Projected climatic drought events in drought-prone cities: Insights from high-resolution downscaled CMIP6 data

Abstract

This study investigated the drought trends, frequency, and duration in three drought-prone cities in Northwest China under various Shared Socioeconomic Pathways (SSPs) climate scenarios from 2015 to 2099. Utilizing a two-step downscaling method, we generated high-resolution (1 km) temperature and precipitation projections for the cities using multiple global climate model (GCM) data. The Standardized Precipitation Evapotranspiration Index (SPEI) was then calculated to assess drought conditions. Our results revealed that under the influence of global climate change, the 12-month SPEI exhibited a significant increasing trend for all three cities, indicating a shift towards a more humid climate. The influence of climate change on drought trends was more pronounced at higher latitudes. Additionally, the occurrence and duration of severe droughts (3-month SPEI < -1.5) were higher in the near future (2015–2056) compared to the far future (2057–2099), suggesting time-lagged and cumulative effects of global climate change on drought. Spatial variations within each city were also observed, with the western mountainous regions of Xi'an showing a more pronounced decrease in drought frequency under higher emission scenarios. Under the influence of different projected scenarios, the variations in drought characteristics across cities exhibited significant spatial heterogeneity. This study highlights the importance of understanding local and inter-regional drought characteristics in the context of climate change, and the need for targeted management policies to effectively cope with climate anomalies and associated disasters in different regions.

Keywords

• Drought trends
• Climate scenarios
• Two-step downscaling
• Deep learning
• Local climate