We have developed an ocean state nowcast/forecast system (JCOPE-T DA) that targets the coastal waters around Japan and assimilates daily remote sensing and in situ data. The ocean model component is developed based on the Princeton Ocean Model with a generalized sigma coordinate and calculates oceanic conditions with a 1/36-degree (2–3 km) resolution and an hourly result output interval. To effectively represent oceanic phenomena with a spatial scale smaller than 100 km, we adopted a data assimilation scheme that explicitly separates larger and smaller horizontal scales from satellite sea surface temperature data. Our model is updated daily through data assimilation using the latest available remote-sensing data. Here we validate the data assimilation products of JCOPE-T DA using various kinds of in situ observational data. This validation proves that the JCOPE-T DA model output outperforms those of a previous version of JCOPE-T, which is based on nudging the values of temperature and salinity toward those provided by a different coarse grid data-assimilated model JCOPE2M. Parameter sensitivity experiments show that the selection of horizontal scale separation parameters considerably affects the representation of sea surface temperature. Additional experiments demonstrate that the assimilation of daily-updated satellite sea surface temperature data actually improves the model’s efficiency in representing typhoon-induced disturbances of sea surface temperature on a time scale of a few days. Assimilation of additional in situ data, such as temperature/salinity/ocean current information, further improves the model’s ability to represent the ocean currents near the coast accurately.

中文翻译：

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使用每日同化遥感和原位数据的日本海岸临近预报/预报系统

我们开发了一个海洋状态临近预报/预报系统 (JCOPE-T DA)，该系统针对日本周围的沿海水域并吸收日常遥感和原位数据。海洋模型组件是基于普林斯顿海洋模型开发的，具有广义 sigma 坐标，并以 1/36 度（2-3 公里）的分辨率和每小时结果输出间隔计算海洋条件。为了有效地表示空间尺度小于 100 公里的海洋现象，我们采用了一种数据同化方案，将较大和较小的水平尺度与卫星海面温度数据明确分开。我们的模型每天通过使用最新可用遥感数据的数据同化进行更新。在这里，我们利用各种原位观测资料验证了 JCOPE-T DA 的资料同化产物。此验证证明 JCOPE-T DA 模型输出优于先前版本的 JCOPE-T，后者基于将温度和盐度值推向不同粗网格数据同化模型 JCOPE2M 提供的值。参数敏感性实验表明，水平尺度分离参数的选择对海面温度的表征有很大影响。额外的实验表明，每天更新的卫星海面温度数据的同化实际上提高了模型在几天时间尺度上表示台风引起的海面温度扰动的效率。同化额外的原位数据，例如温度/盐度/洋流信息，