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Modern and prospective technologies for weather modification activities: Developing a framework for integrating autonomous unmanned aircraft systems

机译：用于天气变化活动的现代和前瞻性技术：开发集成无人驾驶飞机系统的框架

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摘要

This paper builds upon the processes and framework already established for identifying, integrating and testing an unmanned aircraft system (UAS) with sensing technology for use in rainfall enhancement cloud seeding programs to carry out operational activities or to monitor and evaluate seeding operations. We describe the development and assessment methodologies of an autonomous and adaptive UAS platform that utilizes in-situ real time data to sense, target and implement seeding. The development of a UAS platform that utilizes remote and in-situ real-time data to sense, target and implement seeding deployed with a companion UAS ensures optimal, safe, secure, cost-effective seeding operations, and the dataset to quantify the results of seeding. It also sets the path for an innovative, paradigm shifting approach for enhancing precipitation independent of seeding mode. UAS technology is improving and their application in weather modification must be explored to lay the foundation for future implementation. The broader significance lies in evolving improved technology and automating cloud seeding operations that lowers the cloud seeding operational footprint and optimizes their effectiveness and efficiency, while providing the temporal and spatial sensitivities to overcome the predictability or sparseness of environmental parameters needed to identify conditions suitable for seeding, and how such might be implemented. The dataset from the featured approach will contain data from concurrent Eulerian and Lagrangian perspectives over sub-cloud scales that will facilitate the development of cloud seeding decision support tools.
机译：本文建立在已经建立的过程和框架的基础上，该过程和框架用于识别，集成和测试具有传感技术的无人机系统（UAS），用于降雨增强云播种计划，以开展运营活动或监视和评估播种活动。我们描述了一种自主和自适应UAS平台的开发和评估方法，该平台利用现场实时数据来感测，确定目标并实施播种。 UAS平台的开发利用远程和现场实时数据来感测，目标化和实施与配套UAS一起部署的播种，可确保最佳，安全，可靠，具有成本效益的播种操作，并通过数据集来量化结果播种。它还为独立于播种模式的增加降水量的创新范式转移方法奠定了基础。 UAS技术正在进步，必须探索其在天气变化中的应用，为将来的实施奠定基础。更广泛的意义在于不断发展改进的技术并实现云播种操作的自动化，从而降低云播种操作的足迹并优化其有效性和效率，同时提供时空敏感性，以克服确定适合播种条件所需的环境参数的可预测性或稀疏性，以及如何实施。特有方法的数据集将包含同时发生的欧拉和拉格朗日观点的子云规模数据，这将有助于开发云种子决策支持工具。

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  • 来源
    《Atmospheric research》 |2017年第9期|173-183|共11页
  • 作者

    DeFelice T. P.; Axisa Duncan;

  • 作者单位

    Natl Ctr Atmospher Res, Res Applicat Lab, POB 3000, Boulder, CO 80307 USA;

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  • 正文语种 eng
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