North American Monsoon Experiment (NAME) Sounding Data Quality Control and Diagnostic Studies

北美季风实验（NAME）探测数据质量控制和诊断研究

• 批准号: 0639461
• 负责人: Richard Johnson
• 金额: $ 42.24万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0639461&HistoricalAwards=false
• 关键词: North; American; Monsoon; Experiment; NAME

This research is directed toward an improved understanding of key processes within the North American Monsoon System based on analyses of sounding data from the 2004 North American Monsoon Experiment (NAME). The objective of the research is to extend and expand initial investigations of NAME data to (1) improve the quality of the NAME sounding data archive by (a) adding pibal, surface, and research aircraft observations to the gridded analysis, and (b) correcting humidity sensor errors and subsequently incorporate those corrections into the sounding data archive and gridded analyses; and (2) conduct diagnostic studies of monsoon processes over the NAME domain using the improved gridded analysis fields. The intellectual merit of the research derives from the new understanding it will provide of the structural characteristics and physical processes associated with important North American monsoon phenomena. Among these are primary moisture sources for monsoon precipitation, jets and surges along the Gulf of California, tropical and midlatitude wave disturbances affecting the monsoon region, the diurnal cycle of convection, and heating and moistening of the atmosphere by deep convection. The NAME sounding dataset is unprecedented in its spatial and temporal resolution for this region, and therefore provides an opportunity for investigation of these phenomena with a detail heretofore not possible. The gridded analyses to be used to conduct these studies are independent of model data and consequently important diagnostic fields like divergence and vertical motion are not influenced by model parameterizations. The broader impacts of the research relate to how it will improve understanding and ultimately prediction of the North American monsoon system. The operational sounding network over Mexico both prior to and after the NAME field phase is very sparse, which limits its utility in documenting monsoon phenomena. NAME was a short, but important period of enhanced observations (among which soundings are only one component), and it should be fully exploited to provide new insights on monsoon processes. The effort to further improve the quality of the sounding data is important because this dataset will be made available to and be used by diagnosticians and the modeling community for many years to come as a source of analysis and validation in a tropical, coastal mountainous environment that is typical of other coastal regions where much of the world's heaviest precipitation occurs.

这项研究是针对2004年北美季风实验（NAME）的声音数据的分析来改善对北美季风系统中关键过程的理解。这项研究的目的是通过（a）通过（a）将PIBAL，表面和研究飞机的观测值扩展到（1）提高名称数据存档的质量并扩展到（1）在网格分析中的质量，以及（b）纠正湿度传感器错误，随后将这些更正纳入了声音数据库和网格数据存档和网格分析中； （2）使用改进的网格分析字段对季风过程进行季风过程的诊断研究。研究的智力优点源于它将提供与重要北美季风现象相关的结构特征和物理过程的新理解。 其中包括用于季风降水的主要水分来源，沿加利福尼亚湾的喷射和潮流，热带和中纬度波动扰动影响季风区域，对流的昼夜循环以及深度对流的加热和湿润。在该地区的空间和时间分辨率中，该名称的声音数据集是前所未有的，因此为调查这些现象提供了机会，迄今无法进行细节。用于进行这些研究的网格分析与模型数据无关，因此，诸如差异和垂直运动等重要的诊断领域不受模型参数化的影响。该研究的更广泛影响与它将如何改善对北美季风体系的理解和最终预测有关。在名称场阶段之前和之后，墨西哥上的运行声音网络非常稀疏，这限制了其在记录季风现象方面的效用。名称是一个简短但重要的观察结果时期（其中的声音仅是一个组件），应充分利用它以提供有关季风过程的新见解。为了进一步提高声音数据质量的努力很重要，因为该数据集将被诊断师和模型界使用多年来，并在未来多年的建模社区使用，以作为热带，沿海山区环境的分析和验证来源，这是世界上最大的大部分最大降水量发生的其他沿海地区的典型特征。