Improving Numerical Weather Prediction of Rainfall Events Using Radar Data Assimilation

Miranti Indri Hastuti(1*), Jaka Anugrah Ivanda Paski(2), Fatkhuroyan Fatkhuroyan(3)

(1) Indonesian Agency of Meteorology Climatology and Geophysics (BMKG)
(2) Indonesian Agency of Meteorology Climatology and Geophysics (BMKG)
(3) Indonesian Agency of Meteorology Climatology and Geophysics (BMKG)
(*) Corresponding Author


Data assimilation is one of method to improve initial atmospheric conditions data in numerical weather prediction. The assimilation of weather radar data that has quite extensive and tight data is considered to be able to improve the quality of weather prediction and analysis. This study aims to investigate the effect of assimilation of Doppler weather radar data in Weather Research Forecasting (WRF) numerical model for the prediction of heavy rain events in the Jabodetabek area with dates representing four seasons respectively on 20 February 2017, 3 April 2017, 13 June 2017, and 9 November 2017. For this purpose, the reflectivity (Z) and radial velocity (V) data from Plan Position Indicator (PPI) product and reflectivity (Z) data from Constant Altitude PPI (CAPPI) product were assimilated using WRFDA (WRF Data Assimilation) numerical model with 3DVar (The Three Dimensional Variational) system. The output of radar data assimilation and without assimilation of the numerical model of WRF is verified by spatial with GSMaP data and by point with precipitation observation data. In general, WRF radar assimilation provides a better simulation of spatial and point rain events compared to the WRF model without assimilation which is improvements of rain prediction from WRF radar data assimilation would be more visible in areas close to radar sources and not echo-blocked from fixed objects, and more visible during the rainy season


WRFDA; DA – radar; weather radar; heavy rains

Full Text:



Nugroho, S.P. (2002). Evaluasi dan Analisis Curah Hujan Sebagai Penyebab Bencana Banjir Jakarta. Jurnal Sains dan Teknologi Modifikasi Cuaca, 3(2), 91-97.

Gustari, I. ,Hadi T. W. ,Hadi S. , & Renggono F. (2012). Akurasi Prediksi Curah Hujan Harian Operasional di Jabodetabek : Perbandingan Dengan Model WRF. Jurnal Meteorologi dan Geofisika, 13, 119-130

Gustari, I. (2014). Perbaikan Prediksi Cuaca Numerik Kejadian Hujan Sangat Lebat Terkait dengan Sistem Awan di Jabodetabek Menggunakan Asimilasi Data Radar C-Band, Disertation, Sains Kebumian, ITB, Bandung.

Sagita, N. (2017). Asimilasi Model Weather Research And Forecasting (WRF) Dengan Data Observasi Untuk Prediksi Curah Hujan di Wilayah Jawa. Thesis, IPB. Bogor.

Skamarock, William C., Klemp Joseph B., Dudhia J., Gill D O., Barker D.M., Duda M G., Huang X. Y., Wang W., Powers J G. (2008). A Description of the Advanced Research WRF Version 3 NCAR Technical Note. Mesoscale and Microscale Meteorology Division. National Center for Atmospheric Research, Boulder, Colorado, USA.

Liu, J., M. Bray., dan D. Han. (2013). A Study on WRF Radar Data Assimilation for Hydrological Rainfall Prediction. Hydrological Earth System, 17, 3095-3110.

Liu, J., Tian J., Yan D., Li C., Yu F., & Shen F. (2018). Evaluation of Doppler radar and GTS data assimilation for NWP rainfall prediction of an extreme summer storm in northern China: from the hydrological perspective. Hydrology and Earth System Sciences, 22, 4329-4348.

Li W., Xie Y., Deng S. M., & Wang Qi. (2010). Application of the Multigrid Method to the Two-Dimensional Doppler Radar Radial Velocity Data Assimilation. Journal of Atmospheric and Oceanic Technology, 27, 319-322.

Xiao, Q., Kuo, N. Y. H., Sun, J., Lee, W. C., Lim, E., Guo, Y. R., & Barker, D. M. (2005). Assimilation of Doppler Radar Observations with a Regional 3DVar System: Impact of Doppler Velocities on Forecasts of a Heavy Rainfall Case. Journal of Applied Meteorology, 44, 768- 788.

Sugimoto, S., N.A Crook., Sun J., & Xiao Q. (2009). An Examination of WRF 3DVar Radar Data Assimilation on Its Capabilityin Retrieving Unobserved Variables and Forecasting Precipitation through Observing System Simulation Experiments, American Meteorological Society, 137, 4011-4029.

Satrya, L. I. (2012). Asimilasi Data Radar dalam Penerapan Prediksi Cuaca Numerik di Indonesia (Studi Kasus di Jawa Barat), Skripsi, Meteorologi, ITB, Bandung.

Paski, J.A.I. & Gustari, I. (2017), Pengaruh Asimilasi Data Radar C-Band dalam Prediksi Cuaca Numerik (Studi Kasus di Lampung, Jurnal Meteorologi dan Geofisika, 18 (2), 55-64.

Paski, J.A.I., Permana, D.S., Hastuti, M.I. and Sudewi, R.S.S. (2019). Dampak Asimilasi Data Radar Produk Cappi pada Prediksi Kejadian Hujan Lebat di Jabodetabek Menggunakan Model WRF-3DVAR. Jurnal Meteorologi dan Geofisika, 20(1), pp.47-54.

Permana, D. S., Hutapea, T.D.F, Praja, A.S., & Fatkhuroyan, Muzayanah, L.F. (2006). Pengolahan Multi Data Format Radar Cuaca Menggunakan Wradlib Berbasis Python. Jurnal Meteorologi dan Geofisika, 17(3), 157-164.

Wang, H., Bruyère, C., Duda, M., Dudhia, J., Gill, D., Lin, H. C., Michalakes, J., Rizvi, S., & Zhang, X. (2016). WRF-ARW Version 3 Modeling System User’s Guide, National Center for Atmospheric Research, Amerika Serikat.

Wang, H., Sun, J., Zhang, X., Huang, X. Y., & Auligne, T. (2012). Radar Data Assimilation with WRF 4D-Var. Part I: System Development and Preliminary Testing. Monthly Weather Review, 141, 2224-2244.

Wang, H., Sun. J., Fan. S., & Huang X. Y. (2013). Indirect Assimilation of Radar Reflectivity with WRF 3D-Var and Its Impact on Prediction of Four Summertime Convective Events. Journal of Applied Meteorology and Climatology, 52, 889-902.

Lee J.-H., Lee H.-Ha., Choi Y., Kim H.-W., & Lee D.-K. (2010). Radar Data Assimilation for the Simulation of Mesoscale Convective Systems. Advances in Atmospheric Sciences, 27(5), 1025–1042.

Jones, T.A., Otkin J.A., Stensurd D.J., & Knopfmeier, K. (2014). Forecast Evaluation of an Observing System Simulation Experiment Assimilating Both Radar and Satellite Data. Mon. Wea. Rev., 139, 755–773.

Ma Y., Lu, M., Chen, H., Pan, M., Hong, Y. (2018). Atmospheric Moisture Transport Versus Precipitation Across the Tibetan Plateau: A Mini-Review and Current Challenges. Atmospheric Research. 209. 50-58.

Routray, A., Mohanty, U.C., Rizvi, S. R. H., Niyogi D., Osuri K. K., & Pradhan D. (2010). Impact of Doppler weather radar data on numerical forecast of Indian monsoon depressions. Journal of the Royal Meteorology Society, 136, 1836-1850.

Tjasyono, B.H.K. (2009). Meteorologi Indonesia Volume 1, Karakteristik dan sirkulasi Atmosfer, Badan Meteorologi dan Geofisika, Jakarta.

Janiskova, M. (2015). Assimilation of cloud information from space-borne radar and lidar: experimental study using a 1D+4D-Var technique. Journal of the Royal Meteorology Society, 141, 2708-2725.

Wiegand, B, 2015, Introduction to Numerical Weather Prediction. htw saar – Hochschule für Technic und Wirtschaft des Saarlandes (University of Applied Sciences). Fakultät für Ingenieurwissenschaften (School of Engineering).

Fatkhuroyan, A.S Praja, T. Wati. (2019). A preliminary results of assessment of BMKG-WRF numerical model daily rainfall forecasts performance using categorical verification. IOP Conf. Ser.: Earth Environ. Sci. 284 012013. doi:10.1088/1755-1315/284/1/012013

Sun, J. & Wang, H. (2013). Radar Data Assimilation with WRF 4D-Var. Part II: Comparison with 3D-Var for a Squall Line over the U.S. Great Plains. Mon. Wea. Rev., 141, 2245–2264.

Ricciardelli, E., Paola F. D., Gentile, S., Cersosimo, A., Cimini D., Galluci D., Geraldi, E., Larosa, S., Nilo, S. T., Ripepi, E., Romano, F., & Voggiano, M. (2018). Analysis of Livorno Heavy Rainfall Event: Examples of Satellite-Based Observation Techniques in Support of Numerical Weather Prediction. Remote Sens. 2018, 10, 1549. doi:10.3390/rs10101549


Article Metrics

Abstract views : 3818 | views : 2677


Copyright (c) 2019 Miranti Indri Hastuti, Jaka Ivanda Anugrah Paski

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)

ISSN 2354-9114 (online), ISSN 0024-9521 (print)