Sunday, February 25, 2024 | 06:38 WIB

Indonesia’s extreme weather Strengthening early detection

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Jakarta, IO – Changes in seasons and weather patterns in Indonesia are a logical consequence of the increase in the earth’s average annual temperature, which has been approaching 1.5 degrees Celsius in 2023. This means that Indonesia as an archipelagic state needs to immediately master accurate high-resolution weather and climate prediction technology as most of its territory is covered by water.

It is also high time for Indonesia to have full independence in weather prediction technology, by building its own weather and climate modeling tools. Stopping the “import” of global prediction data is the only way to strengthen upstream mitigation capabilities, in the face of the climate crisis. By having reliable prediction tools, Indonesia can use them to support various strategic sectors and help them adapt to climate change. 

Climate change has been a global issue since 2007, marked by the establishment of the Intergovernmental Panel on Climate Change (IPCC), a group which documents thousands of scientific studies on climate change in its plenary sessions. For more than a decade, climate change science has made significant progress, as reflected by the awarding of the Nobel Prize to climate modeling researchers in 2021. 

An important conclusion from these studies reveals that the world is currently at a critical threshold (tipping point), a condition that describes the biosphere as being at a point of imbalance that continues to worsen as a result of the unstoppable increase in global temperature. However, each region responds to climate change differently. Therefore, further research regarding the climate change response at regional and even local scale needs to be carried out continuously. For Southeast Asia, the study shows an increasing threat of drought and extreme rainfall in northern parts of Thailand, Cambodia and Vietnam in the distant future (2050–2100). 

On the other hand, maritime nations, including Malaysia, Singapore, Brunei, the Philippines, Indonesia, Papua New Guinea and Timor Leste, are projected to suffer increased drought, with extreme drops in rain and wind parameters over the same period. However, studies regarding climate projections for the maritime continent have the strongest bias when compared with projections for other regions in Southeast Asia. 

The results also pose a major challenge for climate scientists in describing future climate conditions in the near future (2024-49) and distant future (2050-2100) in the Indonesian Maritime Continent (BMI) region. Identification at the meso scale of the various impacts of rising global temperatures on changes in climate and weather dynamics at BMI is also limited. 

This, despite BMI being a key region in the world, one that plays a critical role in shaping global climate and weather systems. Multiscale and multicomponent interactions in the BMI shape the most complex climate and weather systems and dynamics worldwide. However, complete knowledge and understanding of these interactions is still lacking, due to limited representative high-resolution observational data on BMI. 

As a result, climate and weather models also have the largest rainfall forecast error bias in this region, where two-thirds of its surface is covered by seas. Improving the rainfall prediction results calls for a better understanding of complex multiscale interactions, as well as atmosphere-ocean interactions that can trigger extreme weather events in BMI. The understanding of these mechanisms needs to be incorporated in global climate and weather models. 

Indications 

Many studies discuss changes in several climate parameters in the Southeast Asia region, extending long into the future (2100), from the results of global and regional model projections. The climate parameters that are considered the most important are temperature and rainfall. However, several previous studies project that changes in temperature, rainfall and wind in BMI are not going to be so significant. 

However, there is an important note regarding the poor ability of climate models to simulate these climate parameters in BMI; hence, the need to carry out more detailed studies on a regional and even sub-regional scale. In addition, the latest climatological studies that provide a description of the characteristics of annual and seasonal rainfall in BMI region are needed as a form of validation, so that current indications of actual climate change can be better mapped. These indications can be seen from climatological changes in rainfall parameters through seasonal and extreme weather patterns. 

Shift in seasonal patterns 

Since BMI regions have variations in annual rainfall patterns, climatological studies on a regional scale need to be carried out, especially in areas that are considered scientifically and strategically important. Scientifically, seasonal climatology studies need to be pursued in areas with monsoon wind patterns or seasonal wind directions that have clear and definite differences between dry and rainy seasons. 

Strategically, studies are being carried out in the southern region of Indonesia, given that this region has the highest population density and is a national food bowl, with the most productive agricultural land in the nation. Moreover, based on the latest findings, Java has a moderate-to-high drought risk, especially over the past three decades. 

Nature and duration of seasons 

Previous studies have determined that the duration of the rainy season is longer in Indonesia’s monsoon regions but has exhibited more climate-induced consecutive dry days over the last two decades (2001-20). In addition, the latest study we conducted confirms in more detail at a sub-regional scale that for Area I (parts of Sumatra and Kalimantan), the rainy season lasts 12 days longer, while for Area II (Lampung, West Java and Central Java) it lasts 49 days longer. Meanwhile, in Area III (East Java, Bali, Lombok, Sumbawa and East Nusa Tenggara), the duration of the rainy and dry seasons remains unchanged. 

This study also found that consecutive wet days (more than two days) in BMI tend to be steadier and less influenced by La Niña. On the other hand, for consecutive dry days (more than two days without rain), regions in BMI are highly influenced by the El Niño phenomenon, which means that the number of consecutive dry days varies by region. Therefore, it is necessary to carry out further studies regarding the impact of consecutive dry days in Areas I to III, to understand weather trends over the last two decades. The results show that the longer the duration of the rainy season in Areas I and II, the more likely is a significant increase in the number of consecutive dry days with short to medium duration (6-20 days) in Area I and II, where more than four consecutive dry days account for 18.6 percent and 22.2 percent, respectively. Meanwhile, Area III has the highest rate, at 35 percent.

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