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

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Abstract

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.

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Notes

  1. http://www.data.jma.go.jp/gmd/kaiyou/data/db/kaikyo/ocean/forecast/month.html

  2. Strictly, we used a development version of MRI.COM (ver.3.3) for the experiments in the paper, while JMA’s operation uses a stable version (ver.3.2). Nevertheless, the model performance is the same, since the configurations are identical.

  3. http://www.mirc.jha.or.jp/products/JTOPO30v2/

  4. http://kuroshio.eorc.jaxa.jp/ADEOS/mod_nrt/

  5. http://www.jodc.go.jp/data/coastal/obs_detail_data.htm

  6. http://www.japanriver.or.jp/publish/book/nenpyou_dvd.htm

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Acknowledgments

We thank the members of the oceanography and geochemistry research department of Meteorological Research Institute for fruitful discussions and helpful comments. This work was funded by MRI and was partly supported by JSPS KAKENHI Grant Number 24740323.

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Authors and Affiliations

  1. Meteorological Research Institute, Nagamine, Tsukuba, Ibaraki, 305-0052, Japan

    Kei Sakamoto, Goro Yamanaka, Hiroyuki Tsujino, Hideyuki Nakano, Shogo Urakawa & Norihisa Usui

  2. Global Environment and Marine Department, Japan Meteorological Agency, 1-3-4 Otemachi, Chiyoda-ku, Tokyo, 100-8122, Japan

    Mikitoshi Hirabara

  3. Fukuoka Regional Headquarters, Japan Meteorological Agency, 1-2-36 Obori, Chuou-ku, Fukuoka, 810-0052, Japan

    Koji Ogawa

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  1. Kei Sakamoto
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  2. Goro Yamanaka
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Correspondence to Kei Sakamoto.

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Responsible Editor: Emil Vassilev Stanev

This article is part of the Topical Collection on Coastal Ocean Forecasting Science supported by the GODAE OceanView Coastal Oceans and Shelf Seas Task Team (COSS-TT)

Appendix A: Improvement of the bottom topography

Appendix A: Improvement of the bottom topography

Our MRI.COM model imposes a minimum depth of 32 m due to a restriction of the sigma-z vertical coordinate (Fig. 1b). However, in the latest version of the MRI.COM (ver.4.0), shallower topography can be made by using the z∗ vertical coordinate (Adcroft and Campin 2004). Here, we investigate how this update affects the model performance in coastal regions, by executing an additional experiment, case SHALLOW. In SHALLOW, the z∗ coordinate is used to decrease the minimum depth from 32 to 9 m, and the bottom topography is improved to represent shallow regions in the Seto Inland Sea (Fig. 20b). The experimental settings are the same as CTL, except for the topography.

Fig. 20
figure 20

Mean SST in July 2010 in a CTL, b SHALLOW, and c the satellite observation. The black lines in (b) denotes an isobath of 20 m.

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In the result, SST shows clearly an impact of the topography improvement. Figure 20 shows SST in July, when temperature difference between CTL and SHALLOW is largest throughout the year. In CTL, SST is approximately 23∘C almost homogeneously in the Seto Inland Sea. In SHALLOW, SST is higher than 25∘ C in the regions shallower than 20 m (the black line in Fig. 20b) and shows inhomogeneous distribution reflecting the bottom topography. The satellite observation shows similar distribution that SST is relatively high in the shallow regions, indicating that SST in SHALLOW is more realistic than in CTL. In winter, SST in the shallow regions of SHALLOW is colder than in CTL, and SST becomes inhomogeneous as in summer. This is also similar to the satellite observation (not shown). These differences in the shallow regions are attributed to a decrease in the heat capacity, which results in faster and more sensitive response to atmospheric forcings. However, it should be noted that the RMSE against the coastal observation increases at some stations, though it decreases at other stations. As a result, the RMSE averaged over the 19 stations in the Seto Inland Sea decreases only slightly from 1.8 K in CTL to 1.7 K in SHALLOW.

As for SSH, though time variation is simulated differently from CTL, the RMSE against the coastal observation does not show systematic difference. The RMSE averaged over the 43 stations in the Seto Inland Sea is 7.9 cm in CTL and 7.8 cm in SHALLOW. The case SHALLOW does not produce an observable change for the annual mean current (Fig. 17) or progression of the water exchange (Fig. 19), either. On the other hand, the transport rate of the eastward mean flow through the Seto Inland Sea decreases significantly from 18.8×103 m3 s−1 to 7.7×103 m3 s−1, and the direction of the throughflow is inverted a few times a month. This seems more consistent with Kunii and Fujiwara (2006) than in CTL.

We conclude that good effects of the topography improvement are confirmed for SST and the transport rate of the throughflow. However, further tunings are needed to make a contribution to decrease in errors against coastal observations. On the basis of this result, we are developing a next version of the operational coastal model, using the z∗ coordinate.

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Sakamoto, K., Yamanaka, G., Tsujino, H. et al. Development of an operational coastal model of the Seto Inland Sea, Japan. Ocean Dynamics 66, 77–97 (2016). https://doi.org/10.1007/s10236-015-0908-9

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