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首页> 外文期刊>Journal of the Atmospheric Sciences >An approach for convective parameterization with memory: Separating microphysics and transport in grid-scale equations
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An approach for convective parameterization with memory: Separating microphysics and transport in grid-scale equations

机译:带存储器的对流参数化方法:将微观物理学与网格尺度方程中的传输分开

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摘要

An approach for convective parameterization is presented here, in which grid-scale budget equations of parameterization use separate microphysics and transport terms. This separation is used both as a way to introduce into the parameterization a more explicit causal link between all involved processes and as a vehicle for an easier representation of the memory of convective cells. The equations of parameterization become closer to those of convection-resolving models [cloud-system-resolving models (CSRMs) and large-eddy simulations (LESs)], facilitating parameterization development and validation processes versus a detailed budget of these high-resolution models. The new Microphysics and Transport Convective Scheme (MTCS) equations are presented and discussed. A first version of a convective scheme based on these equations is tested within a single-column framework. The results obtained with the new scheme are close to those of traditional ones in very moist convective cases [ like the Global Atmospheric Research Programme ( GARP) Atlantic Tropical Experiment ( GATE) Phase III, 1974]. The simulation of more difficult drier situations [ European Cloud Systems Study/Global Energy and Water Cycle Experiment (GEWEX) Cloud System Studies (EUROCS/GCSS)] is improved through more memory due to higher sensitivity of simulated convection to dry midtropospheric layers; a prognostic relation between cloudy entrainment and precipitation evaporation dramatically improves the prediction of the phase lag of the convective diurnal cycle over land with respect to surface heat forcing. The present proposal contains both a relatively general equation set, which can deal continuously with dry, moist, and deep precipitating convection, and separate-and still crude-explicit moist microphysics. In the future, when increasing the complexity of microphysical computations, such an approach may help to unify dry, moist, and deep precipitating convection inside a single parameterization, as well as facilitate global climate model (GCM) and limited-area model (LAM) parameterizations in sharing the same formulation of explicit microphysics with CSRMs.
机译:这里介绍了一种对流参数化方法,其中参数化的网格规模预算方程使用单独的微观物理和输运项。这种分离既用作在参数化中引入所有相关过程之间更明确的因果关系的方式,又用作更容易表示对流细胞记忆的媒介。参数化的方程式更接近于对流解析模型[云系统解析模型(CSRM)和大涡流模拟(LESs)],从而简化了参数化开发和验证过程,而这些高分辨率模型的详细预算也不容错过。提出并讨论了新的微物理学和运输对流方案(MTCS)方程。在单列框架内测试了基于这些方程的对流方案的第一个版本。在非常潮湿的对流情况下,新方案获得的结果接近于传统方案[例如,1974年全球大气研究计划(GARP)大西洋热带实验(GATE)第三阶段]。由于更复杂的对流对干燥对流层的敏感性较高,因此可以通过更多的存储来改进对更干燥的情况的仿真[欧洲云系统研究/全球能源和水循环实验(GEWEX)云系统研究(EUROCS / GCSS)]。多云夹带和降水蒸发之间的预后关系极大地改善了地面对流昼夜周期相对于表面热强迫的相位滞后的预测。本建议书既包含一个相对通用的方程组,该方程组可以连续处理干燥,潮湿和深层降水对流,还可以包含分离的和仍然是显性的潮湿微物理学。将来,当增加微物理计算的复杂性时,这种方法可能有助于在单个参数化内统一干燥,潮湿和深层的对流,并促进全球气候模型(GCM)和有限区域模型(LAM)与CSRM共享相同的显式微物理学公式时进行参数化。

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