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NASA NTRS2015

Evaluation of CALIOP 532-nm Aerosol Optical Depth Over Opaque Water Clouds

With its height-resolved measurements and near global coverage, the CALIOP lidar onboard the CALIPSO satellite offers a new capability for aerosol retrievals in cloudy skies. Validation of these retrievals is difficult, however, as independent, collocated and co-temporal data sets are generally not available. In this paper, we evaluate CALIOP aerosol products above opaque water clouds by applying multiple retrieval techniques to CALIOP Level 1 profile data and comparing the results. This approach allows us to both characterize the accuracy of the CALIOP above-cloud aerosol optical depth (AOD) and develop an error budget that quantifies the relative contributions of different error sources. We focus on two spatial domains: the African dust transport pathway over the tropical North Atlantic and the African smoke transport pathway over the southeastern Atlantic. Six years of CALIOP observations (2007-2012) from the northern hemisphere summer and early fall are analyzed. The analysis is limited to cases where aerosol layers are located above opaque water clouds so that a constrained retrieval technique can be used to directly retrieve 532 nm aerosol optical depth and lidar ratio. For the moderately dense Sahara dust layers detected in the CALIOP data used in this study, the mean/median values of the lidar ratios derived from a constrained opaque water cloud (OWC) technique are 45.1/44.4 +/- 8.8 sr, which are somewhat larger than the value of 40 +/- 20 sr used in the CALIOP Level 2 (L2) data products. Comparisons of CALIOP L2 AOD with the OWC-retrieved AOD reveal that for nighttime conditions the L2 AOD in the dust region is underestimated on average by approx. 26% (0.183 vs. 0.247). Examination of the error sources indicates that errors in the L2 dust AOD are primarily due to using a lidar ratio that is somewhat too small. The mean/median lidar ratio retrieved for smoke is 70.8/70.4 +/- 16.2 sr, which is consistent with the modeled value of 70 +/- 28 sr used in the CALIOP L2 retrieval. Smoke AOD is found to be underestimated, on average, by approx. 39% (0.191 vs. 0.311). The primary cause of AOD differences in the smoke transport region is the tendency of the CALIOP layer detection scheme to prematurely assign layer base altitudes and thus underestimate the geometric thickness of smoke layers.

Liu, Z.↗
NASA NTRS2012

Evaluating Nighttime CALIOP 0.532 micron Aerosol Optical Depth and Extinction Coefficient Retrievals

NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 micron aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1 deg X 1 deg resolution versus corresponding/co-incident 0.550 micron AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 micron extinction coefficient are compared with 0.523/0.532 micron ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1 deg. X 1 deg. bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach +/- 20 %. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.

aerosol optical depth↗
NASA NTRS2015

Resolving Ice Cloud Optical Thickness Biases Between CALIOP and MODIS Using Infrared Retrievals

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g approx. = 0.75 in the mid-visible spectrum, 5-15% smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products.This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28%), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Cloud↗
NASA NTRS2014

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

CALIOP and MODIS↗
NASA NTRSDate not supplied

Improvements in CALIOP Smoke Optical Depth over Clouds

Smoke over marine stratocumulus is ubiquitous off the south west coast of Africa during biomass burning season. The vertical profile measurements provided by the CALIOP lidar are successfully able to distinguish between smoke and underlying clouds. With over 14 years of observations, the CALIOP data set is a valuable asset for quantifying the radiative impact of smoke over clouds in this region. However past studies have shown that CALIOP overestimates the base altitudes of strongly attenuating smoke layers. This is because CALIOP layer detection operates on the 532 nm attenuated backscatter signal. Smoke strongly attenuates light at this wavelength, so CALIOP feature detection at times assigns a base altitude that is higher than the true layer base for optically thick layers. This can be confirmed by the 1064 nm attenuated backscatter signal, also measured by CALIOP. In order to improve the AOD for smoke over clouds, a new algorithm has been implemented in for an upcoming CALIOP level 2 data release that will extend the base altitudes of smoke layers over clouds. Tunable restrictions are put in place to ensure that smoke bases are only extended within a reasonable smoke-to-cloud gap distance and only when there is strong reason to believe that smoke exists within the gap. This presentation will summarize the new smoke base extension algorithm and summarize its performance. We will demonstrate that base extension is primarily invoked off the south west coast of Africa as expected. We will also quantify the increase in smoke AOD that will be reported in the upcoming level 2 data release.

Jason L Tackett↗
NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global CCMs where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AtmOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) chemistry-climate model through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗
NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global chemistry-climate models (CCMs) where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) CCM through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗
NASA NTRS2013

CALIOP and AERONET Aerosol Optical Depth Comparisons: One Size Fits None

We compare the aerosol optical depths (AOD) retrieved from backscatter measurements of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite with coincident Aerosol Robotic Network (AERONET) measurements. Overpass coincidence criteria of +/- 2 h and within a 40 km radius are satisfied at least once at 149 globally distributed AERONET sites from 2006 to 2010. Most data pairs (>80%) use AERONET measurements acquired +/- 30 min of the overpass. We examine the differences in AOD estimates between CALIOP and AERONET for various aerosol, environmental, and geographic conditions. Results show CALIOP AOD are lower than AERONET AOD especially at low optical depths as measured by AERONET (500 nm AOD<0.1). Furthermore, the median relative AOD difference between the two measurements is 25% of the AERONET AOD for AOD>0.1. Differences in AOD between CALIOP and AERONET are possibly due to cloud contamination, scene inhomogeneity, instrument view angle differences, CALIOP retrieval errors, and detection limits. Comparison of daytime to nighttime number of 5 km 60m (60m in the vertical) features detected by CALIOP show that there are 20% more aerosol features at night. We find that CALIPSO and AERONET do not agree on the cloudiness of scenes. Of the scenes that meet the above coincidence criteria, CALIPSO finds clouds in more than 45% of the coincident atmospheric columns AERONET classifies as clear.

Omar, A. H.↗
NASA NTRS2012

Characterizing the Vertical Profile of Aerosol Particle Extinction and Linear Depolarization over Southeast Asia and the Maritime Continent: The 2007-2009 View from CALIOP

Vertical profiles of 0.532 μm aerosol particle extinction coefficient and linear volume depolarization ratio are described for Southeast Asia and the Maritime Continent. Quality-screened and cloud-cleared Version 3.01 Level 2 NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) 5-km Aerosol Profile datasets are analyzed from 2007 to 2009. Numerical simulations from the U.S. Naval Aerosol Analysis and Predictive System (NAAPS), featuring two-dimensional variational assimilation of NASA Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging Spectro- Radiometer quality-assured datasets, combined with regional ground-based lidar measurements, are considered for assessing CALIOP retrieval performance, identifying bias, and evaluating regional representativeness. CALIOP retrievals of aerosol particle extinction coefficient and aerosol optical depth (AOD) are high over land and low over open waters relative to NAAPS (0.412/0.312 over land for all data points inclusive, 0.310/0.235 when the per bin average is used and each is treated as single data points; 0.102/0.151 and 0.086/0.124, respectively, over ocean). Regional means, however, are very similar (0.180/0.193 for all data points and 0.155/0.159 when averaged per normalized bin), as the two factors offset one another. The land/ocean offset is investigated, and discrepancies attributed to interpretation of particle composition and a-priori assignment of the extinction-to-backscatter ratio ("lidar ratio") necessary for retrieving the extinction coefficient from CALIOP signals. Over land, NAAPS indicates more dust present than CALIOP algorithms are identifying, indicating a likely assignment of a higher lidar ratio representative of more absorptive particles. NAAPS resolvesmore smoke overwater than identified with CALIOP, indicating likely usage of a lidar ratio characteristic of less absorptive particles to be applied that biases low AOD there. Over open waters except within the Bay of Bengal, aerosol particle scattering is largely capped below 1.5 km MSL, though ground-based lidar measurements at Singapore differ slightly from this finding. Significant aerosol particle presence over land is similarly capped near 3.0 km MSL over most regions. Particle presence at low levels regionally, except over India, is dominated by relatively non-depolarizing particles. Industrial haze, sea salt droplets and fresh smoke are thus most likely present.

linear volume depolarization ratio↗
NASA NTRSDate not supplied

Airborne HSRL Assessment of CALIOP Aerosol Extinction Retrievals Constrained by Column AOD

Current operational CALIOP aerosol extinction profile retrievals usually rely on accurately specifying the relationship between aerosol extinction and backscattering (i.e. lidar ratio). Uncertainties in the assigned lidar ratios are typically the largest source of systematic error (~30-50%) in the CALIOP retrievals of aerosol extinction, backscatter, and aerosol optical depth. Alternatively, column aerosol optical depth (AOD) can be used to solve the lidar equation and obtain column-equivalent lidar ratios and retrieve aerosol extinction profiles from the CALIOP attenuated backscatter profiles. These derived lidar ratios correspond to the aerosols in the altitude range from 0-7 km. We derive column-equivalent aerosol lidar ratios and aerosol extinction profiles from CALIOP attenuated backscatter profiles constrained using co-located column AODs provided by several instruments/techniques: Synergized Optical Depth of Aerosols (SODA), Ocean-Derived Column Optical Depths (ODCOD), MODIS (dark target), MODIS (Multi-Angle Implementation of Atmospheric Correction-MAIAC), and PARASOL (Generalized Retrieval of Aerosol and Surface Properties-GRASP). These various retrievals of AOD and the column-average aerosol lidar ratios and aerosol extinction profiles derived from CALIOP using these AOD constraints are evaluated using the extensive record of coincident and co-located airborne HSRL measurements of AOD, aerosol lidar ratio, and aerosol extinction profiles acquired during more than 140 HSRL underflights of CALIPSO since 2006. The HSRL technique allows for the independent measurement of extinction and backscatter without the need for external constraints or assumptions regarding the lidar ratios. Initial comparisons with these coincident HSRL aerosol extinction profiles show that the CALIOP aerosol extinction profiles retrieved using these various AOD constraints are generally in better agreement with the HSRL measurements than aerosol extinction profiles from the operational techniques. The quality of agreement depends on the accuracy and magnitude of the AOD constraint. We present these comparisons of AOD, column aerosol lidar ratio, and aerosol extinction profiles for each of the AOD constraints described above.

lidar↗
NASA NTRS2022

Retrieving Particulate Matter Concentrations over the Contiguous United States Using CALIOP Observations

Using twelve years (2007-2018) of NASA Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) near-surface 532 nm aerosol extinction retrievals, multi-year mean and trends of particulate matter (PM) concentrations are derived over the contiguous United States (CONUS). Different from past studies that use column integrated aerosol optical thickness, here only near-surface CALIOP aerosol extinction is used for deriving near-surface PM with aerodynamic diameters less than 2.5 µm (PM2.5) concentrations using an innovative, bulk-mass-modeling-based method. Compared against ground based PM2.5 measurements from the U.S. Environmental Protection Agency (EPA), an encouraging relationship between CALIOP-derived PM2.5 and EPA-observed PM2.5 (Deming slope = 0.89; RMSE = 3.42 µg/m3; mean bias = -1.00 µg/m3) is found using combined daytime/nighttime CALIOP data. Also, comparable trends in PM2.5 concentrations from the EPA and daytime and nighttime CALIOP data are found for most of the eastern CONUS and imply that air quality is generally improving over this region for the study period. Over the western CONUS, a seasonal analysis reveals that PM2.5 trends are positive during the more active wildfire season (June through November) but negative for other months. This study suggests that lidar data show promise in their use for obtaining PM2.5 estimates and provides motivation to further explore aerosol extinction-based PM concentration retrievals in anticipation of future space-based lidar missions.

CALIOP↗
NASA NTRS2007

Initial Performance Assessment of CALIOP

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP, pronounced the same as "calliope") is a spaceborne two-wavelength polarizatio n lidar that has been acquiring global data since June 2006. CALIOP p rovides high resolution vertical profiles of clouds and aerosols, and has been designed with a very large linear dynamic range to encompas s the full range of signal returns from aerosols and clouds. CALIOP is the primary instrument carried by the Cloud-Aerosol Lidar and Infrar ed Pathfinder Satellite Observations (CALIPSO) satellite, which was l aunched on April, 28 2006. CALIPSO was developed within the framework of a collaboration between NASA and the French space agency, CNES. I nitial data analysis and validation intercomparisons indicate the qua lity of data from CALIOP meets or exceeds expectations. This paper presents a description of the CALIPSO mission, the CALIOP instrument, an d an initial assessment of on-orbit measurement performance.

Winker, David↗
NASA NTRS2012

Application of the CALIOP Layer Product to Evaluate the Vertical Distribution of Aerosols Estimated by Global Models: AeroCom Phase I Results

The CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) layer product is used for a multimodel evaluation of the vertical distribution of aerosols. Annual and seasonal aerosol extinction profiles are analyzed over 13 sub-continental regions representative of industrial, dust, and biomass burning pollution, from CALIOP 2007-2009 observations and from AeroCom (Aerosol Comparisons between Observations and Models) 2000 simulations. An extinction mean height diagnostic (Z-alpha) is defined to quantitatively assess the models' performance. It is calculated over the 0-6 km and 0-10 km altitude ranges by weighting the altitude of each 100 m altitude layer by its aerosol extinction coefficient. The mean extinction profiles derived from CALIOP layer products provide consistent regional and seasonal specificities and a low inter-annual variability. While the outputs from most models are significantly correlated with the observed Z-alpha climatologies, some do better than others, and 2 of the 12 models perform particularly well in all seasons. Over industrial and maritime regions, most models show higher Z-alpha than observed by CALIOP, whereas over the African and Chinese dust source regions, Z-alpha is underestimated during Northern Hemisphere Spring and Summer. The positive model bias in Z-alpha is mainly due to an overestimate of the extinction above 6 km. Potential CALIOP and model limitations, and methodological factors that might contribute to the differences are discussed.

Aerosols and particles↗
NASA NTRSDate not supplied

A Synopsis of the 8+ Year CALIOP Polar Stratospheric Cloud Data Record

Polar stratospheric clouds (PSCs) play a crucial role in the springtime chemical depletion of ozone at high latitudes. PSC particles (primarily supercooled ternary solution, or STS droplets) provide sites for heterogeneous chemical reactions that transform stable chlorine and bromine reservoir species into highly reactive ozone-destructive forms. Furthermore, large nitric acid trihydrate (NAT) PSC particles can irreversibly redistribute odd nitrogen through gravitational sedimentation (a process commonly known as denitrification), which prolongs the ozone depletion process by slowing the reformation of the stable chlorine reservoirs. Spaceborne observations from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite are providing a rich new dataset for studying PSCs. CALIPSO is an excellent platform for studying polar processes with CALIOP acquiring, on average, over 300,000 backscatter profiles daily at latitudes between 55o and 82o in both hemispheres. PSCs are detected in the CALIOP backscatter profiles using a successive horizontal averaging scheme that enables detection of strongly scattering PSCs (e.g., ice) at the finest possible spatial resolution (5 km), while enhancing the detection of very tenuous PSCs (e.g., low number density NAT) at larger spatial scales (up to 135 km). CALIOP PSCs are separated into composition classes (STS; liquid/NAT mixtures; and ice) based on the ensemble 532-nm scattering ratio (the ratio of total-to-molecular backscatter) and 532-nm particulate depolarization ratio (which is sensitive to the presence of non-spherical, i.e. NAT and ice particles). In this paper, we will provide an overview of the CALIOP PSC detection and composition classification algorithm and then examine the vertical and spatial distribution of PSCs in the Arctic and Antarctic on vortex-wide scales for entire PSC seasons over the more than eight-year data record.

Michael C Pitts↗
NASA NTRS2016

Shortwave Direct Radiative Effects of Above-Cloud Aerosols Over Global Oceans Derived From 8 Years of CALIOP and MODIS Observations

In this paper, we studied the frequency of occurrence and shortwave direct radiative effects (DREs) of above-cloud aerosols (ACAs) over global oceans using 8 years (2007-2014) of collocated CALIOP and MODIS observations. Similar to previous work, we found high ACA occurrence in four regions: southeastern (SE) Atlantic region, where ACAs are mostly light-absorbing aerosols, i.e., smoke and polluted dust according to CALIOP classification, originating from biomass burning over the African Savanna; tropical northeastern (TNE) Atlantic and the Arabian Sea, where ACAs are predominantly windblown dust from the Sahara and Arabian deserts, respectively; and the northwestern (NW) Pacific, where ACAs are mostly transported smoke and polluted dusts from Asia. From radiative transfer simulations based on CALIOP-MODIS observations and a set of the preselected aerosol optical models, we found the DREs of ACAs at the top of atmosphere (TOA) to be positive (i.e., warming) in the SE Atlantic and NW Pacific regions, but negative (i.e., cooling) in the TNE Atlantic Ocean and the Arabian Sea. The cancellation of positive and negative regional DREs results in a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m(exp. -2) [range of -0.03 to 0.06 W m (exp. -2)] at TOA. The DREs at surface and within the atmosphere are -0.015 W m(exp. -2) [range of -0.09 to -0.21 W m(exp. -2)], and 0.17 W m(exp. -2) [range of 0.11 to 0.24 W m(exp. -2)], respectively. The regional and seasonal mean DREs are much stronger. For example, in the SE Atlantic region, the JJA (July-August) seasonal mean cloudy-sky DRE is about 0.7 W m(exp. -2) [range of 0.2 to 1.2 W m(exp. -2)] at TOA. All our DRE computations are publicly available. The uncertainty in our DRE computations is mainly caused by the uncertainties in the aerosol optical properties, in particular aerosol absorption, the uncertainties in the CALIOP operational aerosol optical thickness retrieval, and the ignorance of cloud and potential aerosol diurnal cycle. In situ and remotely sensed measurements of ACA from future field campaigns and satellite missions and improved lidar retrieval algorithm, in particular vertical feature masking, would help reduce the uncertainty.

direct radiative effects↗
NASA NTRS2021

The Thermal Infrared Optical Depth of Mineral Dust Retrieved from Integrated CALIOP and IIR Observations

Recent studies reveal that a higher fraction of coarse mineral dust particles than that estimated by climate model simulations has been observed in the atmosphere, leading to a more significant positive (i.e., warming) longwave (LW) thermal infrared (TIR) direct radiative effect (DRE). However, the magnitude of this DRE remains highly uncertain because our understanding of the radiative properties, quantitatively represented by the optical depth of dust, especially information on the TIR, remains limited. This study presents a simple approach to retrieve the thermal infrared dust aerosol optical depth (DAODTIR) over oceans during nighttime using the observations from the Infrared Imaging Radiometer (IIR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO. For each cloud-free dust-laden profile identified by the IIR-CALIOP observation, a Lookup-Table (LUT) of the 10.6 μm IIR band brightness temperatures difference (dBT) under different DAODTIR with respect to their dust-free BTs is constructed based on the CALIOP retrieved dust vertical profile and pre-assumed dust scattering properties using a fast radiative transfer model. Then the DAODTIR is retrieved by projecting the IIR-observed dBT on the LUT. Sensitivity studies show that the DAODTIR retrieval at 10.6 μm is more susceptible to the dust particle size distribution (PSD) assumption than dust refractive indices. To estimate the uncertainty caused by PSD assumption, two DAODTIR retrieval products, one based on the dust PSD from the AERONET at Cape Verde and the other on an in situ measured PSD from the recent Fennec campaign, are provided. The retrieval uncertainty is mainly contributed by the BT difference between the observation and simulation using auxiliary atmospheric data. The climatology of the retrieval from 2013 to 2019 shows confident spatiotemporal variations of DAODTIR with the global-averaged value of 0.006 and 0.008 based on different pre-assumed dust PSDs. Climatological results agree reasonably well with two independent DAODTIR retrieval products based on the Infrared Atmospheric Sounding Interferometer (IASI) over the active dust transport regions, such as North and Tropical Atlantic (r = 0.904 and 0.819) and Indian Ocean (r = 0.832). The seasonal and interannual variation is also well-compared (r = 0.758) with AERONET coarse-mode AOD at 97 selected sites. The synergic CALIOP observation allows the retrieved DAODTIR to directly compare with the extrapolated DAODTIR from DAOD in visible (i.e., 532 nm), which helps evaluate the observational constraints on DAODTIR. This study offers a unique prospect of collocating active lidar and passive IR observations for retrieving dust DAODTIR.

aerosol↗
NASA NTRSDate not supplied

Progress Towards a Common CERES Cloud Mask Algorithm for MODIS and VIIRS: Evaluation using CALIOP Data

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has endeavored to produce a long-term global climate data record for detecting changes in the Earth’s radiation budget and to improve understanding of how clouds contribute to those changes. CERES incorporates cloud information derived from passive narrowband satellite imaging radiometers, and over the course of the project different instruments have contributed to this effort, namely the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS).Cloud properties have been derived from MODIS on the Aqua satellite for CERES since 2002,and VIIRS on the NOAA-20 satellite launched in 2017 will continue the cloud record once Aqua-MODIS reaches the end of its operational lifetime. However, MODIS and VIIRS have different spectral capabilities and characteristics which complicates our ability to seamlessly transition the record from MODIS to VIIRS. This study evaluates some of the recent algorithm modifications incorporated by the CERES Cloud Working Group towards developing a unified cloud mask algorithm for MODIS and VIIRS that utilizes a set of spectral bands common to both instruments. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products are used to evaluate MODIS and VIIRS regional cloud fraction estimates and identify areas where improvements can be made. The cloud mask algorithm relies on computed estimates of cloud-free top-of-atmosphere radiances to differentiate cloudy and cloud-free imager pixels. The unified cloud mask algorithm currently under development uses a reduced number of spectral bands common to both MODIS and VIIRS and so relies on the accuracy of these simulated cloud-free radiances more heavily than predecessor algorithms, i.e., the CERES Edition 4 cloud mask, which use as much spectral information as available on each imager with less consideration for cross-platform consistency. Our validation strategy using CALIOP data is also described. The CALIOP observations are critical for assessing cloud detection accuracies and for independently confirming cloud-free conditions which enables a more robust evaluation of the simulated cloud-free radiances for biases due to factors such as view angle and the spectral dependence of water vapor absorption. These effects are known to differ for the two satellite instruments. Comparisons of MODIS and VIIRS cloud fractions are presented in context with estimates from CALIOP and from the CERES Edition 4 cloud mask algorithm to gauge current progress in developing accurate and consistent MODIS and VIIRS cloud properties for CERES.

CERES↗
NASA NTRS2008

Evaluation and Applications of Cloud Climatologies from CALIOP

Clouds have a major impact on the Earth radiation budget and differences in the representation of clouds in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing cloud climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous cloud and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average cloud cover measured by CALIOP is about 75%, significantly higher than for existing cloud climatologies due to the sensitivity of CALIOP to optically thin cloud. Day/night biases in cloud detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a cloud climatology, characteristics of cloud cover statistics derived from CALIOP data, and applications of those statistics.

Winker, David↗