Assessing Taiwan's Future Climate: High Resolution Projections and Regional Impacts From Statistical Downscaling of <scp>CMIP6</scp> Data

ABSTRACT This study explores how Taiwan's climate might change in the future, using statistical downscaling techniques to make global climate projection data more relevant to the region. Global climate models often lack the fine detail necessary for small areas, such as Taiwan, particularly given its unique geography and local weather systems. To address this, we used statistical methods to create high‐resolution projections that combine local weather observations with data from the latest international climate model data archive (CMIP6). These projections cover daily temperature and rainfall patterns from the past (1960–2014) and into the future (2015–2100) under four different future socioeconomic and climate change scenarios. Our findings demonstrate that the downscaling method effectively corrects historical temperature and precipitation biases, yielding a robust signal for temperature projections and moderate uncertainty for precipitation trends, compared to low‐resolution climate model simulations. Taiwan is expected to experience significantly warmer temperatures, with heatwaves lasting longer and extremely high temperatures becoming increasingly common by the end of the century. Rainfall patterns are also expected to change, with heavier rain during wet seasons and longer dry spells. Central and southern Taiwan, in particular, are likely to experience more intense rainfall events, thereby increasing the risk of flooding. At the same time, drier regions could face more frequent and severe droughts. This research provides a clearer picture of Taiwan's future climate and offers valuable information for planning ways to adapt to these changes. The detailed climate projection dataset bridges the gap between global climate models and regional applications, providing essential local‐scale climate information for decision‐makers and researchers in fields such as hydrology, forestry and water resource management.