[AAS06-P06] Global 7-km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7)
キーワード：typhoon, numerical weather prediction
The Global 7-km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7; Nakano et al. 2016) is designed to understand and statistically quantify the advantage of high-resolution nonhydrostatic global atmospheric models for improvement of tropical cyclone (TC) prediction. The 137 sets of 5-day simulations using three next-generation nonhydrostatic global models with horizontal resolution 7 km, and conventional hydrostatic global model with horizontal resolution 20 km are run on the Earth Simulator. The three 7-km mesh nonhydrostatic models are the nonhydrostatic global spectral atmospheric Model using Double Fourier Series (DFSM; Yoshimura, 2012), Multi-Scale Simulator for the Geoenvironment (MSSG; Takahashi et al., 2006, 2013), and Nonhydrostatic ICosahedral Atmospheric Model (NICAM; Satoh et al. 2014). The 20-km mesh hydrostatic model is the operational Global Spectral Model (GSM; Japan Meteorological Agency, 2013) of the Japan Meteorological Agency.
Compared with the 20-km mesh GSM, the 7-km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7-km mesh nonhydrostatic global models. While the three 7-km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20-km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improve the TC prediction.
References:
Japan Meteorological Agency: Outline of the operational numerical weather prediction at the Japan Meteorological Agency. Appendix to WMO technical progress report on the global data-processing and forecasting system and numerical weather prediction, 2013, 188p.http://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2013-nwp/index.htm.
Nakano, M., A. Wada, M. Sawada, H. Yoshimura, R. Onishi, S. Kawahara, W. Sasaki, T. Nasuno, M. Yamaguchi, T. Iriguchi, M. Sugi, and Y. Takeuchi: Global 7-km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7): Experimental design and preliminary results, Geosci. Model Dev. Discuss. 2016, under revision, doi:10.5194/gmd-2016-184.
Satoh, M., H. Tomita, H. Yashiro, H. Miura, C. Kodama, T. Seiki, A. T. Noda, Y. Yamada, D. Goto, M. Sawada, T. Miyoshi, Y. Niwa, M. Hara, T. Ohno, S. Iga, T. Arakawa, T. Inoue and H. Kubokawa: The Non-hydrostatic Icosahedral Atmospheric Model: description and development. Progress in Earth and Planetary Science 2014, 1:18. doi: 10.1186/s40645-014-0018-1
Takahashi, K., X. Peng, R. Ohnishi, T. Sugimura, M. Ohdaira, K. Goto. and H. Fuchigami: Multi-Scale Weather/Climate Simulations with Multi-Scale Simulator for the Geoenvironment (MSSG) on the Earth Simulator. Ann. Rep. Earth Simulator Center, 2006, April 2006–March 2007, pp.27–33, ISSN 1348–5822.
Takahashi K., R. Onishi, Y. Baba, S. Kida, K. Matsuda, K. Goto. and H. Fuchigami: Challenge toward the prediction of typhoon behaviour and down pour. J. Phys.: Conference Series, 2013, 454:012,072.
Yoshimura, H.: Development of a nonhydrostatic global spectral atmospheric model using double Fourier series. CAS/JSC WGNE Research Activities in Atmospheric and Ocean Modeling, 2012, 42, 3.05-3.06.
Compared with the 20-km mesh GSM, the 7-km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7-km mesh nonhydrostatic global models. While the three 7-km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20-km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improve the TC prediction.
References:
Japan Meteorological Agency: Outline of the operational numerical weather prediction at the Japan Meteorological Agency. Appendix to WMO technical progress report on the global data-processing and forecasting system and numerical weather prediction, 2013, 188p.http://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2013-nwp/index.htm.
Nakano, M., A. Wada, M. Sawada, H. Yoshimura, R. Onishi, S. Kawahara, W. Sasaki, T. Nasuno, M. Yamaguchi, T. Iriguchi, M. Sugi, and Y. Takeuchi: Global 7-km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7): Experimental design and preliminary results, Geosci. Model Dev. Discuss. 2016, under revision, doi:10.5194/gmd-2016-184.
Satoh, M., H. Tomita, H. Yashiro, H. Miura, C. Kodama, T. Seiki, A. T. Noda, Y. Yamada, D. Goto, M. Sawada, T. Miyoshi, Y. Niwa, M. Hara, T. Ohno, S. Iga, T. Arakawa, T. Inoue and H. Kubokawa: The Non-hydrostatic Icosahedral Atmospheric Model: description and development. Progress in Earth and Planetary Science 2014, 1:18. doi: 10.1186/s40645-014-0018-1
Takahashi, K., X. Peng, R. Ohnishi, T. Sugimura, M. Ohdaira, K. Goto. and H. Fuchigami: Multi-Scale Weather/Climate Simulations with Multi-Scale Simulator for the Geoenvironment (MSSG) on the Earth Simulator. Ann. Rep. Earth Simulator Center, 2006, April 2006–March 2007, pp.27–33, ISSN 1348–5822.
Takahashi K., R. Onishi, Y. Baba, S. Kida, K. Matsuda, K. Goto. and H. Fuchigami: Challenge toward the prediction of typhoon behaviour and down pour. J. Phys.: Conference Series, 2013, 454:012,072.
Yoshimura, H.: Development of a nonhydrostatic global spectral atmospheric model using double Fourier series. CAS/JSC WGNE Research Activities in Atmospheric and Ocean Modeling, 2012, 42, 3.05-3.06.