Retrieval of water vapor mixing ratio from a multiple channel Raman-scatter lidar using an optimal estimation method.

Lidar measurements of the atmospheric water vapor mixing ratio provide an excellent complement to radiosoundings and passive, ground-based remote sensors. Lidars are now routinely used that can make high spatial-temporal resolution measurements of water vapor from the surface to the stratosphere. Many of these systems can operate during the day and night, with operation only limited by clouds thick enough to significantly attenuate the laser beam. To enhance the value of these measurements for weather and climate studies, this paper presents an optimal estimation method (OEM) to retrieve the water vapor mixing ratio, aerosol optical depth profile, Ångstrom exponent, lidar constants, detector dead times, and measurement backgrounds from multichannel vibrational Raman-scatter lidars. The OEM retrieval provides the systematic uncertainties due to the overlap function, calibration factor, air density and Rayleigh-scatter cross sections, in addition to the random uncertainties of the retrieval due to measurement noise. The OEM also gives the vertical resolution of the retrieval as a function of height, as well as the height to which the contribution of the a priori is small. The OEM is applied to measurements made by the Meteoswiss Raman Lidar for Meteorological Observations (RALMO) in the day and night for clear and cloudy conditions. The retrieved water vapor mixing ratio is in excellent agreement with both the traditional lidar retrieval method and coincident radiosoundings.

Retrieval of temperature from a multiple-channel Rayleigh-scatter lidar using an optimal estimation method.

The measurement of temperature in the middle atmosphere with Rayleigh-scatter lidars is an important technique for assessing atmospheric change. Current retrieval schemes for this temperature have several shortcomings, which can be overcome by using an optimal estimation method (OEM). Forward models are presented that completely characterize the measurement and allow the simultaneous retrieval of temperature, dead time, and background. The method allows a full uncertainty budget to be obtained on a per profile basis that includes, in addition to the statistical uncertainties, the smoothing error and uncertainties due to Rayleigh extinction, ozone absorption, lidar constant, nonlinearity in the counting system, variation of the Rayleigh-scatter cross section with altitude, pressure, acceleration due to gravity, and the variation of mean molecular mass with altitude. The vertical resolution of the temperature profile is found at each height, and a quantitative determination is made of the maximum height to which the retrieval is valid. A single temperature profile can be retrieved from measurements with multiple channels that cover different height ranges, vertical resolutions, and even different detection methods. The OEM employed is shown to give robust estimates of temperature, which are consistent with previous methods, while requiring minimal computational time. This demonstrated success of lidar temperature retrievals using an OEM opens new possibilities in atmospheric science for measurement integration between active and passive remote sensing instruments.

New technique for retrieval of atmospheric temperature profiles from Rayleigh-scatter lidar measurements using nonlinear inversion.

The conventional method of calculating atmospheric temperature profiles using Rayleigh-scattering lidar measurements has limitations that necessitate abandoning temperatures retrieved at the greatest heights, due to the assumption of a pressure value required to initialize the integration at the highest altitude. An inversion approach is used to develop an alternative way of retrieving nightly atmospheric temperature profiles from the lidar measurements. Measurements obtained by the Purple Crow lidar facility located near The University of Western Ontario are used to develop and test this new technique. Our results show temperatures can be reliably retrieved at all heights where measurements with adequate signal-to-noise ratio exist. A Monte Carlo technique was developed to provide accurate estimates of both the systematic and random uncertainties for the retrieved nightly average temperature profile. An advantage of this new method is the ability to seed the temperature integration from the lowest rather than the greatest height, where the variability of the pressure is smaller than in the mesosphere or lower thermosphere and may in practice be routinely measured by a radiosonde, rather than requiring a rocket or satellite-borne measurement. Thus, this new technique extends the altitude range of existing Rayleigh-scatter lidars 10-15 km, producing the equivalent of four times the power-aperture product.

Lidar measurements taken with a large-aperture liquid mirror. 2. Sodium resonance-fluorescence system.

Sodium resonance-fluorescence lidar is an established technique for measuring atmospheric composition and dynamics in the mesopause region. A large-power-aperture product (6.6-W m(2)) sodium resonance-fluorescence lidar has been built as a part of the Purple Crow Lidar (PCL) at The University of Western Ontario. This sodium resonance-fluorescence lidar measures, with high optical efficiency, both sodium density and temperature profiles in the 83-100-km region. The sodium lidar operates simultaneously with a powerful Rayleigh- and Raman-scatter lidar (66 W m(2)). The PCL is thus capable of simultaneous measurement of temperature from the tropopause to the lower thermosphere. The sodium resonance-fluorescence lidar is shown to be able to measure temperature to an absolute precision of 1.5 K and a statistical accuracy of 1 K with a spatial-temporal resolution of 72 (km s) at an altitude of 92 km. We present results from three nights of measurements taken with the sodium lidar and compare these with coincident Rayleigh-scatter lidar measurements. These measurements show significant differences between the temperature profiles derived by the two techniques, which we attribute to variations in the ratio of molecular nitrogen to molecular oxygen that are not accounted for in the standard Rayleigh-scatter temperature analysis.

Lidar measurements taken with a large-aperture liquid mirror. 1. Rayleigh-scatter system.

A lidar system has been built to measure atmospheric-density fluctuations and the temperature in the upper stratosphere, the mesosphere, and the lower thermosphere, measurements that are important for an understanding of climate and weather phenomena. This lidar system, the Purple Crow Lidar, uses two transmitter beams to obtain atmospheric returns resulting from Rayleigh scattering and sodium-resonance fluorescence. The Rayleigh-scatter transmitter is a Nd:YAG laser that generates 600 mJ/pulse at the second-harmonic frequency, with a 20-Hz pulse-repetition rate. The sodium-resonance-fluorescence transmitter is a Nd:YAG-pumped ring dye laser with a sufficiently narrow bandwidth to measure the line shape of the sodium D(2) line. The receiver is a 2.65-m-diameter liquid-mercury mirror. A container holding the mercury is spun at 10 rpm to produce a parabolic surface of high quality and reflectivity. Test results are presented which demonstrate that the mirror behaves like a conventional glass mirror of the same size. With this mirror, the lidar system's performance is within 10% of theoretical expectations. Furthermore, the liquid mirror has proved itself reliable over a wide range of environmental conditions. The use of such a large mirror presented several engineering challenges involving the passage of light through the system and detector linearity, both of which are critical for accurate retrieval of atmospheric temperatures. These issues and their associated uncertainties are documented in detail. It is shown that the Rayleigh-scatter lidar system can reliably and routinely measure atmospheric-density fluctuations and temperatures at high temporal and spatial resolutions.