Optimal deployment of the Antarctic surface weather observing network

南极地面天气观测网优化部署

• 批准号: 1043090
• 负责人: Gregory Hakim
• 金额: $ 58.62万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-01 至 2017-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1043090&HistoricalAwards=false
• 关键词: Optimal; deployment; Antarctic; surface; weather

The Antarctic continent, its surrounding ocean and atmosphere are a vastly under observed region of the planet. Environmental observing systems have often historically been sited on largely subjective grounds, including logistic convenience and simple accessibility. As environmental observing networks such as those Antarctic Automated Weather Stations (AAWS) are increasingly being relied upon for operational (e.g. numerical weather prediction), weather research (e.g. mesoscale meteorology, ecosystem change) and climate (e.g. ice mass balance; climate variability and change) studies, more objective considerations are needed for the economical and effective retention or expansion of limited observing assets. Emerging theory from network design offers the basis for some objective guidance in this area. Gridded data from (archived) Antarctic Mesoscale Prediction Systems (AMPS) will be used by University of Washington and NCAR researchers to optimize the spatial correlation length scales for the existing AWS network via ensemble sensitivity theory. These predictions of optimal station placement will in turn be subject to observing systems experiments (OSE) and observing system simulation experiments (OSSE), using both data denial and reconfiguration approaches. Results of this research may inform the placement of the most spatially representative locations of AWS stations for both meteorology (e.g. NWP) and climate related studies. A graduate student and a post-doctoral associate will be involved in this interdisciplinary problem.

南极大陆及其周围的海洋和大气是地球上一个被严重忽视的区域。历史上，环境观测系统的选址往往很大程度上是基于主观的考虑，包括后勤便利性和简单的可达性。 随着南极自动气象站（AAWS）等环境观测网络越来越多地被依赖于运营（例如数值天气预报）、天气研究（例如中尺度气象学、生态系统变化）和气候（例如冰块平衡；气候变率和变化） ）研究表明，为了经济有效地保留或扩大有限的观测资产，需要更客观的考虑。网络设计的新兴理论为该领域的一些客观指导提供了基础。华盛顿大学和 NCAR 研究人员将使用来自（已存档）南极中尺度预测系统 (AMPS) 的网格数据，通过集合敏感性理论优化现有 AWS 网络的空间相关长度尺度。 这些对最佳站点放置的预测反过来将受到观测系统实验（OSE）和观测系统模拟实验（OSSE）的影响，使用数据否认和重新配置方法。这项研究的结果可以为气象学（例如 NWP）和气候相关研究中最具空间代表性的 AWS 站位置的放置提供信息。一名研究生和一名博士后将参与这个跨学科问题。