Rotational Raman lidar to measure the atmospheric temperature from the ground to 30 km

Nedeljković, Dušan; Hauchecorne, Alain; Chanin, Marie-Lise

doi:10.1109/36.210448

Cited by 124 publications

(37 citation statements)

References 8 publications

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“…Retrieved values of r m and σ were more or less constant at 0.3 µm and 1.04 respectively whereas N o varied between 2 and 20 cm −3 . We processed the lidar signal using vibrational Raman detection for determining the BC and rotational Raman detection at 529 and 530 nm to get the in situ temperature using the Rotational Raman Technique (Cooney and Pina, 1976;Nedeljkovic et al, 1993). The determination of a simultaneous and collocated temperature profile improved the accuracy of both the BC and the chemical composition modelling.…”

Section: Evaluation Against a Simplified Estimation Methodologymentioning

confidence: 99%

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

et al. 2008

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Abstract.A method for estimating the stratospheric particle size distribution from multiwavelength lidar measurements is presented. It is based on matching measured and modelsimulated backscatter coefficients. The lidar backscatter coefficients measured at the three commonly used wavelengths 355, 532 and 1064 nm are compared to a precomputed lookup table of model-calculated values. The optical model assumes that particles are spherical and that their size distribution is unimodal. This inverse problem is not trivial because the optical model is highly non-linear with a strong sensitivity to the size distribution parameters in some cases. The errors in the lidar backscatter coefficients are explicitly taken into account in the estimation. The method takes advantage of the statistical properties of the possible solution cluster to identify the most probable size distribution parameters. In order to discard model-simulated outliers resulting from the strong non-linearity of the model, solutions farther than one standard deviation of the median values of the solution cluster are filtered out, because the most probable solution is expected to be in the densest part of the cluster. Within the filtered solution cluster, the estimation algorithm minimizes a cost function of the misfit between measurements and model simulations.Two validation cases are presented on Polar Stratospheric Cloud (PSC) events detected above the ALOMAR observatory (69 • N -Norway). A first validation is performed against optical particle counter measurements carried out in January 1996. In non-depolarizing regions of the cloud (i.e. spherical particles), the parameters of an unimodal size distribution and those of the optically dominant mode of a bimodal size distribution are quite successfully retrieved, especially for the median radius and the geometrical standard deviation. As expected, the algorithm performs poorly when Correspondence to: J. Jumelet (julien.jumelet@aero.jussieu.fr) solid particles drive the backscatter coefficient. A small bias is identified in modelling the refractive index when compared to previous works that inferred PSC type Ib refractive indices. The accuracy of the size distribution retrieval is improved when the refractive index is set to the value inferred in the reference paper.Our results are then compared to values retrieved with another similar method that does not account for the effect of the measurements errors and the non-linearity of the optical model on the likelihood of the solution. The case considered is a liquid PSC observed over northern Scandinavia on January 2005. An excellent agreement is found between the two methods when our algorithm is applied without any statistical filtering of the solution cluster. However, the solution for the geometrical standard deviation appears to be rather unlikely with a value close to unity (σ ≈1.04). When our algorithm is applied with solution filtering, a more realistic value of the standard deviation (σ ≈1.27) is found. This highlights the importance of taking int...

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Section: Evaluation Against a Simplified Estimation Methodologymentioning

confidence: 99%

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

et al. 2008

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“…It is thought to be difficult to correct the extinction by Mie scattering precisely enough (e.g. Nedeljkovic et al, 1993). But, this is not the result of the investigation by experiments with multi-wavelength observations as ours, or even not by the simulation with a detailed optical model.…”

Section: Discussionmentioning

confidence: 85%

Raman Lidar Observations: Simultaneous Measurements of Water Vapor, Temperature and Aerosol Vertical Profiles, Part I.

Shibata

Saicai

Hayashi

et al. 1996

J. geomagn. geoelec

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A Raman lidar was developed to observe vertical profiles of water vapor, temperature and aerosols. The lidar system can detect signal from 5 detectors simultaneously. Two vibrational Raman backscattering echoes from H2O and N2 (or 02) excited by Nd:YAG 3rd harmonics wavelength (355 nm) are used to observe the profiles of water vapor mixing ratio and atmospheric temperature (or density). Nd:YAG fundamental and 2nd harmonics wavelengths (1064 and 532 ran) are used to observe backscattering coefficient profiles of aerosols and clouds at these wavelengths. The scattering at 532 nm is observed in parallel and perpendicular components corresponding to the linear polarization plane of the transmitted linearly-polarized laser pulse to observe depolarization ratio profiles. Observed water vapor and temperature distributions coincide with the simultaneously observedradiosonde sounding dataexcellently. The Raman lidar makes it possible to observe the vertical profiles of water vapor, temperature, aerosols, and clouds simultaneously.

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“…At the lowest kilometers of the atmosphere the broadening of the Rayleigh line by Brillouin scatter might induce some additional, pressure-dependent signal in the rotational Raman channels. But it has been shown by Nedeljkovic et al (1993) that with a sufficient narrow laser wavelength the contribution of the Rayleigh line can be neglected even at surface pressure. For the injection-seeded monomode laser of the IAP RMR lidar we can assume the Brillouin effect to be neglectable compared with the statistical error in the lowest bins.…”

Section: Instruments and Observation Methodsmentioning

confidence: 99%

Temperature lidar measurements from 1 to 105 km altitude using resonance, Rayleigh, and Rotational Raman scattering

et al. 2004

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Abstract. For the first time, three different temperature lidar methods are combined to obtain time-resolved complete temperature profiles with high altitude resolution over an altitude range from the planetary boundary layer up to the lower thermosphere (about 1-105 km). The Leibniz-Institute of Atmospheric Physics (IAP) at Kühlungsborn, Germany (54 • N, 12 • E) operates two lidar instruments, using three different temperature measurement methods, optimized for three altitude ranges: (1) Probing the spectral Doppler broadening of the potassium D 1 resonance lines with a tunable narrow-band laser allows atmospheric temperature profiles to be determined at metal layer altitudes (80-105 km). (2) Between about 20 and 90 km, temperatures were calculated from Rayleigh backscattering by air molecules, where the upper start values for the calculation algorithm were taken from the potassium lidar results. Correction methods have been applied to account for, e.g. Rayleigh extinction or Mie scattering of aerosols below about 32 km. (3) At altitudes below about 25 km, backscattering in the Rotational Raman lines is strong enough to obtain temperatures by measuring the temperature dependent spectral shape of the Rotational Raman spectrum. This method works well down to about 1 km. The instrumental configurations of the IAP lidars were optimized for a 3-6 km overlap of the temperature profiles at the method transition altitudes. We present two night-long measurements with clear wave structures propagating from the lower stratosphere up to the lower thermosphere.

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Rotational Raman lidar to measure the atmospheric temperature from the ground to 30 km

Cited by 124 publications

References 8 publications

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

Raman Lidar Observations: Simultaneous Measurements of Water Vapor, Temperature and Aerosol Vertical Profiles, Part I.

Temperature lidar measurements from 1 to 105 km altitude using resonance, Rayleigh, and Rotational Raman scattering

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