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Maps for accumulated rainfall for the Habagat event (Aug 06-09) from different rainfall products: (a) R(Z S ), (b) GO, 

Maps for accumulated rainfall for the Habagat event (Aug 06-09) from different rainfall products: (a) R(Z S ), (b) GO, 

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Figure 1: The Marikina River Basin (outlined in black) located within...
Figure 2: Maps for accumulated rainfall for the Habagat event (Aug...
Table 2 :
Figure 3: Simulated flows from different rainfall products and the...
Comparison between C-band and S-band radar rainfall for hydrological simulations in Marikina River Basin, Philippines
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Radar-based rainfall retrieval is particularly important in the Philippines where torrential and sustained rainfall from tropical cyclones, monsoon, and thunderstorms regularly affect the country. In 2011, the Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) started to establish a weather radar network, which by...
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Citations

... Kami menggunakan perangkat lunak open-source wradlib berbasis Python untuk mengolah dan menyimpan data radar cuaca [2][3]. Perangkat lunak ini sudah banyak digunakan dalam pengolahan data radar cuaca dan aplikasinya [4][5][6]. Sebagai contoh, wradlib-python telah digunakan untuk estimasi curah hujan dari data radar dan menunjukkan hasil yang cukup baik dalam estimasi debit aliran sungai dan simulasi kejadian banjir di Filipina [5][6]. Beberapa keuntungan dari penggunaan perangkat lunak ini diantaranya: (1) mengatasi kendala lisensi dan ketergantungan terhadap perangkat lunak yang berasal dari produsen radar tertentu, (2) mengolah dan mengekstraksi data radar secara masif dengan visualisasi yang dapat disesuaikan, (3) melakukan pemulihan struktur data radar cuaca dari koordinat polar ke dalam koordinat kartesian dan (4) menyimpan luaran data dalam format NetCDF sehingga memudahkan pengolahan data lebih lanjut. ...
... Perangkat lunak ini sudah banyak digunakan dalam pengolahan data radar cuaca dan aplikasinya [4][5][6]. Sebagai contoh, wradlib-python telah digunakan untuk estimasi curah hujan dari data radar dan menunjukkan hasil yang cukup baik dalam estimasi debit aliran sungai dan simulasi kejadian banjir di Filipina [5][6]. Beberapa keuntungan dari penggunaan perangkat lunak ini diantaranya: (1) mengatasi kendala lisensi dan ketergantungan terhadap perangkat lunak yang berasal dari produsen radar tertentu, (2) mengolah dan mengekstraksi data radar secara masif dengan visualisasi yang dapat disesuaikan, (3) melakukan pemulihan struktur data radar cuaca dari koordinat polar ke dalam koordinat kartesian dan (4) menyimpan luaran data dalam format NetCDF sehingga memudahkan pengolahan data lebih lanjut. ...
PENGOLAHAN MULTI DATA FORMAT RADAR CUACA MENGGUNAKAN WRADLIB BERBASIS PYTHON (MULTI WEATHER RADAR FORMAT DATA PROCESSING USING PYTHON-BASED WRADLIB)
Article
Full-text available
  • Dec 2016
ABSTRAK Informasi prakiraan cuaca berdasarkan data radar sangat penting bagi BMKG dalam memberikan peringatan dini cuaca ekstrim. Saat ini, BMKG memiliki setidaknya ada 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. Perangkat lunak wradlib berbasis python dapat mengolah ketiga format data radar tersebut dan menyimpannya dalam format data yang sama. Kelebihan wradlib-python lainnya adalah berlisensi sumber terbuka (open-source) sehingga dapat di-install di berbagai sistem operasi secara gratis, mengurangi ketergantungan terhadap perangkat lunak dari produsen radar, dapat mengolah dan menampilkan multi format data radar cuaca secara masif, menyimpan data radar dalam format NetCDF koordinat kartesian sehingga memudahkan pengolahan data radar lebih lanjut seperti input untuk asimilasi data. Studi ini memfokuskan pengolahan data radar volumetric (.vol) luaran produk Gematronik dan Baron serta data radar NetCDF (.nc) luaran produk EEC. Wradlib python dapat mengekstrak secara otomatis data Plan Position Indicator (PPI) dan menghitung nilai Constant Altitude PPI (CAPPI) dari data reflektifitas radar. Walaupun intensitas reflektifitas citra radar luaran wradlib-python relatif lebih tinggi dari luaran perangkat lunak dari produsen radar, luaran tersebut memiliki pola spasial yang relatif sama. Oleh karena itu, wradlib-python dapat menjadi salah satu solusi alternatif untuk pengolahan, penyimpanan dan visualisasi data radar cuaca di BMKG. ABSTRACT Weather forecast information based on weather radar is very important for BMKG in providing early warning services for extreme weather. Currently, BMKG has at least three weather radar data format from three radar companies i.e. Gematronik, Enterprise Electronics Corporation (EEC) and Baron which can only be extracted and processed using their original software from each company. The python-based library wradlib can extract and process these three data format and save them into the same data format. Advantages of wradlib-python include having an open-source license so it can be freely installed in multi operating system, reducing dependency on original weather radar software, be able to process and visualize massive multi weather radar data format and be able to save radar data in cartesian coordinate and NetCDF format which make it easier for further data processing such as input for data assimilation. This study only focuses on processing weather radar volumetric data (.vol) from Gematronik and Baron, and NetCDF data (.nc) from EEC. Wradlib-python can automatically extract Plan Position Indicator (PPI) data and calculate Constant Altitude PPI (CAPPI) values from reflectivity data. Although radar images generated by wradlib-python relatively have a greater reflectivity intensity than ones from the original softwares, they have a relatively similar spatial pattern. Therefore, wradlib-python can be one of alternative solutions for extracting, processing and visualization of weather radar data in BMKG.
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