Iskhaq Iskandar

Impact of Indian Ocean Dipole on intraseasonal zonal currents at 90°E on the equator as revealed by self-organizing map

A neural network pattern recognition approach called self-organizing map (SOM) has been used to examine the impact of the Indian Ocean Dipole (IOD) on intraseasonal zonal currents in the eastern equatorial Indian Ocean. This study shows that during negative IOD events the intraseasonal zonal currents are mostly dominated by the first two modes. On the other hand, contributions from the higher modes to the intraseasonal zonal current significantly increase during positive IOD events. This is attributed to the change in the background stratification associated with the IOD events; the sharp pycnocline in the eastern basin during the positive IOD events causes the wind forcing to project more onto the higher modes.

Coherent intraseasonal oceanic variations in the eastern equatorial Indian Ocean and in the Lombok and Ombai Straits from observations and a high‐resolution OGCM

Ongoing acoustic Doppler current profilers (ADCP) observation in the eastern equatorial Indian Ocean and a recent International Nusantara Stratification and Transport (INSTANT) experiment in the Indonesian Throughflow (ITF) straits have shown coherent intraseasonal oceanic variations in this region. The intraseasonal variations are dominated by 30–70 day variations, with a tendency for the observed currents in the eastern equatorial Indian Ocean to lead those at the Lombok and Ombai Straits. Phase speed of these eastward propagating signals estimated using lag correlation analysis does not correspond to one particular baroclinic mode, though it is in the range expected for the first two baroclinic modes. In this study, the dynamics underlying this intraseasonal coherency is evaluated using output from a high-resolution ocean general circulation model developed for the Earth Simulator (OFES). The results from model simulation of January 2001 through December 2007 show that the first two baroclinic modes dominate the intraseasonal variations in this region. While the first and second baroclinic modes have comparable contribution to the intraseasonal oceanic variations in the eastern equatorial Indian Ocean and in the Ombai Strait, the intraseasonal oceanic variations in the Lombok Strait are dominated by the first baroclinic mode. Moreover, the analysis reveals that the intraseasonal variability at all mooring sites is mostly confined in the upper layer above ∼100 m depth. Both equatorial wind from the Indian Ocean and alongshore winds off Sumatra and Java play important roles in generating intraseasonal variations in the Lombok and Ombai Straits.

Chlorophyll- a bloom along the southern coasts of Java and Sumatra during 2006

Nine years of chlorophyll‐a concentration data provided by the Sea‐viewing Wide‐Field of view Sensor (SeaWiFS) revealed an unusual bloom along the southern coastal area of Java and Sumatra during 2006. The bloom was generated by anomalous strong southeasterly winds along the coasts of Java and Sumatra associated with the Indian Ocean Dipole (IOD) event. The bloom evolution started in July 2006 and intensified during August 2006. Peak positive anomalies exceeding 4.0 mg m−3 were evident in September–November coinciding with the peak phase of the IOD. The blooms, thereafter, diminished rapidly in December 2006. In addition, there was an offshore intensification of chlorophyll‐a distribution off eastern Java during November initiated by upwelling‐favourable winds along the coast. Concurrent altimeter data show that the offshore intensification was co‐located with the cyclonic eddies that further enhanced the intensification by increasing the concentration of nutrients in the euphotic zone. On leave from the Department of Physics, University of Sriwijaya, South Sumatra, Indonesia. Currently at the Indian Institute of Tropical Meteorology Pashan, Pune‐411 008, India.

Spatio-temporal variations of sea surface temperature in the Banda Sea during the period of 2002-2008

Spatial and temporal variations of sea surface (SST) in the Banda Sea are studied for the period of June 2002 – May 2008. An empirical orthogonal function (EOF) analysis has been applied to an optimum interpolation SST (OISST) having spatial resolution of 0.25° and temporal resolution of 1 day. The results revealed that the four EOF modes account for 53.1% of the total SST variance. The first EOF mode, which accounts for 33.2% of the total variance, revealed the east-west SST pattern in the Banda Sea. This indicates 180° out of phase temporal variability between the eastern and the western parts of the Banda Sea. The second and the fourth modes explain 9.6% and 4.6% of the total variance respectively. Both two modes show the southeast-northwest spatial pattern. Meanwhile, the third mode accounting for 5.4% of the total variance indicates that the high SST variation is concentrated in the central Banda Sea. In addition, the corresponding principal component time series of the first mode revealed robust sea...

How strong was the 2015/2016 El Niño event?

On the interannual timescale, the Indonesian climate is strongly influenced by a coupled ocean-atmosphere modes in the tropical Pacific Ocean. During a warm phase (El Nino event), negative sea surface temperature anomalies (SSTA) in the western tropical Pacific lead to suppress convection activities causing reduce precipitation over the maritime continent. The situation is reverse during the cold season(La Nina event). In this study, the evolution of 2015/2016 El Nino event is evaluated based on the collected data by the Tropical Atmosphere Ocean/Triangle Trans-Ocean Buoy Network (TAO/TRITON) buoys. The results show that the evolution of the event has started in boreal spring (April – May 2015). It came to thepeak in boreal fall/winter (October – December 2015). The event lasted until boreal spring before it terminated in April/May 2016. In addition, the intensity of the event is classified as a strong event, and it is one of the strongest El Nino events during the last three decades.

Monthly rainfall prediction based on artificial neural networks with backpropagation and radial basis function

Two models of Artificial Neural Network (ANN) algorithm have been developed for monthly rainfall prediction, namely the Backpropagation Neural Network (BPNN) and Radial Basis Function Neural Network (RBFNN). A total data of 238 months (1994-2013) was used as the input data, in which 190 data were used as training data and 48 data used as testing data. Rainfall data has been tested using architecture BPNN with various learning rates. In addition, the rainfall data has been tested using the RBFNN architecture with maximum number of neurons K = 200, and various error goals. Statistical analysis has been conducted to calculate R, MSE, MBE, and MAE to verify the result. The study showed that RBFNN architecture with error goal of 0.001 gives the best result with a value of MSE = 0.00072 and R = 0.98 for the learning process, and MSE = 0.00092 and R = 0.86 for the testing process. Thus, the RBFNN can be set as the best model for monthly rainfall prediction.

Burnscar analysis using normalized burning ratio (NBR) index during 2015 forest fire at Merang-Kepahyang peat forest, South Sumatra, Indonesia

Forest fire, classified as a natural hazard or human-induced hazard, has negative impacts on humans. These negative impacts are including economic loss, health problems, transportation disruption and land degradation or even biodiversity loss. During 2015, forest fire had occurred at the Merang-Kepahyang peat forest that has a total area of about 69.837,00 ha. In order to set a rehabilitation plan for recovering the impact of forest fire, information on the total burnscar area and severity level is required. In this study, the total burnscar area and severity level is evaluated using a calculation on the Normalized Burning Ratio (NBR) Index. The calculation is based on the Near Infra Red (NIR) and Short Wave Infra Red (SWIR) of the satellite imageries from LANDSAT. The images of pre-and post-fire are used to evaluate the severity level, which is defined as a difference in NBR Index of pre- and post-fire. It is found that about 42.906,00 ha of the total area of Merang-Kepahyang peat area have been fired in...

Evolution of 2015/2016 El Niño and its impact on Indonesia

A coupled ocean-atmosphere mode, namely the El Nino event, took place in the tropical Pacific during 2015 – 2016. The event developed in spring (April – May 2015), peaked in late fall to early winter (November – December 2015) and terminated in spring (April – May 2016). The intensity of the event, indicated by the Nino3.4 index, is classified as a strong event. Compare to the previous events, the 2015/2016 El Nino event is one of the strongest event during the last two decades. This study examined the evolution of the event and highlighted some of the important aspects of its influence on the Indonesian climate.A coupled ocean-atmosphere mode, namely the El Nino event, took place in the tropical Pacific during 2015 – 2016. The event developed in spring (April – May 2015), peaked in late fall to early winter (November – December 2015) and terminated in spring (April – May 2016). The intensity of the event, indicated by the Nino3.4 index, is classified as a strong event. Compare to the previous events, the 2015/2016 El Nino event is one of the strongest event during the last two decades. This study examined the evolution of the event and highlighted some of the important aspects of its influence on the Indonesian climate.

Simulated Interannual Modulation of Intraseasonal Kelvin Waves in the Equatorial Indian Ocean

Outputs from a high-resolution ocean general circulation model (OGCM) for the period of 1990-2003 indicate an interannual modulation of intraseasonal Kelvin waves along the equatorial Indian Ocean. During normal conditions without IOD event, the first mode explains about 30-40% of the total variance in the western (60-65oE) and central (75-80oE) basin, while the second mode contributes up to 45% to the total variance in the central basin around the longitude of 82oE. In contrast, during the 1997/98 IOD event, the fourth mode caused about 40% of the total variance in the central and eastern basin. During the 1994 IOD event, the contribution from the fourth baroclinic mode in the eastern basin caused 45% of the total variance. In the central basin, the second and the fourth baroclinic mode caused almost the same variance (~40%). The variations in the characteristics of the intraseasonal Kelvin waves are related to variations in the vertical stratification. During the IOD event, the pycnocline in the eastern basin was raised by about 50 m and the stratification at the upper level is strengthened, while it is weakened at lower levels. These changes lead to an increase in the contribution of higher-order baroclinic modes.

VARIASI TEMPORAL ARUS WYRTKI DI SAMUDERA HINDIA DAN HUBUNGANNYA DENGAN FENOMENA INDIAN OCEAN DIPOLE

Interaksi laut dan atmosfer baik secara lokal, regional maupun global sangat mempengaruhi variasi temporal arus Wyrtki yang terjadi pada arus permukaan ekuator Samudera Hindia yang bergerak ke arah timur. Kajian ini difokuskan pada variasi musiman dan variasi antar-tahunan (interannual) yang dihubungkan dengan fenomena Indian Ocean Dipole (IOD). Analisis dilakukan dengan menggunakan data Ocean Surface Current Analysis-Real time (OSCAR) Project. Hasil penelitian menunjukkan bahwa arus Wyrtki musim peralihan II (Oktober – November) lebih kuat dan berlangsung lebih lama jika dibandingkan dengan arus Wyrtki musim peralihan I. Arus Wyrtki musim peralihan II membentang di sepanjang ekuator dari bujur 50oBT hingga sisi timur Samudera Hindia. Sementara itu, arus Wyrtki musim peralihan I terkonsentrasi di sisi timur Samudera Hindia. Dalam skala antar-tahunan, arus Wyrtki musim peralihan II termodulasi oleh fenomena IOD. Pada kejadian IOD positif, arus Wyrtki musim peralihan II mengalami pelemahan atau bahkan berbalik arah, sementara pada kejadian IOD negatif arus Wyrtki musim peralihan II mengalami peningkatan intensitas. Pola dan amplitudo arus Wyrtki sangat dipengaruhi oleh pola dan amplitudo angin baratan di atas ekuator Samudera Hindia. Angin baratan pada musim peralihan II lebih kuat dan berlangsung lebih lama dibandingkan dengan angin baratan musim peralihan I. Lebih lanjut lagi, ketika terjadi IOD positif di ekuator Samudera Hindia terdapat angin timuran selama musim peralihan II, sedangkan pada saat IOD negatif angin baratan mengalami peningkatan intensitas