Judul: Prediksi Awal Musim Hujan di Provinsi Sulawesi Selatan Menggunakan Data Anomali Suhu Muka Laut
Abstrak: The Province of South Sulawesi is one of the centers for national paddy production with 7% contribution from total paddy production in national level. The increasing of paddy production depends on the water availability. Moreover, the water availability is always associated with the onset of rainy seasons, because if an area has the forward or backward of onset of rainy season, it will influence the water availability and crop calendar. In order to onset of rainy seasons, to reduce the farmer’s loss and to protect the food stability level in Indonesia, it needs to identified the areas which have the sensitivity for the onset of rainy season’s variability to climate control factors like ENSO and IOD. This research has been conducted to study the correlation between onset of rainy seasons (AMH) in South Sulawesi and sea surface temperature anomaly (AnoSML) in Pacific Ocean and Sulawesi Sea, to determine the domain of sea surface temperature predictor which has influence the onset of rainy seasons in South Sulawesi and to develop the onset of rainy season model prediction in South Sulawesi based on the sea surface temperature anomaly in Pacific Ocean and Sulawesi Sea. This research has been conducted using daily rainfall data during 30 years (1980-2010) from rainfall stations in South Sulawesi, sea surface temperature anomaly data for 4 domains i.e. Nino 3 region, Nino 3.4, Nino 4 and Sulawesi Sea on June, July, August and September (JJAS) during 30 years. The first analysis of data was conducted with the examination of observation daily rainfall data and selection of rainfall stations which are used for the development of the rainy season onset prediction model. Further analysis was conducted to determine the onset of rainy seasons using Moron’s method (five days of daily rainfall data/pentad analysis). The result of pentad analysis was used to calculate Principle Component Analysis (PCA) which was used to determine the cluster of rainfall stations. The correlation analysis was then calculated between the onset rainy seasons on each cluster and AnoSML data on JJAS. The last analysis was conducted for development of onset rainfall season model prediction and verification of the model. Based on the checking of observation daily rainfall data with the data availability >70%, there were 45 chosen stations for onset of the rainy season analysis. The result of AMH analysis showed that the average of AMH for whole stations was on the 348th Julian Date (JD) or on 14th December. The highest AMH was obtained at Stasiun BPP. Panincong (PNCG) in Soppeng District with 473th Julian Date or on 18th April. Otherwise, the lowest AMH was obtained at Stasiun BPP. Keera (KERA) in Wajo District with 278th Julian date or on 5th October. The result of PCA analysis showed that there were six PCs which were explained variability of data ± 80%. Based on the PC clustering, there were 3 clusters of rainfall stations. Cluster 1 has 13 rainfall stations which are spread in 9 districts i.e. Bantaeng District, Bulukumba, Enrekang, Gowa, Luwu, Maros, Pinrang, Soppeng and Wajo District. On Cluster 2, there are 10 rainfall stations
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