The Goddard Earth Observing System composition forecast (GEOS‐CF) system is a high‐resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS‐CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space‐based and in‐situ observations. GEOS‐CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS‐Chem chemistry module to provide hindcasts and 5‐days forecasts of atmospheric constituents including ozone (O₃), carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and fine particulate matter (PM_2.5). The chemistry module integrated in GEOS‐CF is identical to the offline GEOS‐Chem model and readily benefits from the innovations provided by the GEOS‐Chem community. Evaluation of GEOS‐CF against satellite, ozonesonde and surface observations for years 2018–2019 show realistic simulated concentrations of O₃, NO₂, and CO, with normalized mean biases of −0.1 to 0.3, normalized root mean square errors between 0.1–0.4, and correlations between 0.3–0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO₂ and an overprediction of summertime O₃ over the Southeast United States. GEOS‐CF v1.0 generally overestimates aerosols by 20%–50% due to known issues in GEOS‐Chem v12.0.1 that have been addressed in later versions. The 5‐days forecasts have skill scores comparable to the 1‐day hindcast. Model skills can be improved significantly by applying a bias‐correction to the surface model output using a machine‐learning approach.

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NASA GEOS 成分预测建模系统 GEOS-CF v1.0 的说明

戈达德地球观测系统成分预测 (GEOS-CF) 系统是美国宇航局全球模拟和同化办公室 (GMAO) 的高分辨率 (0.25°) 全球成分预测系统。GEOS-CF 为大气化学研究提供了一种新工具，旨在补充 NASA 广泛的天基和现场观测。GEOS-CF 通过引入 GEOS-Chem 化学模块扩展了 GEOS 天气和气溶胶建模系统，提供臭氧 (O ₃ )、一氧化碳 (CO)、二氧化氮 (NO ₂ )等大气成分的后报和 5 天预报、二氧化硫 (SO ₂ ) 和细颗粒物 (PM _2.5 )。GEOS-CF 中集成的化学模块与离线 GEOS-Chem 模型相同，并且很容易受益于 GEOS-Chem 社区提供的创新。根据 2018-2019 年卫星、臭氧探空仪和地面观测结果对 GEOS-CF 进行的评估显示了 O ₃、NO ₂和 CO 的真实模拟浓度，归一化平均偏差为 -0.1 至 0.3，归一化均方根误差在 0.1-0.4 之间，相关性在 0.3–0.8 之间。与地面观测的比较突显了世界许多地区和所有季节的空气污染物的成功再现，但也突显了当前的局限性，例如 SO ₂的全球高偏差和美国东南部夏季 O ₃的高估。由于 GEOS-Chem v12.0.1 中的已知问题已在后续版本中得到解决，GEOS-CF v1.0 通常会高估气溶胶 20%–50%。5 天预测的技能得分与 1 天事后预测相当。通过使用机器学习方法对表面模型输出进行偏差校正，可以显着提高模型技能。