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Matthew McGill

Publications and source records attributed to Matthew McGill.

4 recordsLinked to original sources

Information content of data measured with a multiple-field-of-view lidar.

Lidars with multiple fields of view (MFOVs) are promising tools for gaining information on cloud particle size. We perform a study of the information content of MFOV lidar data with the use of eigenvalue analysis. The approach we have developed permits an understanding of the main features of MFOV lidars and provides a way to relate the accuracy of particle size estimation with the measurement uncertainty and the scattering geometry such as the cloud-base height and the lidar sounding depth. Second-order scattering computations are performed for an extended range of particle sizes and for a wide range of lidar fields of view (FOVs). The results obtained allow us to specify the areas of possible applications of these lidars in cloud studies. Comparison of results obtained with polarized and cross-polarized scattered components demonstrate that the cross-polarized signal should provide a more stable retrieval and is preferable when double scattering is highly dominant. Our analysis allows for the estimation of the optimal number of FOVs in the system and their angular distribution, so this work can be a useful tool for practical MFOV lidar design.

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Estimating random errors due to shot noise in backscatter lidar observations.

We discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson- distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root mean square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF, uncertainties can be reliably calculated from or for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar and tested using data from the Lidar In-space Technology Experiment.

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Simple relation between lidar multiple scattering and depolarization for water clouds.

An empirical relationship is derived between the multiple-scattering fraction and the linear depolarization ratio by using Monte Carlo simulations of water clouds measured by backscatter lidar. This relationship is shown to hold for clouds having a wide range of extinction coefficients, mean droplet sizes, and droplet size distribution widths. The relationship is also shown to persist for various instrument fields of view and for measurements made within broken cloud fields. The results obtained from the Monte Carlo simulations are verified by using multiple-field-of-view lidar measurements. For space-based lidars equipped to measure linear depolarization ratios, this new relationship can be used to accurately assess signal perturbations due to multiple scattering within nonprecipitating water clouds.

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Cloud physics lidar: instrument description and initial measurement results.

The new Cloud Physics Lidar (CPL) has been built for use on the NASA ER-2 high-altitude aircraft. The purpose of the CPL is to provide multiwavelength measurements of cirrus, subvisual cirrus, and aerosols with high temporal and spatial resolution. The CPL utilizes state-of-the-art technology with a high repetition rate, a low-pulse-energy laser, and photon-counting detection. The first deployment for the CPL was the Southern African Regional Science Initiative's 2000 field campaign during August and September 2000. We provide here an overview of the instrument and initial data results to illustrate the measurement capability of the CPL.

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