The CALIPSO Level II data are analyzed to assess the veracity of the CALIPSO aerosol type identification algorithm and generate distributions of aerosol types and their respective optical
characteristics. The distributions show that the classification algorithm has no surface type or diurnal dependencies. For this initial assessment of algorithm performance, we analyze global distributions of the CALIPSO aerosol types, along with distributions of integrated attenuated backscatter, backscatter color ratio, and volume depolarization ratio for each type. The aerosol type distributions are further partitioned according to various geophysical discriminators (e.g., geographic region, land
vs. ocean, and day vs. night). The algorithm generates the expected results in most scenes. The total color ratio distributions show significant overlap between the aerosol types. Since the aerosol typing algorithm uses a logical decision tree based on fixed thresholds, we test the sensitivity of the typing algorithm to perturbations in these threshold values. To test the CALIPSO extinction to backscatter ratio estimates, we compare
extinction-to-backscatter ratios derived using the transmittance method
to the values in the look up tables.
The extinction-to-backscatter ratio (Sa) is an important parameter used in the determination of the aerosol extinction and subsequently the optical depth from lidar backscatter measurements. We outline the algorithm used to determine Sa for the Cloud and Aerosol Lidar and Infrared Pathfinder Spaceborne Observations (CALIPSO) lidar. Sa for the CALIPSO lidar will either be selected from a look-up table or calculated using the lidar measurements depending on the characteristics of aerosol layer. Whenever suitable lofted layers are encountered, Sa is computed directly from the integrated backscatter and transmittance. In all other cases, the CALIPSO observables: the depolarization ratio, δ, the layer integrated attenuated backscatter, β', and the mean layer total attenuated color ratio, γ, together with the surface type, are used to aid in aerosol typing. Once the type is identified, a look-up-table developed primarily from worldwide observations, is used to determine the Sa value. The CALIPSO aerosol models include desert dust, biomass burning, background, polluted continental, polluted dust, and marine aerosols.
The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite will be launched in April of 2005, and will make continuous measurements of the Earth's atmosphere for the following three years. Retrieving the spatial and optical properties of clouds and aerosols from the CALIPSO lidar backscatter data will be confronted by a number of difficulties that are not faced in the analysis of ground-based data. Among these are the very large distance from the target, the high speed at which the satellite traverses the ground track, and the ensuing low signal-to-noise ratios that result from the mass and power restrictions imposed on space-based platforms. In this work we describe an integrated analysis scheme that employs a nested, multi-grid averaging technique designed to optimize tradeoffs between spatial resolution and signal-to-noise ratio. We present an overview of the three fundamental retrieval algorithms (boundary location, feature classification, and optical properties analysis), and illustrate their interconnections using data product examples that include feature top and base altitudes, feature type (i.e., cloud or aerosol), and layer optical depths.
We use measurements and models to develop aerosol models for use in the inversion algorithms for the Cloud Aerosol Lidar and Imager Pathfinder Spaceborne Observations (CALIPSO). Radiance measurements and inversions of the AErosol RObotic NETwork (AERONET) are used to group global atmospheric aerosols using optical and microphysical parameters. This study uses more than 105 records of radiance measurements, aerosol size distributions, and complex refractive indices to generate the optical properties of the aerosol at more 200 sites worldwide. These properties together with the radiance measurements are then classified using classical clustering methods to group the sites according to the type of aerosol with the greatest frequency of occurrence at each site. Six significant clusters are identified: desert dust, biomass burning, urban industrial pollution, rural background, marine, and dirty pollution. Three of these are used in the CALIPSO aerosol models to characterize desert dust, biomass burning, and polluted continental aerosols. The CALIPSO aerosol model also uses the coarse mode of desert dust and the fine mode of biomass burning to build a polluted dust model. For marine aerosol, the CALIPSO aerosol model uses measurements from the SEAS experiment. In addition to categorizing the aerosol types, the cluster analysis provides all the column optical and microphysical properties for each cluster.
In this paper, a 1.5 micron, 3-D scanning, portable and eyesafe aerosol lidar system is presented. The design, testing and field measurements of this lidar are introduced. An aerosol lidar model is used to evaluate lidar system's performance. At the end, the experimental and theoretic atmospheric detection results are presented and compared.