IntroductionAtmospheric River (AR) is a long, narrow stream of water vapor that moves in the earth’s atmosphere and carries abound moisture from the mid-latitude, engendering extreme rainfall upon landfall (Ralph et al., 2006). According to Zhu & Newell, (1998), around 90% of the largest rainfall events in the world have been followed by ARs. Furthermore, recent research shows the relevance of AR in occurring extreme precipitation in South East Asia, especially in the Bay of Bengal Region (Yang et al., 2018). Hence, the role of AR in generating extreme rainfall in Meghalaya is necessary for a better understanding of flash floods in the North Eastern (NE) region of Bangladesh. The NE region of Bangladesh is exposed to regular flash floods because of the rapid rainfall-runoff response from the extreme precipitation in Meghalaya. On June 2022, this region experienced one of the most devastating floods, more than 70% of the Sylhet and Sunamganj district went under water, as the aftermath of the heaviest rainfall in the last 102 years in Mawsynram, Meghalaya in conjunction with the existing water in the floodplain due to the flash flood in the previous month.  Therefore, this study illustrates the contribution of AR in generating the extreme precipitation in the Meghalaya region on June 2022 that created enormous flooding in the NE region of Bangladesh. MethodologyTo analyze the contribution of AR in the extreme rainfall event in Meghalaya on June 2022, the Vertically integrated Northward and Eastward Water Vapor Flux or Integrated Vapor Transport (IVT) in Meridian and Zonal direction data are collected from the European Center of Medium Range Weather Forecasts (ECMWF) ERA-5 Reanalysis data of June 2022 with an interval of 6 hours. Secondly, the extreme rainfall days have been identified from gauge station rainfall data from the Indian Meteorological Department (IMD). After that, the presence of AR will be detected by calculating the magnitude of IVT and identifying the geometric Criteria of AR (Length and area of AR, Length to Width ratio, and the direction of the IVT front)(Xu et al., 2020) from the collected data. Finally, the identified AR for June 2022 will be compared with the extreme rainfall timeline to determine the contribution of AR to this extreme rainfall. The conceptual framework of the study is provided in Figure 1.