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.