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The Visible Infrared Imaging Radiometer Suite (VIIRS) is the next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. The VIIRS aerosol Environmental Data Record (EDR) is expected to continue the decade-long successful multispectral aerosol retrieval from the NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) for scientific research and applications. Since the launch of the Suomi National Polar-orbiting Partnership (S-NPP), the VIIRS aerosol calibration/validation team has been continuously monitoring, evaluating, and improving the performance of VIIRS aerosol retrievals. In this study, the VIIRS aerosol optical thickness (AOT) at 550 nm EDR at current Provisional maturity level is evaluated by comparing it with MODIS retrievals and measurements from the Aerosol Robotic Network (AERONET) and the Maritime Aerosol Network (MAN). The VIIRS global mean AOT at 550 nm differs from that of MODIS by approximately À0.01 over ocean and 0.03 over land (0.00 and À0.01 for the collocated retrievals) but shows larger regional biases. Global validation with AERONET and with MAN measurements shows biases of 0.01 over ocean and À0.01 over land, with about 64% and 71% of retrievals falling within the expected uncertainty range established by MODIS over ocean (±(0.03 + 0.05AOT)) and over land (±(0.05 + 0.15AOT)), respectively. The VIIRS retrievals over land exhibit slight overestimation over vegetated surfaces and underestimation over soil-dominated surfaces. These results show that the VIIRS AOT at 550 nm product provides a solid global data set for quantitative scientific investigations and environmental monitoring.

[1] This paper aims to evaluate CALIOP aerosol optical depth (AOD) retrieval using MODIS AOD with the goal of improving the CALIOP selection of the lidar ratio leveraging the vertical resolved CALIOP and multispectral MODIS observations. Comparing the MODIS fine mode ratio to CALIOP, we find that the CALIOP integrated attenuated total color ratio provides sensitivity to the aerosol size and type. This finding can be used to better constrain the lidar ratio and improve the CALIOP AOD independent from MODIS.To retrieve the aerosol optical depth from CALIOP requires knowledge of the aerosol lidar ratio that varies significantly as a function of aerosol type. For most CALIOP retrievals the lidar ratio is estimated by correlating CALIOP observables (depolarization and backscatter) with precomputed lidar ratio climatologies. Applying a lidar ratio not representative of the observed aerosols can result in significant AOD biases and is one of the primary sources of uncertainty in the current CALIOP AOD. We demonstrate that over ocean the MODIS sensitivity to the fine-and coarse-mode aerosol mixing ratios provides additional constraints to the aerosol lidar ratio. When MODIS fine-mode retrievals are collocated with CALIOP, the improved lidar ratio significantly reduces the CALIOP AOD mean biases from |0.064| to |0.020| when compared to MODIS. In addition, we demonstrate that the CALIOP integrated attenuated total color ratio is correlated with the MODIS fine and coarse mixing ratios in marine environments. This finding suggests that for a CALIOP-only AOD retrieval the integrated attenuated total color ratio can be used to better constrain the lidar ratio. Using the CALIOP integrated attenuated total color ratio, the CALIOP-only AOD retrieval improves the AOD mean biases (|0.064| to |0.007|) when compared to the MODIS AOD.Citation: Oo, M., and R. Holz (2011), Improving the CALIOP aerosol optical depth using combined MODIS-CALIOP observations and CALIOP integrated attenuated total color ratio,

Abstract. 2012 Level-2 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite-based cloud data sets are investigated for thresholds that distinguish the presence of cirrus clouds in autonomous lidar measurements, based on temperatures, heights, optical depth and phase. A thermal threshold, proposed by Sassen and Campbell (2001) C, respectively, for tops and bases) and optical depths (1.18 vs. 1.23) reflect the sensitivity to this constraint. Over 99 % of all T top ≤ −37 • C clouds are classified as ice by CALIOP Level-2 algorithms. Over 81 % of all ice clouds correspond with T top ≤ −37 • C. For instruments lacking polarized measurements, and thus practical estimates of phase, T top ≤ −37 • C provides sufficient justification for distinguishing cirrus, as opposed to the risks of glaciated liquid-water cloud contamination occurring in a given sample from clouds identified at relatively "warm" (T top > −37 • C) temperatures. Although accounting for uncertainties in temperatures collocated with lidar data (i.e., model reanalyses/sondes) may justifiably relax the threshold to include warmer cases, the ambiguity of "warm" ice clouds cannot be fully reconciled with available measurements, conspicuously including phase. Cloud top heights and optical depths are investigated, and global distributions and frequencies derived, as functions of CALIOP-retrieved phase. These data provide little additional information, compared with temperature alone, and may exacerbate classification uncertainties overall. MotivationCirrus clouds are recognized by sky gazers for their translucent and fibrous appearance, cast frequently as delicate white filaments across otherwise clear blue skies at relatively high tropospheric altitudes. To climate scientists however, cirrus clouds, which are composed almost exclusively of ice crystals, are distinct for their physical and radiative properties (e.g., Liou, 1986). As cold and optically thin counterparts to most liquid-water and mixed-phase clouds (e.g., Sassen and Cho, 1992), the net column-integrated radiative impact of cirrus cloud presence during sunlit hours varies between positive and negative, depending on the relative magnitudes of their simultaneous and offsetting contributions diurnally to tropospheric warming (infrared absorption and reemission) and cooling (solar albedo effects; Stephens et al., 1990). This attribute makes cirrus relatively unique among cloud genera. Combined with their relatively high occurrence frequencies globally (e.g., Holz et al., 2008), cirrus are significant and distinct contributors to climate overall .Lidars are primary remote-sensing tools used for monitoring cirrus clouds (e.g., Sassen, 1991). Two complementary NASA lidar projects are presently tasked with compiling Published by Copernicus Publications on behalf of the European Geosciences Union.

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