Argo大洋观测资料的同化及其在短期气候预测和海洋分析中的应用

Argo Global Ocean Data Assimilation and Its Applications in Short-Term Climate Prediction and Oceanic Analysis

国际Argo(Array for Real-time Geostrophic Oceanography)计划的实施,提供了前所未有的全球深海大洋0～2000m水深范围内的海水温度和盐度观测资料,在大气和海洋科研业务中应用这一全新的资料,是深入认识大气和海洋变异、提高我国气候预测、海洋监测分析和预报能力的一个关键所在。通过开发非线性温-盐协调同化方案和利用同化高度计资料来调整模式的温度和盐度场,建立了可同化包括Argo等多种海洋观测资料的全球海洋资料变分同化系统,提高了对全球海洋的监测分析能力。实现了海洋资料同化系统与全球海气耦合模式的耦合,显著提高了短期气候预测水平。利用Argo资料改进了海洋动力模式中的物理过程参数化方案,有效提高了海洋模式对真实大洋的模拟能力和对厄尔尼诺/拉尼娜的预测能力。开发了利用Argo浮标漂流轨迹推算全球海洋表层和中层流的方法,提高了推算的全球表层流、中层流资料质量,有效弥补了洋流观测的匮乏。

The implementation of the international Array for Real-time Geostrophic Oceanography （Argo） Project facilitates unprecedented global ocean observations of sea-water temperature and salinity from the sea surface to a depth of 2000 m. Application of these new oceanic data in atmospheric and oceanic research and operation is essential for understanding the atmospheric and oceanic variability and increasing the accuracy of climate prediction and oceanic monitoring and analysis. The global ocean data assimilation systems are set up by developing a nonlinear temperaturesalinity coordinated assimilation scheme and adjusting the temperature and salinity on the basis of altimetry data, which enhances the monitoring and analyzing capability for the global ocean. The global ocean data assimilation systems are integrated with coupled atmosphere--ocean models, which increases the forecast skills for short-term climate prediction. Argo data are applied for improving physical parameterization schemes in oceanic models, and the model capability of describing the real oceans and forecasting E1 Nifio/Southem Oscillation is increased. A novel method has been developed for estimating surface and mid-layer ocean currents on the basis of the trajectories of Argo float drifting, which improves the accuracy of estimation of global surface and mid-layer ocean currents and makes up the insufficiency in observed ocean currents.