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US-India Cooperative Research: Studies of Mesoscale (beta and gamma) Weather Systems over Indian Region Using Regional Atmospheric Modelling System of Colorado State University

美印合作研究：利用科罗拉多州立大学区域大气模拟系统研究印度地区中尺度（β 和 γ）天气系统

基本信息

批准号：
9977991
负责人：
William Cotton
金额：
$ 0.45万
依托单位：
Colorado State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
1999
资助国家：
美国
起止时间：
1999-09-01 至 2002-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=9977991&HistoricalAwards=false
关键词：
US India Cooperative Research Studies

项目摘要

9977991Cotton Description: This award supports the US-India Cooperative Research: Studies of Mesoscale Weather Systems over the Indian Region Using Regional Atmospheric Modeling System (RAMS) of Colorado State University (CSU). US PI William Cotton, Colorado State University will collaborate with Indian PI S.S. Singh, Indian Institute of Tropical Meteorology (IITM). Using RAMS for the Indian sub-continent, the researchers expect to identify-- predictability of mesoscale weather systems, entrainment in the boundary layer, and mechanisms controlling diurnal variations in precipitation during monsoon months. Scope: Colorado State will host the Indian co-PI to acquaint that person with RAMS and the US PI will visit the IITM to present lectures on applications of RAMS. Colorado State is the developer of the RAMS computer model and has the resources to perform complex simulations of weather systems. The IITM scientists are very experienced with weather systems over the Indian sub-continent and have identified key unknowns in our understanding of those weather systems. This collaboration is likely to make a major contribution to our understanding of weather systems in that region and identify how predictions can be improved upon.

棉花描述：该奖项支持美印合作研究：使用科罗拉多州立大学(CSU)的区域大气模拟系统(RAMS)对印度地区中尺度天气系统的研究。美国科罗拉多州立大学的皮威廉·科顿将与印度热带气象研究所(IITM)的印度派·S·S·辛格合作。利用印度次大陆的RAMS，研究人员希望确定--中尺度天气系统的可预测性、边界层中的夹带以及控制季风月降水量日变化的机制。范围：科罗拉多州将主办印度联合PI，以使此人了解RAMS，而美国PI将访问IITM，介绍RAMS的应用。科罗拉多州立大学是RAMS计算机模型的开发商，拥有执行复杂天气系统模拟的资源。IITM的科学家对印度次大陆上的天气系统非常有经验，并在我们对这些天气系统的理解中确定了关键的未知数。这种合作可能会对我们了解该地区的天气系统做出重大贡献，并确定如何改进预报。