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

Adapting CALIPSO Climate Measurements for Near Real Time Analyses and Forecasting

The Cloud-Aerosol Lidar and Infrared Pathfinder satellite Observations (CALIPSO) mission was originally conceived and designed as a climate measurements mission, with considerable latency between data acquisition and the release of the level 1 and level 2 data products. However, the unique nature of the CALIPSO lidar backscatter profiles quickly led to the qualitative use of CALIPSO?s near real time (i.e., ? expedited?) lidar data imagery in several different forecasting applications. To enable quantitative use of their near real time analyses, the CALIPSO project recently expanded their expedited data catalog to include all of the standard level 1 and level 2 lidar data products. Also included is a new cloud cleared level 1.5 profile product developed for use by operational forecast centers for verification of aerosol predictions. This paper describes the architecture and content of the CALIPSO expedited data products. The fidelity and accuracy of the expedited products are assessed via comparisons to the standard CALIPSO data products

CALIOP Level 3 Ice Cloud Product

No abstract availabl

Strategies for Improved CALIPSO Aerosol Optical Depth Estimates

In the spring of 2010, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) project will be releasing version 3 of its level 2 data products. In this paper we describe several changes to the algorithms and code that yield substantial improvements in CALIPSO's retrieval of aerosol optical depths (AOD). Among these are a retooled cloud-clearing procedure and a new approach to determining the base altitudes of aerosol layers in the planetary boundary layer (PBL). The results derived from these modifications are illustrated using case studies prepared using a late beta version of the level 2 version 3 processing code

CALIOP Calibration: Version 4.0 Algorithm Updates

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar, onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, has been providing a near continuous record of high-resolution vertical profiles of clouds and aerosols properties since the summer of 2006. Key to the generation of these vertical profiles is proper calibration of the 532 nm and 1064 nm channels. This abstract summarizes improvements to the calibration techniques used to calibrate the 532 nm and 1064 nm signals for the recent version 4 (V4) Lidar Level 1 data release

CALIOP V4 cloud thermodynamic phase assignment and the impact of near-nadir viewing angles

International audienceAccurate determination of thermodynamic cloud phase is critical for establishing the radiative impact of clouds on climate and weather. Depolarization of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 532 nm signal provides an independent piece of information for determining cloud phase, a critical addition to other methods of thermodynamic phase discrimination that rely on temperature, cloud top altitude or a temperature-based cloud phase climatology. The CALIOP phase algorithm primarily uses layer-integrated depolarization and attenuated backscatter to determine the dominant thermodynamic phase of hydrometeors present in a vertical cloud layer segment, at horizontal resolutions varying between 333 m and 80 km. Ice cloud backscatter observations taken with a 0.3° near-nadir view include a significant amount of specular reflection from hexagonal smooth crystal faces that are oriented perpendicularly to the incident lidar beam. These specular reflections are often caused by horizontally oriented ice crystals (HOI), and are shown to occur between 0 and −40° C, with a peak in the distribution globally at −15° C. To avoid these reflections, the viewing angle was changed from 0.3 to 3° in November 2007. Since then the instrument has been observing clouds almost continuously for almost 12 more years. Recent viewing angle testing occurring during 2017 at 1, 1.5 and 2° quantifies the impact of changing the viewing angle to CALIOP global observations of attenuated backscatter and depolarization. These CALIOP results verify earlier observations by POLDER, showing that at the peak of the HOI distribution the mean backscatter from ice clouds decreases by 50 % and depolarization increases by a factor of 5 as the viewing angle increases from 0.3 to 3°. This has provided more data for a thorough evaluation of phase determination at the 3° viewing angle and suggested changes to the CALIOP cloud phase algorithm for Version 4 (V4). Combined with extensive calibration changes that impact the 532 nm and 1064 nm backscatter observations, V4 represents the first major Level 2 phase algorithm adjustment since 2009. For V4 the algorithm has been simplified to exclude over-identification of HOI at 3°, particularly in cold clouds. The V4 algorithm also considers temperature at the 532 nm cloud layer centroid, as opposed to cloud top or mid-cloud temperature as a secondary means of determining cloud phase and has been streamlined for more consistent identification of water and ice clouds. In this paper we summarize the major Version 3 (V3) to V4 cloud phase algorithm changes. We also characterize the impacts of applying the V4 phase algorithm globally and describe changes that can be expected when comparing V4 with V3. In V4 there are more cloud layers detected in V4, with edges that may extend further than in V3, for a combined increase in total atmospheric cloud volume of 6–9 % for high confidence cloud phases and 1–2 % for all cloudy bins. Some cloud layer boundaries have changed because 532 nm layer-integrated attenuated backscatter in V4 has increased due to improved calibration and extended layer boundaries, while the corresponding depolarization has stayed about the same. Collocated CALIPSO Imaging Infrared Radiometer (IIR) observations of ice and water cloud particle microphysical indices complement the CALIOP ice and water cloud phase determinations

Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements

Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth s atmosphere is critical in assessing the planet s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing platform, and the spatial variability of the measurement targets. Detailed descriptions are then provided for both the adaptive threshold algorithm used to detect features of interest within individual lidar profiles and the fully automated multiresolution averaging engine within which this profile scanner functions. The resulting fusion of profile scanner and averaging engine is specifically designed to optimize the trade-offs between the widely varying signal-to-noise ratio of the measurements and the disparate spatial resolutions of the detection targets. Throughout the paper, specific algorithm performance details are illustrated using examples drawn from the existing CALIPSO dataset. Overall performance is established by comparisons to existing layer height distributions obtained by other airborne and space-based lidars

CALIPSO lidar calibration at 532 nm: version 4 nighttime algorithm

International audienceData 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