Inversion of multiwavelength Raman lidar data for retrieval of bimodal aerosol size distribution

Abstract

We report on the feasibility of deriving microphysical parameters of bimodal particle size distributions from Mie-Raman lidar based on a triple Nd:YAG laser. Such an instrument provides backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The inversion method employed is Tikhonov's inversion with regularization. Special attention has been paid to extend the particle size range for which this inversion scheme works to approximately 10 microm, which makes this algorithm applicable to large particles, e.g., investigations concerning the hygroscopic growth of aerosols. Simulations showed that surface area, volume concentration, and effective radius are derived to an accuracy of approximately 50% for a variety of bimodal particle size distributions. For particle size distributions with an effective radius of < 1 microm the real part of the complex refractive index was retrieved to an accuracy of +/- 0.05, the imaginary part was retrieved to 50% uncertainty. Simulations dealing with a mode-dependent complex refractive index showed that an average complex refractive index is derived that lies between the values for the two individual modes. Thus it becomes possible to investigate external mixtures of particle size distributions, which, for example, might be present along continental rims along which anthropogenic pollution mixes with marine aerosols. Measurement cases obtained from the Institute for Tropospheric Research six-wavelength aerosol lidar observations during the Indian Ocean Experiment were used to test the capabilities of the algorithm for experimental data sets. A benchmark test was attempted for the case representing anthropogenic aerosols between a broken cloud deck. A strong contribution of particle volume in the coarse mode of the particle size distribution was found.

An Adaptive Base Point Algorithm for the Retrieval of Aerosol Microphysical Properties

“…Another technique that is widely used is the Tikhonov-Phillips Regularization (TPR), which shifts the spectrum of the operator (see [3,6,7]), thus…”

“…Also, there is lots of research into the questions on how special a priori information on the solution can be used to improve the results. In [7], for instance, a special algorithm for the retrieval of bi-modal distributions is proposed. Another example can be found in [8], which takes special care to incorporate a priori information on the solution in the form of a nonnegativity constraint.…”

Independent Retrieval of Aerosol Type From Lidar

“…Although having multiple advantages (high dynamic range, high spatial and temporal resolution), lidar data suffer by a limited physical content. Both the problems of retrieving optical profiles and microphysical properties from lidar data are ill-posed, needing advanced mathematical algorithms [1]- [3].…”

Study of Droplet Activation in Thin Clouds Using Ground-Based Raman Lidar and Ancillary Remote Sensors

“…The source and type of aerosols in cloud-free regions close to the cloud boundaries are identified from the analysis of the air mass backtrajectories provided by NOAA Hysplit model [5], along with the values of multi-wavelength aerosol lidar ratios (S) and the Ångström exponents (å) [6], averaged over the altitude range between the cloud base and the cloud top. In the same region, the aerosol size distribution close to the clouds is also retrieved from multi-wavelength aerosol extensive optical properties, averaged over the altitude range between the base and the top of the cloudy region, using the algorithm developed by Veselovskii [7]. …”