Alexander Petkov

Determination of smoke plume and layer heights using scanning lidar data

The methodology of using mobile scanning lidar data for investigation of smoke plume rise and high-resolution smoke dispersion is considered. The methodology is based on the lidar-signal transformation proposed recently [Appl. Opt. 48, 2559 (2009)]. In this study, similar methodology is used to create the atmospheric heterogeneity height indicator (HHI), which shows all heights at which the smoke plume heterogeneity was detected by a scanning lidar. The methodology is simple and robust. Subtraction of the initial lidar signal offset from the measured lidar signal is not required. HHI examples derived from lidar scans obtained with the U.S. Forest Service, Fire Sciences Laboratory mobile lidar in areas polluted by wildfires are presented, and the basic details of the methodology are discussed.

Validation of smoke plume rise models using ground-based Lidar

Biomass fires can significantly degrade regional air quality through the emission of primary aerosols and the photochemical production of ozone and secondary aerosols. The injection height of smoke from biomass burning into the atmosphere (‘plume rise height’) is one of the critical factors in determining the impact of fire emissions on air quality. Plume rise models are used to simulate plume rise height and prescribe the vertical distribution of fire emissions for input to smoke dispersion and air quality models. While several plume rise models exist, their uncertainties, biases, and application limits when applied to biomass fires are not well characterized. The poor state of model evaluation is due in large part to a lack of appropriate observational datasets. We have initiated a research project to address this critical observation gap. In August of 2013 we performed a multi-agency field experiment designed to obtain the data necessary to improve the air quality models used by agricultural smoke managers in the northwestern United States. In the experiment, the ground-based mobile lidar, developed at the US Forest Service Missoula Fire Science Laboratory, was used to monitor plume rise heights for nine agricultural fires in the northwestern United States. The lidar measurements were compared with plume rise heights calculated with the Briggs equations, which are used in several smoke management tools. Here we present the preliminary evaluation results and provide recommendations regarding the application of the models to agricultural burning based on lidar measurements made in the vicinity of Walla Walla, Washington, on August 24, 2013.

Lidar monitoring of regions of intense backscatter with poorly defined boundaries

The upper height of a region of intense backscatter with a poorly defined boundary between this region and a region of clear air above it is found as the maximal height where aerosol heterogeneity is detectable, that is, where it can be discriminated from noise. The theoretical basis behind the retrieval technique and the corresponding lidar-data-processing procedures are discussed. We also show how such a technique can be applied to one-directional measurements. Examples of typical results obtained with a scanning lidar in smoke-polluted atmospheres and experimental data obtained in an urban atmosphere with a vertically pointing lidar are presented.

Alternative method for determining the constant offset in lidar signal

We present an alternative method for determining the total offset in lidar signal created by a daytime background-illumination component and electrical or digital offset. Unlike existing techniques, here the signal square-range-correction procedure is initially performed using the total signal recorded by lidar, without subtraction of the offset component. While performing the square-range correction, the lidar-signal monotonic change due to the molecular component of the atmosphere is simultaneously compensated. After these corrections, the total offset is found by determining the slope of the above transformed signal versus a function that is defined as a ratio of the squared range and two molecular scattering components, the backscatter and transmittance. The slope is determined over a far end of the measurement range where aerosol loading is zero or, at least, minimum. An important aspect of this method is that the presence of a moderate aerosol loading over the far end does not increase dramatically the error in determining the lidar-signal offset. The comparison of the new technique with a conventional technique of the total-offset estimation is made using simulated and experimental data. The one-directional and multiangle measurements are analyzed and specifics in the estimate of the uncertainty limits due to remaining shifts in the inverted lidar signals are discussed. The use of the new technique allows a more accurate estimate of the signal constant offset, and accordingly, yields more accurate lidar-signal inversion results.

Backscatter near-end solution in processing of scanning lidar data.

The significant issue of the classic multiangle data-processing technique is that the height up to which this technique allows the reliable profiling of the searched atmosphere is always significantly less than the maximum operative range of the scanning lidar signals. The existing multiangle inversion methodology does not allow for the proper inversion into optical profiles of the distant range signals measured in and close to zenith. In this study, a data-processing technique is considered which allows for increasing the maximal heights when profiling the atmosphere with scanning lidar; it is achieved by using the auxiliary backscatter near-end solution and the assumption of a constant lidar ratio over high altitudes. Simulated and experimental data are presented that illustrate the specifics of such a combined technique.