PROYEKSI AWAL MUSIM DI JAWA BERBASIS HASIL DOWNSCALING CONFORMAL CUBIC ATMOSPHERIC MODEL (CCAM) (SEASON ONSET PROJECTION IN JAVA BASED ON CCAM DOWNSCALING OUTPUT)

Penelitian mengenai awal musim dengan kriteria Badan Meteorologi, Klimatologi dan Geofisika (BMKG) yang menggunakan curah hujan dasarian di Indonesia telah banyak dilakukan, namun data yang digunakan masih memiliki keterbatasan dalam periode analisis, resolusi spasial yang masih rendah dan masih belum dapat menghasilkan proyeksi ke depan. Penggunaan model iklim adalah jawaban untuk mengatasi semua keterbatasan tersebut. Penelitian ini menggunakan Conformal Cubic Atmospheric Model (CCAM) untuk downscaling dari data model iklim global dan reanalisis National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). Periode waktu yang digunakan adalah periode 1991 2010 (20 tahun) sebagai periode baseline (kondisi saat ini) dan periode 2011 2030 sebagai periode proyeksi ke depan. Penentuan awal musim pada penelitian ini menggunakan kriteria curah hujan dasarian dari Badan Meteorologi, Klimatologi dan Geofisika (BMKG). Hasil dari penelitian ini menunjukkan bahwa proyeksi dengan menggunakan skenario A2 IPCC menyimpulkan bahwa Awal Musim Kemarau (AMK) di sebagian besar daerah Pulau Jawa datang lebih cepat, sedangkan Awal Musim Hujan (AMH) cenderung mundur atau datang lebih lambat dari baseline. Dengan kata lain, Pulau Jawa diproyeksikan mengalami musim kemarau yang lebih panjang dan musim hujan yang lebih pendek dibandingkan kondisi saat ini.Kata kunci: CCAM, Downscaling, AMK, AM

Interaksi El-Nino, Monsun Dan Topografi Lokal Terhadap Anomali Curah Hujan Di Pulau Jawa

hal. 59-7

Analisis Pola Spatio-Temporal Dan Komparasi Hasil Downscaling CCAM (Conformal Cubic Atmospheric Model) untuk Parameter Curah Hujan 3 Jam-an

hal. 70-8

Pola Sebaran Suhu Udara Permukaan di Indonesia Menggunakan Data AIRS (Atmospheric Infrared sounder)

Hal. 91-9

Analisis Pola Spatio-Temporal dan Komparasi Hasil Dowscaling CCAM (Conformal Cubic Atmospheric Model) Untuk Parameter Curah Hujan 3 Jam-an

Validation and comparison are necessary to analyze and evaluate the performance of the model atmosphere. The comparison is carried out between model outputs with observed data or satellite. Downscaling is used to obtain data with high spatial resolution. This study uses a dynamic downscaling model (CCAM) where the input data is the Reanalysis NCEP / NCAR data. The results of this study explain that the CCAM downscaling output for 3 hourly rainfall over Java still not produces a high correlation coefficient with the TRMM data. This is because the results of CCAM downscaling tend to show a lower value (under-estimate) when compared to the TRMM, but the results of CCAM downscaling showed similar temporal patterns. Although the spatial patterns of diurnal rainfall of CCAM are more similar with TRMM, with the peak ofrainfall in the ocean occured in the morning - noon (starting at 01.00- 10.00 LT) and for land occurred at noon - night (13.00 to 19.00 LT).Validasi dan komparasi sangat diperlukan untuk menganalisis dan mengevaluasi kinerj a model dengan cara membandingkan hasil keluaran model yang telah dilakukan downscaling dengan data observasi. Downscaling digunakan untuk mendapatkan data dengan resolusi spasial yang lebih rapat. Penelitian ini menggunakan metode downscaling dinamis dengan model CCAM dimana data input yang digunakan adalah data reanalisis NCEP/NCAR. Hasil dari penelitian ini adalah curah hujan 3 jam-an di Pulau Jawa hasil downscaling CCAM masih belum rnenghasilkan koefisien korelasi yang tinggi dengan data TRMM. Hal ini disebabkan hasil downscaling CCAM cenderung menunjukkan nilai yang lebih rendah (under-estimate) jika dibandingkan dengan TRMM, namun hasil downscaling CCAM sudah menunjuldcan pola temporal yang hampir mina. Sedangkan pola spasial curah hujan diurnal basil downscaling CCAM sudah hampir menyerupai TRMM, dengan puncak curah hujan diurnal di lautan terjadi pada pagi - siang Bari (dimulai pukul 01:00-10:00 LT) dan untuk daratan terjadi pada siting - sore hari (13:00-19:00 LT).Hal. 70-8

Karakteristik Penyimpangan Curah Hujan Saat Kejadian Enso (El Nino Southern Oscillation) Di Indonesia Berbasis Satelit TRMM

Indonesia where was located on the west of Pacific Ocean, has a climate strongly influenced by oscillations that occur in the ocean. This research was conducted, to obtain spatial results, which can explain the correlation between rainfalls in Indonesia with the southern oscillation phenomenon. With spatial method, it will get anywhere regions which significantly affect the incident in Indonesia. This is important, because many previous studies still use the station or in the form of point data, so the analysis only focused on the temporal side in some areas of observation only. Analysis of spatial correlation in Indonesia for both these parameters, are still rarely found. Calculation and analysis results obtained is a map of rainfall deviation during the Southern Oscillation Index (SOI) extremes and the map correlation coefficient between rainfall in Indonesia and the SOI, with values between -0.2 to 0.5, with a fairly high correlation found in the north Sulawesi island. Correlation analysis was also performed between rainfall in every season (3 months) with the SOI, which can be generated correlation value, both in DJF (December, January, February), MAM (March, April, May), JJA (June, July , August) and SON (September, October, November). The resulting correlation values ranging from -0.5 to 0.7.Hal. 235-24

Analisis Spasial Perubahan Suhu Udara Permukaan di Wilayah Indonesia Berbasis Data Satelit

Hal. 261-27

Analisis Spasial Perubahan Suhu Udara Permukaan di Wilayah Indonesia Berbasis Data Satelit

Hal. 261-27

Kajian Perubahan Iklim Terhadap Awal Musim di Pulau Jawa Berbasis Data Downscaling CCAM (Conformal Cubic Atmospheric Model)

xv, 35p.,ill.; 30 c

Analisis Perubahan Curah Hujan Di Lima Kota Besar Indonesia Berbasis Data TRMM

Changes of rainfall pattern and variability are important to be known as one of climate change indicator. High variations in rainfall patterns in Indonesia, spatially and temporally, causing changes of rainfall to be more localized (different from one region to another). This study discusses the changes of monthly rainfall (trend, average and variability) occurred in five major cities in Indonesia, namely Medan, Jakarta, Bandung, Semarang and Surabaya, based on TRMM satellite data which has period of January 1998 to June 2011. The results showed that there were differences found in patterns of rainfall changes in each city. The highest rainfall increase occurred in Bandung in December with a slope of +18.8, while the lowest decrease occurred in Medan, which was also recorded in December with a slope of -19.1. Bandung and Semarang have a quite same pattern, since both cities have more number of months of increasing rainfall. In contrast, months of decreasing rainfall occurred more frequently in Medan. While, Jakarta and Surabaya has the same number of months that rainfall has increased or decreased. The study also found that the largest variation of rainfall occurred in Medan in the month of October, with a standard deviation of 436.5 mm, while the lowest variation occurred in Surabaya in August with a standard deviation of 4.6 mm.Hal. 97-10