@article{81350ede131c4eb7bef55c5fd3b96f5b,
title = "Characteristics and causes of Taiwan's extreme rainfall in 2022 January and February",
author = "Huang, {Shao Chin} and Huang, {Wan Ru} and Wu, {Yi chao} and Yu, {Yi Chiang} and Chu, {Jung Lien} and Jou, {Ben Jong Dao}",
note = "Funding Information: Fig. 9a demonstrates a positive relationship between the increase in JF rainfall in Taiwan and the southwesterly moisture flux transport at 700 hPa, which mostly extends from the western SCS to Taiwan and south of Japan. There is also a weak positive relationship over north of the BoB; however, this is located behind the India-Burma Trough and is not connected to the positive relationship over SCS (Fig. 9a). Relative to JF climate (Fig. 9a), both pre-2002 and post-2002 periods (Fig. 9b–c) show an increase in moisture transport from SCS to support the increase in JF rainfall in Taiwan. However, the area with moisture transport passed the significant test at a 90% confidence interval extended to the southeastern BoB only for the post-2002 period (Fig. 9d). These features are consistent with those inferred from SSTA changes (Fig. 8), suggesting that the enhanced moisture needed to support the increase in JF rainfall in Taiwan originates from SCS for the pre-2002 period and that the enhanced moisture source extended westward to the southeastern BoB for the post-2002 period. It is likely that the enhanced atmospheric moisture pattern extending all the way from the southeastern BoB to SCS supports the active convection zone observed in JF 2022; this is consistent with what is observed in Fig. 7. This increasing impact of SSTA changes over the southeastern BoB might be one of the possible explanations for the observed increase in the maximum JF rainfall in Taiwan over the post-2002 period.We thank the data provider of Global Precipitation Climatology Project (https://psl.noaa.gov/data/gridded/data.gpcp.html), ECMWF Reanalysis v5 (https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5), and the Optimum Interpolation Sea Surface Temperature dataset version 2 (https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.html). W.-R. Huang was supported by the National Science and Technology Council of Taiwan under MOST 111-2111-M-003-006. Funding Information: We thank the data provider of Global Precipitation Climatology Project ( https://psl.noaa.gov/data/gridded/data.gpcp.html ), ECMWF Reanalysis v5 ( https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5 ), and the Optimum Interpolation Sea Surface Temperature dataset version 2 ( https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.html ). W.-R. Huang was supported by the National Science and Technology Council of Taiwan under MOST 111-2111-M-003-006 . Publisher Copyright: {\textcopyright} 2022 The Authors",
year = "2022",
month = dec,
doi = "10.1016/j.wace.2022.100532",
language = "English",
volume = "38",
journal = "Weather and Climate Extremes",
issn = "2212-0947",
publisher = "Elsevier BV",
}
