Collaborative Research: Tropical Waves and Intertropical Convergence Zones in Simulations with Explicit Convection

协作研究：显式对流模拟中的热带波和热带辐合带

基本信息

批准号：
1146701
负责人：
David Nolan
金额：
$ 26.95万
依托单位：
University of Miami
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2012
资助国家：
美国
起止时间：
2012-02-15 至 2015-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1146701&HistoricalAwards=false
关键词：
Collaborative Research Tropical Waves Intertropical

项目摘要

This collaborative project will employ models with explicit convection to study Intertropical Convergence Zones (ITCZ) over the oceans, their interactions with tropical waves, and the dependence of both on convective and mesoscale processes. The primary modeling tool will be the Weather Research and Forecast (WRF) system, which has been augmented to run either as a high-resolution nested tropical channel or as a lower-resolution model with a cloud-resolving model used as a "superparameterization" for convection. This unique model framework allows side-by-side comparisons of simulated ITCZs and convectively coupled waves using standard convection parameterizations, superparameterization, or cloud-resolving horizontal resolution. A suite of idealized cloud-resolving experiments will be performed to test the hypothesis that horizontal mixing by eddies tends to make the ITCZ broader and weaker than it would be in their absence.Convection-related tropical biases are a major source of error and uncertainty in global atmosphere models, so advances in understanding in this area should lead to improvements in a wide array of weather and climate applications. The project will support the education and training of an atmospheric sciences graduate student. The superparameterized version of the WRF model will eventually be made available to researchers in the broader atmospheric science community. Thus the broader impacts are substantial.

该协作项目将采用具有明确对流的模型来研究海洋中的热带收敛区（ITCZ），它们与热带波的相互作用以及对流和中尺度过程的依赖性。主要的建模工具将是天气研究和预测（WRF）系统，该系统已被扩展为作为高分辨率嵌套热带通道或具有云分辨模型的低分辨率模型运行，该模型用作对流的“超级参数”。这个独特的模型框架允许使用标准对流参数化，超级参数或云分辨率水平分辨率对模拟的ITCZ进行并排比较。将进行一套理想化的云解决实验，以测试以下假设：涡流的水平混合倾向于使ITCZ比缺席的ITCZ更广泛，更弱。与视觉相关的热带偏见是全球大气模型中的错误和不确定性的主要来源，因此在该领域的应用中，在该领域的范围内的进步范围很广。该项目将支持大气科学研究生的教育和培训。 WRF模型的超级参数化版本最终将提供给更广泛的大气科学界的研究人员。因此，更广泛的影响是巨大的。