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All Journal The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Iddam Hairuly Umam
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Earth & Planetary Sciences

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PRELIMINARY STUDY OF A RADIO FREQUENCY INTERFERENCE FILTER FOR NON-POLARIMETRIC C-BAND WEATHER RADAR IN INDONESIA (CASE STUDY: TANGERANG WEATHER RADAR) Abdullah Ali; Iddam Hairuly Umam; Hidde Leijnse; Umi Sa’adah
International Journal of Remote Sensing and Earth Sciences Vol. 18 No. 2 (2021)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3727

Abstract

C-Band weather radar that operates at a frequency of 5 GHz is very vulnerable to radio frequency interference (RFI) because it is located on a free used frequency. RFI can cause image misinterpretation and precipitation echo distortion. The new allocation for free spectrum recommended by the World Radio Conference 2003 and weather radar frequency protection in Indonesia controlled by the Balai Monitoring Spektrum Frekuensi (BALMON) have not provided permanent protection against weather radar RFI. Several RFI filter methods have been developed for polarimetric radars, but there have been no studies related to RFI filters on non-polarimetric radars in Indonesia. This research aims to conduct an initial study of RFI filters on such radars. Four methods were applied in the initial study. The Himawari 8 cloud mask was used to eliminate interference echo based on VS, IR, and I2 channels, while the nature of false echo interference that does not have a radial velocity value was used as the basis for the application of the Doppler velocity filter. Another characteristic in the form of consistent echo interference up to the maximum range was used as the basis for applying a beam filling analysis filter with reflectivity thresholds of 5 dBZ and 10 dBZ, with beam filling of more than 75%. Finally, supervised learning Random Forest (RF) was also used to identify interference echo based on the characteristics of the sampling results on reflectivity, radial velocity, and spectral width data. The results show that the beam filling analysis method with a threshold of 5 dBZ provides the best RFI filter without eliminating echo precipitation.
AN ENHANCEMENT TO THE QUANTITATIVE PRECIPITATION ESTIMATION USING RADAR-GAUGE MERGING Abdullah Ali; Gumilang Deranadyan; Iddam Hairuly Umam
International Journal of Remote Sensing and Earth Sciences Vol. 17 No. 1 (2020)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2020.v17.a3316

Abstract

Quantitative Precipitation Estimation (QPE) is quite important information for the hydrology fields and has many advantages for many purposes. Its dense spatial and temporal resolution can be combined with the surface observation to enhance the accuracy of the estimation. This paper presents an enhancement to the QPE product from BMKG weather radar network at Surabaya by adjusting the estimation value form radar to the real data observation from rain gauge. A total of 58 rain gauge is used. The Mean Field Bias (MFB) method used to determine the correction factor through the difference between radar estimation and rain gauge observation value. The correction factor obtained at each gauge points are interpolated to the entire radar grid in a multiplicative adjustment. Radar-gauge merging results a significant improvement revealed by the decreasing of mean absolute error (MAE) about 40% and false alarm ratio (FAR) as well an increasing of possibility of detection (POD) more than 50% at any rain categories (light rain, moderate rain, heavy rain, and very heavy rain). This performance improvement is very beneficial for operational used in BMKG and other hydrological needs.
Co-Authors Abda Abda Gumilang Deranadyan Hidde Leijnse Umi Sa’adah