Implementasi Metode Deteksi Hujan Es Berbasis Data Radar Cuaca Menggunakan Algoritma Severe Hail Index (SHI)

Authors

  • Abdullah Ali BMKG
  • Umi Sa’adah Stasiun Meteorologi Soekarno-Hatta BMKG

DOI:

https://doi.org/10.25077/jfu.11.3.380-386.2022

Keywords:

Hail Detection Algorithm, Hujan Es, Radar Cuaca, , Severe Hail Index

Abstract

Metode Severe Hail Index (SHI)  ini merupakan metode pendeteksian hujan es yang paling komprehensif dengan output berupa indeks probabilitas hujan es (pada setiap ukuran) dalam satuan Jm-1s-1, probabilitas severe hail dalam satuan %, dan prakiraan ukuran maksimum batu es yang mencapai permukaan dalam satuan milimeter. Penelitian ini bertujuan mengimplementasikan metode SHI sebagai detektor dan prediktor kejadian hujan es di Indonesia. Dari 13 kejadian hujan es diperoleh nilai maksimum indeks probabilitas hujan es untuk setiap ukuran sebesar 269 Jm-1s-1 dan nilai minimum 0 Jm-1s-1, nilai maksimum indeks probabilitas severe hail sebesar 64.4 % dan nilai minimum 0%, sedangkan nilai maksimum prakiraan ukuran maksimum batu es mencapai 63.76 mm dan minimum 8.25 mm. Simulasi dilakukan dengan membandingkan nilai SHI dengan WT yang kemudian digunakan untuk menentukan nilai POD (Possibility of Detection), CSI (Critical Succes Index), dan FAR (False Alarm Ratio). POD pada simulasi ini diperoleh nilai 0.307 dan 0.230, FAR 0.0, dan CSI 0.307. FAR bernilai 0.0 menunjukkan metode ini mempunyai tingkat kesalahan yang sangat kecil untuk mendeteksi atau memperdiksi adanya huajan es namun nilai POD masih tergolong rendah, sehingga metode ini juga cukup sulit untuk mendeteksi eksistenesi hail di lapangan. Hasil simulasi tersebut menunjukkan bahwa perlunya modifikasi pada perumusan WT untuk meningkatkan performa metode SHI dalam mendeteksi dan memprediksi kejadian hujan es.

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Published

2022-07-05

How to Cite

Ali, A., & Sa’adah, U. (2022). Implementasi Metode Deteksi Hujan Es Berbasis Data Radar Cuaca Menggunakan Algoritma Severe Hail Index (SHI). Jurnal Fisika Unand, 11(3), 380–386. https://doi.org/10.25077/jfu.11.3.380-386.2022

Issue

Vol. 11 No. 3 (2022)

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