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J Kar

Publications and source records attributed to J Kar.

TPSAS-NF1676L-11609-DND

China and much of East Asia experienced a drought in the spring of 2010 that is said to be the worst in the past century. Strong winds (wind speed > 7 m/s) occurred in spring this year ~40% more than average in recent years. MODIS imagery indicates numerous major dust storms occurring in the Taklimakan and Gobi deserts. Intense, persistent dust was subsequently observed over North America by space-based, airborne and ground-based lidars during April 2010. Using CALIPSO lidar (CALIOP) measurements and air parcel back trajectories, we track the dust measured over North America back to East Asian source regions (mainly in the Tarim Basin). We also interpret the CALIOP and other A-Train observations using results from a 3D chemical transport model (GEOS-Chem) and investigate the meteorological context that gave rise to these dust storms.

Z Liu↗

TPSAS-NF1676L-31882-DND

Lidar ratios are required to retrieve the extinction profiles in CALIOP algorithm. Unconstrained retrievals: A default lidar ratio is used depending upon the aerosol subtype. Constrained retrievals: The lidar ratio (S) is retrieved from the measured two way transmittance (T2), when clear air is found both above and below the layer for at least 2.5 km (T^2 = / ; S = (1-T2)/2γ’), where and are the mean attenuated scattering ratios below and above the layer respectively, and γ’ is the layer integrated attenuated backscatter. A multiple scattering factor of 1 is assumed. In general, constrained lidar ratios are expected to be more representative (but also noisier) than the unconstrained cases, hence accuracy of the unconstrained lidar ratios can be assessed using the constrained ones.

J Kar↗

TPSAS-NF1676L-20108-DND

This presentation describes several enhancements planned for the version 4 aerosol subtyping and lidar ratio selection algorithms of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The CALIOP subtyping algorithm determines the most likely aerosol type from CALIOP measurements (attenuated backscatter, estimated particulate depolarization ratios de, layer altitude), and surface type. The aerosol type, so determined, is associated with a lidar ratio (LR) from a discrete set of values. In the version 3 algorithms, there are 6 pairs of 532 and 1064 nm lidar ratios. Some of these lidar ratios will be updated in the version 4 algorithms. In particular, the dust and polluted dust will be adjusted to reflect the latest measurements and model studies of these types. The algorithms are being updated to eliminate the occasional confusion between smoke and clean marine aerosols seen in version 3 by modifications to the elevated layer flag definitions that are used to determine the presence of smoke aerosols over the ocean. In the subtyping algorithms pure dust is determined by high estimated particulate depolarization ratios [de > 0.20]. Mixtures of dust and other aerosol types are determined by intermediate values of the estimated depolarization ratio [0.075< de <0.2]. The version 3 algorithms are limited to mixtures of dust and smoke, the so-called polluted dust aerosol type. To differentiate between mixtures of dust and smoke, and dust and marine aerosols, a new aerosol type will be added in the version 4 data products. In the revised classification algorithms, polluted dust will still defined as dust + smoke/pollution but in the marine boundary layer instances of moderate depolarization will be typed as dusty marine aerosols with a lower lidar ratio [LR = 35 sr] than polluted dust [currently LR = 55 sr]. The dusty marine type introduced in version 4 is modeled as a mixture of dust + marine aerosol. In the v3 algorithms the frequency of dust and polluted dust aerosols at daytime is higher than at nighttime. We present possible reasons for this and present the v4 distributions resulting from both improved background slope corrections of the daytime depolarization ratios and changes to the daytime thresholds for the polluted dust and dusty marine types of version 4. To gauge the impact of the enhancements, we contrast the following between versions 3 and 4: aerosol type, parameter distributions of each type, layer heights of maximum frequency, and distributions of smoke in biomass burning regions. To illustrate specific impacts the presentation shows case studies of version 3 and version 4 vertical feature masks of the aerosol subtypes, where appropriate, for the above enhancements.

A Omar↗

TPSAS-NF1676L-11598-DND

Satellite data show a strong summertime maximum in aerosol optical depth (AOD) over the Southeastern (SE) USA that can not be explained by anthropogenic sulfate or organic aerosols at the surface (Goldstein et al., 2009). The biogenic volatile organic compound (BVOC) emissions peak over the same region and models indicate a large source of secondary organic aerosols (SOA) here (van Donkelaar et al., 2007, Zhang et al., 2007, Liao et al., 2007). Aircraft measurements indicate dominance of organic aerosols over sulfates with altitude and models suggest most SOA production from isoprene oxidation takes place above the surface layers. Goldstein et al. (2009) hypothesized that these SOA drive the AOD maximum in summer with an altitude dependence. We examine the distributions of AOD and other optical properties over SE USA using height resolved aerosol data from CALIPSO. We also use AOD data from MODIS and OMI and UV aerosol index from OMI to characterize the aerosols over SE USA.

J Kar↗

On Improving the Dust Lidar Ratios for Version 5 of CALIOP by Using Measurements with Source-tagged Model Results

Vertically resolved retrievals of aerosol backscatter and extinction have been available since 2006 from global measurements acquired by the space borne lidar CALIOP onboard the CALIPSO satellite. These retrievals depend crucially upon the ratio of extinction to backscatter (i.e., lidar ratio) which typically has to be assumed for the various aerosol species for an elastic backscatter lidar like CALIOP. For all CALIPSO data releases up until now (version 4.2), these lidar ratios have been taken as constant both spatially and temporally. However, it is well established that the aerosol lidar ratios can vary significantly regionally, seasonally, and also as a function of age and relative humidity. In particular, the dust lidar ratios show significant variation depending upon their source regions, which is related to the mineral composition of dust in that region. In this paper, we shall present a scheme to obtain the regionally and seasonally dependent lidar ratios of dust. In this scheme, which may be implemented in a forthcoming version of CALIOP aerosol extinction retrievals, we first derive lidar ratios of aerosol layers globally, classified as dust by CALIOP, by using the backscatter measurements constrained by collocated MODIS aerosol optical depths. Since this dust will frequently be a mixture of dust from various source regions, we obtain the corresponding regional contributions from the dust simulations using the GEOS model tagged to nine source regions. Finally, combining information from both measurements and models, we obtain the lidar ratios of dust corresponding to the nine source regions. The lidar ratio of the mixed dust anywhere can now be obtained from the tagged model fractions and the corresponding regional lidar ratio. We shall show the application of this scheme for various regions and seasons.

CALIPSO↗