EVALUASI PERFORMA INDEKS MONSUN AUSMI DAN WNPMI DI WILAYAH INDONESIA

Intisari Iklim di wilayah Indonesia sangat dipengaruhi oleh aktivitas monsun Asia-Australia. Variabilitas kedua sistem monsun tersebut dapat direpresentasikan dengan baik masing-masing oleh indeks monsun Australian Summer Monsoon Index (AUSMI) dan Western North Pacific Monsoon Index (WNPMI). Saat ini, BMKG secara operasional menggunakan indeks AUSMI dan WNPMI untuk memonitor aktivitas monsun di wilayah Indonesia sebagai bahan prakiraan musim. Meskipun banyak literatur menyatakan bahwa wilayah Indonesia merupakan bagian dari sistem monsun Asia-Australia, namun kondisi topografi lokal yang kompleks berpotensi memodifikasi sirkulasi monsun sehingga perlu dikaji performa kedua indeks tersebut sebelum digunakan secara operasional. Penelitian ini dilakukan untuk menguji performa indeks monsun AUSMI dan WNPMI dalam menggambarkan variasi antartahunan (interannual), variasi dalam musim (intraseasonal), dan siklus tahunan (annual cycle) hujan monsun Indonesia. Hasil penelitian mengungkapkan bahwa kedua indeks memiliki performa yang sangat baik hanya di wilayah dimana indeks tersebut didefinisikan namun kurang baik untuk wilayah Indonesia seperti yang ditunjukan oleh nilai koefisien korelasi yang tidak signifikan dari hasil uji statistik antara kedua indeks dengan curah hujan dari Global Precipitation Climatology Project (GPCP) pada periode 1981-2010. Selain itu, kedua indeks juga memperlihatkan karakteristik siklus tahunan yang berbeda dengan karakteristik siklus tahunan hujan wilayah Jawa sebagai wilayah kunci monsun Indonesia. Hasil ini mengindikasikan perlunya pendefinisian indeks sendiri untuk memonitor aktivitas monsun di wilayah Indonesia. Abstract The climate of Indonesia is strongly affected by the Asian-Australian monsoon system. The variability of the two monsoon systems can be well represented by the Western North Pacific Monsoon Index (WNPMI) and the Australian Summer Monsoon Index (AUSMI) respectively. For producing seasonal forecast, BMKG uses the WNPMI and AUSMI monsoon index to monitor monsoon activity in Indonesia. Although most literature states that the Indonesian region is part of the Asian-Australian monsoon system, the complex local topography may modify the monsoon circulation. Hence, it is necessary to assess the performance of the two indices before they are operationally used. This study was conducted to evaluate the performance of the AUSMI and WNPMI monsoon indices in describing the annual cycle, intraseasonal and interannual variability of the Indonesian monsoon rainfall. The results revealed that the two indices only performed very well in the areas where the index was defined but lack of skill for the Indonesian region because of insignificant linear correlation based on a statistical significance test between the two indices and the Global Precipitation Climatology Project (GPCP) rainfall in the 1981-2010 period. In addition, both monsoon indices and Java rainfall showed different characteristics of the annual cycle. These results indicate that it is necessary to define a specific index for monitoring monsoon activity in Indonesia.

The Australian monsoon, Part 2 : Depressions and cyclones

A study of the NCEP/NCAR Reanalysis for the Australian region during the southern summer reveals that most of the depressions and cyclones over the region form and develop in a stationary wave that develops along the continent's northern coastline during this period due to land-sea thermal contrast. The structure and properties of the stationary wave are brought out in detail and internal and external forcings that lead to its development into depressions and cyclones are discussed. Environmental factors that appear to influence the movement and recurvature of cyclones over the region are discussed with two case studies.

The Australian monsoon Part-I : Climatological features and the Asian connection

Climatological fields of several meteorological variables associated with the Australian summer monsoon, as revealed by NCEP/NCAR reanalysis, are reviewed in the context of observed weather and climate over the continent and surrounding regions. Inter-hemispheric distributions of pressure, temperature and circulation features suggest a see-saw relationship of the Australian monsoon with the monsoons of Asia during both summer and winter. Computed values of cross-equatorial fluxes of air appear to lend credence to this hypothesis.

Intraseasonal variability of global land monsoon precipitation and recent change

Accurate prediction of global land monsoon rainfall on a subseasonal (2-8 weeks) time scale has become a worldwide demand. Current forecasts of weekly-mean rainfall in most monsoon regions, however, have limited skills beyond two weeks. Given that two-thirds of the world’s population lives in the monsoon regions, this challenge calls for a more profound understanding of monsoon intraseasonal variability (ISVs). Our comparison of individual land monsoons shows that the high-frequency (HF; 8-20 days) ISV, crucial for the Week 2 and Week 3 predictions, accounts for about 53-70% of the total (8-70 days) ISV in various monsoons, and the low-frequency (LF; 20-70 days) ISV has a relatively high contribution over Australia (AU; 47%), South Asia (SA; 43%), and South America (SAM; 40%) monsoons. The leading modes of HFISVs in Northern Hemisphere (NH) monsoons primarily originate from convectively coupled equatorial Rossby waves (Asia), mixed Rossby-gravity waves (North America, NAM), and Kelvin waves (northern Africa, NAF), while from mid-latitude wave trains for Southern Hemisphere (SH) monsoons and East Asian (EA) monsoon. The Madden-Julian Oscillation (MJO) directly regulates LFISVs in the Asian-Australian monsoon while affecting the American and African monsoons by exciting Kelvin waves and mid-latitude teleconnections. During the past four decades, the HF (LF) ISVs have considerably intensified over the Asian (Asian-Australian) monsoon but weakened over the American (SAM) monsoon. Subseasonal-to-seasonal (S2S) prediction models do exhibit higher subseasonal (Weekly 2-Weekly 4) prediction skills over SA, AU, and SAM monsoons that have larger LFISV contributions than the other monsoons. The results suggest an urgent need to improve the simulation of convectively coupled equatorial waves and two-way interactions between regional monsoon ISVs and mid-latitude processes and between MJO and regional monsoons, especially under the global warming scenarios.

Analysis of Multi-Scale Hydrometeorological Triggering Flash Flood Event of the 13 July 2020 in North Luwu, South Sulawesi

During 12-13 July 2020, heavy rainfall had caused Masamba, Rongkong, and Rada rivers to overflow, causing flash floods in the North Luwu regency. This event resulted in many casualties; at least 38 people died and displaced thousands of people. This study presents an analysis of the multi-scale hydrometeorological settings that led to the development of these intense storms in the North Luwu fl ood. Boreal Summer Intraseasonal Oscillation (BSISO) Normalized PC2 has entered phases 4 and 5 on 7 - 13 July 2020, associated with cloud growth in the Indonesian Maritime Continent. Besides, the sub-seasonal tropical disturbance of Kelvin Waves is convectively active in the Sulawesi region on 7 - 13 July, increasing the intensity of rainfall at the location. Sea Surface Temperatures (SSTs) were in warmer conditions in the Bonne Bay region south of North Luwu, supplying more water vapor into the atmosphere. The easterly wind (Australian monsoon) enhanced the diurnal cycle of the water vapor mass movement from Bonne Bay to the highlands of North Luwu. From the observation of GPM satellite imagery, the accumulation of spatial rainfall on July 12 and 13 was concentrated in the eastern region of Sulawesi, which reached >150 mm/day and >50 mm/day in North Luwu.

Strengthening the Early Detection and Tracking of Tropical Cyclones near Indonesian Waters

In early April 2021, the territory of Indonesia, around the province of East Nusa Tenggara in particular, was severely damaged due to being hit by tropical cyclone Seroja. The impact of tropical cyclone Seroja does not only occur in Nusa Tenggara but also in Australia. In fact, the impact that hit Australia exceeded the damage that occurred in East Nusa Tenggara. The impacts caused by tropical cyclone Seroja in East Nusa Tenggara included 181 deaths and 74,222 houses damaged. Tropical cyclones are extreme weather anomalies that hit many countries, especially in the middle latitudes associated with vast oceans, such as the area around the South China Sea, the Pacific Ocean and the Atlantic Ocean, such as the Philippines, Japan, America, Australia, Europe, etc. Early detection systems for the genesis of tropical cyclones are still being developed by international collaborations such as The Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) in the Indian Ocean, Tropical Atmosphere Ocean (TAO) in the Pacific Ocean, and Prediction and Research Moored, Array in the Tropical Atlantic (PIRATA). To find out the early sign of a tropical cyclone, it is characterized by sea surface temperatures > 26.5 C, the growth of very broad and thick convective clouds, and rotating wind speeds of > 63 km/hour. For this reason, continuous observations are needed in the area where the tropical cyclone first developed. Observation equipment required includes satellite observations, buoys, and weather radar. Unfortunately, in the territory of Indonesia, especially in the Indian and Pacific oceans around Indonesia, this equipment is not equipped with such equipment due to very expensive funding factors and vandalism constraints. For this reason, in the future, national and international cooperation will be needed to start building an early warning system for the emergence of tropical cyclones among research centers globally.

Analysis of climate indicator association with hotspots in Indonesia using heterogeneous correlation map

In several regions, land and forest fires of Indonesia occurred almost annually during the drought season. The severity of Indonesia's drought season is mainly influenced by the Australian Monsoon, local cloud formation controlled by Sea Surface Temperature (SST) around Indonesia. Moreover, it affects the severity of land and forest fires itself indirectly. This research aims to examine the association of the Australian Monsoon and local SST with land and forest fires in Indonesia. This research uses the Australian Monsoon Index (AUSMI) as an indicator for the Australian Monsoon and SST in the Karimata Strait and the Java Sea as indicators of local SST. An indicator of land and forest fires that will be used is the number of hotspots. A heterogeneous Correlation Map (HCM) is used to describe hotspots associated with AUSMI and local SST. The analysis shows that the east wind pattern of AUSMI associated with hotspots in Indonesia, especially in years when zonal winds enter an upward phase more slowly. Karimata Strait’s SST is associate with hotspots in the coastal part of Riau. Meanwhile, Java Sea’s SST is associate with hotspots in Lampung, South Sumatra, Jambi, and Kalimantan.

Seasonal climate influences on the timing of the Australian monsoon onset

The timing of the first monsoon burst of the season, or the monsoon onset, can be a critical piece of information for agriculture, fire management, water management, and emergency response in monsoon regions. Why do some monsoon seasons start earlier or later than others? Previous research has investigated the impact of climate influences such as the El Niño–Southern Oscillation (ENSO) on monsoon variability, but most studies have considered only the impact on rainfall and not the timing of the onset. While this question could be applied to any monsoon system, this research presented in this paper has focused on the Australian monsoon. Even with the wealth of research available on the variability of the Australian monsoon season, the timing of the monsoon onset is one aspect of seasonal variability that still lacks skilful seasonal prediction. To help us better understand the influence of large-scale climate drivers on monsoon onset timing, we recreated 11 previously published Australian monsoon onset datasets and extended these to all cover the same period from the 1950/1951 through the 2020/2021 Australian wet seasons. The extended datasets were then tested for correlations with several standard climate indices to identify which climate drivers could be used as predictors for monsoon onset timing. The results show that many of the relationships between monsoon onset dates and ENSO that were previously published are not as strong when considering the extended datasets. Only a strong La Niña pattern usually has an impact on monsoon onset timing, while ENSO-neutral and El Niño patterns lacked a similar relationship. Detrended Indian Ocean Dipole (IOD) data showed a weak relationship with monsoon onset dates, but when the trend in the IOD data is retained, the relationship with onset dates diminishes. Other patterns of climate variability showed little relationship with Australian monsoon onset dates. Since ENSO is a tropical climate process with global impacts, it is prudent to further re-examine its influences in other monsoon regions too, with the aim to evaluate and improve previously established prediction methodologies.