Impact of Climate Change on Consecutive Dry Days in Taiwan

ABSTRACT Climate change poses a significant threat to water resources in Taiwan, particularly impacting agricultural areas. This study investigates the influence of climate change on the occurrence of consecutive dry days (CDD) using historical data (1960–2014) and Coupled Model Intercomparison Project phase 6 (CMIP6) future projections (SSP1‐2.6 to SSP5‐8.5). Our analysis of historical trends reveals a strong spatial dependence of variation in seasonal CDD, with increasing trends (0.5–1.5 days per decade) in southern and central Taiwan during autumn, in contrast to decreasing trends (−0.5 days per decade) in southern Taiwan during winter. Projections suggest that under high‐emission scenarios (SSP3‐7.0 and SSP5‐8.5), prolonged CDD will occur across most of Taiwan during the dry seasons (spring, autumn, winter) by the late 21st century. An SSP5‐8.5 scenario could lead to a further increase of 1.2 days per decade. This projected increase in seasonal CDD is linked to anticipated changes in the East Asian monsoon system, including seasonal precipitation patterns and atmospheric circulation. In contrast, projected low‐emission scenarios (SSP1‐2.6 and SSP2‐4.5) suggest a return towards baseline spring CDD levels, and the potential for persistence of the spring rainband over Taiwan. Furthermore, correlation analysis demonstrates a consistent link between atmospheric oscillations (i.e., AMO, PDO and ENSO) and prolonged spring CDD in specific regions in Taiwan. These findings suggest that monitoring climate indices informs spring drought mitigation strategies in Taiwan.

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Publication Details

Journal
International Journal of Climatology
Published
2025-06-27
DOI
https://doi.org/10.1002/joc.70008
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00

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article

Impact of Climate Change on Consecutive Dry Days in Taiwan

Chao‐An Chen, Amba Shalishe Shanka, Yuei‐An Liou, Yi‐Ying Chen
International Journal of Climatology
Climate variability and models
article

Impact of Climate Change on Consecutive Dry Days in Taiwan

Chao‐An Chen, Amba Shalishe Shanka, Yuei‐An Liou, Yi‐Ying Chen
article en

Abstract

ABSTRACT Climate change poses a significant threat to water resources in Taiwan, particularly impacting agricultural areas. This study investigates the influence of climate change on the occurrence of consecutive dry days (CDD) using historical data (1960–2014) and Coupled Model Intercomparison Project phase 6 (CMIP6) future projections (SSP1‐2.6 to SSP5‐8.5). Our analysis of historical trends reveals a strong spatial dependence of variation in seasonal CDD, with increasing trends (0.5–1.5 days per decade) in southern and central Taiwan during autumn, in contrast to decreasing trends (−0.5 days per decade) in southern Taiwan during winter. Projections suggest that under high‐emission scenarios (SSP3‐7.0 and SSP5‐8.5), prolonged CDD will occur across most of Taiwan during the dry seasons (spring, autumn, winter) by the late 21st century. An SSP5‐8.5 scenario could lead to a further increase of 1.2 days per decade. This projected increase in seasonal CDD is linked to anticipated changes in the East Asian monsoon system, including seasonal precipitation patterns and atmospheric circulation. In contrast, projected low‐emission scenarios (SSP1‐2.6 and SSP2‐4.5) suggest a return towards baseline spring CDD levels, and the potential for persistence of the spring rainband over Taiwan. Furthermore, correlation analysis demonstrates a consistent link between atmospheric oscillations (i.e., AMO, PDO and ENSO) and prolonged spring CDD in specific regions in Taiwan. These findings suggest that monitoring climate indices informs spring drought mitigation strategies in Taiwan.

International Journal of ClimatologyVol. 45(11)
National Science and Technology Center for Disaster Reduction (TW), National Central University (TW), Institute of Information Science, Academia Sinica (TW), Research Center for Environmental Changes, Academia Sinica (TW), Arba Minch University (ET), Academia Sinica (TW)
Academia Sinica, National Science and Technology Council
Openalex Percentile: Top 85%
Climate variability and models
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