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The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Operations (CALIPSO) mission released version 4.1 (V4) of their lidar level 2 cloud and aerosol data products in November 2016. These new products were derived from the CALIPSO V4 lidar level 1 data, in which the calibration of the measured backscatter data at both 532 and 1064 nm was significantly improved. This paper describes updates to the V4 level 2 cloud–aerosol discrimination (CAD) algorithm that more accurately differentiate between clouds and aerosols throughout the Earth's atmosphere. The level 2 data products are improved with new CAD probability density functions (PDFs) that were developed to accommodate extensive calibration changes in the level 1 data. To enable more reliable identification of aerosol layers lofted into the upper troposphere and lower stratosphere, the CAD training dataset used in the earlier data releases was expanded to include stratospheric layers and representative examples of volcanic aerosol layers. The generic "stratospheric layer" classification reported in previous versions has been eliminated in V4, and cloud–aerosol classification is now performed on all layers detected everywhere from the surface to 30 km. Cloud–aerosol classification has been further extended to layers detected at single-shot resolution, which were previously classified by default as clouds. In this paper, we describe the underlying rationale used in constructing the V4 PDFs and assess the performance of the V4 CAD algorithm in the troposphere and stratosphere. Previous misclassifications of lofted dust and smoke in the troposphere have been largely improved, and volcanic aerosol layers and aerosol layers in the stratosphere are now being properly classified. CAD performance for single-shot layer detections is also evaluated. Most of the single-shot layers classified as aerosol occur within the dust belt, as may be expected. Due to changes in the 532 nm calibration coefficients, the V4 feature finder detects ∼9.0 % more features at night and ∼2.5 % more during the day. These features are typically weakly scattering and classified about equally as clouds and aerosols. For those tropospheric layers detected in both V3 and V4, the CAD classifications of more than 95 % of all cloud and daytime aerosol layers remain unchanged, as do the classifications of ∼89 % of nighttime aerosol layers. Overall, the nighttime net cloud and aerosol fractions remain unchanged from V3 to V4, but the daytime net aerosol fraction is increased by about 2 % and the daytime net cloud fraction is decreased by about 2 %. [ABSTRACT FROM AUTHOR]

Radiometric calibration of space-based elastic backscatter lidars is accomplished by comparing the measured backscatter signals to theoretically expected signals computed for some well-characterized calibration target. For any given system and wavelength, the choice of calibration target is dictated by several considerations, including signal-to-noise ratio (SNR) and target availability. This paper describes the newly implemented procedures used to calibrate the 1064 nm measurements acquired by CALIOP (i.e., the Cloud-Aerosol Lidar with Orthogonal Polarization), the two-wavelength (532 and 1064 nm) elastic backscatter lidar currently flying on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission. CALIOP's 532 nm channel is accurately calibrated by normalizing the molecular backscatter from the uppermost aerosol-free altitudes of the CALIOP measurement region to molecular model data obtained from NASA's Global Modeling and Assimilation Office. However, because CALIOP's SNR for molecular backscatter measurements is prohibitively lower at 1064 nm than at 532 nm, the direct high-altitude molecular normalization method is not a viable option at 1064 nm. Instead, CALIOP's 1064 nm channel is calibrated relative to the 532 nm channel using the backscatter from a carefully selected subset of cirrus cloud measurements. In this paper we deliver a full account of the revised 1064 nm calibration algorithms implemented for the version 4.1 (V4) release of the CALIPSO lidar data products, with particular emphases on the physical basis for the selection of "calibration quality" cirrus clouds and on the new averaging scheme required to characterize intra-orbit calibration variability. The V4 procedures introduce latitudinally varying changes in the 1064 nm calibration coefficients of 25 % or more, relative to previous data releases, and are shown to substantially improve the accuracy of the V4 1064 nm attenuated backscatter coefficients. By evaluating calibration coefficients derived using both water clouds and ocean surfaces as alternate calibration targets, and through comparisons to independent, collocated measurements made by airborne high spectral resolution lidar, we conclude that the CALIOP V4 1064 nm calibration coefficients are accurate to within 3 %. [ABSTRACT FROM AUTHOR]

Data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the Level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP's other radiometric calibration procedures - i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime - depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30-34 km to the upper possible signal acquisition range of 36-39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. Additionally, an enhanced strategy for filtering the radiation-induced noise from high-energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), model. An aerosol scattering ratio of 1:01±0:01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2-3% lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) are reduced from 3:6%±2:2%in the version 3 data set to 1:6%±2:4% in the version 4 release. [ABSTRACT FROM AUTHOR]

Abstract: We advance a novel retrieval technique that combines a Raman and multi-wavelength elastic backscattered signals to retrieve multi-wavelength lidar ratio profiles of aerosol. With profile of backscatter coefficients at 355 nm retrieved from elastic backscatter signal at 355 nm and Raman scattering signal at 387 nm, lidar ratio profiles can be calculated at 532 nm and 1064 nm from the elastic backscatter signals at these wavelengths, taking advantage that the 532 nm/355 nm and 1064 nm/355 nm backscatter ratios are generally approximately equal for two neighboring range bins. This technique has been tested using numerical simulations and applied to lidar measurements at the Hampton University, Hampton, Virginia. [Copyright &y& Elsevier]

Abstract: The CALIPSO satellite mission consistently measures volume (including molecule and particulate) light depolarization ratio of ∼2% for smoke, compared to ∼1% for marine aerosols and ∼15% for dust. The observed ∼2% smoke depolarization ratio comes primarily from the nonspherical habits of particles in the smoke at certain particle sizes. In this study, the depolarization of linearly polarized light by small sphere aggregates and irregular Gaussian-shaped particles is studied, to reveal the physics between the depolarization of linearly polarized light and smoke aerosol shape and size. It is found that the depolarization ratio curves of Gaussian-deformed spheres are very similar to sphere aggregates in terms of scattering-angle dependence and particle size parameters when particle size parameter is smaller than 1.0π. This demonstrates that small randomly oriented nonspherical particles have some common depolarization properties as functions of scattering angle and size parameter. This may be very useful information for characterization and active remote sensing of smoke particles using polarized light. We also show that the depolarization ratio from the CALIPSO measurements could be used to derive smoke aerosol particle size. From the calculation results for light depolarization ratio by Gaussian-shaped smoke particles and the CALIPSO-measured light depolarization ratio of ∼2% for smoke, the mean particle size of South-African smoke is estimated to be about half of the 532nm wavelength of the CALIPSO lidar. [Copyright &y& Elsevier]

Abstract: Lidar ratio (i.e., extinction-to-backscatter ratio) is a key parameter required for retrieving extinction profiles and optical depths from elastic backscatter lidar measurements, and the quality of any extinction retrieval depends critically on the accuracy of the assumed or measured lidar ratio. In this study, we analyze the first two and a half years of the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) data acquired during nighttime. Distributions of the effective lidar ratio (ELR), which is the product of the lidar ratio and an instrument-dependent multiple scattering factor, are derived for opaque dust layers observed by CALIOP over the North Africa. The median and mean ELR values are, respectively, 36.4 and 38.5sr at 532nm and 47.7 and 50.3sr at 1064nm. For these opaque dust layers, the derived ELR decreases as the volume depolarization ratio (VDR) increases, reflecting the impact of multiple scattering within the dense layers. The particulate depolarization ratio is typically ∼0.3 at 532nm for African dust observed by CALIOP. This ratio can increase to ∼0.4 in the presence of significant multiple scattering. Correspondingly, the calculated ELR will decrease to ∼20sr at 532nm and to ∼30sr at 1064nm. The median and mean effective lidar ratio values approach, respectively, to 38 and 40sr at 532nm and 52 and 55sr at 1064nm for smaller VDR values measured in less dense layers where the multiple scattering is relatively insignificant. These values are very close to those derived in previous case studies for moderately dense dust. Case studies are also performed to examine the impacts of multiple scattering. The results obtained are generally consistent with Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission was launched in April 2006 and has continuously acquired collocated multisensor observations of the spatial and optical properties of clouds and aerosols in the earth’s atmosphere. The primary payload aboard CALIPSO is the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), which makes range-resolved measurements of elastic backscatter at 532 and 1064 nm and linear depolarization ratios at 532 nm. CALIOP measurements are important in reducing uncertainties that currently limit understanding of the global climate system, and it is essential that these measurements be accurately calibrated. This work describes the procedures used to calibrate the 532-nm measurements acquired during the nighttime portions of the CALIPSO orbits. Accurate nighttime calibration of the 532-nm parallel-channel data is fundamental to the success of the CALIOP measurement scheme, because the nighttime calibration is used to infer calibration across the day side of the orbits and all other channels are calibrated relative to the 532-nm parallel channel. The theoretical basis of the molecular normalization technique as applied to space-based lidar measurements is reviewed, and a comprehensive overview of the calibration algorithm implementation is provided. Also included is a description of a data filtering procedure that detects and removes spurious high-energy events that would otherwise introduce large errors into the calibration. Error estimates are derived and comparisons are made to validation data acquired by the NASA airborne high–spectral resolution lidar. Similar analyses are also presented for the 532-nm perpendicular-channel calibration technique. [ABSTRACT FROM AUTHOR]

Abstract: CALIPSO aerosol backscatter enhancement in the transition zone between clouds and clear sky areas is revisited with particular attention to effects of data selection based on the confidence level of cloud–aerosol discrimination (CAD). The results show that backscatter behavior in the transition zone strongly depends on the CAD confidence level. Higher confidence level data has a flatter backscatter far away from clouds and a much sharper increase near clouds (within 4km), thus a smaller transition zone. For high confidence level data it is shown that the overall backscatter enhancement is more pronounced for small clear-air segments and horizontally larger clouds. The results suggest that data selection based on CAD reduces the possible effects of cloud contamination when studying aerosol properties in the vicinity of clouds. [Copyright &y& Elsevier]

Abstract: Quantifying above-cloud aerosol can help improve the assessment of aerosol intercontinental transport and climate impacts. In this study we conduct an integrated analysis of aerosols above clouds by using multi-sensor A-Train measurements, including above-cloud aerosol optical depth at 532nm (AOD532) from CALIPSO lidar, the UV aerosol index (AI) from OMI, and cloud fraction and cloud optical depth (COD) from MODIS. The analysis of Saharan dust outflow and Southwest African smoke outflow regions shows that the above-cloud AOD correlates positively with AI in an approximately linear manner, and that the AOD532/AI ratio decreases with increasing COD. The dependence of AOD532/AI ratio on COD doesn''t depend on aerosol type when potential biases in the CALIOP AOD measurements are empirically accounted for. Our results may suggest the potential of combining OMI AI and MODIS cloud measurements to empirically derive above-cloud AOD with a spatial coverage much more extensive than CALIPSO measurements, which needs to be further explored in the future. [Copyright &y& Elsevier]