Collaborative Research: Optimized Deployment of Antarctic Surface Weather Observations

合作研究：南极表面天气观测的优化部署

• 批准号: 1542766
• 负责人: Gregory Hakim
• 金额: $ 35.14万
• 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: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1542766&HistoricalAwards=false
• 关键词: Collaborative; Research; Optimized; Deployment; Antarctic

Numerical experiments are to be used to test probabilistic predictions as to the optimal and sub-optimal siting of surface Automated Weather Station (AWS) observations in Antarctica. Sensor placement is a generic problem across the goesciences, and this project may have far-reaching impact as to fidelity and cost of observational networks. In particular, problems where measurements are difficult to obtain and/or expensive may be prioritized objectively with the approach tested here. If successful, this research provides the basis for an objectively optimized augmentation or re-configuration of the AWS network to meet climate monitoring (such as locating new or paleoclimate proxy records) and weather forecasting goals. 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, using both data denial and reconfiguration approaches.A related line of enquiry is to be an evaluation of the current locations of the active Antarctic radiosonde network, as judged by the network?s ability to account for tropospheric variance in archived AMPS forecast temperature data. Sonde measurements also may collocate with validation observations from infrared soundings from satellites, or GPS radio occultation.

数值试验将用于检验关于南极洲地面自动气象站观测的最佳和次佳地点的概率预测。传感器放置是整个科学界的普遍问题，该项目可能对观测网络的保真度和成本产生深远影响。特别是，测量难以获得和/或昂贵的问题可以客观地优先考虑这里测试的方法。如果成功，这项研究将为客观优化AWS网络的增强或重新配置提供基础，以满足气候监测（例如定位新的或古气候代理记录）和天气预报目标。华盛顿大学和NCAR的研究人员将使用来自（存档的）南极中尺度预报系统（AMPS）的网格化数据，通过集合灵敏度理论优化现有AWS网络的空间相关长度尺度。 这些预测的最佳站的位置将反过来受到观测系统的实验，使用数据拒绝和重新配置的方法。的能力，占对流层方差存档AMPS预报温度数据。探空仪测量也可以与卫星红外探测或全球定位系统无线电掩星的验证观测配合使用。