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.
Dynamiques spatiotemporelles et facteurs multidimensionnels de l'amplitude thermique diurne urbaine : Preuves provenant d'un apprentissage intégré à l'échelle nationale en Chine | Synapse