PERFORMA MODEL WRF ASIMILASI DATA SATELIT CUACA PADA KEJADIAN CURAH HUJAN LEBAT DI JABODETABEK
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Abstract
Prediksi cuaca numerik saat ini terus dikembangkan untuk memenuhi kebutuhan prakiraan curah hujan beresolusi tinggi. Namun, prediksi cuaca numerik di Indonesia masih bermasalah dalam hal akurasi model numerik. Beberapa penelitian sebelumnya menunjukkan bahwa akurasi pemodelan sangat dipengaruhi oleh error pada data kondisi inisial. Penelitian ini mengkaji upaya untuk memperbaiki data inisial model Weather Research and Forecasting (WRF) dengan menggunakan prosedur asimilasi radiance satelit untuk prakiraan curah hujan di wilayah Jabodetabek untuk empat studi kasus pada musim yang berbeda selama 2017. Enam eksperimen model dijalankan dengan data satelit AMSUA, MHS, HIRS4, dan ATMS menggunakan WRFDA 3DVar. Penelitian ini dilakukan dengan analisis pengaruh asimilasi terhadap data inisial model, analisis skill model berdasarkan diagram taylor, kriteria curah hujan, curah hujan spasial, dan akumulasi curah hujan time series dibandingkan dengan data observasi curah hujan BMKG dan data curah hujan GSMaP. Hasil penelitian menunjukkan bahwa eksperimen DA AMSUA, MHS, dan MIX dapat memodifikasi data kondisi inisial model dengan baik. Sementara itu, hasil verifikasi diagram taylor mengungkapkan bahwa eksperimen DA-MHS memiliki performa terbaik dibandingkan dengan asimilasi lainnya, sedangkan verifikasi prediksi curah hujan berdasarkan kriteria hujan, verifikasi spasial, dan akumulasi curah hujan time series pada eksperimen DA-AMSUA adalah yang terbaik dengan skill model yang cukup konsisten di wilayah Jabodetabek pada berbagai musim.
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