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

基本信息

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

项目摘要

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.

数值实验应用于测试概率预测，以了解南极洲表面自动气象站（AWS）观测值的最佳和最佳位置。传感器放置是整个过程中的通用问题，该项目可能对观察网络的忠诚度和成本具有深远的影响。特别是，在此处测试的方法可以客观地将测量值难以获得和/或昂贵的问题进行优先考虑。如果成功，这项研究为AWS网络的客观优化增强或重新配置提供了基础，以满足气候监控（例如，找到新的或古气候的代理记录）和天气预报目标。华盛顿大学和NCAR研究人员将使用来自（存档的）南极中尺度预测系统（AMP）的网格数据，以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。最佳站点放置的这些预测将依次受到观察系统实验的影响，同时使用数据否定和重新配置方法。相关的查询线是评估主动南极辐射网络的当前位置，该网络以该网络的能力计算了在存档的Ampospheric Amposper Ampast Ampast Ampast Ampast Perecast Preecast Preecast Proecast Procast Perecast Perecast proecast proecast procast network判断。 SONDE测量还可能与来自卫星或GPS无线电掩盖的红外响料的验证观察结果相关。