Extinction and optical depth retrievals for CALIPSO's Version 4 data release

The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite has been making near-global height-resolved measurements of cloud and aerosol layers since mid-June 2006. Version 4.10 (V4) of the CALIOP data products, released in November 2016, introduces extensive upgrades to the algorithms used to retrieve the spatial and optical properties of these layers, and thus there are both obvious and subtle differences between V4 and previous data releases. This paper describes the improvements made to the extinction retrieval algorithms and illustrates the impacts of these changes on the extinction and optical depth estimates reported in the CALIPSO lidar level 2 data products. The lidar ratios for both aerosols and ice clouds are generally higher than in previous data releases, resulting in generally higher extinction coefficients and optical depths in V4. A newly implemented algorithm for retrieving extinction coefficients in opaque layers is described and its impact examined. Precise lidar ratio estimates are also retrieved in these opaque layers. For semi-transparent cirrus clouds, comparisons between CALIOP V4 optical depths and the optical depths reported by MODIS collection 6 show substantial improvements relative to earlier comparisons between CALIOP version 3 and MODIS collection 5.</p

CALIPSO Lidar Level 3 Aerosol Profile Product: Version 3 Algorithm Design

The CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) level 3 aerosol profile product reports globally gridded, quality-screened, monthly mean aerosol extinction profiles retrieved by CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarization). This paper describes the quality screening and averaging methods used to generate the version 3 product. The fundamental input data are CALIOP level 2 aerosol extinction profiles and layer classification information (aerosol, cloud, and clear-air). Prior to aggregation, the extinction profiles are quality-screened by a series of filters to reduce the impact of layer detection errors, layer classification errors, extinction retrieval errors, and biases due to an intermittent signal anomaly at the surface. The relative influence of these filters are compared in terms of sample rejection frequency, mean extinction, and mean aerosol optical depth (AOD). The extinction QC flag filter is the most influential in preventing high-biases in level 3 mean extinction, while the misclassified cirrus fringe filter is most aggressive at rejecting cirrus misclassified as aerosol. The impact of quality screening on monthly mean aerosol extinction is investigated globally and regionally. After applying quality filters, the level 3 algorithm calculates monthly mean AOD by vertically integrating the monthly mean quality-screened aerosol extinction profile. Calculating monthly mean AOD by integrating the monthly mean extinction profile prevents a low bias that would result from alternately integrating the set of extinction profiles first and then averaging the resultant AOD values together. Ultimately, the quality filters reduce level 3 mean AOD by 24 and 31 % for global ocean and global land, respectively, indicating the importance of quality screening

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 (&lt; 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 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 (<i>g</i>) 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 <i>g</i> ≈ 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

New Directions: Emerging Satellite Observations of Above-cloud Aerosols and Direct Radiative Forcing

Spaceborne lidar and passive sensors with multi-wavelength and polarization capabilities onboard the A-Train provide unprecedented opportunities of observing above-cloud aerosols and direct radiative forcing. Significant progress has been made in recent years in exploring these new aerosol remote sensing capabilities and generating unique datasets. The emerging observations will advance the understanding of aerosol climate forcing

An evaluation of CALIOP/CALIPSO’s aerosol-above-cloud detection and retrieval capability over North America

Assessing the accuracy of the aerosol-above-cloud (AAC) properties derived by CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarization) is challenged by the shortage of accurate global validation measurements. We have used measurements of aerosol vertical profiles from the NASA Langley airborne High Spectral Resolution Lidar (HSRL-1) in 86 CALIOP-coincident flights to evaluate CALIOP AAC detection, classification, and retrieval. Our study shows that CALIOP detects ~23% of the HSRL-detected AAC. According to our CALIOP-HSRL data set, the majority of AAC aerosol optical depth (AOD) values are \u3c 0.1 at 532 nm over North America. Our analyses show that the standard CALIOP retrieval algorithm substantially underestimates the occurrence frequency of AAC when optical depths are less than ~0.02. Those aerosols with low AOD values can still have a consequent radiative forcing effect depending on the underlying cloud cover and overlying aerosol absorption properties. We find essentially no correlation between CALIOP and HSRL AAC AOD (R2 = 0.27 and N = 151). We show that the CALIOP underestimation of AAC is mostly due to tenuous aerosol layers with backscatter less than the CALIOP detection threshold. The application of an alternate CALIOP AAC retrieval method (depolarization ratio) to our data set yields very few coincident cases. We stress the need for more extensive suborbital CALIOP validation campaigns to acquire a process-level understanding of AAC implications and further evaluate CALIOPs AAC detection and retrieval capability, especially over the ocean and in different parts of the world where AAC are more frequently observed and show higher values of AOD

A New Approach for Checking and Complementing CALIPSO Lidar Calibration

We have been studying the backscatter ratio of the two CALIPSO wavelengths for 3 different targets. We are showing the ratio of integrate attenuated backscatter coefficient for cirrus clouds, ocean surface and liquid. Water clouds for one month of nightime data (left:July,right:December), Only opaque cirrus classified as randomly oriented ice[1] are used. For ocean and water clouds, only the clearest shots, determined by a threshold on integrated attenuated backscatter are used. Two things can be immediately observed: 1. A similar trend (black dotted line) is visible using all targets, the color ratio shows a tendency to be higher north and lower south for those two months. 2. The water clouds average value is around 15% lower than ocean surface and cirrus clouds. This is due to the different multiple scattering at 532 nm and 1064 nm [2] which strongly impact the water cloud retrieval. Conclusion: Different targets can be used to improve CALIPSO 1064 nm calibration accuracy. All of them show the signature of an instrumental calibration shift. Multiple scattering introduce a bias in liquid water cloud signal but it still compares very well with all other methods and should not be overlooked. The effect of multiple scattering in liquid and ice clouds will be the subject of future research. If there really is a sampling issue. Combining all methods to increase the sampling, mapping the calibration coefficient or trying to reach an orbit per orbit calibration seems an appropriate way

Chaos, Consternation and CALIPSO Calibration: New Strategies for Calibrating the CALIOP 1064 nm Channel

The very low signal-to-noise ratios of the 1064 nm CALIOP molecular backscatter signal make it effectively impossible to employ the "clear air" normalization technique typically used to calibrate elastic back-scatter lidars. The CALIPSO mission has thus chosen to cross-calibrate their 1064 nm measurements with respect to the 532 nm data using the two-wavelength backscatter from cirrus clouds. In this paper we discuss several known issues in the version 3 CALIOP 1064 nm calibration procedure, and describe the strategies that will be employed in the version 4 data release to surmount these problems

THE DIURNAL AND SEASONAL RADIATIVE EFFECTS OF CIRRUS CLOUDS UTILIZING LARGE AIRBORNE AND SPACE-BORNE LIDAR DATASETS

Cirrus clouds are globally the most common cloud type, however, their radiative impact on the Earth remains a large source of uncertainty in global climate models. Cirrus are unique in that they are absorptive to terrestrial outgoing longwave radiation, while also relatively transmissive to incoming solar radiation. The interactions of this greenhouse and albedo effect determine the sign and magnitude of cirrus radiative effects. Cirrus are microphysically complex, and can exhibit a variety of different ice crystal shapes and sizes depending on the thermodynamic environment in which they form, and their dynamic formation mechanism. Our ability to reliably model cirrus radiative effects is dependent upon accurate observations and parameterizations incorporated into radiative transfer simulations. Laser lidar instruments provide valuable measurements of cirrus clouds unavailable by other radar systems, passive remote sensors, or in-situ instruments alone. In this dissertation I developed and tested an improved calibration technique for the ACATS lidar instrument, and its impact on the direct retrieval of cirrus HSRL optical properties. HSRL retrievals theoretically have reduced uncertainty over those from a standard backscatter lidar. ACATS flew on two field campaigns in 2012 and 2015 where it was unable to consistently calibrate its etalon. It has been operating from the lab in NASA GSFC collecting zenith pointing data of cirrus layers where the improved calibration has resulted in consistent and reliable separation of the particulate and Rayleigh signal components. The diurnal trend of cirrus influence on the global scale has primarily been limited to data provided by satellites in sun-synchronous orbit, which provide only a snapshot of conditions at two times a day. Utilizing data from the CATS lidar aboard the ISS I investigated cirrus at four periods throughout the day in morning, afternoon, evening, and night across all seasons. Cirrus radiative effects were found to have a large latitudinal dependence, and have a greater potential to cool than many studies suggest with their primary warming contributions skewed towards the nighttime hours. Constrained lidar retrievals reduce the assumptions made in retrieving cirrus optical properties. Utilizing the expansive airborne CPL dataset from six flight campaigns I model the radiative effects of over twenty thousand constrained cirrus observations. Mid-latitude cirrus were found to have a mean positive daytime forcing equivalent to that of the CO2 greenhouse effect. However, synoptic cirrus were found to have a greater warming effect than convective cirrus, which were more likely to have a cooling effect

Retrieval of Aerosol Optical Depth Above Clouds from OMI Observations: Sensitivity Analysis, Case Studies

A large fraction of the atmospheric aerosol load reaching the free troposphere is frequently located above low clouds. Most commonly observed aerosols above clouds are carbonaceous particles generally associated with biomass burning and boreal forest fires, and mineral aerosols originated in arid and semi-arid regions and transported across large distances, often above clouds. Because these aerosols absorb solar radiation, their role in the radiative transfer balance of the earth atmosphere system is especially important. The generally negative (cooling) top of the atmosphere direct effect of absorbing aerosols, may turn into warming when the light-absorbing particles are located above clouds. The actual effect depends on the aerosol load and the single scattering albedo, and on the geometric cloud fraction. In spite of its potential significance, the role of aerosols above clouds is not adequately accounted for in the assessment of aerosol radiative forcing effects due to the lack of measurements. In this paper we discuss the basis of a simple technique that uses near-UV observations to simultaneously derive the optical depth of both the aerosol layer and the underlying cloud for overcast conditions. The two-parameter retrieval method described here makes use of the UV aerosol index and reflectance measurements at 388 nm. A detailed sensitivity analysis indicates that the measured radiances depend mainly on the aerosol absorption exponent and aerosol-cloud separation. The technique was applied to above-cloud aerosol events over the Southern Atlantic Ocean yielding realistic results as indicated by indirect evaluation methods. An error analysis indicates that for typical overcast cloudy conditions and aerosol loads, the aerosol optical depth can be retrieved with an accuracy of approximately 54% whereas the cloud optical depth can be derived within 17% of the true value