Dynamic evolution of Day-To-Day Temperature fluctuations and population exposure on a global scale

Understanding the spatiotemporal variations in Day-to-Day Temperature Difference (DTD) and the associated population exposure is essential for evaluating the impacts of climate change on human health, ecosystems, and socio-economic systems. This study offers a comprehensive global analysis of the spatiotemporal patterns of DTD and its interaction with population exposure. Using the CPC Global Unified Gauge-Based Analysis of Daily (CPC GU-GDAD) dataset alongside the LandScan global population data, it evaluates global DTD dynamics and exposure trends from 2000 to 2022. Furthermore, the relative contributions of climatic factors, demographic shifts, and their interactions to changes in exposure levels are systematically quantified. The results demonstrate a pronounced hemispheric asymmetry in DTD distribution, with higher values concentrated in the Northern Hemisphere and a latitudinal peak near 60°N. During the study period, a significant decline in DTD was observed globally, with trends of -0.055°C/decade for daily maximum temperatures and -0.042°C/decade for daily minimum temperatures, indicating an overall stabilization of short-term temperature variability. In contrast, population exposure to DTD exhibited a substantial upward trajectory, increasing annually by 2064 People·°C for maximum temperatures and 1648 People·°C for minimum temperatures, predominantly across the Northern Hemisphere (People·°C: the product of the population size and DTD, used to express the exposure of the population to temperature variability). Furthermore, although global Day-to-Day Temperature variability has declined, population exposure has continued to increase, suggesting that the potential risks associated with temperature fluctuations may persist or intensify, pending further empirical investigation. These findings may support adaptation strategies in urban planning, public health, and climate resilience, particularly in regions with strong DTD variability.