Molod Andrea, Hackert Eric, Vikhliaev Yury, Zhao Bin, Barahona Donifan, Vernieres Guillaume, Borovikov Anna, Kovach Robin M, Marshak Jelena, Schubert Siegfried, Li Zhao, Lim Young-Kwon, Andrews Lauren C, Cullather Richard, Koster Randal, Achuthavarier Deepthi, Carton James, Coy Lawrence, Freire Julliana L M, Longo Karla M, Nakada Kazumi, Pawson Steven
NASA, Goddard Space Flight Center, Greenbelt, MD 20771.
SSAI, Science Systems and Applications, Inc. Lanham, MD 20706.
J Geophys Res Atmos. 2020 Mar 16;125(5). doi: 10.1029/2019jd031767. Epub 2020 Feb 14.
The Global Modeling and Assimilation Office (GMAO) has recently released a new version of the Goddard Earth Observing System (GEOS) Sub-seasonal to Seasonal prediction (S2S) system, GEOS-S2S-2, that represents a substantial improvement in performance and infrastructure over the previous system. The system is described here in detail, and results are presented from forecasts, climate equillibrium simulations and data assimilation experiments. The climate or equillibrium state of the atmosphere and ocean showed a substantial reduction in bias relative to GEOS-S2S-1. The GEOS-S2S-2 coupled reanalysis also showed substantial improvements, attributed to the assimilation of along-track Absolute Dynamic Topography. The forecast skill on subseasonal scales showed a much-improved prediction of the Madden-Julian Oscillation in GEOS-S2S-2, and on a seasonal scale the tropical Pacific forecasts show substantial improvement in the east and comparable skill to GEOS-S2S-1 in the central Pacific. GEOS-S2S-2 anomaly correlations of both land surface temperature and precipitation were comparable to GEOS-S2S-1, and showed substantially reduced root mean square error of surface temperature. The remaining issues described here are being addressed in the development of GEOS-S2S Version 3, and with that system GMAO will continue its tradition of maintaining a state of the art seasonal prediction system for use in evaluating the impact on seasonal and decadal forecasts of assimilating newly available satellite observations, as well as to evaluate additional sources of predictability in the earth system through the expanded coupling of the earth system model and assimilation components.
全球建模与同化办公室（GMAO）最近发布了戈达德地球观测系统（GEOS）次季节到季节预测（S2S）系统的新版本GEOS-S2S-2，与之前的系统相比，该系统在性能和基础设施方面有了显著改进。本文详细描述了该系统，并展示了预报、气候平衡模拟和数据同化实验的结果。相对于GEOS-S2S-1，大气和海洋的气候或平衡状态偏差大幅降低。GEOS-S2S-2耦合再分析也显示出显著改进，这归因于沿轨绝对动力地形的同化。次季节尺度上的预报技巧显示，GEOS-S2S-2对马登-朱利安振荡的预报有了很大改进，在季节尺度上，热带太平洋地区的预报在东部有显著改进，在中部太平洋地区与GEOS-S2S-1的技巧相当。GEOS-S2S-2的地表温度和降水异常相关性与GEOS-S2S-1相当，且地表温度的均方根误差大幅降低。本文所述的其余问题正在GEOS-S2S第3版的开发中得到解决，通过该系统，GMAO将继续保持其维护最先进季节预测系统的传统，用于评估同化新获取的卫星观测资料对季节和年代际预报的影响，以及通过扩展地球系统模型和同化组件的耦合来评估地球系统中额外的可预报性来源。
