Determination of aerosol extinction coefficient profiles from LIDAR data using the optical depth solution method

The profile of aerosol extinction coefficient can help understand the air pollution transportation and development of the atmospheric boundary layer. The charge-coupled device (CCD)-laser aerosol detection system (CLADS) was widely used to measure the profile of aerosol extinction coefficient, which has excellent resolution near the ground. Traditionally, a constant aerosol scattering phase function and single scattering albedo (SSA) is assumed when retrieving the profile of aerosol extinction coefficient using the measured signals from CLADS. Sensitivity studies in this research show that aerosol scattering phase function leads to an uncertainty up to 462% of the retrieved profile of aerosol extinction coefficient, while SSA leads to an uncertainty up to 25%. A new method is proposed to derive the profile of aerosol extinction coefficient by using two CCD cameras. The aerosol scattering phase function can be determined by minimizing the difference between profiles of aerosol extinction coefficient from the two CCD cameras without any assumption. The profile of aerosol extinction coefficient can be retrieved with high accuracy by using our optimized aerosol scattering phase function. This method is validated by simulation studies where the relative difference between the pre-parameterized aerosol extinction profile and retrieved aerosol extinction profile is below 6%. This dual CCD detection system is employed in a field measurement and proved to be reliable. Our proposed method can obtain more accurate profile of aerosol extinction coefficient for further works about air pollution and atmospheric boundary layer development.

Determination of the boundary value of the aerosol extinction coefficient and its effects on the extinction coefficient profile of aerosol in lower atmosphere

Accurately capturing cloud condensation nuclei (CCN) concentrations is key to understanding the aerosol-cloud interactions that continue to feature the highest uncertainty amongst numerous climate forcings. In situ CCN observations are sparse and most non-polarimetric passive remote sensing techniques are limited to providing column-effective CCN proxies such as total aerosol optical depth (AOD). Lidar measurements, on the other hand, resolve profiles of aerosol extinction and/or backscatter coefficients that are better suited for constraining vertically-resolved aerosol optical and microphysical properties. Here we present relationships between aerosol backscatter and extinction coefficients measured by the airborne High Spectral Resolution Lidar 2 (HSRL-2) and in situ measurements of CCN concentrations. The data were obtained during three deployments in the NASA ObseRvations of Aerosols above Clouds and their intEractionS (ORACLES) project, which took place over the Southeast Atlantic (SEA) during September 2016, August 2017, and September–October 2018. Our analysis of spatiotemporally collocated in situ CCN concentrations and HSRL-2 measurements indicates strong linear relationships between both data sets. The correlation is strongest for supersaturations greater than 0.25 % and dry ambient conditions above the stratocumulus deck, where relative humidity (RH) is less than 50 %. We find CCN – HSRL-2 Pearson correlation coefficients between 0.95–0.97 for different parts of the seasonal burning cycle that suggest fundamental similarities in biomass burning aerosol (BBA) microphysical properties. We find that ORACLES campaign-average values of in situ CCN and in situ extinction coefficients are qualitatively similar to those from other regions and aerosol types, demonstrating overall representativeness of our data set. We compute CCN – backscatter and CCN – extinction regressions that can be used to resolve vertical CCN concentrations across entire above-cloud lidar curtains. These lidar-derived CCN concentrations can be used to evaluate model performance, which we illustrate using an example CCN concentration curtain from WRF-CAM5. These results demonstrate the utility of deriving vertically-resolved CCN concentrations from lidar observations to expand the spatiotemporal coverage of limited or unavailable in situ observations.

Impact of CALIPSO profile data assimilation on 3-D aerosol improvement in a size-resolved aerosol model

<p>The Aladin instrument on-board the ESA Earth Explorer satellite Aeolus is a UV high spectral resolution Doppler Wind Lidar. The main mission product is profiles of horizontally projected line-of-sight winds, and the instrument design is therefore optimized to measure Doppler shifts of the atmospheric backscatter signals compared to the UV light emitted at ~355 nm (ESA, 2008; Stoffelen, 2005). Since the lidar backscatter contains information on the location of optically thin aerosol and cloud layers and cloud tops, spin-off products have been developed to retrieve aerosol and cloud backscatter and extinction coefficient and lidar ratio profile products (ESA, 2008; Flamant, 2008; Flamant, 2017). The advantage of a high spectral resolution lidar is that it measures molecular and particle backscatter separately in two dedicated channels. Still, some contributions from molecular backscatter exists in the measurements from the Fizeau channel and vice versa. This channel cross-talk requires correction during the product retrieval.</p><p>The Aeolus L2A operational aerosol and cloud retrieval algorithm is applying the so-called high spectral resolution retrieval method for the calculation of the particle and extinction backscatter coefficient products. The algorithm, developed at IPSL and Météo-France, is called the Standard Correct Algorithm (SCA) (Flamant, 2008; Flamant, 2017). High signal noise is obtained due to ever-decreasing laser energies and instrument receive path transmission. As a result, the Aeolus SCA optical properties retrieval is hampered. Particularly the ill-posed particle extinction coefficient retrieval is severely affected. In the past, attempts were made to mitigate nonphysical optical properties by measures like zero-flooring or signal accumulation in even coarser range gates (Flamant, 2017). Their success was limited.</p><p>An alternative noise suppression approach by Maximum Likelihood Estimation has therefore been prototyped that permits the retrieval of extinction coefficients and lidar ratios solely within pre-defined physical bounds. The optical properties are fitted to the 24 Aeolus atmospheric range gates within single atmospheric columns, minimizing the corresponding distance to the observed L1B useful signals measured by both spectrometers. This up to 48-dimensional non-linear regression problem is solved by means of the L-BFGS-B algorithm (Zhu, 1997). The method has proven its usefulness in noise suppression with astonishing efficiency. Particularly, the retrieved extinction coefficient profiles are less noisy, clearly revealing atmospheric layers also visible in the L1B useful signal profiles. The method is validated on end-to-end simulations and in-orbit observations.</p><p><strong>References<br></strong></p><p>ESA, ADM-Aeolus Science Report. ESA SP-1311, ESA Communication Production Office, 121 pp., 2008, available on http://www.esa.int/aeolus.</p><p>Flamant, P. H., Cuesta, J., Denneulin, M.-L., Dabas, A., Huber, D. ADM-Aeolus retrieval algorithms for aerosol and cloud products, Tellus, 60A, 273-286, 2008, https://doi.org/10.1111/j.1600-0870.2007.00287.x.</p><p>Flamant, P. et al. ADM-Aeolus L2A Algorithm Theoretical Baseline Document, 2017, available on https://earth.esa.int/aos/AeolusCalVal.</p><p>Stoffelen, A. et al. The atmospheric dynamics mission for global wind field measurement, Bulletin of the American Meteorological Society, 86, 73-88, 2005, https://doi.org/10.1175/BAMS-86-1-73.</p><p>Zhu, C., Byrd R. H. and Nocedal, J. L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale bound constrained optimization, ACM Transactions on Mathematical Software, 23 (4), 550-560, 1997, https://doi.org/10.1145/279232.279236. <br><br></p>

Abstract. Vertical profiles of aerosol extinction coefficients were measured by a micro-pulse lidar at Naqu (31.5° N, 92.1° E; 4508 m a.m.s.l.), a meteorological station located on the central part of the Tibetan Plateau during summer 2011. Observations show a persistent maximum in aerosol extinction coefficients in the upper troposphere–lower stratosphere (UTLS). These aerosol layers were generally located at an altitude of 18–19 km a.m.s.l., 1–2 km higher than the tropopause, with broad layer depth ranging approximately 3–4 km and scattering ratio of 4–9. Daily averaged aerosol optical depths (AODs) of the enhanced aerosol layers in UTLS over the Tibetan Plateau varied from 0.007 to 0.030, in agreement with globally averaged levels of 0.018 ± 0.009 at 532 nm from previous observations, but the percentage contributions of the enhanced aerosol layers to the total AOD over the Tibetan Plateau are higher than those observed elsewhere. The aerosol layers in UTLS wore off gradually with the reducing intensity of the Asian monsoon over the Tibetan Plateau at the end of August. The eruption of Nabro volcano on 13 June 2011 is considered an important factor to explain the enhancement of tropopause aerosols observed this summer over the Tibetan Plateau.

Lidar has proven to be an effective instrument for obtaining high resolution profiles of atmospheric aerosols. Deriving the optical properties of aerosols from the experimentally obtained lidar data is one of the most interesting and challenging task for the atmospheric scientists. A few methods had been developed so far, to obtain the quantitative profiles of extinction and backscattering coefficient of aerosols from the pulsed backscattering lidar measurements. Most of the existing inversion methods assume a range independent value for the scattering ratio for inverting the lidar signal even though it is known that the scattering ratio depends on the nature of aerosols and as such range dependent. We used a modified Klett's method for the inversion of lidar signal that uses range dependent scattering ratio ( s ) for the characterization of atmospheric aerosols. This method provides the constants k and s for all the altitude regions of the atmosphere and leads to derive the aerosol extinction profile for the lidar data. In this paper we made a study on the errors involved in the extinction profiles derived using the range dependent scattering ratio and discuss the approach in this regard to obtain the accurate extinction profiles.

A description is given of the first-ever global stratospheric aerosol climatology which is being developed by the earth-orbiting SAM II and SAGE satellite-based sensors. These sensors use the technique of solar occulation; that is, for every spacecraft sunrise and sunset, the modulation of solar intensity caused by the intervening earth-limb is measured. These data are mathematically inverted to yield vertical profiles of aerosol extinction coefficients with 1 km resolution. The data show seasonal variations which are similar in each hemisphere, with strong correlation between aerosol extinction and the corresponding temperature field. Typical values of extinction in the stratosphere are found to be about 0.0001 to 0.0002 per km at 1 micrometer; stratospheric optical depths at this wavelength are about 0.002. The peak extinction in the stratospheric aerosol layer follows the tropopause with altitude, with peak extinction ratios about 10 km above the local tropopause.

Aerosol vertical profile retrieved from ground-based MAX-DOAS observation and characteristic distribution during wintertime in Shanghai, China

New calculations of the relative optical air mass function are made over the 0°–87° range of apparent solar zenith angle θ, for various vertical profiles of background aerosol, diamond dust and thin cirrus cloud particle extinction coefficient in the Arctic and Antarctic atmospheres. The calculations were carried out by following the Tomasi and Petkov (2014) procedure, in which the above-mentioned vertical profiles derived from lidar observations were used as weighting functions. Different sets of lidar measurements were examined, recorded using: (i) the Koldewey-Aerosol-Raman Lidar (KARL) system (AWI, Germany) at Ny-Ålesund (Spitsbergen, Svalbard) in January, April, July and October 2013; (ii) the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite-based sensor over Barrow (Alaska), Eureka (Nunavut, Canada) and Sodankylä (northern Finland), and Neumayer III, Mario Zucchelli and Mirny coastal stations in Antarctica in the local summer months of the last two years; (iii) the National Institute of Optics (INO), National Council of Research (CNR) Antarctic lidar at Dome C on the Antarctic Plateau for a typical “diamond dust” case; and (iv) the KARL lidar at Ny-Ålesund and the University of Rome/National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) lidar at Thule (northwestern Greenland) for some cirrus cloud layers in the middle and upper troposphere. The relative optical air mass calculations are compared with those obtained by Tomasi and Petkov (2014) to define the seasonal changes produced by aerosol particles, diamond dust and cirrus clouds. The results indicate that the corresponding air mass functions generally decrease as angle θ increases with rates that are proportional to the increase in the pure aerosol, diamond dust and cirrus cloud particle optical thickness.

The present study evaluates the aerosol optical property computing performance of the Regional Climate Model (RegCM4) which is interactively coupled with anthropogenic-desert dust schemes, in South Africa. The validation was carried out by comparing RegCM4 estimated: aerosol extinction coefficient profile, Aerosol Optical Depth (AOD), and Single Scattering Albedo (SSA) with AERONET, LIDAR, and MISR observations. The results showed that the magnitudes of simulated AOD at the Skukuza station (24°S, 31°E) are within the standard deviation of AERONET and ±25% of MISR observations. Within the latitudinal range of 26.5°S to 24.5°S, simulated AOD and SSA values are within the standard deviation of MISR retrievals. However, within the latitude range of 33.5°S to 27°S, the model exhibited enhanced AOD and SSA values when compared with MISR observations. This is primarily associated with the dry bias in simulated precipitation that leads to the overestimation of dust emission and underestimation of aerosol wet deposition. With respect to LIDAR, the model performed well in capturing the major aerosol extinction profiles. Overall, the results showed that RegCM4 has a good ability in reproducing the major observational features of aerosol optical fields over the area of interest.

ILAS (Improved Limb Atmospheric Spectrometer) /ADEOS data retrieval algorithms

The results of multi-wavelength lidar investigating atmospheric aerosol parameters over background and industrial regions have been presented. Technical characteristics of the lidar station are described. The mean profiles of aerosol extinction and backscatter coefficient are compared with calculated ones for existing optical models of the atmosphere. Statistical characteristics of fluctuations of atmospheric optical parameters at various altitudes are estimated.

Regular aerosol extinction and backscatter measurements using a UV Raman lidar have been performed from January 2001 to December 2004 at Thessaloniki, Greece (40.5°N, 22.9°E), in the framework of the European Aerosol Research Lidar Network (EARLINET). Profiles of the aerosol extinction coefficient, backscatter coefficient, and extinction‐to‐backscatter ratio (so‐called “lidar ratio”) were acquired under nighttime conditions and have been used for statistical investigations. The statistical analysis was made both for the planetary boundary layer and for the free troposphere. It was found that the 4‐year mean boundary layer particle optical depth at 355 nm was 0.44 ± 0.18, and the total aerosol optical depth was 0.63 ± 0.27. Free tropospheric particles account on the average for 30% of the total aerosol optical depth, ranging from 5% (clean free troposphere conditions) to 55% (mainly Saharan dust events). For the cases examined, the integral of the lidar‐derived extinction coefficient was in good agreement with colocated aerosol optical depth measurements at 355 nm obtained with a Brewer spectroradiometer. The mean value of the lidar ratio at 355 nm derived, for the period of measurements at Thessaloniki, was 40 sr with a standard deviation of 21 sr. Mean height profiles of the particle lidar ratio, extinction, and backscatter coefficients are shown along with their seasonal dependence, showing a significant seasonal variability in the free troposphere. An analysis of the data using back trajectories showed also a dependence of the aerosol optical depth and the lidar ratio on the origin of the air mass, with higher values mostly corresponding to air masses originating from the northeast Balkans and eastern Europe.

Ceilometer aerosol extinction coefficient (AExtC) profiles in Hangzhou city (HZ) in East China are assimilated from 1 to 31 December 2020 by applying the WRFDA‐Chem model system. The analysis field obtained from data assimilation (DA) is set as the chemical initial condition (IC) for WRF‐Chem (Weather Research and Forecasting model coupled with Chemistry) aerosol prediction. Observations, including ceilometer AExtC profiles in HZ, ground PM2.5 in East China are adopted to verify the analysis and predictions. The RMSE (root mean square error between model and observation) improvements for ceilometer AExtC, and PM2.5 persist for at least 18 forecast hours, with the mean RMSE decreasing by 13% and 8%, respectively. Moreover, the contributions of different observation systems (ceilometer profiles versus ground PM2.5) to predicting three‐dimensional (3D) aerosol structures are also investigated. The contribution of ceilometer DA is comparable to that of direct PM2.5 DA to the PM2.5 predictions in HZ and its environs, with RMSE decreased by 8% and 10%, respectively. In areas far from the assimilation stations' locations (HZ city), ceilometer DA showed an even better performance. The performance of ground PM2.5 DA is inferior to that of the direct ceilometer DA experiment in predicting ceilometer AExtC vertical profiles. The joint assimilation of ceilometer and PM2.5 data was conducted. Best 3D aerosol structure predictions are obtained through the joint DA of ceilometer profiles and ground PM2.5.