Spatiotemporal dynamics and multidimensional drivers of urban diurnal temperature range: Evidence from integrated learning at the national scale in China

Key Points

• Urban diurnal temperature range shows significant variability, highlighting its response to multiple drivers.
• Integrated learning techniques reveal interactions among various factors affecting temperature variations over time.
• Analysis of national-scale data provides insights into climate variability and urban heat management strategies.
• Understanding these dynamics may enable better adaptation strategies for urban environments facing climate change.