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

在主要研究仪器计划（MRI）下，主要研究人员升级和改进了现有的天气观测网络，即俄克拉何马中网。Mesonet是一个国际公认的远程环境监测站网络。它由自1994年3月以来连续运作的114个场址组成。Mesonet的传感器从地面上10米延伸到地下75厘米，自投入使用以来，Mesonet已经存档了超过99.95%的观测数据（超过4500万次观测数据）。俄克拉何马州立法机构为网络的维护和运营提供主要资金。在MRI下完成的工作被称为俄克拉何马州大气表层仪器系统（OAISIS）项目。OASIS项目通过以下方式推进了中尺度和风暴尺度气象研究的前沿：(1)利用俄克拉荷马中尺度网络的114个运行站点建立了地面通量站系统；(2)开发新一代低功率、低成本和低维护的现场磨矿机，部署在嵌入mesonnetwork边界的42个站点的微网络站点上，这些站点位于小Washita流域（俄克拉荷马城西南）。由这些升级产生的新的、独特的数据集将解决许多以前由于缺乏观测而无法回答的关键问题。例如，对整个州地表能量预算的定量评估将为先进区域预测系统提供更好的初始化，该系统是由俄克拉荷马大学风暴分析和预测中心开发的，该中心是NSF科学技术中心之一。除其他优点外，这将允许在各种条件下测试表面能通量的相对重要性。从新开发的野外工厂获得的电场数据将能够调查风暴与风暴之间电活动的变化，以及电活动与风暴中其他气象观测的关系，例如雷达反射率。从基本和升级的中尺度和微尺度网络获得的数据将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.