Land-Atmosphere Interactions: A Core Program in Support of Community Climate Models

ATM-9419715，罗伯特·E·狄金森，亚利桑那州大学题目：陆地-大气相互作用--支持社区气候模拟的核心计划这个项目的重点是在全球变化模型的背景下理解陆地和大气之间的相互作用并将其参数化。其目标是：通过数据分析、数值过程研究和模式模拟，从与陆面过程耦合的角度确定最重要的大气过程的作用；并在这些研究的基础上，为全球气候机制开发新的或改进的参数，在NCAR社区气候系统模式中实施和测试这些参数，并向NCAR气候模拟社区提供成功的参数。这项建议汇集并支持了一支强大的研究团队，他们具有广泛的背景和经验，每个人都具有重要的个人技能。拟议的工作将：扩大对导致陆地-大气耦合的过程的基本理解；确定这些过程在NCAR社区模式中如何运行；确定这些过程与其他具有类似优点的气候模型中的过程有何不同；确定如何有必要进行这些观测、敏感性研究和模型相互比较，以澄清不同参数化的相对正确性；并开发在全球气候变化框架下适用于科学界未来改进和升级的指示的新的处理方法。为实现这些目标而设计的个别次级项目包括：研究地表与行星边界云之间的相互作用；云辐射通量的特征及其与陆地表面的耦合；全球气候机制中中尺度环流的影响的参数化，包括潮湿过程、云和降水；观测特征云性质、大气热力学性质和土地覆盖之间的关系；观测亚马逊砍伐森林对云过程的影响；进一步探索亚马逊砍伐森林对气候的影响，以更好地了解陆地与地表的相互作用；以及古气候联系。这些研究将使用卫星、无线电探空仪和地面数据进行观测分析。卫星数据分析将着重使用高分辨率(30公里)ISCCP数据的地方档案。他们还将使用中尺度和全球气候模型的集成，后者的重点是NCAR社区模型。理论和参数分析将使用中尺度模式积分和各种一维对流参数。拟议的工作将极大地促进对使用NCAR气候系统模型预测未来气候的理解和信心。这将通过促进在气候模拟的科学理解和实际方面来看，目前可以说是模型性能最薄弱的方面之一的重大进展来实现。拟议研究的实施将为一代研究生和博士后实习生提供关于这些问题的培训和教育。该奖项是根据USGCRP气候建模、分析和预测(CMAP)项目颁发的。

Abstract ATM-9419715 Dickinson, Robert E. University of Arizona Title: Land-Atmosphere Interactions - A Core Program in Support of Community Climate Modeling This project focuses on understanding and parameterizing the interactions between land and the atmosphere in the context of global change models. Its objectives are: to establish, through data analyses, numerical process studies and model stimulations, the function of the most important atmospheric processes, from the viewpoint of coupling to land-surface processes; and on the basis of these studies, to develop new or improved parameterizations for GCMs, implement and test these parameterizations in NCAR community climate system models, and provide successful parameterizations to the NCAR climate modeling community. This proposal brings together and supports a strong research team with a wide variety of background and experience, each with important individual skills. The proposed work will: expand the basic understanding of the processes responsible for land-atmosphere coupling; determine how these operate in NCAR community models; determine how these processes differ, if they do, from those in other climate models of comparable merit; determine how these observations, sensitivity studies, and model intercomparisons are necessary to clarify the relative correctness of differing parameterizations; and develop indicated new treatments that are suitable, in the context of GCM's, for future improvements and upgrades by the scientific community. Individual subprojects designed to pursue these objectives include: studies of interactions between the land surface and clouds in the planetary boundary (PBL); characterization of cloud radiative fluxes and their coupling to the land surface; parameterization of the effects of mesoscale circulations in a GCM, including moist processes, clouds and precipitation; observation characterization of relationships between cloud properties, atmospheric thermodynamics propert ies, and land cover; observational search for effects of Amazon deforestation on cloud processes; further exploration of climate effects of Amazon deforestation to better understand land-surface interactions; and paleoclimatic linkages. These studies will use satellite, radiosonde, and surface data for their observational analyses. Satellite data analyses will emphasize the use of a local archive of high-resolution (30 km) ISCCP data. They will also use integrations of mesoscale and global climate models, with an emphasis for the latter on NCAR community models. Theoretical and parameterizations analyses will use mesoscale model integration and various 1-D convection parameterizations. The proposed work will contribute substantially to great understanding of and confidence in the use of NCAR climate system models for projections of future climate. This will be done by promoting major advances in what is arguably now one of the weakest aspects of model performance from the viewpoint of scientific understanding and practical aspects of climate simulation. The performance of the proposed research will provide training and education on these questions for a generation of graduate students and post-doctoral trainees. This award is under the USGCRP, Climate Modeling, Analysis and Prediction (CMAP) project.