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Wojciech W. Grabowski

others. However, in nature, convective clouds continuously interact with their surroundings through gravity waves and detrainment that modify their environment (e.g., Bretherton and Smolarkiewicz 1989 ). These interactions affect development of subsequent clouds. Thus, it is irrelevant what the first cloud does, but what matters is a response of an ensemble of clouds to realistic forcings averaged over many cloud realizations. (An exception to this argument might be when the first cloud causes a

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Jie Peng, Zhanqing Li, Hua Zhang, Jianjun Liu, and Maureen Cribb

, which would decrease maximum wind speeds. This was supported by observations of how variations in aerosols accounted for an 8% variation in the intensity of Atlantic hurricanes ( Rosenfeld et al. 2011 ). Wang et al. (2014) have also shown that both precipitation and net cloud radiative forcing (CRF) over the northwestern Pacific are enhanced by Asian pollution via the invigoration of winter cyclones. A review of aerosol effects on the intensity and microphysics of tropical cyclones has been given

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Peter J. Marinescu, Susan C. van den Heever, Max Heikenfeld, Andrew I. Barrett, Christian Barthlott, Corinna Hoose, Jiwen Fan, Ann M. Fridlind, Toshi Matsui, Annette K. Miltenberger, Philip Stier, Benoit Vie, Bethan A. White, and Yuwei Zhang

type of deep convective cloud system under consideration can alter the effect that aerosol particles have within deep convective updrafts (e.g., Seifert and Beheng 2006b ; Khain et al. 2008 ; van den Heever et al. 2011 ). Supercells that are primarily driven by dynamical forcings have been shown to have lesser impacts from varying CCN concentrations than other types of deep convection (e.g., Grant and van den Heever 2015 ). Another cause of complication stems from differences in studies that

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Jiwen Fan, Yuan Wang, Daniel Rosenfeld, and Xiaohong Liu

impacts on cloud radiative forcing from the meteorological effects in observations and poor parameterizations of convection and clouds in numerical simulations especially for large-scale models cause the largest uncertainty in current estimates of climate forcing, which resides in aerosol–cloud interactions (ACI) that are traditionally referred to as aerosol indirect effects ( IPCC 2013 ). How aerosols affect cloud properties and precipitation through ACI strongly varies among cloud types that are

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Jianjun Liu, Zhanqing Li, and Maureen Cribb

indirect effect; Albrecht 1989 ). AIE are the dominant contributors to the overall aerosol radiative forcing in most climate models yet are poorly constrained and can vary by a factor of 5 across different models ( Quaas et al. 2009 ; Wood et al. 2015 ). Marine boundary layer (MBL) clouds are common over the subtropical and midlatitude oceans and are particularly susceptible to perturbations in aerosols ( Wood et al. 2015 ). These clouds strongly influence regional and global climate systems

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Tianmeng Chen, Jianping Guo, Zhanqing Li, Chuanfeng Zhao, Huan Liu, Maureen Cribb, Fu Wang, and Jing He

isolate the signal attributed to aerosol loading from that attributed to environmental forcing. The LTS is calculated as the difference between potential temperatures at 700 and 1000 hPa. The ω at the following pressure levels were chosen for investigation of the dependence of aerosol–cloud interaction on atmospheric environment: 825 hPa for shallow and deep Cu clouds, 600 hPa for Ns clouds, and 400 hPa for DCC. The roles of these environmental factors in the development of MCOG and CTH under clean

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Yun Lin, Yuan Wang, Bowen Pan, Jiaxi Hu, Yangang Liu, and Renyi Zhang

those of its individual cloud components, it is necessary to evaluate the long-term response of the various cloud types when assessing the aerosol direct and indirect radiative forcings. 4. Summary and conclusions The aerosol microphysical and radiative effects on an evolving continental cloud complex occurring from 25 May to 27 May 2009 during the DOE ARM RACORO field campaign are investigated. The TAMU-WRF model with a two-moment bulk microphysics by Li et al. (2008b) and a modified Goddard

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Wojciech W. Grabowski and Hugh Morrison

from the effects of different flow realizations is difficult. One possibility is to consider high-resolution convection-permitting numerical weather prediction (NWP)-type simulations driven by observed meteorology. If the simulation domain is large enough, such an approach includes many clouds and thus incorporates feedbacks between cloud processes and the large-scale environment. If the simulation period is long, say, many days, such simulations sample realistic meteorological conditions (forcings

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Baolin Jiang, Bo Huang, Wenshi Lin, and Suishan Xu

1. Introduction The annual discharge of anthropogenic aerosols into the atmosphere is considerable, but the effects of those aerosols on weather and climate remain very uncertain ( IPCC 2007 ). Aerosols can absorb and reflect solar radiation, thereby reducing the surface temperature and planetary boundary layer height, but they also act as cloud condensation nuclei (CCN) or ice nuclei, affecting cloud microphysics and subsequent precipitation rates, and increasing cloud coverage, albedo, and

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Luke B. Hande, C. Hoose, and C. Barthlott

1. Introduction Ice particles in mixed-phase clouds have a large impact on cloud lifetime, precipitation amount, and cloud radiative properties ( Boucher et al. 2013 ; Lau and Wu 2003 ; Lohmann and Feichter 2005 ; Morrison et al. 2005 ), so correctly modeling ice formation processes is important for simulations performed on all spatial and temporal scales. Ice forms on aerosol particles, known as ice nucleating particles (INP), through four different processes: immersion freezing

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