气象高性能计算环境中模式协同研发管理

面向气象科学的数值预报模式的研发过程是一个多学科交叉、持续改进型的复杂系统工程。在地球系统模式、E级计算和后摩尔时代的发展趋势下，气象数值模式研发协同面临更复杂的协同、更专业的计算平台调试分析、更广泛的共享应用等挑战。从以上需求和挑战出发，在气象高性能计算环境中，采用Git分布式技术、Python及工作流技术，建设气象数值模式研发协同管理支撑环境和标准，实现模式协同研发过程的管理、成果的集成共享和研发调试试验及分析一体化的支撑，以提升模式研发协同效率和业务化效率，保障研发成果的完整性和可跟踪性，提升大规模科学软件研发的管理能力。应用效果表明，本研究规范化了模式研发的协同过程，并建立流畅的协同支撑环境，提升模式迭代升级和业务化效率，能够为科学研究、科学计算等大型传统科学计算模型的持续研发改进管理及软件工程协同管理提供借鉴。

R&D Collaborative Management of Meteorological Model in High Performance Computing

The process of numerical prediction model research and development is a multi-disciplinary complex system engineering. As Moore’s law approaches its limit , exascale computing is coming and with the trend of earth system, the R & D collaboration of meteorological numerical model faces more complex collaboration, more professional computing platform to debug, wider shared demand challenges. In view of the above challenges, application research has been carried out around the solution of collaborative management, R & D process, code integration and sharing, model debug and experiment test-bed in high-performance computing environment with Git, Python and workflow to improve the collaborative efficiency and operational efficiency. The results show that this research standardizes the R & D process and achievement management, supports the convenient R & D management, debugging and analysis, improves the efficiency of upgrading and operation, it can provide reference for large-scale traditional scientific research on high performance computing.