The OASIS Project: Oklahoma Atmospheric and Surface/Layer Instrumentation System

根据重大研究仪器计划(MRI)，首席研究人员升级和改进现有的被称为俄克拉荷马州中间网络的天气观测网络。Mesonet是一个国际公认的远程环境监测站网络。它由114个站点组成，自1994年3月以来一直在持续运营。由于传感器从地面以上10米延伸到地面以下75厘米，自调试以来，Mesonet已经记录了所有可能的观测(超过4500万次观测)的99.95%以上。俄克拉荷马州议会为该网络的维护和运营提供主要资金。在这项核磁共振成像下完成的工作被称为俄克拉荷马州大气和表层仪器系统(OAISIS)项目。绿洲项目通过以下方式推动了中尺度和风暴尺度气象研究的前沿：(1)利用俄克拉荷马州中间网络的114个作业地点开发地面通量站系统；(2)开发新一代低功率、低成本和低维护的野外磨浆机，部署在嵌入中间网络边界内并位于小沃希塔分水岭(俄克拉荷马市西南)内的微型站点的42个地点。这些升级产生的新的、独特的数据集将解决一些关键问题，这些问题以前没有得到今天的观测结果的解答。例如，对整个州地表能量预算的定量评估将为高级区域预测系统提供更好的初始化，该系统由美国国家科学基金科学和技术中心之一俄克拉荷马大学风暴分析和预测中心开发。除其他优点外，这将允许测试各种条件下表面能通量的相对重要性。来自新开发的野外研磨机的电场数据将能够调查风暴之间电活动的变化，以及风暴中电活动与其他气象观测数据的关系，如雷达反射率。从基本和升级的中微网络获得的数据将被存档并提供给研究界。

Under the Major Research Instrumentation Program (MRI), the Principal Investigators upgrade and improve an existing weather observational network known as the Oklahoma Mesonetwork. The Mesonet is an internationally recognized network of remote environmental-monitoring stations. It consists of 114 sites that have operated continuously since March of 1994. With sensors that extend from 10 m above ground to 75 cm below ground, the Mesonet has archived more than 99.95% of all observations possible since commissioning (over 45 million observations). The Oklahoma Legislature provides primary funding for the maintenance and operation of the network. The work accomplished under this MRI is termed the Oklahoma Atmospheric & Surface-layer Instrumentation System (OAISIS) Project. The OASIS Project advances the frontier of mesoscale and storm-scale meteorological research by: (1) development of a system of surface-flux stations using the 114 operating sites in the Oklahoma Mesonetwork; (2) development of a new generation of low powered, low cost and low maintenance field mills, deployed over the 42 sites of a Micronetwork of stations embedded within the boundaries of the Mesonetwork and located within the Little Washita watershed (southwest of Oklahoma City). The new, unique data sets resulting from these upgrades will address a number of key questions not previously answered with today's lack of observations. For example, quantitative assessment of the surface energy budget for the entire state will provide better initialization for the Advanced Regional Prediction System, developed by the Center for Analysis and Prediction of Storms at the University of Oklahoma, one of the NSF Science and Technology Centers. This will allow, among other advantages, tests of the relative importance of surface energy fluxes under various conditions. Electric-field data from the newly developed field mills will enable investigations of variations in electrical activity from storm-to-storm, and relati ons of electrical activity to other meteorological observables in storms, such as radar reflectivity. Data acquired from the basic and upgraded Meso- and Micronetworks will be archived and made available to the research community.