ALBERT

Description: Author(s): S. C. Wang, X. H. Zhou, Y. D. Fang, Y. H. Zhang, N. T. Zhang, B. S. Gao, M. L. Liu, J. G. Wang, F. Ma, Y. X. Guo, S. C. Li, X. L. Yan, L. He, Z. G. Wang, F. Fang, X. G. Wu, C. Y. He, Y. Zheng, Z. M. Wang, G. X. Dong, and F. R. Xu Excited states in 195 Au have been studied experimentally via the 192 Os( 7 Li, 4 n ) reaction at a beam energy of 44 MeV. Based on the γ - γ - t coincidence measurement, a level scheme consisting of 15 new transitions and 10 new levels is established for 195 Au. The triaxial shape-polarizing effect of the hig... [Phys. Rev. C 85, 027301] Published Mon Feb 06, 2012

Description: Author(s): Hui-Min Zhang, Yi Sun, Wei Li, Jun-Ping Peng, Can-Li Song, Ying Xing, Qinghua Zhang, Jiaqi Guan, Zhi Li, Yanfei Zhao, Shuaihua Ji, Lili Wang, Ke He, Xi Chen, Lin Gu, Langsheng Ling, Mingliang Tian, Lian Li, X. C. Xie, Jianping Liu, Hui Yang, Qi-Kun Xue, Jian Wang, and Xucun Ma Two-dimensional Gallium grown on an insulating GaN substrate has a superconductor transition temperature of 5.4 K, five times larger than that of a bulk Ga sample. [Phys. Rev. Lett. 114, 107003] Published Tue Mar 10, 2015

Description: Author(s): Zuhuang Chen, Zhanghui Chen, Z. Q. Liu, M. E. Holtz, C. J. Li, X. Renshaw Wang, W. M. Lü, M. Motapothula, L. S. Fan, J. A. Turcaud, L. R. Dedon, C. Frederick, R. J. Xu, R. Gao, A. T. N’Diaye, E. Arenholz, J. A. Mundy, T. Venkatesan, D. A. Muller, L.-W. Wang, Jian Liu, and L. W. Martin Emergent phenomena at polar-nonpolar oxide interfaces have been studied intensely in pursuit of next-generation oxide electronics and spintronics. Here we report the disentanglement of critical thicknesses for electron reconstruction and the emergence of ferromagnetism in polar-mismatched LaMnO 3 / SrT... [Phys. Rev. Lett. 119, 156801] Published Wed Oct 11, 2017

Description: Author(s): B. S. Gao, X. H. Zhou, Y. D. Fang, Y. H. Zhang, S. C. Wang, N. T. Zhang, M. L. Liu, J. G. Wang, F. Ma, Y. X. Guo, X. G. Wu, C. Y. He, Y. Zheng, Z. M. Wang, S. C. Li, X. L. Yan, L. He, Z. G. Wang, Y. Zheng, F. Fang, and X. M. Chen High-spin states in the odd-odd 194 Au nucleus have been investigated using the 192 Os( 7 Li,5 n ) reaction at a beam energy of 44 MeV. The previously known structures built on the π h 11/2 −1 ⊗ ν i 13/2 −1 and π h 11/2 −1 ⊗ ν i 13/2 −2 ν j configurations are extended to high-spin states, and a new I π = (20 + ) state associat... [Phys. Rev. C 86, 054310] Published Fri Nov 16, 2012

Description: Author(s): C. B. Li, X. G. Wu, X. F. Li, C. Y. He, Y. Zheng, G. S. Li, S. H. Yao, S. P. Hu, H. W. Li, J. L. Wang, J. J. Liu, C. Xu, J. J. Sun, and W. W. Qu The lifetime of the 2 1 + state in 174 Os was measured in a fast timing experiment using LaBr 3 (Ce) crystals for γ -ray detection. The excellent energy resolution in conjunction with the superb time properties of the new material allows for the reliable handling of the background, thus providing very pre... [Phys. Rev. C 86, 057303] Published Mon Nov 19, 2012

Description: Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 20011. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds NRC [2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path and the "semi-direct" effect on cloud coverage. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect, is even more complex, especially for mixed-phase convective clouds. ln this paper, a cloud-resolving model (CRM) with detailed spectral-bin microphysics was used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: South Florida, Oklahoma and the Central Pacific. In all three cases, rain reaches the ground earlier for the low CCN (clean) case. Rain suppression is also evident in all three cases with high CCN (dirty) case. However, this suppression only occurs during the first hour of the simulations. During the mature stages of the simulations, the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case, to almost no effect in the Florida case, to rain enhancement in the Pacific case. These results show the complexity of aerosol interactions with convection.

Description: Over the past twenty years, rainfall retrieval algorithms have been developed to retrieve rainfall and vertical hydrometeor structures from passive microwave observations by making use of the fact that weighting functions for various frequencies peak at different levels within a rainy atmosphere. GPROF is one of two TMI rainfall algorithms. It is physically based retrieval that finds the vertical hydrometeor profile that best fits the brightness temperatures in the available passive radiometer channels. Matching is achieved using a library of hydrometeor profiles generated by cloud-resolving models (CRMs). The hydrometeor profiles have a corresponding surface precipitation rate. The algorithm retrieves the hydrometeor profiles and associated surface rainfall using a Bayesian approach that gives the estimated expected values. The ability of CRMs to produce cloud structures that are reliable and representative of observed storms is crucial for the success of GPROF. The cloud mycrophysics are one of the keys to achieving this. In addition, CRMs have been a very useful tool for GPM-algorithm developers through Cloud-Radiation Simulations (CRS), one of the nine GPM disciplinary research themes. This paper will discuss how to generate consistent and comprehensive 4D cloud datasets from an improved (i.e., in regard to bulk and multi-moment microphysics) CRM for TRMM and GPM rainfall retrieval algorithm developers. These cloud datasets include CRM-simulated clouds and cloud systems from different geographic locations in the tropics and midlatitudes. By linking the CRM with a passive microwave radiative-transfer model and using satellite and airborne data, the performance of the "cloud physics" can be assessed and in turn modified and improved. This paper will also address how to assess and improve the performance of various latent and diabatic heating algorithms and develop an algorithm to retrieve the vertical structure of apparent moistening (Q2). Considering that the GPM will produce high (temporal and spatial) resolution heating and rainfall data, these algorithms will be used to obtain the temporal and spatial distributions of surface rainfall and the associated vertical heating and moistening profiles throughout the subtropical and midlatitudes.

Description: Cloud physics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distribution below the clouds. Therefore, the size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral--bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Description: Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Description: Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.