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首页> 外文期刊>Journal of Climate >An Improved Convective Ice Parameterization for the NASA GISS Global Climate Model and Impacts on Cloud Ice Simulation
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An Improved Convective Ice Parameterization for the NASA GISS Global Climate Model and Impacts on Cloud Ice Simulation

机译:NASA GIS全球气候模型的改进对流冰参数和对云冰仿真的影响

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Partitioning of convective ice into precipitating and detrained condensate presents a challenge for GCMs since partitioning depends on the strength and microphysics of the convective updraft. It is an important issue because detrainment of ice from updrafts influences the development of stratiform anvils, impacts radiation, and can affect GCM climate sensitivity. Recent studies have shown that the CMIP5 configurations of the Goddard Institute for Space Studies (GISS) GCM simulated upper-tropospheric ice water content (IWC) that exceeded an estimated upper bound by a factor of 2. Partly in response to this bias, a new GCM parameterization of convective cloud ice has been developed that incorporates new ice particle fall speeds and convective outflow particle size distributions (PSDs) from the NASA African Monsoon Multidisciplinary Analyses (NAMMA), NASA Tropical Composition, Cloud and Climate Coupling (TC4), DOE ARM-NASA Midlatitude Continental Convective Clouds Experiment (MC3E), and DOE ARM Small Particles in Cirrus (SPARTICUS) field campaigns. The new parameterization assumes a normalized gamma PSD with two novel developments: no explicit assumption for particle habit in the calculation of mass distributions, and a formulation for translating ice particle fall speeds as a function of maximum diameter into fall speeds as a function of melted-equivalent diameter. Two parameters (particle volume-and projected area-weighted equivalent diameter) are diagnosed as a function of temperature and IWC in the convective plume, and these parameters constrain the shape and scale of the normalized gamma PSD. The diagnosed fall speeds and PSDs are combined with the GCM's parameterized convective updraft vertical velocity to partition convective updraft condensate into precipitating and detrained components. A 5-yr prescribed sea surface temperature GCM simulation shows a 30%-50% decrease in upper-tropospheric deep convective IWC, bringing the tropical and global mean ice water path into closer agreement with CloudSat best estimates.
机译:对流冰沉淀和抑制的冷凝物的分配给了GCMS的挑战,因为分配取决于对流上升流的强度和微生物。这是一个重要问题,因为从上升流脱冰会影响层状砧座的发展,影响辐射,并且可以影响GCM气候敏感性。最近的研究表明,戈达德空间研究所(GISS)GCM的CMIP5配置(GISS)GCM模拟上层对流层冰水含量(IWC),其超过估计的上限为2.部分以回应这一偏差,一个新的已经开发了对流云冰的GCM参数化,其中包括来自美国宇航局非洲季风多学科分析(NAMMA),美国国家航空航天局的热带组合物,云和气候偶联(TC4),母鹿-NASA中型大陆对流云实验(MC3E),藤蔓母羊小颗粒(SPArticus)田野运动。新的参数化假设具有两种新的开发的标准化伽马PSD:颗粒习惯在计算质量分布中没有明确假设,以及用于将冰颗粒落速作为最大直径的函数转换为下降速度的配方作为熔化的函数。等效直径。在对流羽流中诊断为温度和IWC的函数(粒子体积和投影区域加权等效直径),这些参数限制了归一化伽马PSD的形状和比例。诊断出的秋季速度和PSD与GCM的参数化对流上升垂直速度相结合,以将对流上升凝结物凝结成沉淀和污染的组分。 5 yr规定的海表面温度GCM仿真显示上层对流层深度对流IWC减少30%-50%,使热带和全球平均冰水道与Cloudsat最佳估算更仔细。

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    《Journal of Climate》 |2017年第1期|共20页
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  • 正文语种 eng
  • 中图分类 气候学;
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