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Development of an operational coastal model of the Seto Inland Sea, Japan

机译：开发日本濑户内海沿岸作战模型

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We have developed a coastal model of the Seto Inland Sea, Japan, for a monitoring and forecasting system operated by the Japan Meteorological Agency (JMA). We executed a hindcast experiment using reanalysis datasets for the atmospheric and lateral boundaries without ocean initialization by data assimilation. The seasonal variability is verified to be realistic by comparing sea surface temperature and salinity of the hindcast experiment with observations. With a horizontal resolution of approximately 2 km, the model represents explicitly various coastal phenomena with a scale of 10-100 km, such as the Kuroshio water intrusion into Japanese coasts. This leads to good representation of intramonthly variations. For example, intensity of the sea level undulations with a period shorter than 23 days shows 1.6-fold improvement, as compared to the present model of JMA with the horizontal resolution of approximately 10 km. In addition to the increased resolution, the model is optimized for coastal modeling as follows. Incorporation of a tidal mixing parameterization reduces a high temperature bias in the Bungo Channel (a western channel of the Seto Inland Sea) and contributes to formation of a frontal structure. An accurate dataset of the river discharges is used for runoff, which has a strong impact on salinity. Enhancement of coastal friction improves surface currents. Owing to the increased resolution and these optimizations, the model shows realistic variability in a wide temporal range from several days to seasons. Root-mean-square errors of sea surface temperature and heights are evaluated as 1-2 K and 7-10 cm, respectively, without data assimilation. In the eastern part, however, the predictability is relatively low, which might be related to representation of an eastward mean flow in the Seto Inland Sea.
机译：我们已经开发了日本濑户内海的沿海模型，用于由日本气象厅（JMA）运营的监视和预报系统。我们使用重新分析数据集对大气和横向边界进行了一次后验实验，而没有通过数据同化来初始化海洋。通过将后预报实验的海表温度和盐度与观测值进行比较，证明季节性变化是现实的。该模型的水平分辨率约为2 km，可明确表示10-100 km范围内的各种海岸现象，例如黑潮对日本海岸的入侵。这样可以很好地代表月内变化。例如，与JMA的当前模型（水平分辨率约为10 km）相比，短于23天的海平面起伏强度显示出1.6倍的改善。除了提高分辨率外，该模型还针对海岸建模进行了如下优化。潮汐混合参数化的结合减少了邦戈河道（濑户内海的西部河道）中的高温偏差，并有助于形成锋面结构。准确的河流流量数据集用于径流，这对盐度有很大影响。沿海摩擦力的增强改善了表面流。由于提高了分辨率和进行了优化，该模型显示了从几天到季节的宽广时间范围内的实际可变性。没有数据同化的情况下，海面温度和高度的均方根误差分别估计为1-2 K和7-10 cm。但是在东部，可预测性相对较低，这可能与濑户内海向东的平均流量的表示有关。

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