Download as PDF Authors
Affiliations
1 Japan Meteorological Business Support Center, Tokyo101-0054, Japan; k-saito@jmbsc.or.jp
2 Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa 277-8564, Japan; k_saito@aori.u.tokyo.ac.jp
3 Meteorological Research Institute, Japan Meteorological Agency, Tsukuba 305-0052, Japan; ksaito@mri-jam.go.jp
4 National Center for Hydro-Meteorological Forecasting, Hanoi 10000, Vietnam; maikhanhhung18988@gmail.com; duductien@gmail.com
*Corresponding author: k-saito@jmbsc.or.jp; Tel.: +813–55772178
Abstracts
We developed a prototype system of the very short-range forecast of precipitation in Vietnam by merging kinematic extrapolations of composite hourly rainfall analysis and NWP, verified its performance for the case of a heavy rainfall event in July 2021 over central Vietnam. First, we produced hourly composite rainfall analysis over Vietnam with a grid distance of 5 km using AWS, radar, and satellite data. Next, we computed lag correlations between two hourly rainfall intensities at specific templates of 50 × 50 grids, and obtained lag indexes that maximize the lag correlation at 11 × 10 points. The moving vectors of precipitation areas at all grids are obtained by Cressman interpolation of the lag indexes, and a quality check using NWP horizontal winds at 700 hPa level was applied. Kinematic extrapolation of rainfall analysis was conducted using the above moving vectors and was merged with hourly rainfall prediction by a regional NWP model at NCHMF of VNMHA (WRF3kmIFS-DA) by weighted averaging. The magnitude of weight for the NWP in the merger was linearly increased from 0 to 1 for FT = 2 to 6 (from 03 UTC to 07 UTC, 12 July 2021). Verifications showed that the merged rainfalls outperformed both NWP and kinematically extrapolated precipitations for the time range of FT = 3 to 5.
Keywords
Cite this paper
Saito, K.; Hung, M.K.; Tien, D.D. Development of a prototype system of the very short-range forecast of precipitation in Vietnam. J. Hydro-Meteorol. 2023, 15, 59-79.
References
1. Tonouchi, M.; Kasuya, Y.; Tanaka, Y.; Akatsu, K.; Akaeda, K.; Nguyen, V.T. Activities of JICA on disaster prevention and achievement of JICA project in Period 1. VN J. Hydrometeorol. 2020, 5, 1–12. Doi:10.36335/VNJHM.2020(5).1-12.
2. Mikami, M.; Ichijo, H.; Matsubara, M.; Nguyen, H.A.; Duc, L.X. A proposal of AWS maintenance and periodic calibration tools and installation of ARGs for Radar QPE calibration. VN J. Hydrometeorol. 2020, 5, 13–35. Doi: 10.36335/VNJHM.2020(5).1-35.
3. Kimpara, C.; Tonouchi, M; Hoa, B.T.K.; Hung, N.V.; Cuong, N.M.; Akaeda, K. Quantitative precipitation estimation by combining rain gauge and meteorological radar network in Vietnam. VN J. Hydrometeorol. 2020, 5, 36–50. Doi:10.36335/VNJHM.2020(5).36-50.
4. Saito, K.; Hung M.K.; Hung N.V.; Vinh N.Q.; Tien D.D. Heavy rainfall in central Viet Nam in December 2018 and modification of precipitation analysis at VNMHA. VN J. Hydrometeorol. 2020, 5, 65-79. Doi:10.36335/VNJHM.2020(5).65-79.
5. Hung, M.K.; Saito, K.; Khiem, M.V.; Tien, D.D.; Hung, N.V. Verification of GSMaP data in precipitation nowcasting at Vietnamese National Center for Hydro-Meteorological Forecasting. VN J. Hydrometeorol 2020, 5, 80–94. Doi: 10.36335/VNJHM.2020(5).80-94.
6. Kigawa, S. Analysis and forecasting techniques of high-resolution precipitation nowcasting. Sokko-jiho 2014, 81, 55–76. Available online: https://www.jma.go.jp/jma/kishou/books/sokkou/81/vol81p055.pdf. (In Japanese)
7. Saito, K.; Makihara, Y. On the very short range forecast of precipitation at JMA. J. Water Env. Japan 2007, 30(5), 230–235. Available online: https://www.jswe.or.jp/publications/journals/contents/2007/index.html) (In Japanese)
8. Tsujimura, Y. Modification of very short range forecast of precipitation. Forecasting Technology Training Textbook, JMA 2019, 24, 146–153. Available online at https://www.jma.go.jp/jma/kishou/books/yohkens/24/chapter7.pdf. (In Japanese)
9. Li, P.W.; Wong, W.K.; Cheung, P.; Yeung, H.Y. An overview of nowcasting development, applications, and services in the Hong Kong Observatory. J. Meteor. Res. 2014, 28, 859–876. Doi:10.1007/s13351-014-4048-9.
10. Japan Meteorological Agency website. https://www.jma.go.jp/jma/kishou/know/bosai/riskmap.html.
11. World Meteorological Organization. WMO guidelines on multi-hazard impact-based forecast and warning services. WMO No.1150. 2015, pp. 34. ISBN: 978-92-63-11150-0.
12. Kobayashi, R.; Duc, L.X.; Tien, P.M. Attempt to detect maintenance-need rain gauge station by double–mass analysis. J. Hydro-Meteorol. 2023, 15, 10–20.
13. Vicente, G.; Scofield, R.A.; Mensel, W.P. The operational GOES infrared rainfall estimation technique. Bull. Amer. Meteor. Soc. 1998, 79, 1881–1898. Doi:10.1175/1520-0477(1998)079<1883:TOGIRE>2.0.CO;2.
14. Rinehart, R.E.; Garvey, E.T. Three-dimensional storm motion detection by conventional weather radar. Nature 1978, 273, 287–289.
15. Hamada, T. Cloud wind estimation system summary of GMS system. Tech. Note Meteor. Satt. Cent. 1979, II–2, 14–42.
16. Takano, I.; Saito, K. Statisitical analyses of wind field obtained from short interval VISSR observations. Tech. Note Meteor. Satt. Cent. 1986, 14, 29–37.
17. Tavolate, C.; Isaksen, L. On the use of a Huber norm for observation quality control in the ECMWF 4D-Var. Quart. J. Roy. Meteor. Soc. 2015, 141, 1514–1527. Doi:10.1002/qj.2440.
18. Shimizu, S.; Ueda, H. Algorithm for the identification and tracking of convective cells based on constant and adaptive threshold methods using a new cell-merging and - splitting scheme. J. Meteor. Soc. Japan 2012, 90, 869−889. Doi:10.2151/jmsj.2012-602.