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.

数值实验将用于测试对南极洲地面自动气象站（AWS）观测的最佳和次优选址的概率预测。传感器放置是整个地球科学的一个普遍问题，该项目可能会对观测网络的保真度和成本产生深远的影响。特别是，测量难以获得和/或昂贵的问题可以通过此处测试的方法客观地优先考虑。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奠定基础，以满足气候监测（例如查找新的或古气候代理记录）和天气预报的目标。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。 这些对最佳站点位置的预测反过来将受到观测系统实验的影响，使用数据否认和重新配置方法。相关的调查路线是对活跃的南极无线电探空仪网络的当前位置进行评估，根据该网络考虑存档的 AMPS 预测温度数据中的对流层方差的能力来判断。探空仪测量还可以与卫星红外探测或 GPS 无线电掩星的验证观测结果结合起来。