Review and Prospect of Global Operational Ocean Forecasting

The marine environmental forecast plays an increasingly important role in economic growth and infrastructure development, and touches upon many fields and aspects, including marine security, energy resources development and protection, ocean shipping and fisheries. Global Ocean Data Assimilation Experiment (GODAE) OceanView supports the national research groups providing them with coordination and technical support among the partners. Forecasting centers develop and establish global operational ocean forecast systems. The global operational ocean forecasting system uses the ocean dynamic numerical model as the dynamic framework, and the near real-time high-quality observation input field is integrated into the model by data assimilation to realize the future environmental forecasts of the marine conditions covering the multi-time scale. The products are routinely validated with observations in order to assess their quality. This paper briefly introduced and reviewed the development process and current situation of the global ocean forecasting system covered by GODAE OceanView, and outlined the future development of global ocean forecasting.     

Toward a global ocean data assimilation system based on ensemble optimum interpolation: altimetry data assimilation experiment

A global ocean data assimilation system based on the ensemble optimum interpolation (EnOI) has been under development as the Chinese contribution to the Global Ocean Data Assimilation Experiment. The system uses a global ocean general circulation model, which is eddy permitting, developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. In this paper, the implementation of the system is described in detail. We describe the sampling strategy to generate the stationary ensembles for EnOI. In addition, technical methods are introduced to deal with the requirement of massive memory space to hold the stationary ensembles of the global ocean. The system can assimilate observations such as satellite altimetry, sea surface temperature (SST), in situ temperature and salinity from Argo, XBT, Tropical Atmosphere Ocean (TAO), and other sources in a straightforward way. As a first step, an assimilation experiment from 1997 to 2001 is carried out by assimilating the sea level anomaly (SLA) data from TOPEX/Poseidon. We evaluate the performance of the system by comparing the results with various types of observations. We find that SLA assimilation shows very positive impact on the modeled fields. The SST and sea surface height fields are clearly improved in terms of both the standard deviation and the root mean square difference. In addition, the assimilation produces some improvements in regions where mesoscale processes cannot be resolved with the horizontal resolution of this model. Comparisons with TAO profiles in the Pacific show that the temperature and salinity fields have been improved to varying degrees in the upper ocean. The biases with respect to the independent TAO profiles are reduced with a maximum magnitude of about 0.25°C and 0.1 psu for the time-averaged temperature and salinity. The improvements on temperature and salinity also lead to positive impact on the subsurface currents. The equatorial under current is enhanced in the Pacific although it is still underestimated after the assimilation.     

Estimating the 4DVAR analysis error of GODAE products

We explore the ocean circulation estimates obtained by assimilating observational products made available by the Global Ocean Data Assimilation Experiment (GODAE) and other sources in an incremental, four-dimensional variational data assimilation system for the Intra-Americas Sea. Estimates of the analysis error (formally, the inverse Hessian matrix) are computed during the assimilation procedure. Comparing the impact of differing sea surface height and sea surface temperature products on both the final analysis error and difference between the model state estimates, we find that assimilating GODAE and non-GODAE products yields differences between the model and observations that are comparable to the differences between the observation products themselves. While the resulting analysis error estimates depend on the configuration of the assimilation system, the basic spatial structures of the standard deviations of the ocean circulation estimates are fairly robust and reveal that the assimilation procedure is capable of reducing the circulation uncertainty when only surface data are assimilated.     

21世纪初海洋预报系统发展现状和趋势

海洋预报是一切海上活动的基础,人类社会需求驱动着海洋预报的发展。海洋观测、数据同化、数值模拟和高性能计算机等技术的进步推动着全球海洋业务预报的发展。国际先进的海洋数值模式有NLOM、NCOM、HYCOM、NEMO、MOM、POM和ROMS等。在GODAE和GODAEOceanView项目期间,通过国际合作和交流,全球海洋业务预报系统得到快速发展。21世纪初,全球海洋预报系统水平分辨率最高达到1/32°,预报时效一般为一周,部分海洋预报系统能够预报诊断海洋涡旋和海洋锋等。未来海洋预报系统的分辨率和预报精度将继续提高,预报要素扩展到海洋生态和生物地球化学等学科。海洋数据同化技术、海洋物理过程参数化方案和模式耦合技术是推动海洋预报发展的重要研究方向。