Constructing Rapid Refresh System for Rainfall Nowcasting (0-6 h) at the Ho Chi Minh City
Main Article Content
Abstract
This study presents an hourly updated assimilation and model forecast system (Rapid Refresh - RAP) designed for rainfall nowcasting at Ho Chi Minh city (named HCM-RAP). The HCM-RAP implemented the Weather Research and Forecasting (WRF) model, driven by Global Forecast System (GFS) data at horizontal resolution of 0.25x0.25 degree, in combination with rapid update of radar data at Nha Be station. The HCM-RAP is evaluated during the heavy rainfall event of 25-26 November 2018 against observation data at 10 stations. Results show the advantage of data assimilation in the improvement of hourly rainfall forecast, in compared with the forecast from the experiment without assimilated data. However, the rainfall forecast amount was still underestimated by the HCM-RAP. This is the first attempt for heavy rainfall forecasting and warning for Ho Chi Minh city. In order to implementing the HCM-RAP for operational forecast, further study is recommended, for instance, more heavy rainfall events and in merger with quantitative precipitation estimation from radar and satellite data.
Keywords:
Nowcasting, Rapid refresh, Ho Chi Minh city, WRF-DA.
References
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[4] S. G. Benjamin et al., An Hourly Assimilation Forecast Cycle: The Ruc, Mon. Wea. Rev., Vol. 132, 2014, pp. 495-518.
[5] S. G. Benjamin et al., A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh, Mon. Wea. Rev., Vol. 144, 2016, pp. 1669-1694, https://doi.org/10.1175/mwr-d-15-0242.1.
[6] P. Brousseau, Y. Seity, D. Ricard, J. Léger, Improvement of the Forecast of Convective Activity from the Arome France System, Q. J. R. Meteorol. Soc., Vol. 142, 2016, pp. 2231-2243, https://doi.org/10.1002/qj.2822.
[7] D. J. Kim, Recent Progresses in Convective-Scale and Next Generation Global Modeling at KMA, Wgne-31 Pretoria, South Africa, 26-29 April 2016.
[8] The CWB NWP Overview, https://www.cwb.gov.tw/V7/climate/climate_info/information/seminars/0507-1/03.pdf/ (accessed on: March 20th, 2020).
[9] J. O. Pinto, J. A. Grim, M. Steiner, Assessment of the High-Resolution Rapid Refresh Model’s Ability to Predict Mesoscale Convective Systems Using Object-Based Evaluation, Wea. Forecasting Vol. 30, No. 4, 2015, pp. 892-913, https://doi.org/10.1175/WAF-D-14-00118.1.
[10] P. Lynch, X. Y. Huang, Initialization of the HIRLAM Model Using a Digital Filter, Mon. Wea. Rev., Vol. 120 , 1992, pp. 1019-1034, https:// doi.org/10.1175/1520- 493.
[11] S. E. Peckham, T. G. Smirnova, S. G. Benjamin, J. M. Brown, J. S. Kenyon, Implementation of a Digital Filter Initialization in the WRF Model and Its Application in the Rapid Refresh, Mon. Wea. Rev., Vol. 144, No. 1, 2016, pp. 99-106, https://doi.org/10.1175/MWR-D-15-0219.1.
[12] B. M. Tang et al., Developing an Operational Heavy Rainfall Forecast System with 3-Day Leadtime in Reducing and Preventing Flooding-Related Disaster Over Central, Vietnam, the National Project KHDL-2014 Synthesis Report Funded by the Vietnamese Ministry of Science and Technology, 2014 (in Vietnamese).
[13] C. Thanh, T. D. Thuc, Radar Data Assimilation in WRF Model to Forecast Heavy Rainfall at Ho Chi Minh City, Journal of Science: Earth and Environmental Sciences, Vol. 34, No. 1S , 2018, pp. 59-70 (in Vietnamese).
[14] D. D. Tien et al., Assimilation of Dong Ha Radar Data for Improving Heavy Rainfall Forecast over the Central of Vietnam, Vietnam Journal of Hydrometeorology, No. 617, 2014, pp. 22-30 (in Vietnamese).
[15] H. D. Cuong et al., Developing an Operational Heavy Rainfall Forecast System for the Northern Part of Vietnam, The KC.08.06/16-20 Project Synthesis Report Funded by the Vietnamese Ministry of Science and Technology, 2019 (in Vietnamese).
[16] K. T. Xin et al., Study on the Prediction of the Large-Scale Heavy Rainfall for Flooding Prevention in Vietnam Using High Technology, the National Project KHDL-02/2002 Synthesis Report Funded by the Vietnamese Ministry of Science And Technology, 2005 (in Vietnamese).
[17] T. T. Tien, N. M. Truong, C. Thanh, K. Q. Chanh, RAMS’s Application to Simulate Heavy Rainfall in the Central Vietnam in September 2002, VNU Journal of Science, No. 3S, 2004, pp. 51-60
(in Vietnamese).
[18] V. T. Hang, K. T. Xin, Forecasting Heavy Rainfall in the Central Vietnam Using Heise Convective Parameterization Scheme for HRM Model, Vietnam Journal of Hydrometeorology, No. 560, 2007, pp. 49-54 (in Vietnamese).
[19] H. M. Hien, N. V. Thu, The Application of GMS-5 Products for Rainfall Validation. Vietnam Journal of Hydrometeorology, No. 479, 2000, pp. 30-35 (in Vietnamese).
[20] N. T. T. Thanh et al., The Study on the Very Short-Range Precipitation Forecasting and Thunderstorms Warning, The Ministerial-Level Report, Funded by Ministry of Natural Resources and Environment, 2010 (in Vietnamese).
[21] W. C. Skamarock et al., A Description of the Advanced Research WRF Version 3, NCAR Tech, Note NCAR/TN-4751STR, 2008, pp. 113.
[22] T. Schwitalla, W. Volker, Radar Data Assimilation Experiments Using the IPM WRF Rapid Update Cycle, Meteorologische Zeitschrift, Vol. 23, No. 1, 2014, pp. 79-102, https://doi.org/10.1127/0941-2948/2014/0513.
[23] D. F. Parrish, J. C. Derber, The National Meteorological Center’s Spectral Statistical-Interpolation Analysis System, Mon. Wea. Rev., Vol. 120, 1992, pp. 1747-1763.
[24] National Centers for Environmental Prediction/National Weather Service/NOAA/U.S, Department of Commerce, 2015. NCEP GFS 0.25 Degree Global Forecast Grids Historical Archive, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, CO, https://doi.org/10.5065/D65D8PWK.