The Utilization of Weather Research Forecasting (WRF) Model of 3DVar (Three Dimensional Variational) and Himawari-8 Satellite Imagery to the Heavy Rain in Palangkaraya (Case Study : April 27, 2018)
DOI:
https://doi.org/10.31172/jmg.v23i3.790Keywords:
WRF 3DVar, Himawari-8, Python Programming, Flood, Heavy RainAbstract
On April 27, 2018 heavy rain was occurred in Palangkaraya. Based on surface data observations at Tjilik Riwut Meteorological Station, the peak of rain occurred between 18-21 UTC, which 54 mm within 3 hours. As a result, the flood inundated on the following day. This research purposed to discover the cause of heavy rain used the WRF model of 3DVar technique that assimilated with AMSU-A satellite which used the tropical physic suite parameterization scheme and Himawari-8 Satellite (IR-1 data), processed by Python Programming. Based on the results, the WRF of the 3DVar model is not representative enough in total rainfall results. However, several weather disturbances show the potency for severe weather occurrence from WRF 3DVar modeling. These are indicated by the shear line and eddy circulation at 18 and 21 UTC, and the time series of air pressure decreases with a 0.5 Mb tendency between 15 to 18 UTC. Moreover, the cloud top temperature graph from Himawari-8 Satellite data shows a drastic reduction in temperature to -61.4323 at 18.20 UTC, which supports the heavy rain process. The weather analysis above show that WRF 3DVar is not representative enough for total rainfall result, but appropriate for other weather aspects (shear line, eddy, and air pressure). Therefore, the heavy rain is caused by shear line and eddy condition, air pressure and low temperature of the cloud top.
References
D.M. Barker, “A Three-Dimensional Variational (3DVAR) Data Assimilation System For Use With MM5,” Mon. Wea. Rev American Meteorology Society., vol. 132, pp. 897-914, 2004.
J.R. Holton. An Introduction to Dynamic Meteorology Fourth Edition. San Diego California: Elsevier Academic Press, 2004.
P. Ismail , A.K. Silitonga, A. Fadlan, “Performa Model WRF Asimilasi Data Satelit Cuaca Pada Kejadian Curah hujan Lebat di Jabodetabek,” Jurnal Sains dan Teknologi Modifikasi Cuaca., vol. 19(2), pp. 69-74, 2018.
J. Paski, “Pengaruh Asimilasi Data Penginderaan Jauh (Radar dan Satelit) Pada Prediksi Cuaca Numerik untuk Estimasi Curah Hujan," Jurnal Penginderaan Jauh., vol. 14(2), pp. 79-88, 2017.
N. Sagita, R. Hidayati, R. Hidayat , I. Gustari and Fatkhuroyan, “Using 3D-Var Data Assimilation for Improving the Accuracy of Initial Condition of Weather Research and Forecasting (WRF) Model in Java Region (Case Study : 23 January 2015),” Forum Geografi., vol. 30(2), pp. 112-119, 2016.
R. Stull. Pratical Meteorology : An Algebra based Survey of Atmospheric Science. Canada: University of British Columbia, 2015.
H. Wang, C. Bruyère, M. Duda, J. Dudhia, D. Gill, H.C Lin, J. Michalakes, S. Rizvi and X, Zhang, WRF-ARW Version 3 Modeling System
User’s Guide. USA: National Center for Atmospheric Research, 2016.
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