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Comparison of a global-climate model simulation to a cloud-system resolving model simulation for long-term thin stratocumulus clouds

机译:长期薄层积云的全球气候模型模拟与云系统解析模型模拟的比较

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摘要

A case of thin, warm marine-boundary-layer (MBL) clouds is simulated by acloud-system resolving model (CSRM) and is compared to the same case ofclouds simulated by a general circulation model (GCM). In this study, thesimulation by the CSRM adopts higher resolutions which are generally used inlarge-eddy simulations (LES) and more advanced microphysics as compared tothose by the GCM, enabling the CSRM-simulation to act as a benchmark toassess the simulation by the GCM. Explicitly simulated interactions amongthe surface latent heat (LH) fluxes, buoyancy fluxes, and cloud-topentrainment lead to the deepening-warming decoupling and thereby thetransition from stratiform clouds to cumulus clouds in the CSRM. However, inthe simulation by the GCM, these interactions are not resolved and thus thetransition to cumulus clouds is not simulated. This leads to substantialdifferences in liquid water content (LWC) and radiation between simulationsby the CSRM and the GCM. When stratocumulus clouds are dominant prior to thetransition to cumulus clouds, interactions between supersaturation and clouddroplet number concentration (CDNC) (controlling condensation) and thosebetween rain evaporation and cloud-base instability (controlling clouddynamics and thereby condensation) determine LWC and thus the radiationbudget in the simulation by the CSRM. These interactions result in smallercondensation and thus smaller LWC and reflected solar radiation by clouds inthe simulation by the CSRM than in the simulation by the GCM where theseinteractions are not resolved. The resolved interactions (associated withcondensation and the transition to cumulus clouds) lead to better agreementbetween the CSRM-simulation and observation than that between theGCM-simulation and observation.
机译:通过云系统解析模型(CSRM)模拟了一个薄而温暖的海洋边界层(MBL)云的案例,并将其与由一般环流模型(GCM)模拟的同一云实例进行了比较。在这项研究中,与GCM相比,CSRM的模拟采用了大涡模拟(LES)和更先进的微观物理学中通常使用的更高分辨率,从而使CSRM仿真可以作为评估GCM的基准。显式模拟的表面潜热通量,浮力通量和云通量训练之间的相互作用导致加深-加热解耦,从而导致CSRM中从层状云向积云过渡。然而,在由GCM进行的模拟中,这些相互作用没有得到解决,因此没有模拟向积云的过渡。这导致CSRM和GCM在模拟之间的液态水含量(LWC)和辐射存在很大差异。当平流层积云在过渡为积云之前占主导地位时,过饱和度与云滴数浓度(CDNC)之间的相互作用(控制凝结)以及雨水蒸发和云层基体失稳之间的相互作用(控制云动力学从而凝结)决定了LWC,因此决定了由CSRM进行模拟。与没有解决这些相互作用的GCM模拟相比,这些相互作用导致较小的冷凝,从而导致较小的LWC和较小的云反射LWC和反射的太阳辐射。解析的相互作用(伴随着凝结和向积云的过渡)导致CSRM模拟和观测之间的一致性比GCM模拟和观测之间的一致性更好。

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