
PROFILES IN THE MESOSPHERE WITH RAYLEIGH 
BACKSCATTER LIDAR AND INFLATABLE FALLING SPHERE 
MEASUREMENTS,
Remsberg E.E., L.E. Deaver, J.G. Wells, G. 
Lingenfelser, P.P. Bhatt, L.L. Gordley, R. 
Thompson, M. McHugh, J.M. Russell III, P. 
Keckhut, and F.J. Schmidlin,  J. Geophys. Res., 
107(D19), 10.129/2001jD001521, 2002.

MESOSPHERIC TEMPERATURE FROM UARS MLS: RETRIEVAL AND VALIDATION
Wu D.L., W.G. Read, Z. Shippony, T. Leblanc, T.J. 
Duck, D.A. Ortland, R.J. Sica, P.S. Argall, J. 
Oberheide, A. Hauchecorne, P. Keckhut, C.Y. She, 
and D.A. Krueger, J.  Atmos.  Sol. Terr. Phys., 
65, 245-267, 2003.

REVIEW OF MESOSPHERIC TEMPERATURE TRENDS,
Beig G., P. Keckhut, R.P. Lowe, R.G. Roble, M.G. Mlynczak, J. Scheer, V.I. Fomichev, 
D. Offermann, W.J.R. French, M.G. Shepherd, A.I. 
Semenov, E.E. Remsberg, C.Y. She, F.J. Lübken, J. 
Bremer, B.R. Clemesha, J. Stegman, F. Sigernes, 
and S. Fadnavis,
Reviews of Geophysics, 41(4), 1015, doi: 10.1029/2002RG000121.

SPARC INTERCOMPARAISON OF MIDDLE ATMOSPHERE CLIMATOLOGIES,
Randel, W., Udelhofen, P., Fleming, E., Geller, 
M., Gelman, M., Hamilton, K., Karoly, D., 
Ortland, D., Pawson, S., Swinbank, R., Wu, F., 
Baldwin, M., Chanin, M.L., Keckhut, P., Labitzke, 
K., Remsberg, E., Simmons, A. and Wu, D.,
J. Clim., 17(5), 986-1003, 2004.

REVIEW OF OZONE AND TEMPERATURE LIDAR VALIDATIONS 
PERFORMED WITHIN THE FRAMEWORK OF THE NETWORK FOR 
THE DETECTION OF STRATOSPHERIC CHANGE
P. Keckhut, S. McDermid, D. Swart, T. McGee, S. 
Godin-Beekmann, A. Adriani, J. Barnes, J-L. 
Baray, H. Bencherif, H. Claude, G. Fiocco, G. 
Hansen, A. Hauchecorne, T. Leblanc, C.H. Lee, S. 
Pal, G. Megie, H. Nakane, R. Neuber, W. 
Steinbrecht, and J. Thayer,  J. Environ. Monit., 
6, 721-733, 2004.

INTERCOMPARAISON OF STRATOSPHERIC OZONE AND 
TEMPERATURE MEASUREMENTS AT THE OBSERVATOIRE DE 
HAUTE PROVENCE DURING THE OTOIC NDSC VALIDATION 
CAMPAIGN FROM 1-18 JULY 1997,
Braathen G.O., S. Godin, P. Keckhut, T.J. McGee, 
M.R. Gross, C. Vialle, and A. Hauchecorne,
Atmospheric Chemistry and Physics Discussions, Vol.4, pp5303-5344, 2004.


Instrument Description:
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This lidar uses the second harmonic of a ND:Yag 
pulse Laser (532.2 nm). The laser provides an 
energy of 350 mJ per pulse at 50 Hz. The beam 
divergence is reduced using an afocal system to 
0.04 mrad. The receiving area is composed by a 
mosaic of four 0.5 meter diameter mirrors.
Light is collected using optical fibers 
(diameter: 300 micrometers) located at each of 
the four focus points leading to a field of view 
equal to 0.2 mrad. The four fibers are mixed 
together in a single fiber. As the first channel 
received too many backscattered photons according 
to the bandwidth of the counting system, a second 
independent channel of lower sensitivity was 
implemented to cover the lower altitude range 
(30-50km). It is composed by a 0.2 meter diameter 
mirror providing a field of view of 0.55 mrad. 
The both optical fibers drive the photons up to 
two receiver boxes where filtering is insured 
using an interference filter of 1 nm.
Detection is made by cooled Hamamatsu 
photomultiplier tubes running on a counting mode. 
Counting gating is 0.5 microsecond providing a 75 
meters vertical resolution. Electronic gates is 
used on each channel, in an effort to reduce the 
effects of the large initial burst of light and 
the resulting signal induced noise. Reasons for 
the choice of this instrumental configuration 
have been detailed in Keckhut et al. (1993).

Algorithm Description:
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The method used to retrieve temperature profiles 
from molecular backscattered signal and the 
associated errors have been given in detail by 
Hauchecorne and Chanin (1980). More recently a 
description of the instrumental errors sources 
and biais have been reported by Keckhut et al. 
(1993).
Since 1987, the two existing channels have been 
mixed together to provide a single signal for the 
entire height range. This is achieved in 
comparing the both channels in the common 
altitude range (30-50 km) and in calculating the 
ratio between the both channels. Simultaneously, 
the channel providing the highest sensitivity 
(upper altitude range) is corrected for 
non-linearity effects in assuming an exponential 
function of the number of shots and in 
considering the channel for low altitudes as a 
reference. The signal-induced noise (SIN) is 
considerably reduced using electronic gating, but 
still can be identified from the very low mean 
background noise. To estimate the background 
noise and the SIN, a model backscattered signal 
is constructed by normalising the MSIS model to 
the experimental data at 40 km. By subtracting 
this model signal from the real bacscattered 
signal, a  first estimate of the SIN is obtained. 
For the altitude range where the backscattered 
signal is small compare to the noise, a quadratic 
fit of the estimated noise is calculated. This 
noise function is then extrapolated back to lower 
altitudes and subtracted from the data.
Computation of temperature profiles requires a 
pressure initialisation. Instead of assuming that 
the pressure at the top of the profile is equal 
to the value given by the standard atmosphere 
model, the scale height of the pressure (which is 
directly related to the temperature) is ajusting 
on the atmospheric model. Part of the actual 
algorithm can be found in Keckhut et al. (1993) 
and in Singh et al. (1996).
In the beginning of the 90's a new software have 
been developed including no major algorithm 
changes except the calculation of g as a function 
of altitude, an automatic calculation of the 
altitude range where the background noise should 
be calculated, the use of msis 90 instead of cira 
86 model, and a more severe limitation of the 
highest altitude of temperature computation 
(noise/signal=15%). This version V2 have been 
evaluated (Leblanc et al., 1998), corrected from 
bugs and never used for routine NDSC processing. 
The use of the corrected version V3 coincides 
with the change of the new electronics on August 
23, 1994. This version was used until April 4, 
1998 where the processing was improved in 
including in the version V4 an automatic data 
selection/rejection (Keckhut et al., 2001).

Expected Precision/Accuracy of Instrument:
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The accuracy in determining density and 
temperature is directly related to photon noise 
and is associated to temporal and vertical 
resolution. Statistical noise increases with the 
altitude and becomes suddenly very large as the 
signal amplitude reach the noise level. Relative 
and absolute uncertainties have been identified 
and quantified using simulated data (leblanc et 
al., 1998).
Error calculation can be found in Hauchecorne and 
Chanin (1980). For NDSC purposes vertical 
resolution is constant with altitude and equal to 
around 3 km. The integration time changes from 
night to night as it depend on weather 
conditions. The amplitude of the correction of 
the non-linearities of the counting is around 1-2 
K that is determined with an accuracy of 0.1 K. 
The error due to the initialisation was estimated 
to be equal to 15 % at the initialisation level. 
The calculation of uncertainty shows that this 
error becomes rapidly negligible as opposed to 
the noise statistic. The sum of these 
uncertainties have been reported on the NDSC 
archive. Comparison and data analyses have reveal 
that the possible biais occur mainly at the 
bottom part of the profile induced by 
miss-alignement problem or by the presence of 
aerosols. Improvments on signal and noise may 
have induced some spurious trend in the data 
series in the upper mesosphere.
Comparison with the mobile GSFC/NASA lidar in 
summer 1992 (Singh et al., 1996) reveals bias 
smaller than 2K between both instruments while 
variability of the differences between the both 
instruments is larger than estimated error 
between 35 to 45 km. A very good agreement on 
analysis software are obtained at that time.

Instrument History:
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The main evolution of the lidar have been 
described in Keckhut et al. (1993). Many 
instrumental changes have occurred since 1979. 
The last main change took place in September 1994 
as receiving telescopes, electronic counting 
system (vertical resolution) and computer were 
replaced. The analysis algorithm has been adapted 
to these changes and has been migrated from VMS 
to UNIX environment. Data series analyses and the 
last intercomparison with the GSFC mobile lidar 
show some temperature drops of nearly 4 K at 40 
km to -3K at 65 km revealing a possible 
miss-estimation of the correct altitude of 
several hundred meters probably associated to 
these last instrumental modifications.