Abstract. During the 2012 Deep Convective Clouds and Chemistry (DC3) experiment the National Science Foundation/National Center for Atmospheric Research Gulfstream V (GV) aircraft sampled the upper anvils of two storms that developed in eastern Colorado on 6 June 2012. A cloud particle imager (CPI) mounted on the GV aircraft recorded images of ice crystals at altitudes of 12.0 to 12.4 km and temperatures (T) from −61 to −55 ∘C. A total of 22 393 CPI crystal images were analyzed, all with maximum dimension (Dmax⁡)<433 µm and with an average Dmax⁡ of 80.7±45.4 µm. The occurrence of well-defined pristine crystals (e.g., columns and plates) was less than 0.04 % by number. Single frozen droplets and frozen droplet aggregates (FDAs) were the dominant habits with fractions of 73.0 % (by number) and 46.3 % (by projected area), respectively. The relative frequency of occurrence of single frozen droplets and FDAs depended on temperature and position within the anvil cloud. A new algorithm that uses the circle Hough transform technique was developed to automatically identify the number, size, and relative position of element frozen droplets within FDAs. Of the FDAs, 42.0 % had two element frozen droplets with an average of 4.7±5.0 element frozen droplets. The frequency of occurrence gradually decreased with the number of element frozen droplets. Based on the number, size, and relative position of the element frozen droplets within the FDAs, possible three-dimensional (3-D) realizations of FDAs were generated and characterized by two different shape parameters, the aggregation index (AI) and the fractal dimension (Df), that describe 3-D shapes and link to scattering properties with an assumption of spherical shape of element frozen droplets. The AI of FDAs decreased with an increase in the number of element frozen droplets, with larger FDAs with more element frozen droplets having more compact shapes. The Df of FDAs was about 1.20–1.43 smaller than that of black carbon (BC) aggregates (1.53–1.85) determined in previous studies. Such a smaller Df of FDAs indicates that FDAs have more linear chain-like branched shapes than the compact shapes of BC aggregates. Determined morphological characteristics of FDAs along with the proposed reconstructed 3-D representations of FDAs in this study have important implications for improving the calculations of the microphysical (e.g., fall velocity) and radiative (e.g., asymmetry parameter) properties of ice crystals in upper anvil clouds.

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In this paper, a Multiple Adaptive-resourceallocation Real-time Supervisor (MARS) scheme for hybrid cloud-assisted Industrial Internet of Things (IIoT) is proposed to support reliable cloud services even under rapidly changing service demands that occur in massive IIoT networks. Virtual Machines (VMs) in both private cloud and public clouds can be elastically and accurately allocated through the proposed MARS scheme, which uses Karush-Kuhn-Tucker (KKT) optimization applied to the VM Continuous-Time Markov Chain (CTMC) scheme. Because the MARS scheme can immediately determine the optimal number of VMs based on the hybrid cloud situation, a significant improvement in the elasticity performance can be obtained. Compared to using the CTMC scheme, the results show that the MARS scheme can improve the response time up to 19.3 ∼ 73% (based on the activation rate) and the elasticity by 26.7%, and reduce the cost by 1.2%.

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