Airborne High Spectral Resolution Lidar Research Articles

Boundary Layer Structures Over the Northwest Atlantic Derived From Airborne High Spectral Resolution Lidar and Dropsonde Measurements During the ACTIVATE Campaign

AbstractThe Planetary Boundary Layer height (PBLH) is essential for studying PBL and ocean‐atmosphere interactions. Marine PBL is usually defined to include a mixed layer (ML) and a capping inversion layer. The ML height (MLH) estimated from the measurements of aerosol backscatter by a lidar was usually compared with PBLH determined from radiosondes/dropsondes in the past, as the PBLH is usually similar to MLH in nature. However, PBLH can be much greater than MLH for decoupled PBL. Here we evaluate the retrieved MLH from an airborne lidar (HSRL‐2) by utilizing 506 co‐located dropsondes during the ACTIVATE field campaign over the Northwest Atlantic from 2020 to 2022. First, we define and determine the MLH and PBLH from the temperature and humidity profiles of each dropsonde, and find that the MLH values from HSRL‐2 and dropsondes agree well with each other, with a coefficient of determination of 0.66 and median difference of 18 m. In contrast, the HSRL‐2 MLH data do not correspond to dropsonde‐derived PBLH, with a median difference of −47 m. Therefore, we modify the current operational and automated HSRL‐2 wavelet‐based algorithm for PBLH retrieval, decreasing the median difference significantly to −8 m. Further data analysis indicates that these conclusions remain the same for cases with higher or lower cloud fractions, and for decoupled PBLs. These results demonstrate the potential of using HSRL‐2 aerosol backscatter data to estimate both marine MLH and PBLH and suggest that lidar‐derived MLH should be compared with radiosonde/dropsonde‐determined MLH (not PBLH) in general.

Assessing the utility of high spectral resolution lidar for measuring particulate backscatter in the ocean and evaluating satellite ocean color retrievals

Airborne high spectral resolution lidar (HSRL) measurements of ocean particulate backscatter (bbp) offer dramatic improvements in spatiotemporal coverage over in situ techniques, filling observational “blind spots” that limit our ability to study ocean processes. However, the technique has been assessed in only a few limited cases, and uncertainties remain regarding its applicability across a diversity of optical domains. In this study, we present the first comprehensive comparison of bbp derived from airborne HSRL, satellite ocean color, and in situ measurements to increase confidence in HSRL bbp retrievals and to demonstrate the value of airborne HSRL for assessing/improving satellite ocean color algorithms. Retrievals of bbp performed using the NASA Langley HSRL-1 instrument agreed with in situ measurements performed across a diversity of optical and ecological domains. Comparisons across multiple campaigns revealed regional and seasonal dependencies in the ocean color retrievals that likely resulted from applying a single configuration of the ocean color retrieval across multiple distinct domains. In two case studies, atmospheric measurements from HSRL-1 and systematic differences in bbp between HSRL and the 2018 NASA ocean color distribution provided evidence of insufficient atmospheric correction of the ocean color retrieval. These differences in bbp were absent from comparisons against the 2022 ocean color distribution, suggesting that changes made to the algorithm resulted in improved retrievals. These cases highlight the advantages of airborne HSRL for assessing and improving ocean color retrievals, namely its ability to provide simultaneous, independent profiles of atmosphere and ocean optical properties, and improvements in the spatiotemporal coverage of satellite matchups.

Evaluating WRF-GC v2.0 predictions of boundary layer height and vertical ozone profile during the 2021 TRACER-AQ campaign in Houston, Texas

Abstract. The TRacking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ) campaign probed Houston air quality with a comprehensive suite of ground-based and airborne remote sensing measurements during the intensive operating period in September 2021. Two post-frontal high-ozone episodes (6–11 and 23–26 September) were recorded during the aforementioned period. In this study, we evaluated the simulation of the planetary boundary layer (PBL) height and the vertical ozone profile by a high-resolution (1.33 km) 3-D photochemical model, the Weather Research and Forecasting (WRF)-driven GEOS-Chem (WRF-GC). We evaluated the PBL heights with a ceilometer at the coastal site La Porte and the airborne High Spectral Resolution Lidar 2 (HSRL-2) flying over urban Houston and adjacent waters. Compared with the ceilometer at La Porte, the model captures the diurnal variations in the PBL heights with a very strong temporal correlation (R>0.7) and ±20 % biases. Compared with the airborne HSRL-2, the model exhibits a moderate to strong spatial correlation (R=0.26–0.68), with ±20 % biases during the noon and afternoon hours during ozone episodes. For land–water differences in PBL heights, the water has shallower PBL heights compared to land. The model predicts larger land–water differences than the observations because the model consistently underestimates the PBL heights over land compared to water. We evaluated vertical ozone distributions by comparing the model against vertical measurements from the TROPospheric OZone lidar (TROPOZ), the HSRL-2, and ozonesondes, as well as surface measurements at La Porte from a model 49i ozone analyzer and one Continuous Ambient Monitoring Station (CAMS). The model underestimates free-tropospheric ozone (2–3 km aloft) by 9 %–22 % but overestimates near-ground ozone (<50 m aloft) by 6 %-39 % during the two ozone episodes. Boundary layer ozone (0.5–1 km aloft) is underestimated by 1 %–11 % during 8–11 September but overestimated by 0 %–7 % during 23–26 September. Based on these evaluations, we identified two model limitations, namely the single-layer PBL representation and the free-tropospheric ozone underestimation. These limitations have implications for the predictivity of ozone's vertical mixing and distribution in other models.

Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic

Abstract. 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 (S) 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 the Weather Research and Forecasting Model coupled with physics packages from the Community Atmosphere Model version 5 (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.

Vertical structure of biomass burning aerosol transported over the southeast Atlantic Ocean

Abstract. Biomass burning in southwestern Africa produces smoke plumes that are transported over the Atlantic Ocean and overlie vast regions of stratocumulus clouds. This aerosol layer contributes to direct and indirect radiative forcing of the atmosphere in this region particularly during the months of August, September, and October. There was a multi-year international campaign to study this aerosol and its interactions with clouds. Here, we report on the evolution of aerosol distributions and properties as measured by the airborne high spectral resolution lidar (HSRL-2) during the ORACLES (Observations of Aerosols above Clouds and their intEractionS) campaign in September 2016. The NASA Langley HSRL-2 instrument was flown on the NASA ER-2 aircraft for several days in September 2016. Data were aggregated at two pairs of 2∘ × 2∘ grid boxes to examine the evolution of the vertical profile of aerosol properties during transport over the ocean. Results showed that the structure of the profile of aerosol extinction and microphysical properties is maintained over a 1 to 2 d timescale. In the 3–5 km altitude range, 95 % of the aerosol extinction was contributed by particles in the 0.05–0.50 µm radius size range with the aerosol in this size range having an average effective radius of 0.16 µm. This indicates that there is essentially no scavenging or dry deposition at these altitudes. Moreover, there is very little day-to-day variation in these properties, such that time sampling as happens in such campaigns may be representative of longer periods such as monthly means. Below 3 km, there is considerable mixing with larger aerosol, most likely continental source near land. Furthermore, these measurements indicated that there was often a distinct gap between the bottom of the aerosol layer and cloud tops at the selected locations as evidenced by a layer of several hundred meters that contained relatively low aerosol extinction values above the clouds.

Lidar Ratio-Depolarization Ratio Relations of Atmospheric Dust Aerosols: The Super-Spheroid Model and High Spectral Resolution Lidar Observations.

The backscattering optical properties of an ensemble of randomly oriented dust particles at a wavelength of 355 nm were comprehensively studied by examining the invariant imbedding T‐matrix results of the super‐spheroid dust model. In particular, we focused on the lidar ratio (S) and depolarization ratio (δ) relations of dust aerosols to aid interpretation of data from the Atmospheric Lidar (ATLID) instrument that will be onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite. Super‐spheroid models with various aspect ratios (α), roundness parameters (n), and refractive indices were investigated over a wide range of particle sizes and compared to the observation data of the National Aeronautics and Space Administration (NASA) Langley 355‐nm airborne high spectral resolution lidar. We found that super‐spheroid dust particles with different sets of n and α could be used to model almost the entire range of the observed joint distributions of S and δ. The S−δ relation could effectively discriminate among dust particle types. The observed S and δ values with the largest population density were best covered by models with n > 2, especially by those with n varying from 2.4 to 3.0.

Synergistic aircraft and ground observations of transported wildfire smoke and its impact on air quality in New York City during the summer 2018 LISTOS campaign

Air pollution associated with wildfire smoke transport during the summer can significantly affect ozone (O3) and particulate matter (PM) concentrations, even in heavily populated areas like New York City (NYC). Here, we use observations from aircraft, ground-based lidar, in-situ analyzers and satellite to study and assess wildfire smoke transport, vertical distribution, optical properties, and potential impact on air quality in the NYC urban and coastal areas during the summer 2018 Long Island Sound Tropospheric Ozone Study (LISTOS). We investigate an episode of dense smoke transported and mixed into the planetary boundary layer (PBL) on August 15–17, 2018. The horizontal advection of the smoke is shown to be characterized with the prevailing northwest winds in the PBL (velocity > 10 m/s) based on Doppler wind lidar measurements. The wildfire sources and smoke transport paths from the northwest US/Canada to northeast US are identified from the NOAA hazard mapping system (HMS) fires and smoke product and NOAA-HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory analysis. The smoke particles are distinguished from the urban aerosols by showing larger lidar-ratio (70-sr at 532-nm) and smaller depolarization ratio (0.02) at 1064-nm using the NASA High Altitude Lidar Observatory (HALO) airborne high-spectral resolution lidar (HSRL) measurements. The extinction-related angstrom exponents in the near-infrared (IR at 1020–1640 nm) and Ultraviolet (UV at 340–440 nm) from NASA-Aerosol Robotic Network (AERONET) product show a reverse variation trend along the smoke loadings, and their absolute differences indicate strong correlation with the smoke-Aerosol Optical Depth (AOD) (R > 0.94). We show that the aloft smoke plumes can contribute as much as 60–70% to the column AOD and that concurrent high-loadings of O3, carbon monoxide (CO), and black carbon (BC) were found in the elevated smoke layers from the University of Maryland (UMD) aircraft in-situ observations. Meanwhile, the surface PM2.5 (PM with diameter ≤ 2.5 μm), organic carbon (OC) and CO measurements show coincident and sharp increase (e.g., PM2.5 from 5 μg/m3 before the plume intrusion to ~30 μg/m3) with the onset of the plume intrusions into the PBL along with hourly O3 exceedances in the NYC region. We further evaluate the NOAA-National Air Quality Forecasting Capability (NAQFC) model PBL-height, PM2.5, and O3 with the observations and demonstrate good consistency near the ground during the convective PBL period, but significant bias at other times. The aloft smoke layers are sometimes missed by the model.

Study on Airborne High Spectral Resolution Lidar Detecting Optical properties and Pollution of Atmospheric Aerosol

Study on Airborne High Spectral Resolution Lidar Detecting Optical properties and Pollution of Atmospheric Aerosol

EARLINET observations of Saharan dust intrusions over the northern Mediterranean region (2014–2017): properties and impact on radiative forcing

Abstract. Remote sensing measurements of aerosols using depolarization Raman lidar systems from four EARLINET (European Aerosol Research Lidar Network) stations are used for a comprehensive analysis of Saharan dust events over the Mediterranean basin in the period 2014–2017. In this period, 51 dust events regarding the geometrical, optical and microphysical properties of dust were selected, classified and assessed according to their radiative forcing effect on the atmosphere. From west to east, the stations of Granada, Potenza, Athens and Limassol were selected as representative Mediterranean cities regularly affected by Saharan dust intrusions. Emphasis was given on lidar measurements in the visible (532 nm) and specifically on the consistency of the particle linear depolarization ratio (δp532), the extinction-to-backscatter lidar ratio (LR532) and the aerosol optical thickness (AOT532) within the observed dust layers. We found mean δp532 values of 0.24±0.05, 0.26±0.06, 0.28±0.05 and 0.28±0.04, mean LR532 values of 52±8, 51±9, 52±9 and 49±6 sr and mean AOT532 values of 0.40±0.31, 0.11±0.07, 0.12±0.10 and 0.32±0.17, for Granada, Potenza, Athens and Limassol, respectively. The mean layer thickness values were found to range from ∼ 1700 to ∼ 3400 m a.s.l. Additionally, based also on a previous aerosol type classification scheme provided by airborne High Spectral Resolution Lidar (HSRL) observations and on air mass backward trajectory analysis, a clustering analysis was performed in order to identify the mixing state of the dusty layers over the studied area. Furthermore, a synergy of lidar measurements and modeling was used to analyze the solar and thermal radiative forcing of airborne dust in detail. In total, a cooling behavior in the solar range and a significantly lower heating behavior in the thermal range was estimated. Depending on the dust optical and geometrical properties, the load intensity and the solar zenith angle (SZA), the estimated solar radiative forcing values range from −59 to −22 W m−2 at the surface and from −24 to −1 W m−2 at the top of the atmosphere (TOA). Similarly, in the thermal spectral range these values range from +2 to +4 W m−2 for the surface and from +1 to +3 W m−2 for the TOA. Finally, the radiative forcing seems to be inversely proportional to the dust mixing ratio, since higher absolute values are estimated for less mixed dust layers.

New attenuated backscatter profile by removing the CALIOP receiver's transient response

The photomultiplier tubes (PMTs) used to measure altitude-resolved 532 nm backscatter intensity by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) do not recover rapidly following exposure to very high light levels (e.g., from optically dense water clouds). Instead, they exhibit exponentially decaying “noise tails” that can cause substantial misestimates when determining layer base altitudes and deriving cloud extinction coefficients. Here we present a deconvolution correction algorithm to remove these noise tails in the CALIOP level 1 science data products. The corrected 532 nm attenuated backscatter profiles generated by the deconvolution algorithm are evaluated using the corresponding CALIOP observations at 1064 nm and coincident profiles measured at 532 nm by the NASA-Langley airborne high spectral resolution lidar. Results indicate that our deconvolution correction algorithm effectively removes the non-ideal PMT recovery effects on the CALIOP level 1 vertical profiles, showing excellent performance for surface and water cloud lidar returns when the attenuated backscatter coefficients are greater than 0.01 km−1 sr−1.

Validation of an airborne high spectral resolution Lidar and its measurement for aerosol optical properties over Qinhuangdao, China.

Compared with ground-based lidar, airborne lidar has a wider observation area, which is useful for studying aerosol distribution and transportation. A dual-wavelength high spectral resolution Lidar (HSRL) was developed for the validation and calibration of an upcoming satellite payload. The HSRL was installed on an airplane, and field campaigns were conducted in Qinhuangdao, China. Meanwhile, four observation sites were established at different locations on the ground to verify the results of the airborne lidar. This article compares the HSRL measurements with those from ground-based micro-pulse lidar (MPL), Mie-scattering lidar, sun photometer, and spaceborne cloud-aerosol Lidar and infrared pathfinder satellite observations (CALIPSO), and Moderate Resolution Imaging Spectroradiometer (MODIS). The stability and reliability of the HSRL system were fully verified. The flight area covered several surface types, including ocean, town, mountain, and forest, which strongly affect the AOD above them. The boundary layer AOD was analyzed in different regions, based on the impact of human activities. The results demonstrated that the AOD in urban area was the largest, and smallest in marine areas, a result ascribed to the influence of industrial activities.

Shifts in Phytoplankton Community Structure Across an Anticyclonic Eddy Revealed From High Spectral Resolution Lidar Scattering Measurements

Changes in airborne high spectral resolution lidar (HSRL) measurements of scattering, depolarization, and attenuation coincided with a shift in phytoplankton community composition across an anticyclonic eddy in the North Atlantic. We normalized the total depolarization ratio (delta) by the particulate backscattering coefficient (b(b)(p)) to account for the covariance in delta and b(b)(p) that has been attributed to multiple scattering. A 15% increase in delta/b(b)(p) inside the eddy coincided with decreased phytoplankton biomass and a shift to smaller and more elongated phytoplankton cells. Taxonomic changes (reduced dinoflagellate relative abundance inside the eddy) were also observed. The delta signal is thus potentially most sensitive to changes in phytoplankton shape because neither the observed change in the particle size distribution (PSD) nor refractive index (assuming average refractive indices) are consistent with previous theoretical modeling results. We additionally calculated chlorophyll-a (Chl) concentrations from measurements of the diffuse light attenuation coefficient (K-d) and divided by b(b)(p) to evaluate another optical metric of phytoplankton community composition (Chl:b(bp)), which decreased by more than a factor of two inside the eddy. This case study demonstrates that the HSRL is able to detect changes in phytoplankton community composition. High spectral resolution lidar measurements reveal complex structures in both the vertical and horizontal distribution of phytoplankton in the mixed layer providing a valuable new tool to support other remote sensing techniques for studying mixed layer dynamics. Our results identify fronts at the periphery of mesoscale eddies as locations of abrupt changes in near-surface optical properties.

Saharan Dust Events Over the Northern Mediterranean: 4 Years of Measurements Over 4 Earlinet Stations

Four years (2014-2017) of observations of depolarization Raman Lidar systems of four EARLINET (European Aerosol research Lidar Network) stations [from West to East: Granada (Spain), Potenza (Italy), Athens (Greece) and Limassol (Cyprus)] were collected and used to a statistical analysis of Saharan dust events over Mediterranean basin. In this study, emphasis is given to the consistency of the particle linear depolarization ratio (δp532), the extinction-to-backscatter ratio mentioned as Lidar Ratio (LR532) and the Aerosol Optical Thickness (AOT532) within the observed Saharan dust layers, corresponding to the visible range (532 nm). Geometrical properties and clusters of aerosol mixtures are also presented. Our clustering was based on previous classification by airborne High Spectral Resolution Lidar (HSRL) observations and was further supported by backward trajectory analysis. We found mean δp532 values of 0.24±0.05, 0.26±0.06, 0.28±0.05 and 0.28±0.04, mean LR532 values of 52±8 sr, 51±9 sr, 52±9 sr and 49±6 sr, mean AOT532 values of 0.40±0.31, 0.11±0.07, 0.12±0.10 and 0.32±0.17 and mean layer thicknesses of 3392±1458 m, 2150±1082 m, 1872±816 m and 1716±567 m for Granada, Potenza, Athens and Limassol respectively. This work could assist in bridging the existing gaps related to the extensive and intensive dust aerosol properties over the Mediterranean and enriching the bibliography about mixed aerosol layers from different sources (e.g. dust and biomass burning (BB) aerosols, dust and urban/ industrial aerosols).

Оценка достоверности мониторинга аэрозольных загрязнений в атмосфере путем сравнения результатов обработки данных лидарного зондирования и локального забора проб

Data measured with remote (lidar) sensing and in situ during ORACLES campaign in 2016 became publically accessible. Inversion of the data measured with lidar and including the aerosol backscatter coefficients at 355, 532 and 1064 nm and extinction coefficients at 355 and 532 nm is carried out in the study. Airborne high spectral resolution lidar was used in the measurements. Specially developed regularization algorithm is applied to invert the lidar data into aerosol optical and microphysical parameters. In frame of ORACLES campaign the aerosol optical and microphysical parameters were measured in situ as well. In situ and remote (lidar) measurements were spatially and temporarily co-located. In situ results are used to validate the inversion of lidar data with regularization algorithm. Uncertainties of 25% for effective radius, number and volume concentrations, 0.05 and 0.005 for real and imaginary parts of complex refractive index respectively and 0.05 for single scattering albedo are validated with reliability 90%.

CALIPSO lidar calibration at 1064 nm: version 4 algorithm

Abstract. 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 %.

CALIPSO lidar calibration at 532 nm: version 4 daytime algorithm

Abstract. The Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission released version 4.00 of their lidar level 1 data set in April of 2014, and subsequently updated this to version 4.10 in November of 2016. The primary difference in the newly released version 4 (V4) data is a suite of updated calibration coefficients calculated using substantially revised calibration algorithms. This paper describes the revisions to the V4 daytime calibration procedure for the 532 nm parallel channel. As in earlier releases, the V4 daytime calibration coefficients are derived by scaling the raw daytime signals to the calibrated nighttime signals acquired within a calibration transfer region, and thus the new V4 daytime calibration benefits from improvements made to the V4 532 nm nighttime calibration. The V4 calibration transfer region has been moved upward from the upper troposphere to the more stable lower stratosphere. The identification of clear-air columns by an iterative thresholding scheme, crucial to selecting the observation regions used for calibration, now uses uncalibrated 1064 nm data rather than recursively using the calibrated 532 nm data, as was done in version 3 (V3). A detailed account of the rationale and methodology for this new calibration approach is provided, along with results demonstrating the improvement of this calibration over the previous version. Extensive validation data acquired by NASA's airborne high spectral resolution lidar (HSRL) shows that during the daytime the average difference between collocated CALIPSO and HSRL measurements of 532 nm attenuated backscatter coefficients is reduced from 3.3 %±3.1 % in V3 to 1.0 %±3.5 % in V4.

CALIPSO Lidar Calibration at 532 nm: Version 4 Nighttime Algorithm.

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 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. As well, 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 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.

Creating Aerosol Types from CHemistry (CATCH): A New Algorithm to Extend the Link Between Remote Sensing and Models

AbstractCurrent remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH‐derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first‐generation airborne High Spectral Resolution Lidar (HSRL‐1) retrievals during the Ship‐Aircraft Bio‐Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH‐derived aerosol types are determined by multivariate clustering of model‐calculated variables that have been trained using retrievals of aerosol types from HSRL‐1. CATCH‐derived aerosol types (with the exception of smoke) compare well with HSRL‐1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System‐ with Chemistry (GEOS‐Chem) model. Spatial distributions of CATCH‐derived aerosol types for the North American model domain during July/August 2014 show that aerosol type‐specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model‐generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL‐1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

Vertically- resolved phytoplankton carbon and net primary production from a high spectral resolution lidar.

Passive ocean observing sensors are unable to detect subsurface structure in ocean properties, resulting in errors in water column integrated phytoplankton biomass and net primary production (NPP) estimates. Active lidar (light detection and ranging) sensors make quantitative measurements of depth-resolved backscatter (bbp) and diffuse light attenuation (Kd) coefficients in the ocean and can provide critical measurements for biogeochemical models. Sub-surface phytoplankton biomass, light, chlorophyll, and NPP fields were characterized using both in situ measurements and coincident airborne high spectral resolution lidar (HSRL-1) measurements collected as part of the SABOR (Ship-Aircraft Bio-Optical Research) field campaign. We found that depth-resolved data are critical for calculating phytoplankton stocks and NPP, with improvements in NPP estimates up to 54%. We observed strong correlations between coincident HSRL-1 and in situ IOP measurements of both bbp (r = 0.94) and Kd (r = 0.90).

Aerosol Retrievals from CALIPSO Lidar Ocean Surface Returns

This paper describes approaches to retrieve important aerosol results from the strong lidar return signals that are received by the space-borne CALIPSO lidar system after reflecting off-ocean surfaces. Relations, from which the theoretically expected values of area under ocean surface returns can be computed, are presented. A detailed description of the lidar system response to the ocean surface returns and the processes of sampling and averaging of lidar return signals are provided. An effective technique that reconstructs the lidar response to surface returns—starting from down-linked samples—and calculates the area under it, has been developed and described. The calculated area values are validated after comparing them to their theoretically predicted counterpart values. Methods to retrieve aerosol optical depths (AODs) from these calculated areas are described and retrieval results are presented, including retrieval comparison with independent AOD measurements made by an airborne High Spectral Resolution Lidar (HSRL) that yielded quite good agreement. Techniques and results are also presented on using the spectral ratios of the surface response areas to determine spectral ratios of aerosol round-trip transmission and AOD spectral difference, without need of a specific/accurate ocean-surface reflectance model.