Perbandingan Metodologi Koreksi Bias Data Curah Hujan CHIRPS

Misnawati Misnawati, Rizaldi Boer, Tania June, Akhmad Faqih

Abstract


Penggunaan data global makin meningkat dalam mengatasi permasalahan ketersedian data curah hujan observasi. Salah satu data global yang sering digunakan yaitu data Climate Hazards Group InfraRed Precipitation with Station (CHIRPS). Namun demikian, data CHIRPS tidak bebas dari permasalahan bias, sehingga perlu divalidasi dan dikoreksi dengan menggunakan data observasi hasil pengamatan di lapangan. Penelitian ini bertujuan untuk mengidentifikasi metode koreksi bias yang memberikan performa paling baik dalam memperbaiki inkonsistensi data curah hujan CHIRPS terhadap curah hujan observasi. Metode-metode yang digunakan dalam penelitian ini adalah metode interpolasi error, metode Piani, metode Lenderink dan metode regresi power. Evaluasi performa masing-masing metode tersebut dilakukan berdasarkan nilai R2 dan MSE. Hasil penelitian menunjukkan bahwa metode koreksi bias intepolasi error memberikan hasil yang terbaik dengan nilai R2 dan MSE paling kecil. Pola curah hujan harian dan bulanan CHIRPS terkoreksi metode interpolasi error juga menunjukkan konsistensi yang paling baik terhadap curah hujan observasi.

Keywords


CHIRPS, koreksi bias, performa

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References


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