随着人工智能技术的快速发展,AI在天气预报领域的应用已成为提升预报准确率的重要手段。本文深入介绍了国内AI中期预报大模型的最新研究成果与创新价值,具体聚焦于风乌气象大模型、伏羲气象大模型和华为盘古气象大模型。风乌模型通过多模态多任务学习方法、不确定性损失函数及重放缓冲机制,显著提升了预报的准确性和时效性,特别是在全球500 hPa位势高度和台风路径预报方面展现出卓越性能。伏羲模型则采用级联机器学习架构和纬度加权损失函数,优化了长期天气预报,尤其在对小到中等降水事件的预报上表现出色。华为盘古气象大模型凭借三维地球特定变换器和分层时间聚合算法,实现了高空气象变量和地表气象变量的高精度预测,同时在极端天气事件的预报上展现出强大能力。这些模型不仅提高了预报精度和效率,还减少了对高性能计算资源的依赖。本文还探讨了AI气象大模型与数值预报的互补关系,并对未来AI在气象预报领域的发展趋势进行了展望,强调了实时数据同化和极端天气模型构建的重要性。尽管AI气象大模型在常规气象预报方面取得了显著成果,但在极端天气事件预报、数据同化、高分辨率数据处理等方面仍面临挑战。这些研究成果和创新价值为气象预报领域的研究和实践提供了有价值的参考和启示。With the rapid development of artificial intelligence technology, AI has become an important means to improve the accuracy of weather forecasting. This article provides an in-depth introduction to the latest research achievements and innovative value of domestic AI mid-term forecasting models, focusing on the Wind Wu Meteorological Model, the Fuxi Meteorological Model, and Huawei’s Pangu Meteorological Model. The Wind Wu model, through multi-modal multi-task learning methods, uncertainty loss functions, and replay buffer mechanisms, has significan
气象海洋保障作为海上发射的重要环节,已经成为高密度海上发射的制约因素。本文分析了未来海上发射高密度的任务形势,归纳了海上发射气象海洋保障的特点,总结了当前海上发射气象海洋保障的现状及问题,最后提出了应对高密度海上发射气象海洋保障策略。提高参试人员及装备对海上发射任务的适应能力是完成海上发射任务和提供气象海洋保障的基础,建立基于“混合云”的联合气象海洋保障模式、制定海上发射气象海洋保障标准体系、打造高素质气象海洋人才队伍等是实现气象海洋优质高效保障的有效措施。Meteorological and oceanographic support is a crucial component of maritime launches and has become a limiting factor for high-density maritime launches. This paper analyzes the future situation of high-density maritime launch missions, summarizes the characteristics of meteorological and oceanographic support for maritime launches, reviews the current status and issues of meteorological and oceanographic support for maritime launches, and finally proposes strategies for meteorological and oceanographic support in response to high-density maritime launches. Enhancing the adaptability of personnel and equipment to maritime launch missions is fundamental to accomplishing these missions and providing meteorological and oceanographic support. Establishing a joint meteorological and oceanographic support model based on a “hybrid cloud” framework, developing a standard system for maritime launch meteorological and oceanographic support, and cultivating a high-quality team of meteorological and oceanographic personnel are effective measures to achieve high-quality and efficient support.
