PREDIKSI ANOMALI CURAH HUJAN BULANAN DI WILAYAH MAKASSAR MENGGUNAKAN TEKNIK STATISICAL DOWNSCALING

Authors

  • Mamenun Mamenun Badan Meteorologi Klimatologi dan Geofisika (BMKG)

DOI:

https://doi.org/10.31172/jmg.v13i3.132

Keywords:

anomali suhu muka laut, anomali curah hujan, PCR, PLSR, sea surface temperature anomaly, rainfall anomaly, PLSR.

Abstract

Suhu permukaan laut (SST) merupakan salah satu parameter siklus atmosfer global yang mempunyai peran besar dalam pembentukan uap air dan awan di atmosfer hingga terjadinya hujan. Keragaman curah hujan di Indonesia  diduga kuat dipengaruhi oleh suhu permukaan laut. Data anomali suhu permukaan laut pada wilayah grid perairan Sulawesi (ukuran 8x8), grid perairan Indonesia (26x10) dan grid Nino3.4 (26x7) digunakan sebagai prediktor untuk membuat model prediksi anomali curah hujan di Makassar. Teknik statistical downscaling, yaitu model PCR dan PLSR, selanjutnya digunakan untuk mengetahui sensitivitas anomali SST terhadap anomali curah hujan dan untuk memprediksi anomali curah hujan menggunakan model terbaik. Sifat hujan di wilayah Makassar mempunyai pola monsun dengan satu kali puncak hujan. Pada model PCR, nilai korelasi anomali curah hujan dan anomali SST paling tinggi yaitu terdapat pada wilayah grid perairan Indonesia, sedangkan pada model PLSR nilai korelasi paling tinggi terdapat pada wilayah grid perairan Sulawesi. Selanjutnya dilakukan perbandingan antara model PCR dan PLSR pada masing-masing wilayah perairan dimana masing–masing model menunjukkan performa berbeda. Prediksi anomali hujan di wilayah Makassar dipengaruhi lebih kuat oleh suhu permukaan laut di wilayah perairan Sulawesi dengan nilai korelasi tertinggi menggunakan model PLSR.

 

Sea surface temperature (SST) has a huge effect creating water vapor and cloud for precipitation in the atmosphere. Rainfall variability in Indonesia has been influenced by SST. The anomaly of SST data on the Sulawesi Ocean grid, Indonesia Ocean grid and Nino3.4 grid are used as predictors to develop a rainfall anomaly model prediction in Makassar. On this paper, PCR and PLSR models as statistical downscaling technique are used to assess the rainfall sensitivities toward SST. Furthermore, this model will be chosen and will be used to predict rainfall. On the PCR model, correlation value between rainfall and SST anomaly in Indonesia Ocean grid is the highest than the others. Comparison between PCR and PLSR model in each grid has been done in which every model showed different performance. Prediction of rainfall anomaly in Makassar is more influenced by SST anomaly in grid Sulawesi using PLSR model.

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Published

2012-12-15

How to Cite

Mamenun, M. (2012). PREDIKSI ANOMALI CURAH HUJAN BULANAN DI WILAYAH MAKASSAR MENGGUNAKAN TEKNIK STATISICAL DOWNSCALING. Jurnal Meteorologi Dan Geofisika, 13(3). https://doi.org/10.31172/jmg.v13i3.132

Issue

Vol. 13 No. 3 (2012)

Section

Article

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