Analysis and Prediction of Significant Meteorological (SIGMET) in the Eastern Indonesia Aviation Region

Muhlis, Sandi, Anita Ramadhani, Halmar Halide

Analysis and Prediction of Significant Meteorological (SIGMET) in the Eastern Indonesia Aviation Region

Muhlis, Sandi, Anita Ramadhani, Halmar Halide

The spatial and temporal distribution of Significant Meteorological Information (SIGMET) in Eastern Indonesia reflects the complex dynamics of geographical and meteorological interactions influencing the formation of extreme weather events. This study highlights the distribution patterns of SIGMET from 2019 to 2022, focusing on Papua, Southeast Sulawesi, and South Kalimantan. SIGMET serves as a critical indicator for mitigating aviation risks, particularly concerning thunderstorms, convective clouds, and turbulence.

Spatially, Papua emerges as the region with the highest SIGMET activity, supported by its mountainous topography that creates local convergence zones. Southeast Sulawesi exhibits significant SIGMET patterns, particularly around the Bone Gulf, driven by the interaction between the southwest monsoon winds and complex topography. South Kalimantan, despite its relatively flat terrain, also records notable SIGMET activity influenced by airflow from the Java Sea. Temporally, SIGMET activity is more pronounced during the rainy season (October–March), when the western monsoon brings moisture from the Indian Ocean, fostering favorable conditions for convective cloud formation. In contrast, activity decreases during the dry season (April–September), except in certain regions such as Papua, which sporadically experiences SIGMET due to localized conditions.

During transitional seasons, from rainy to dry (March–May) and dry to rainy (September–November), SIGMET distribution patterns vary. The analysis reveals concentrated activity in Papua and South Kalimantan, driven by key factors such as moisture transport, sea surface temperature (SST), and tropopause temperature. These factors support atmospheric instability and the formation of extreme weather phenomena. These findings provide crucial insights into understanding SIGMET distribution and its implications for aviation safety in Eastern Indonesia.