International Symposium on the 15th Anniversary of the Equatorial Atmosphere Radar EAR
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values via empirical power-law Z-R relationships. This study presents the analyses and comparison of radar- based rainfall estimates from Padang weather radar data and ground rainfall observation at two BMKG
stations in Minangkabau and Teluk Bayur. Rainfall rates estimations were derived from two common Z-R relationships of Marshall-Palmer MP with Z = 200R
1.6
for general stratiform precipitation Marshall et al., 1947; Rinehart, 2010 and Rosenfeld RO with Z = 250R
1.2
for tropical convective rain Rosenfeld et al., 1993. In addition, WRF model simulation are also performed during this extreme event.
A B
C D
Figure 1. The global ocean and atmospheric conditions during the extreme rainfall on June 16, 2016 in West Sumatra,
Indonesia. A. SST anomaly B. Sea level pressure and streamline C. Relative humidity at 500 mb level and D. Infrared channel from HIMAWARI Satellite represent top cloud temperatures during the event.
2. DATA AND METHOD
For this study, data collected from C-band radar in Minangkabau station 100.3°E; 0.79°S; 24 meter above ground level during June 16, 2016 are used. The radar has a maximum horizontal coverage of 240
km, however, in this study the reflectivity data for up to 120 km radius only is used. This is to avoid the low quality reflectivity data, because at a great distance from radar, the signal received by radar is influenced by
noise Sebastianelli et al., 2010. Data are archived every 10 minutes in volumetric format which consist of 10 Plan Position Indicator PPI scans 0.5, 1.6, 2.9, 4.5, 6.4, 8.8, 11.8, 15.3, 19.7 and 25.0 degree elevation
Figure 2A and each of them contains the reflectivity values in decibel dBZ with dBZ = 10log
10
Z. On the other hand, ground rainfall observation were accumulatively measured every 3 hours at BMKG
stations in Minangkabau 100.3°E; 0.79°S; with distance of 1-2 km from the radar site and Teluk Bayur 100.37°E; 0.99°S; with distance of ~25 km from the radar site during the day event Figure 2B. Rainfall
data at 00 to 21 UTC on June 16, 2016 were available in Minangkabau and Teluk Bayur.
International Symposium on the 15th Anniversary of the Equatorial Atmosphere Radar EAR
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Radar data processing and rainfall estimation were conducted using the open source library wradlib based on Python Heistermann et al., 2013. Constant Altitude PPI CAPPI values were calculated for every 0.5
km from altitudes 0.5 to 5 km with horizontal resolution of 0.5 kmpixel. BMKG usually uses a parameter CAPPI-CMAX maximum CAPPI values in altitude column to analyze the extreme weather events.
Therefore, we utilize dBZ values from CAPPI-CMAX to derive the rainfall rate estimates. Specifically, we extract dBZ values from 9 grid points closest to the ground rainfall stations and calculate their average values
dBZave and maximum values dBZmax. The instantaneous dBZave and dBZmax values at every 10 minutes interval are averaged into hourly and three-hourly values for each station. Rainfall rates estimation
from the MP and RO relationships are compared with ground measured rainfall at the two stations to investigate their performances by calculating Root Mean Squared Error RMSE and Mean Absolute Error
MAE. In this study, the rainfall field is assumed to remain stationary in space and intensity during the sampling interval, where the raindrop is assumed to fall vertically downward Mapiam et al., 2008. In
addition, this event were also simulated by WRF model run by Center for Research and Development Center of BMKG http:www.puslitbang.bmkg.go.idwrf.
A B
Figure 2. A PPI scan strategy of weather radar in Padang. B The Padang radar site black triangle and BMKG
stations circles in West Sumatera.
3. RESULTS AND DISCUSSION
