Chilson Phillip B, Bell Tyler M, Brewster Keith A, Britto Hupsel de Azevedo Gustavo, Carr Frederick H, Carson Kenneth, Doyle William, Fiebrich Christopher A, Greene Brian R, Grimsley James L, Kanneganti Sai Teja, Martin Joshua, Moore Andrew, Palmer Robert D, Pillar-Little Elizabeth A, Salazar-Cerreno Jorge L, Segales Antonio R, Weber Mark E, Yeary Mark, Droegemeier Kelvin K
School of Meteorology, University of Oklahoma, Norman, OK 73072, USA.
Center for Autonomous Sensing and Sampling, University of Oklahoma, Norman, OK 73072, USA.
Sensors (Basel). 2019 Jun 17;19(12):2720. doi: 10.3390/s19122720.
The deployment of small unmanned aircraft systems (UAS) to collect routine in situ vertical profiles of the thermodynamic and kinematic state of the atmosphere in conjunction with other weather observations could significantly improve weather forecasting skill and resolution. High-resolution vertical measurements of pressure, temperature, humidity, wind speed and wind direction are critical to the understanding of atmospheric boundary layer processes integral to air-surface (land, ocean and sea ice) exchanges of energy, momentum, and moisture; how these are affected by climate variability; and how they impact weather forecasts and air quality simulations. We explore the potential value of collecting coordinated atmospheric profiles at fixed surface observing sites at designated times using instrumented UAS. We refer to such a network of autonomous weather UAS designed for atmospheric profiling and capable of operating in most weather conditions as a 3D Mesonet. We outline some of the fundamental and high-impact science questions and sampling needs driving the development of the 3D Mesonet and offer an overview of the general concept of operations. Preliminary measurements from profiling UAS are presented and we discuss how measurements from an operational network could be realized to better characterize the atmospheric boundary layer, improve weather forecasts, and help to identify threats of severe weather.
部署小型无人机系统(UAS)以结合其他气象观测收集大气热力学和运动学状态的常规现场垂直剖面数据,可显著提高天气预报的技能和分辨率。对压力、温度、湿度、风速和风向进行高分辨率垂直测量,对于理解大气边界层过程至关重要,这些过程是空气与地表(陆地、海洋和海冰)之间能量、动量和水分交换不可或缺的一部分;它们如何受到气候变化的影响;以及它们如何影响天气预报和空气质量模拟。我们探讨了在指定时间使用装备仪器的无人机在固定地面观测站点收集协调一致的大气剖面数据的潜在价值。我们将这样一个为大气剖面测量而设计、能够在大多数天气条件下运行的自主气象无人机网络称为三维中尺度观测网。我们概述了一些推动三维中尺度观测网发展的基本且具有重大影响的科学问题和采样需求,并对其总体运行概念进行了概述。文中展示了剖面测量无人机的初步测量结果,并讨论了如何实现来自运行网络的测量,以更好地表征大气边界层、改善天气预报,并有助于识别恶劣天气的威胁。