Pengolahan Dan Pemulihan Data Radar Cuaca Menggunakan Wradlib Berbasis Python

Permana, Donaldi Sukma; Hutapea, T D; Praja, Alfan Sukmana; Fatkhuroyan, Fatkhuroyan; Muzayanah, Linda F.

doi:10.31172/jmg.v17i3.350

Cited by 10 publications

(9 citation statements)

References 3 publications

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“…A python-based open-source software Wradlib was utilized to process weather radar data. Wradlib has been widely used in the processing of weather radar data and its application [ 6 , 7 ]. It has an important function in weather radar data processing, particularly in generating the Quantitative Precipitation Estimation (QPE) products.…”

Section: Methodsmentioning

confidence: 99%

Reconstruction of Extreme Rainfall Event on September 19-20, 2017, Using a Weather Radar in Bengkulu of Sumatra Island

Paski

Alfahmi

Permana

et al. 2020

The Scientific World Journal

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Extreme rainfall accompanied by strong winds hit the province of Bengkulu in the western coastal area of Sumatera Island during September 19-20, 2017, causing floods and landslides in Seluma and Central Bengkulu district. This extreme rainfall was recorded by Bengkulu Meteorological Station about 257.0 mm day−1 using rain-gauge observation. The spatial distribution of extreme rainfall cannot be seen if only using a rain-gauge observation in this location. The spatial distribution of extreme rainfall is needed to identify the impact of rainfall on landslides in large areas. The study aims to (1) develop the reconstruction of the spatial distribution of extreme rainfall using weather radar and (2) investigate the trigger that caused extreme rainfall by analyzing the synoptic-scale tropical waves. Each weather radar datum is saved in a Constant Altitude Plan Position Indicator (CAPPI). To get rainfall information, the CAPPI must be derived from Quantitative Precipitation Estimation (QPE) values. In this paper, we derived CAPPI using a Marshall-Palmer reflectivity-rain rate relationship. The result shows that rainfall formed on September 20, 2017, 21.00 UTC with total daily rainfall ranged between 176 and 247 mm in both districts and the mean of total daily rainfall has exceeded the average of monthly rainfall. The analysis of tropical waves suggests that only Kelvin waves were active and served as a possible trigger factor while the Madden-Julian Oscillation (MJO) and Equatorial Rossby (ER) waves were inactive during this extreme rainfall.

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Section: Methodsmentioning

confidence: 99%

Reconstruction of Extreme Rainfall Event on September 19-20, 2017, Using a Weather Radar in Bengkulu of Sumatra Island

Paski

Alfahmi

Permana

et al. 2020

The Scientific World Journal

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“…One example of its use is for estimation rainfall from radar data showing good results in the estimation of river flow discharge and simulation of flood events in the Philippines [8,9,10]. Wradlib has an important function in the processing of weather radar data and allows performing Quantitative Precipitation Estimation (QPE) analysis based on weather radar data [1,11].…”

Section: Methodsmentioning

confidence: 99%

Using the c-band Doppler weather radar data to reconstruct extreme rainfall event on 11th march 2018 in Bangka island, Indonesia

Paski

Permana

2018

MATEC Web Conf.

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Extreme weather in the form of heavy rainfall hit Bangka Island, Indonesia on 10 - 11 March 2018 caused flooding in some areas such as in Pangkal Pinang and Muntok in Bangka Barat District, Air Asam Belinyu in Bangka Induk District, and Koba in Bangka Tengah District. Observation of weather conditions at Pangkal Pinang Meteorological Station on 10 March 2018 recorded temperature ranged from 23 to 25°C; relative humidity (RH) ranged from 91 to 100% and measured rainfall reached 84.4 mm/day. In Muntok, the measured rainfall reached 257.5 mm/day which exceeds the March average rainfall 250 mm/month. This study aims to reconstruct this extreme rainfall using C-Band Doppler weather radar centered in Palembang, South Sumatera Province with Python-wradlib library. Weather radar images were displayed in Constant Altitude Plan Position Indicator (CAPPI) and Quantitative Precipitation Estimation (QPE) temporal analysis was performed in areas of extreme rainfall by applying the Marshall-Palmer reflectivity-rain rate (Z-R) relationship. The analysis was conducted by observing the movement and growth of convective clouds through the Palembang radar over Bangka Island and identifying the regional extreme rainfall using Indonesia In-House Radar Integration System (IIRIS) over Sumatra Island. The results suggest that the reconstructed rainfall reached 236.7 mm/day for Muntok, 92.1 mm/day for Pangkal Pinang, 106.0 mm/day for Koba and 80.8 mm/day for Air Asam Belinyu. Although most of the location sites are more than 200 km from the radar center, both of the reconstructed and measured rainfall is well comparable.

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“…Informasi prakiraan cuaca berdasarkan data radar sangat penting bagi BMKG dalam memberikan peringatan dini cuaca ekstrim. Saat ini, BMKG memiliki setidaknya tiga format data radar cuaca yang berasal dari tiga produsen radar yakni Gematronik, Enterprise Electronics Corporation (EEC) dan Baron yang hanya dapat diolah menggunakan perangkat lunak dari masing-masing produsen radar (Permana et al, 2016).…”

Section: Pendahuluanunclassified

Metode Pencuplikan Nilai Echo Citra Radar *.Png Dengan Referensi Spasial Dan Kombinasi Warna RGB

Purwadi

Fitriano

2017

JSTMC

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IntisariData meteorologi yang berupa citra/gambar sulit dianalisis dan dikombinasikan dengan data lain. Dalam karya tulis ini akan dijelaskan metode pencuplikan citra/gambar radar yang dipublikasikan oleh BMKG menjadi data teks. Proses pengolahan terdiri dari dua tahap yaitu proses pemetaan setiap pixel dalam citra radar menjadi koordinat bumi (latitude dan longitude) dan penentuan nilai echo radar (dBZ). Dari legenda pada citra radar didapatkan 9 pola warna RGB yang digunakan sebagai penentu nilai dBZ setiap pixel dalam citra radar. Hasil pengolahan citra radar berupa data teks yang terdiri dari longitude, latitude, dan nilai dBZ. Untuk membandingkan dengan data asli, data radar teks hasil pengolahan ditampilkan pada Website Global Informasion System (WebGIS). Warna data radar pada WebGIS ditentukan dengan persamaan warna sebagai fungsi dari nilai dBZ. Secara kualitatif, hasil perbandingan gambar radar asli dengan data numerik yang ditampilkan pada WebGIS menunjukkan bahwa hasil data numerik cukup presisi pada posisi longitude dan latitude. Namun, dari segi nilai numerik echo radar (dBZ) yang dihasilkan terdeteksi kurang akurat pada batas awan karena latar belakang gambar yang berwarna hitam. Selain itu, pada keterangan nama kota dan batas wilayah yang berwarna abu-abu menujukkan pixel yang kosong walaupun disekelilingnya terlihat adanya awan, sehingga diperlukan penelitian lebih lanjut untuk mengatasi permasalahan tersebut dengan menambahkan filter untuk mengoreksi nilai pixel pada batas gambar dan teknik interpolasi untuk mengisi kekosongan nilai pada area pixel. AbstractMeteorological data in the form of image has difficulty in further analysis such as to combine the data with other data sources. In this research, the proposed method for converting image data into texts using image processing for BMKG data provided is presented. The processing scenarios consist of two main steps; mapping process of every pixel of the images into the earth coordinate (latitude and longitude) step and radar echo values estimation in dBZ step. From the analysis, the 9 color patterns of RGB are obtained and used as the dBZ justification tool for the pixel color of radar image. The results of this image processing step are the texts data of latitude, longitude and the radar echo values in dBZ. In order to compare the analysis results with the original data, the processing data are then reshown to global information system website (WebGIS). The radar color data on WebGIS is determined based on color equation as a function of the echo radar. Qualitatively, the results of this comparison show that the numerical data results are precise in terms of longitude and latitude positions. However, in terms of numerical values echo radar (dBZ), the results perform less accurate especially on the boundary of the cloud due to the black color of background image. In addition, the description of the city name and the border of the gray area show the data are empty although by visual inspection there are surrounding clouds. Thus, further research is needed to solve the problem by adding filters to correct the pixel value at the image boundary and applying the interpolation technique to fill the void value in the pixel area.

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Pengolahan Dan Pemulihan Data Radar Cuaca Menggunakan Wradlib Berbasis Python

Cited by 10 publications

References 3 publications

Reconstruction of Extreme Rainfall Event on September 19-20, 2017, Using a Weather Radar in Bengkulu of Sumatra Island

Reconstruction of Extreme Rainfall Event on September 19-20, 2017, Using a Weather Radar in Bengkulu of Sumatra Island

Using the c-band Doppler weather radar data to reconstruct extreme rainfall event on 11th march 2018 in Bangka island, Indonesia

Metode Pencuplikan Nilai Echo Citra Radar *.Png Dengan Referensi Spasial Dan Kombinasi Warna RGB

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