模块化海洋数据同化系统(MODAS)研究

模块化海洋数据同化系统(Modular Ocean Data Assimilation System,MODAS)是美国海军用来确定全球海洋三维温度和盐度场的主要工具。MODAS通过同化卫星遥感测得的海面温度和海面高度,产生一种动态气候态,能够更接近地预报出海洋的真实状况。文中介绍了MODAS的应用价值和构建原理,对中国海军数字化海洋战场环境的建设具有重要的借鉴作用。     

MODAS试验数据统计分析

模块化海洋数据同化系统（MODAS）通过同化卫星遥感测得的海面温度和海面高度,产生一种动态气候态,能够更接近地预报出海洋的真实状况。介绍了MODAS基本原理,并选择试验海区,对MODAS数据进行了统计和分析。     

Evaluation of the U.S. Navy’s Modular Ocean Data Assimilation System (MODAS) Using South China Sea Monsoon Experiment (SCSMEX) Data

The Navy’s Modular Ocean Data Assimilation System (MODAS) is an oceanographic tool to create high-resolution temperature and salinity on three-dimensional grids, by assimilating a wide range of ocean observations into a starting field. The MODAS products are used to generate the sound speed for ocean acoustic modeling applications. Hydrographic data acquired from the South China Sea Monsoon Experiment (SCSMEX) from April through June 1998 are used to verify the MODAS model. MODAS has the capability to provide reasonably good temperature and salinity nowcast fields. The errors have a Gaussian-type distribution with mean temperature nearly zero and mean salinity of −0.2 ppt. The standard deviations of temperature and salinity errors are 0.98°C and 0.22 ppt, respectively. The skill score of the temperature nowcast is positive, except at depth between 1750 and 2250 m. The skill score of the salinity nowcast is less than that of the temperature nowcast, especially at depth between 300 and 400, where the skill score is negative. Thermocline and halocline identified from the MODAS temperature and salinity fields are weaker than those based on SCSMEX data. The maximum discrepancy between the two is in the thermocline and halocline. The thermocline depth estimated from the MODAS temperature field is 10–40 m shallower than that from the SCSMEX data. The vertical temperature gradient across the thermocline computed from the MODAS field is around 0.14°C/m, weaker than that calculated from the SCSMEX data (0.19°–0.27 °C/m). The thermocline thickness computed from the MODAS field has less temporal variation than that calculated from the SCSMEX data (40–100 m). The halocline depth estimated from the MODAS salinity field is always deeper than that from the SCSMEX data. Its thickness computed from the MODAS field varies slowly around 30 m, which is generally thinner than that calculated from the SCSMEX data (28–46 m).     

卫星遥感SSH数据在水下温度垂直分布反演中的应用研究

结合MODAS基本原理,应用动态气候态的数据同化概念,阐述应用卫星遥感SSH数据反演水下温度垂直分布的理论和方法,并利用西太平洋海区的ARGO数据进行试验,建立了单点的温度剖面,通过引入SSH数据进行水温反演,演示结果显示了卫星遥感SSH资料同化的有效性,并得出分析结论。