Development of a Physically-based GCM Cloud Parameterization

这项研究的目的是继续发展 云及其辐射的物理参数化 大气环流模式（GCM）使用的相互作用。 的 将实施和测试改进的参数化方案 使用俄勒冈州州立大学7层大气GCM。 仔细和详细的疗效评估 将执行参数化程序。 云/ 辐射参数化可以减少海面误差 GCMS模拟的温度场，并将使 潜在关键云的定量测定 光学深度反馈过程的数值实验 气候变化是由于大气中二氧化碳的增加。 施莱辛格博士还将涉及两名本科生 (Ms.博加尔和毕晓普女士）在与此相关的研究任务中 格兰特. Bogar女士将协助分析 GCM输出中的变异性信号。 毕晓普女士将致力于 前一次间冰期气候条件模拟 (115 000年前）。 除了获得技术研究 经验，这两个本科生将受益于工作下 密切监督PI并与其他 研究生和程序员。

The objective of this research is to continue development of a physically-based parameterization of clouds and their radiative interaction for use by general circulation models (GCM's). The refined parameterization scheme will be implemented and tested using the Oregon State University 7-layer atmospheric GCM. Careful and detailed evaluation of the efficacy of the parameterization procedure will be carried out. This cloud/ radiation parameterization may reduce errors in the sea-surface temperature fields simulated by GCMS and will enable a quantitative determination of the potentially crucial cloud optical depth feedback process in numerical experiments of climate change due to increasing atmospheric carbon dioxide. Dr. Schlesinger will also involve two undergraduate students (Ms. Bogar and Ms. Bishop) in research tasks related to this grant. Ms. Bogar will asist in analyzing the inter-annual variability signal in GCM outputs. Ms. Bishop will work on modeling of climatic conditions during the previous interglacial (115,000 years ago). Besides gaining technical research experience, both undergraduates will benefit from working under close supervision of the PI and in collaboration with other graduate students and programmers.