Collaborative Research: Optimized Deployment of Antarctic Surface Weather Observations

数值试验将被用来检验关于南极地面自动气象站(AWS)观测的最佳和次最佳选址的概率预测。传感器布置是整个科学领域的一个普遍问题，这个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，对于难以获得和/或昂贵测量的问题，可以使用此处测试的方法客观地确定优先级。如果成功，这项研究将为AWS网络的客观优化扩充或重新配置提供基础，以满足气候监测(如定位新的或古气候代理记录)和天气预报目标。来自(存档)南极中尺度预报系统(AMPS)的格网数据将被华盛顿大学和NCAR的研究人员用来通过集合敏感性理论来优化现有AWS网络的空间相关长度尺度。这些最佳站点位置的预测将反过来受到观测系统实验的影响，使用数据否认和重新配置方法。一个相关的问题是评估活跃的南极无线电探空网的当前位置，正如该网络所判断的那样-S解释存档的AMPS预报温度数据中对流层变化的能力。探空仪测量也可以与来自卫星的红外探测或GPS无线电掩星的验证观测相结合。

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.