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Myanmar's climate is heavily influenced by its geographic location and relief. Located between the Indian summer monsoon (ISM) and the East Asian summer monsoon (EASM), Myanmar's climate is distinguished by the alternation of seasons known as the monsoon. The north-south direction of peaks and valleys creates a pattern of alternate zones of heavy and scanty precipitation during both the northeast and southwest monsoons. The majority of the rainfall has come from Myanmar's southwest monsoon (MSwM), which is Myanmar's rainy season (summer in global terms, June–September). This study explained both threshold-based and nonthreshold-based objective definitions of the onset and withdrawal of large-scale MSwM. The seasonal transitions in MSwM circulation and precipitation are convincingly represented by the new index, which is based on change point detection of the atmospheric moisture flow converging in the MSwM region (10–28 N, 92–102 E). A transition in vertically integrated moisture transport (VIMT), the reversal of surface winds, and an increase in precipitation may also be considered when defining MSwM onset objectively. We also define a change point of the MSwM (CPI) index for MSwM onset and withdrawal dates. The climatological mean onset of MSwM is day 135 (May 14), withdrawal is day 278 (October 4), and the total season length is 144 days. We are investigating spatial patterns of rainfall progression at and after the start of the monsoon, rather than transitions within a single region of the MSwM. The local southwest monsoon duration is well correlated with the CPI duration on interannual timescales, particularly in the peak rainfall regions, with a delay (advance) in large-scale onset or withdrawal associated with a delay (advance) of onset or withdrawal by local index. Hence, the next phase of this research is to study the maintenance and break of the monsoon to understand the underlying physical processes governing the monsoon circulation. The results of this study provide a possibility to reconstruct Myanmar's monsoon climate dynamics, and the findings of this study can help unravel many remaining questions regarding the greater Asian monsoon system's variability. [ABSTRACT FROM AUTHOR]

The aviation industry has a global economic impact of $2.7 trillion (including direct, indirect, induced, and tourism catalytic effects) and contributes 3.6 percent of global GDP. Weather is one of the most essential elements impacting how an aircraft runs and how safely it can fly. The correlation coefficient is the most significant index explaining the relationship between variables and can result in teleconnection patterns of climate indices. El Nino-Southern Oscillation (ENSO) and India Ocean Dipole (IOD) were used in this study based on the ERA5 reanalysis dataset for 30 years (1991–2020). Myanmar's Yangon International Airport has recorded more than 119874 times of observation data from 2009 to 2019. The mean percentage of occurrences of weather elements is calculated for each month and each season. Analysis of flight delay and accident data was obtained statistically from the Aviation Safety Network (ASN). According to the monthly delay index, July, August, and March are the maximum delay index months, and the correlation value between aircraft movement and delays is maximum in July and August and minimum in January and February. After examining numerous characteristics of Yangon International Airport, we identified which elements had a big impact on operations through vital interviews with operators, the accident case study section, and climatology analysis. As a result, we identified two meteorological occurrences: thunderstorm rain (TSRA) and fog (FG) are of high frequency and TSRA poses a larger risk than FG for aviation operation. The maximum frequency (%) of thunderstorm occurrences was 22% in July and the minimum was 1% in January. Annual frequency analysis revealed that TSRA days are becoming more common year after year as a result of global climate change. According to a spatial gridded analysis by ERA5 reanalysis data (1991–2020), the annual convective available potential energy (CAPE) values over local airport regions, the Bay of Bengal (BOB), the western equatorial Pacific, and the South China Sea show a positive correlation with convective rainfall. In contrast, negative convective inhibition (CIN) anomalies have been observed over the same areas as above, except for the western part of BOB along the Indian Coast. The primary innovation is that we look at the effects of thunderstorms on airport operations before determining their link with ENSO and the IOD individually and then combining them during their full phases. This raises a new question and a new possibility for viewing climatology from a new perspective. [ABSTRACT FROM AUTHOR]