UJI PERFORMA WRF DENGAN DATA ASIMILASI RADAR, SATELIT DAN SYNOP UNTUK PREDIKSI HUJAN DI JAKARTA
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Abstract
Asimilasi data merupakan suatu metode estimasi yang diperoleh dari penggabungan antara output model NWP dan data-data pengukuran. Dalam beberapa tahun terakhir, model mesoscale resolusi tinggi diinisialisasi dengan menggunakan teknik data asimilasi (3DVAR/4DVAR) yang diterapkan untuk mempelajari fenomena meteorologi. Penelitian ini dilakukan di wilayah Jakarta dengan memanfaatkan data observasi sinoptik, data radiance satelit dan data radar Doppler C-Band EEC (Enterprise Electronics Corporation) di Jakarta. Penelitian ini menggunakan model numerik Weather Research and Forecasting (WRF) untuk menjalankan model tanpa asimilasi dan model dengan asimilasi data radar, satelit dan sinoptik menggunakan sistem 3DVAR. Analisis dilakukan secara kuantitatif untuk menguji performa model terhadap data observasi dan analisis spasial dengan mencari nilai selisih curah hujan dengan data GSMaP melalui metode overlay. Hasil membuktikan performa terbaik dari hasil prediksi distribusi hujan spasial adalah model asimilasi satelit kemudian model asimilasi radar dan terakhir model asimilasi synoptic. Uji performa melalui tabel kontingensi untuk mengetahui nilai PC, TS, FAR, dan POD. Model asimilasi satelit memiliki performa paling baik daripada model asimilasi lain. Untuk prediksi sesuai kategori hujan ringan model asimilasi satelit yang terbaik, sementara untuk kategori hujan sangat lebat model asimilasi synop adalah yang paling unggul.
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